Complexity, Robustness, and Network Thermodynamics in Large-Scale and Multiagent Systems: A Hybrid Control Approach

DTIC Science & Technology

2012-01-11

dynamic behavior , wherein a dissipative dynamical system can deliver only a fraction of its energy to its surroundings and can store only a fraction of the...collection of interacting subsystems. The behavior and properties of the aggregate large-scale system can then be deduced from the behaviors of the...uniqueness is established. This state space formalism of thermodynamics shows that the behavior of heat, as described by the conservation equations of

Decompositions of large-scale biological systems based on dynamical properties.

PubMed

Soranzo, Nicola; Ramezani, Fahimeh; Iacono, Giovanni; Altafini, Claudio

2012-01-01

Given a large-scale biological network represented as an influence graph, in this article we investigate possible decompositions of the network aimed at highlighting specific dynamical properties. The first decomposition we study consists in finding a maximal directed acyclic subgraph of the network, which dynamically corresponds to searching for a maximal open-loop subsystem of the given system. Another dynamical property investigated is strong monotonicity. We propose two methods to deal with this property, both aimed at decomposing the system into strongly monotone subsystems, but with different structural characteristics: one method tends to produce a single large strongly monotone component, while the other typically generates a set of smaller disjoint strongly monotone subsystems. Original heuristics for the methods investigated are described in the article. altafini@sissa.it

Robust scalable stabilisability conditions for large-scale heterogeneous multi-agent systems with uncertain nonlinear interactions: towards a distributed computing architecture

NASA Astrophysics Data System (ADS)

Manfredi, Sabato

2016-06-01

Large-scale dynamic systems are becoming highly pervasive in their occurrence with applications ranging from system biology, environment monitoring, sensor networks, and power systems. They are characterised by high dimensionality, complexity, and uncertainty in the node dynamic/interactions that require more and more computational demanding methods for their analysis and control design, as well as the network size and node system/interaction complexity increase. Therefore, it is a challenging problem to find scalable computational method for distributed control design of large-scale networks. In this paper, we investigate the robust distributed stabilisation problem of large-scale nonlinear multi-agent systems (briefly MASs) composed of non-identical (heterogeneous) linear dynamical systems coupled by uncertain nonlinear time-varying interconnections. By employing Lyapunov stability theory and linear matrix inequality (LMI) technique, new conditions are given for the distributed control design of large-scale MASs that can be easily solved by the toolbox of MATLAB. The stabilisability of each node dynamic is a sufficient assumption to design a global stabilising distributed control. The proposed approach improves some of the existing LMI-based results on MAS by both overcoming their computational limits and extending the applicative scenario to large-scale nonlinear heterogeneous MASs. Additionally, the proposed LMI conditions are further reduced in terms of computational requirement in the case of weakly heterogeneous MASs, which is a common scenario in real application where the network nodes and links are affected by parameter uncertainties. One of the main advantages of the proposed approach is to allow to move from a centralised towards a distributed computing architecture so that the expensive computation workload spent to solve LMIs may be shared among processors located at the networked nodes, thus increasing the scalability of the approach than the network size. Finally, a numerical example shows the applicability of the proposed method and its advantage in terms of computational complexity when compared with the existing approaches.

Computational Models of Consumer Confidence from Large-Scale Online Attention Data: Crowd-Sourcing Econometrics

PubMed Central

2015-01-01

Economies are instances of complex socio-technical systems that are shaped by the interactions of large numbers of individuals. The individual behavior and decision-making of consumer agents is determined by complex psychological dynamics that include their own assessment of present and future economic conditions as well as those of others, potentially leading to feedback loops that affect the macroscopic state of the economic system. We propose that the large-scale interactions of a nation's citizens with its online resources can reveal the complex dynamics of their collective psychology, including their assessment of future system states. Here we introduce a behavioral index of Chinese Consumer Confidence (C3I) that computationally relates large-scale online search behavior recorded by Google Trends data to the macroscopic variable of consumer confidence. Our results indicate that such computational indices may reveal the components and complex dynamics of consumer psychology as a collective socio-economic phenomenon, potentially leading to improved and more refined economic forecasting. PMID:25826692

Computational models of consumer confidence from large-scale online attention data: crowd-sourcing econometrics.

PubMed

Dong, Xianlei; Bollen, Johan

2015-01-01

Economies are instances of complex socio-technical systems that are shaped by the interactions of large numbers of individuals. The individual behavior and decision-making of consumer agents is determined by complex psychological dynamics that include their own assessment of present and future economic conditions as well as those of others, potentially leading to feedback loops that affect the macroscopic state of the economic system. We propose that the large-scale interactions of a nation's citizens with its online resources can reveal the complex dynamics of their collective psychology, including their assessment of future system states. Here we introduce a behavioral index of Chinese Consumer Confidence (C3I) that computationally relates large-scale online search behavior recorded by Google Trends data to the macroscopic variable of consumer confidence. Our results indicate that such computational indices may reveal the components and complex dynamics of consumer psychology as a collective socio-economic phenomenon, potentially leading to improved and more refined economic forecasting.

The birth of gravitational evolutionary dynamics of stellar systems (from Th. Wright to W. Herschel).

NASA Astrophysics Data System (ADS)

Eremeeva, A. J.

1995-05-01

Th. Wright, I. Kant and I. H. Lambert used well-known ideas about the structure and dynamics of the Solar system as a basis of their concepts of the stellar Universe. W. Herschel discovered the main features of the true, non-hierarchical large-scale structure of the Universe. He was also a pioneer of stellar dynamics with its new statistical laws and also of the theory of dynamical evolution in stellar systems at different scales.

Molecular dynamics simulations of large macromolecular complexes.

PubMed

Perilla, Juan R; Goh, Boon Chong; Cassidy, C Keith; Liu, Bo; Bernardi, Rafael C; Rudack, Till; Yu, Hang; Wu, Zhe; Schulten, Klaus

2015-04-01

Connecting dynamics to structural data from diverse experimental sources, molecular dynamics simulations permit the exploration of biological phenomena in unparalleled detail. Advances in simulations are moving the atomic resolution descriptions of biological systems into the million-to-billion atom regime, in which numerous cell functions reside. In this opinion, we review the progress, driven by large-scale molecular dynamics simulations, in the study of viruses, ribosomes, bioenergetic systems, and other diverse applications. These examples highlight the utility of molecular dynamics simulations in the critical task of relating atomic detail to the function of supramolecular complexes, a task that cannot be achieved by smaller-scale simulations or existing experimental approaches alone. Copyright © 2015 Elsevier Ltd. All rights reserved.

Phase Transitions and Scaling in Systems Far from Equilibrium

NASA Astrophysics Data System (ADS)

Täuber, Uwe C.

2017-03-01

Scaling ideas and renormalization group approaches proved crucial for a deep understanding and classification of critical phenomena in thermal equilibrium. Over the past decades, these powerful conceptual and mathematical tools were extended to continuous phase transitions separating distinct nonequilibrium stationary states in driven classical and quantum systems. In concordance with detailed numerical simulations and laboratory experiments, several prominent dynamical universality classes have emerged that govern large-scale, long-time scaling properties both near and far from thermal equilibrium. These pertain to genuine specific critical points as well as entire parameter space regions for steady states that display generic scale invariance. The exploration of nonstationary relaxation properties and associated physical aging scaling constitutes a complementary potent means to characterize cooperative dynamics in complex out-of-equilibrium systems. This review describes dynamic scaling features through paradigmatic examples that include near-equilibrium critical dynamics, driven lattice gases and growing interfaces, correlation-dominated reaction-diffusion systems, and basic epidemic models.

Asymptotic stability and instability of large-scale systems. [using vector Liapunov functions

NASA Technical Reports Server (NTRS)

Grujic, L. T.; Siljak, D. D.

1973-01-01

The purpose of this paper is to develop new methods for constructing vector Lyapunov functions and broaden the application of Lyapunov's theory to stability analysis of large-scale dynamic systems. The application, so far limited by the assumption that the large-scale systems are composed of exponentially stable subsystems, is extended via the general concept of comparison functions to systems which can be decomposed into asymptotically stable subsystems. Asymptotic stability of the composite system is tested by a simple algebraic criterion. By redefining interconnection functions among the subsystems according to interconnection matrices, the same mathematical machinery can be used to determine connective asymptotic stability of large-scale systems under arbitrary structural perturbations.

Stability of large-scale systems.

NASA Technical Reports Server (NTRS)

Siljak, D. D.

1972-01-01

The purpose of this paper is to present the results obtained in stability study of large-scale systems based upon the comparison principle and vector Liapunov functions. The exposition is essentially self-contained, with emphasis on recent innovations which utilize explicit information about the system structure. This provides a natural foundation for the stability theory of dynamic systems under structural perturbations.

Survey on large scale system control methods

NASA Technical Reports Server (NTRS)

Mercadal, Mathieu

1987-01-01

The problem inherent to large scale systems such as power network, communication network and economic or ecological systems were studied. The increase in size and flexibility of future spacecraft has put those dynamical systems into the category of large scale systems, and tools specific to the class of large systems are being sought to design control systems that can guarantee more stability and better performance. Among several survey papers, reference was found to a thorough investigation on decentralized control methods. Especially helpful was the classification made of the different existing approaches to deal with large scale systems. A very similar classification is used, even though the papers surveyed are somehow different from the ones reviewed in other papers. Special attention is brought to the applicability of the existing methods to controlling large mechanical systems like large space structures. Some recent developments are added to this survey.

Pynamic: the Python Dynamic Benchmark

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

Lee, G L; Ahn, D H; de Supinksi, B R

2007-07-10

Python is widely used in scientific computing to facilitate application development and to support features such as computational steering. Making full use of some of Python's popular features, which improve programmer productivity, leads to applications that access extremely high numbers of dynamically linked libraries (DLLs). As a result, some important Python-based applications severely stress a system's dynamic linking and loading capabilities and also cause significant difficulties for most development environment tools, such as debuggers. Furthermore, using the Python paradigm for large scale MPI-based applications can create significant file IO and further stress tools and operating systems. In this paper, wemore » present Pynamic, the first benchmark program to support configurable emulation of a wide-range of the DLL usage of Python-based applications for large scale systems. Pynamic has already accurately reproduced system software and tool issues encountered by important large Python-based scientific applications on our supercomputers. Pynamic provided insight for our system software and tool vendors, and our application developers, into the impact of several design decisions. As we describe the Pynamic benchmark, we will highlight some of the issues discovered in our large scale system software and tools using Pynamic.« less

A dynamical systems approach to studying midlatitude weather extremes

NASA Astrophysics Data System (ADS)

Messori, Gabriele; Caballero, Rodrigo; Faranda, Davide

2017-04-01

Extreme weather occurrences carry enormous social and economic costs and routinely garner widespread scientific and media coverage. The ability to predict these events is therefore a topic of crucial importance. Here we propose a novel predictability pathway for extreme events, by building upon recent advances in dynamical systems theory. We show that simple dynamical systems metrics can be used to identify sets of large-scale atmospheric flow patterns with similar spatial structure and temporal evolution on time scales of several days to a week. In regions where these patterns favor extreme weather, they afford a particularly good predictability of the extremes. We specifically test this technique on the atmospheric circulation in the North Atlantic region, where it provides predictability of large-scale wintertime surface temperature extremes in Europe up to 1 week in advance.

Multi-agent based control of large-scale complex systems employing distributed dynamic inference engine

NASA Astrophysics Data System (ADS)

Zhang, Daili

Increasing societal demand for automation has led to considerable efforts to control large-scale complex systems, especially in the area of autonomous intelligent control methods. The control system of a large-scale complex system needs to satisfy four system level requirements: robustness, flexibility, reusability, and scalability. Corresponding to the four system level requirements, there arise four major challenges. First, it is difficult to get accurate and complete information. Second, the system may be physically highly distributed. Third, the system evolves very quickly. Fourth, emergent global behaviors of the system can be caused by small disturbances at the component level. The Multi-Agent Based Control (MABC) method as an implementation of distributed intelligent control has been the focus of research since the 1970s, in an effort to solve the above-mentioned problems in controlling large-scale complex systems. However, to the author's best knowledge, all MABC systems for large-scale complex systems with significant uncertainties are problem-specific and thus difficult to extend to other domains or larger systems. This situation is partly due to the control architecture of multiple agents being determined by agent to agent coupling and interaction mechanisms. Therefore, the research objective of this dissertation is to develop a comprehensive, generalized framework for the control system design of general large-scale complex systems with significant uncertainties, with the focus on distributed control architecture design and distributed inference engine design. A Hybrid Multi-Agent Based Control (HyMABC) architecture is proposed by combining hierarchical control architecture and module control architecture with logical replication rings. First, it decomposes a complex system hierarchically; second, it combines the components in the same level as a module, and then designs common interfaces for all of the components in the same module; third, replications are made for critical agents and are organized into logical rings. This architecture maintains clear guidelines for complexity decomposition and also increases the robustness of the whole system. Multiple Sectioned Dynamic Bayesian Networks (MSDBNs) as a distributed dynamic probabilistic inference engine, can be embedded into the control architecture to handle uncertainties of general large-scale complex systems. MSDBNs decomposes a large knowledge-based system into many agents. Each agent holds its partial perspective of a large problem domain by representing its knowledge as a Dynamic Bayesian Network (DBN). Each agent accesses local evidence from its corresponding local sensors and communicates with other agents through finite message passing. If the distributed agents can be organized into a tree structure, satisfying the running intersection property and d-sep set requirements, globally consistent inferences are achievable in a distributed way. By using different frequencies for local DBN agent belief updating and global system belief updating, it balances the communication cost with the global consistency of inferences. In this dissertation, a fully factorized Boyen-Koller (BK) approximation algorithm is used for local DBN agent belief updating, and the static Junction Forest Linkage Tree (JFLT) algorithm is used for global system belief updating. MSDBNs assume a static structure and a stable communication network for the whole system. However, for a real system, sub-Bayesian networks as nodes could be lost, and the communication network could be shut down due to partial damage in the system. Therefore, on-line and automatic MSDBNs structure formation is necessary for making robust state estimations and increasing survivability of the whole system. A Distributed Spanning Tree Optimization (DSTO) algorithm, a Distributed D-Sep Set Satisfaction (DDSSS) algorithm, and a Distributed Running Intersection Satisfaction (DRIS) algorithm are proposed in this dissertation. Combining these three distributed algorithms and a Distributed Belief Propagation (DBP) algorithm in MSDBNs makes state estimations robust to partial damage in the whole system. Combining the distributed control architecture design and the distributed inference engine design leads to a process of control system design for a general large-scale complex system. As applications of the proposed methodology, the control system design of a simplified ship chilled water system and a notional ship chilled water system have been demonstrated step by step. Simulation results not only show that the proposed methodology gives a clear guideline for control system design for general large-scale complex systems with dynamic and uncertain environment, but also indicate that the combination of MSDBNs and HyMABC can provide excellent performance for controlling general large-scale complex systems.

Dynamical systems proxies of atmospheric predictability and mid-latitude extremes

NASA Astrophysics Data System (ADS)

Messori, Gabriele; Faranda, Davide; Caballero, Rodrigo; Yiou, Pascal

2017-04-01

Extreme weather ocurrences carry enormous social and economic costs and routinely garner widespread scientific and media coverage. Many extremes (for e.g. storms, heatwaves, cold spells, heavy precipitation) are tied to specific patterns of midlatitude atmospheric circulation. The ability to identify these patterns and use them to enhance the predictability of the extremes is therefore a topic of crucial societal and economic value. We propose a novel predictability pathway for extreme events, by building upon recent advances in dynamical systems theory. We use two simple dynamical systems metrics - local dimension and persistence - to identify sets of similar large-scale atmospheric flow patterns which present a coherent temporal evolution. When these patterns correspond to weather extremes, they therefore afford a particularly good forward predictability. We specifically test this technique on European winter temperatures, whose variability largely depends on the atmospheric circulation in the North Atlantic region. We find that our dynamical systems approach provides predictability of large-scale temperature extremes up to one week in advance.

Resolving Dynamic Properties of Polymers through Coarse-Grained Computational Studies

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

Salerno, K. Michael; Agrawal, Anupriya; Perahia, Dvora

2016-02-05

Coupled length and time scales determine the dynamic behavior of polymers and underlie their unique viscoelastic properties. To resolve the long-time dynamics it is imperative to determine which time and length scales must be correctly modeled. In this paper, we probe the degree of coarse graining required to simultaneously retain significant atomistic details and access large length and time scales. The degree of coarse graining in turn sets the minimum length scale instrumental in defining polymer properties and dynamics. Using linear polyethylene as a model system, we probe how the coarse-graining scale affects the measured dynamics. Iterative Boltzmann inversion ismore » used to derive coarse-grained potentials with 2–6 methylene groups per coarse-grained bead from a fully atomistic melt simulation. We show that atomistic detail is critical to capturing large-scale dynamics. Finally, using these models we simulate polyethylene melts for times over 500 μs to study the viscoelastic properties of well-entangled polymer melts.« less

Dynamic structural disorder in supported nanoscale catalysts

NASA Astrophysics Data System (ADS)

Rehr, J. J.; Vila, F. D.

2014-04-01

We investigate the origin and physical effects of "dynamic structural disorder" (DSD) in supported nano-scale catalysts. DSD refers to the intrinsic fluctuating, inhomogeneous structure of such nano-scale systems. In contrast to bulk materials, nano-scale systems exhibit substantial fluctuations in structure, charge, temperature, and other quantities, as well as large surface effects. The DSD is driven largely by the stochastic librational motion of the center of mass and fluxional bonding at the nanoparticle surface due to thermal coupling with the substrate. Our approach for calculating and understanding DSD is based on a combination of real-time density functional theory/molecular dynamics simulations, transient coupled-oscillator models, and statistical mechanics. This approach treats thermal and dynamic effects over multiple time-scales, and includes bond-stretching and -bending vibrations, and transient tethering to the substrate at longer ps time-scales. Potential effects on the catalytic properties of these clusters are briefly explored. Model calculations of molecule-cluster interactions and molecular dissociation reaction paths are presented in which the reactant molecules are adsorbed on the surface of dynamically sampled clusters. This model suggests that DSD can affect both the prefactors and distribution of energy barriers in reaction rates, and thus can significantly affect catalytic activity at the nano-scale.

Generalized Master Equation with Non-Markovian Multichromophoric Förster Resonance Energy Transfer for Modular Exciton Densities

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

Jang, Seogjoo; Hoyer, Stephan; Fleming, Graham

2014-10-31

A generalized master equation (GME) governing quantum evolution of modular exciton density (MED) is derived for large scale light harvesting systems composed of weakly interacting modules of multiple chromophores. The GME-MED offers a practical framework to incorporate real time coherent quantum dynamics calculations of small length scales into dynamics over large length scales, and also provides a non-Markovian generalization and rigorous derivation of the Pauli master equation employing multichromophoric Förster resonance energy transfer rates. A test of the GME-MED for four sites of the Fenna-Matthews-Olson complex demonstrates how coherent dynamics of excitonic populations over coupled chromophores can be accurately describedmore » by transitions between subgroups (modules) of delocalized excitons. Application of the GME-MED to the exciton dynamics between a pair of light harvesting complexes in purple bacteria demonstrates its promise as a computationally efficient tool to investigate large scale exciton dynamics in complex environments.« less

Potential utilization of the NASA/George C. Marshall Space Flight Center in earthquake engineering research

NASA Technical Reports Server (NTRS)

Scholl, R. E. (Editor)

1979-01-01

Earthquake engineering research capabilities of the National Aeronautics and Space Administration (NASA) facilities at George C. Marshall Space Flight Center (MSFC), Alabama, were evaluated. The results indicate that the NASA/MSFC facilities and supporting capabilities offer unique opportunities for conducting earthquake engineering research. Specific features that are particularly attractive for large scale static and dynamic testing of natural and man-made structures include the following: large physical dimensions of buildings and test bays; high loading capacity; wide range and large number of test equipment and instrumentation devices; multichannel data acquisition and processing systems; technical expertise for conducting large-scale static and dynamic testing; sophisticated techniques for systems dynamics analysis, simulation, and control; and capability for managing large-size and technologically complex programs. Potential uses of the facilities for near and long term test programs to supplement current earthquake research activities are suggested.

Chaotic dynamics of large-scale double-diffusive convection in a porous medium

NASA Astrophysics Data System (ADS)

Kondo, Shutaro; Gotoda, Hiroshi; Miyano, Takaya; Tokuda, Isao T.

2018-02-01

We have studied chaotic dynamics of large-scale double-diffusive convection of a viscoelastic fluid in a porous medium from the viewpoint of dynamical systems theory. A fifth-order nonlinear dynamical system modeling the double-diffusive convection is theoretically obtained by incorporating the Darcy-Brinkman equation into transport equations through a physical dimensionless parameter representing porosity. We clearly show that the chaotic convective motion becomes much more complicated with increasing porosity. The degree of dynamic instability during chaotic convective motion is quantified by two important measures: the network entropy of the degree distribution in the horizontal visibility graph and the Kaplan-Yorke dimension in terms of Lyapunov exponents. We also present an interesting on-off intermittent phenomenon in the probability distribution of time intervals exhibiting nearly complete synchronization.

Shake Test Results and Dynamic Calibration Efforts for the Large Rotor Test Apparatus

NASA Technical Reports Server (NTRS)

Russell, Carl R.

2014-01-01

A shake test of the Large Rotor Test Apparatus (LRTA) was performed in an effort to enhance NASAscapability to measure dynamic hub loads for full-scale rotor tests. This paper documents the results of theshake test as well as efforts to calibrate the LRTA balance system to measure dynamic loads.Dynamic rotor loads are the primary source of vibration in helicopters and other rotorcraft, leading topassenger discomfort and damage due to fatigue of aircraft components. There are novel methods beingdeveloped to reduce rotor vibrations, but measuring the actual vibration reductions on full-scale rotorsremains a challenge. In order to measure rotor forces on the LRTA, a balance system in the non-rotatingframe is used. The forces at the balance can then be translated to the hub reference frame to measure therotor loads. Because the LRTA has its own dynamic response, the balance system must be calibrated toinclude the natural frequencies of the test rig.

Resolving Properties of Polymers and Nanoparticle Assembly through Coarse-Grained Computational Studies.

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

Grest, Gary S.

2017-09-01

Coupled length and time scales determine the dynamic behavior of polymers and polymer nanocomposites and underlie their unique properties. To resolve the properties over large time and length scales it is imperative to develop coarse grained models which retain the atomistic specificity. Here we probe the degree of coarse graining required to simultaneously retain significant atomistic details a nd access large length and time scales. The degree of coarse graining in turn sets the minimum length scale instrumental in defining polymer properties and dynamics. Using polyethylene as a model system, we probe how the coarse - graining scale affects themore » measured dynamics with different number methylene group s per coarse - grained beads. Using these models we simulate polyethylene melts for times over 500 ms to study the viscoelastic properties of well - entangled polymer melts and large nanoparticle assembly as the nanoparticles are driven close enough to form nanostructures.« less

The influence of cosmic rays on the stability and large-scale dynamics of the interstellar medium

NASA Astrophysics Data System (ADS)

Kuznetsov, V. D.

1986-06-01

The diffusion-convection formulation is used to study the influence of galactic cosmic rays on the stability and dynamics of the interstellar medium which is supposedly kept in equilibrium by the gravitational field of stars. It is shown that the influence of cosmic rays on the growth rate of MHD instability depends largely on a dimensionless parameter expressing the ratio of the characteristic acoustic time scale to the cosmic-ray diffusion time. If this parameter is small, the cosmic rays will decelerate the build-up of instabilities, thereby stabilizing the system; in contrast, if the parameter is large, the system will be destabilized.

Collective motion of macroscopic spheres floating on capillary ripples: Dynamic heterogeneity and dynamic criticality

NASA Astrophysics Data System (ADS)

Sanlı, Ceyda; Saitoh, Kuniyasu; Luding, Stefan; van der Meer, Devaraj

2014-09-01

When a densely packed monolayer of macroscopic spheres floats on chaotic capillary Faraday waves, a coexistence of large scale convective motion and caging dynamics typical for glassy systems is observed. We subtract the convective mean flow using a coarse graining (homogenization) method and reveal subdiffusion for the caging time scales followed by a diffusive regime at later times. We apply the methods developed to study dynamic heterogeneity and show that the typical time and length scales of the fluctuations due to rearrangements of observed particle groups significantly increase when the system approaches its largest experimentally accessible packing concentration. To connect the system to the dynamic criticality literature, we fit power laws to our results. The resultant critical exponents are consistent with those found in densely packed suspensions of colloids.

Collective motion of macroscopic spheres floating on capillary ripples: dynamic heterogeneity and dynamic criticality.

PubMed

Sanlı, Ceyda; Saitoh, Kuniyasu; Luding, Stefan; van der Meer, Devaraj

2014-09-01

When a densely packed monolayer of macroscopic spheres floats on chaotic capillary Faraday waves, a coexistence of large scale convective motion and caging dynamics typical for glassy systems is observed. We subtract the convective mean flow using a coarse graining (homogenization) method and reveal subdiffusion for the caging time scales followed by a diffusive regime at later times. We apply the methods developed to study dynamic heterogeneity and show that the typical time and length scales of the fluctuations due to rearrangements of observed particle groups significantly increase when the system approaches its largest experimentally accessible packing concentration. To connect the system to the dynamic criticality literature, we fit power laws to our results. The resultant critical exponents are consistent with those found in densely packed suspensions of colloids.

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.

Modeling systems-level dynamics: Understanding without mechanistic explanation in integrative systems biology.

PubMed

MacLeod, Miles; Nersessian, Nancy J

2015-02-01

In this paper we draw upon rich ethnographic data of two systems biology labs to explore the roles of explanation and understanding in large-scale systems modeling. We illustrate practices that depart from the goal of dynamic mechanistic explanation for the sake of more limited modeling goals. These processes use abstract mathematical formulations of bio-molecular interactions and data fitting techniques which we call top-down abstraction to trade away accurate mechanistic accounts of large-scale systems for specific information about aspects of those systems. We characterize these practices as pragmatic responses to the constraints many modelers of large-scale systems face, which in turn generate more limited pragmatic non-mechanistic forms of understanding of systems. These forms aim at knowledge of how to predict system responses in order to manipulate and control some aspects of them. We propose that this analysis of understanding provides a way to interpret what many systems biologists are aiming for in practice when they talk about the objective of a "systems-level understanding." Copyright © 2014 Elsevier Ltd. All rights reserved.

Efficient On-Demand Operations in Large-Scale Infrastructures

ERIC Educational Resources Information Center

Ko, Steven Y.

2009-01-01

In large-scale distributed infrastructures such as clouds, Grids, peer-to-peer systems, and wide-area testbeds, users and administrators typically desire to perform "on-demand operations" that deal with the most up-to-date state of the infrastructure. However, the scale and dynamism present in the operating environment make it challenging to…

Tools for Large-Scale Mobile Malware Analysis

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

Bierma, Michael

Analyzing mobile applications for malicious behavior is an important area of re- search, and is made di cult, in part, by the increasingly large number of appli- cations available for the major operating systems. There are currently over 1.2 million apps available in both the Google Play and Apple App stores (the respec- tive o cial marketplaces for the Android and iOS operating systems)[1, 2]. Our research provides two large-scale analysis tools to aid in the detection and analysis of mobile malware. The rst tool we present, Andlantis, is a scalable dynamic analysis system capa- ble of processing over 3000more » Android applications per hour. Traditionally, Android dynamic analysis techniques have been relatively limited in scale due to the compu- tational resources required to emulate the full Android system to achieve accurate execution. Andlantis is the most scalable Android dynamic analysis framework to date, and is able to collect valuable forensic data, which helps reverse-engineers and malware researchers identify and understand anomalous application behavior. We discuss the results of running 1261 malware samples through the system, and provide examples of malware analysis performed with the resulting data. While techniques exist to perform static analysis on a large number of appli- cations, large-scale analysis of iOS applications has been relatively small scale due to the closed nature of the iOS ecosystem, and the di culty of acquiring appli- cations for analysis. The second tool we present, iClone, addresses the challenges associated with iOS research in order to detect application clones within a dataset of over 20,000 iOS applications.« less

Local dynamics and spatiotemporal chaos. The Kuramoto- Sivashinsky equation: A case study

NASA Astrophysics Data System (ADS)

Wittenberg, Ralf Werner

The nature of spatiotemporal chaos in extended continuous systems is not yet well-understood. In this thesis, a model partial differential equation, the Kuramoto- Sivashinsky (KS) equation ut+uxxxx+uxx+uux =0 on a large one-dimensional periodic domain, is studied analytically, numerically, and through modeling to obtain a more detailed understanding of the observed spatiotemporally complex dynamics. In particular, with the aid of a wavelet decomposition, the relevant dynamical interactions are shown to be localized in space and scale. Motivated by these results, and by the idea that the attractor on a large domain may be understood via attractors on smaller domains, a spatially localized low- dimensional model for a minimal chaotic box is proposed. A (de)stabilized extension of the KS equation has recently attracted increased interest; for this situation, dissipativity and analyticity areproven, and an explicit shock-like solution is constructed which sheds light on the difficulties in obtaining optimal bounds for the KS equation. For the usual KS equation, the spatiotemporally chaotic state is carefully characterized in real, Fourier and wavelet space. The wavelet decomposition provides good scale separation which isolates the three characteristic regions of the dynamics: large scales of slow Gaussian fluctuations, active scales containing localized interactions of coherent structures, and small scales. Space localization is shown through a comparison of various correlation lengths and a numerical experiment in which different modes are uncoupled to estimate a dynamic interaction length. A detailed picture of the contributions of different scales to the spatiotemporally complex dynamics is obtained via a Galerkin projection of the KS equation onto the wavelet basis, and an extensive series of numerical experiments in which different combinations of wavelet levels are eliminated or forced. These results, and a formalism to derive an effective equation for periodized subsystems externally forced from a larger system, motivate various models for spatially localized forced systems. There is convincing evidence that short periodized systems, internally forced at the largest scales, form a minimal model for the observed extensively chaotic dynamics in larger domains.

Wafer-scale pixelated detector system

DOEpatents

Fahim, Farah; Deptuch, Grzegorz; Zimmerman, Tom

2017-10-17

A large area, gapless, detection system comprises at least one sensor; an interposer operably connected to the at least one sensor; and at least one application specific integrated circuit operably connected to the sensor via the interposer wherein the detection system provides high dynamic range while maintaining small pixel area and low power dissipation. Thereby the invention provides methods and systems for a wafer-scale gapless and seamless detector systems with small pixels, which have both high dynamic range and low power dissipation.

Forecasting of magnitude and duration of currency crises based on the analysis of distortions of fractal scaling in exchange rate fluctuations

NASA Astrophysics Data System (ADS)

Uritskaya, Olga Y.

2005-05-01

Results of fractal stability analysis of daily exchange rate fluctuations of more than 30 floating currencies for a 10-year period are presented. It is shown for the first time that small- and large-scale dynamical instabilities of national monetary systems correlate with deviations of the detrended fluctuation analysis (DFA) exponent from the value 1.5 predicted by the efficient market hypothesis. The observed dependence is used for classification of long-term stability of floating exchange rates as well as for revealing various forms of distortion of stable currency dynamics prior to large-scale crises. A normal range of DFA exponents consistent with crisis-free long-term exchange rate fluctuations is determined, and several typical scenarios of unstable currency dynamics with DFA exponents fluctuating beyond the normal range are identified. It is shown that monetary crashes are usually preceded by prolonged periods of abnormal (decreased or increased) DFA exponent, with the after-crash exponent tending to the value 1.5 indicating a more reliable exchange rate dynamics. Statistically significant regression relations (R=0.99, p<0.01) between duration and magnitude of currency crises and the degree of distortion of monofractal patterns of exchange rate dynamics are found. It is demonstrated that the parameters of these relations characterizing small- and large-scale crises are nearly equal, which implies a common instability mechanism underlying these events. The obtained dependences have been used as a basic ingredient of a forecasting technique which provided correct in-sample predictions of monetary crisis magnitude and duration over various time scales. The developed technique can be recommended for real-time monitoring of dynamical stability of floating exchange rate systems and creating advanced early-warning-system models for currency crisis prevention.

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

Rizzi, Silvio; Hereld, Mark; Insley, Joseph

In this work we perform in-situ visualization of molecular dynamics simulations, which can help scientists to visualize simulation output on-the-fly, without incurring storage overheads. We present a case study to couple LAMMPS, the large-scale molecular dynamics simulation code with vl3, our parallel framework for large-scale visualization and analysis. Our motivation is to identify effective approaches for covisualization and exploration of large-scale atomistic simulations at interactive frame rates.We propose a system of coupled libraries and describe its architecture, with an implementation that runs on GPU-based clusters. We present the results of strong and weak scalability experiments, as well as future researchmore » avenues based on our results.« less

Large-area photogrammetry based testing of wind turbine blades

NASA Astrophysics Data System (ADS)

Poozesh, Peyman; Baqersad, Javad; Niezrecki, Christopher; Avitabile, Peter; Harvey, Eric; Yarala, Rahul

2017-03-01

An optically based sensing system that can measure the displacement and strain over essentially the entire area of a utility-scale blade leads to a measurement system that can significantly reduce the time and cost associated with traditional instrumentation. This paper evaluates the performance of conventional three dimensional digital image correlation (3D DIC) and three dimensional point tracking (3DPT) approaches over the surface of wind turbine blades and proposes a multi-camera measurement system using dynamic spatial data stitching. The potential advantages for the proposed approach include: (1) full-field measurement distributed over a very large area, (2) the elimination of time-consuming wiring and expensive sensors, and (3) the need for large-channel data acquisition systems. There are several challenges associated with extending the capability of a standard 3D DIC system to measure entire surface of utility scale blades to extract distributed strain, deflection, and modal parameters. This paper only tries to address some of the difficulties including: (1) assessing the accuracy of the 3D DIC system to measure full-field distributed strain and displacement over the large area, (2) understanding the geometrical constraints associated with a wind turbine testing facility (e.g. lighting, working distance, and speckle pattern size), (3) evaluating the performance of the dynamic stitching method to combine two different fields of view by extracting modal parameters from aligned point clouds, and (4) determining the feasibility of employing an output-only system identification to estimate modal parameters of a utility scale wind turbine blade from optically measured data. Within the current work, the results of an optical measurement (one stereo-vision system) performed on a large area over a 50-m utility-scale blade subjected to quasi-static and cyclic loading are presented. The blade certification and testing is typically performed using International Electro-Technical Commission standard (IEC 61400-23). For static tests, the blade is pulled in either flap-wise or edge-wise directions to measure deflection or distributed strain at a few limited locations of a large-sized blade. Additionally, the paper explores the error associated with using a multi-camera system (two stereo-vision systems) in measuring 3D displacement and extracting structural dynamic parameters on a mock set up emulating a utility-scale wind turbine blade. The results obtained in this paper reveal that the multi-camera measurement system has the potential to identify the dynamic characteristics of a very large structure.

On decentralized control of large-scale systems

NASA Technical Reports Server (NTRS)

Siljak, D. D.

1978-01-01

A scheme is presented for decentralized control of large-scale linear systems which are composed of a number of interconnected subsystems. By ignoring the interconnections, local feedback controls are chosen to optimize each decoupled subsystem. Conditions are provided to establish compatibility of the individual local controllers and achieve stability of the overall system. Besides computational simplifications, the scheme is attractive because of its structural features and the fact that it produces a robust decentralized regulator for large dynamic systems, which can tolerate a wide range of nonlinearities and perturbations among the subsystems.

Methods of information geometry in computational system biology (consistency between chemical and biological evolution).

PubMed

Astakhov, Vadim

2009-01-01

Interest in simulation of large-scale metabolic networks, species development, and genesis of various diseases requires new simulation techniques to accommodate the high complexity of realistic biological networks. Information geometry and topological formalisms are proposed to analyze information processes. We analyze the complexity of large-scale biological networks as well as transition of the system functionality due to modification in the system architecture, system environment, and system components. The dynamic core model is developed. The term dynamic core is used to define a set of causally related network functions. Delocalization of dynamic core model provides a mathematical formalism to analyze migration of specific functions in biosystems which undergo structure transition induced by the environment. The term delocalization is used to describe these processes of migration. We constructed a holographic model with self-poetic dynamic cores which preserves functional properties under those transitions. Topological constraints such as Ricci flow and Pfaff dimension were found for statistical manifolds which represent biological networks. These constraints can provide insight on processes of degeneration and recovery which take place in large-scale networks. We would like to suggest that therapies which are able to effectively implement estimated constraints, will successfully adjust biological systems and recover altered functionality. Also, we mathematically formulate the hypothesis that there is a direct consistency between biological and chemical evolution. Any set of causal relations within a biological network has its dual reimplementation in the chemistry of the system environment.

Chaos in high-dimensional dissipative dynamical systems

PubMed Central

Ispolatov, Iaroslav; Madhok, Vaibhav; Allende, Sebastian; Doebeli, Michael

2015-01-01

For dissipative dynamical systems described by a system of ordinary differential equations, we address the question of how the probability of chaotic dynamics increases with the dimensionality of the phase space. We find that for a system of d globally coupled ODE’s with quadratic and cubic non-linearities with randomly chosen coefficients and initial conditions, the probability of a trajectory to be chaotic increases universally from ~10−5 − 10−4 for d = 3 to essentially one for d ~ 50. In the limit of large d, the invariant measure of the dynamical systems exhibits universal scaling that depends on the degree of non-linearity, but not on the choice of coefficients, and the largest Lyapunov exponent converges to a universal scaling limit. Using statistical arguments, we provide analytical explanations for the observed scaling, universality, and for the probability of chaos. PMID:26224119

Theory of wavelet-based coarse-graining hierarchies for molecular dynamics.

PubMed

Rinderspacher, Berend Christopher; Bardhan, Jaydeep P; Ismail, Ahmed E

2017-07-01

We present a multiresolution approach to compressing the degrees of freedom and potentials associated with molecular dynamics, such as the bond potentials. The approach suggests a systematic way to accelerate large-scale molecular simulations with more than two levels of coarse graining, particularly applications of polymeric materials. In particular, we derive explicit models for (arbitrarily large) linear (homo)polymers and iterative methods to compute large-scale wavelet decompositions from fragment solutions. This approach does not require explicit preparation of atomistic-to-coarse-grained mappings, but instead uses the theory of diffusion wavelets for graph Laplacians to develop system-specific mappings. Our methodology leads to a hierarchy of system-specific coarse-grained degrees of freedom that provides a conceptually clear and mathematically rigorous framework for modeling chemical systems at relevant model scales. The approach is capable of automatically generating as many coarse-grained model scales as necessary, that is, to go beyond the two scales in conventional coarse-grained strategies; furthermore, the wavelet-based coarse-grained models explicitly link time and length scales. Furthermore, a straightforward method for the reintroduction of omitted degrees of freedom is presented, which plays a major role in maintaining model fidelity in long-time simulations and in capturing emergent behaviors.

Systematic methods for defining coarse-grained maps in large biomolecules.

PubMed

Zhang, Zhiyong

2015-01-01

Large biomolecules are involved in many important biological processes. It would be difficult to use large-scale atomistic molecular dynamics (MD) simulations to study the functional motions of these systems because of the computational expense. Therefore various coarse-grained (CG) approaches have attracted rapidly growing interest, which enable simulations of large biomolecules over longer effective timescales than all-atom MD simulations. The first issue in CG modeling is to construct CG maps from atomic structures. In this chapter, we review the recent development of a novel and systematic method for constructing CG representations of arbitrarily complex biomolecules, in order to preserve large-scale and functionally relevant essential dynamics (ED) at the CG level. In this ED-CG scheme, the essential dynamics can be characterized by principal component analysis (PCA) on a structural ensemble, or elastic network model (ENM) of a single atomic structure. Validation and applications of the method cover various biological systems, such as multi-domain proteins, protein complexes, and even biomolecular machines. The results demonstrate that the ED-CG method may serve as a very useful tool for identifying functional dynamics of large biomolecules at the CG level.

Slow dynamics in translation-invariant quantum lattice models

NASA Astrophysics Data System (ADS)

Michailidis, Alexios A.; Žnidarič, Marko; Medvedyeva, Mariya; Abanin, Dmitry A.; Prosen, Tomaž; Papić, Z.

2018-03-01

Many-body quantum systems typically display fast dynamics and ballistic spreading of information. Here we address the open problem of how slow the dynamics can be after a generic breaking of integrability by local interactions. We develop a method based on degenerate perturbation theory that reveals slow dynamical regimes and delocalization processes in general translation invariant models, along with accurate estimates of their delocalization time scales. Our results shed light on the fundamental questions of the robustness of quantum integrable systems and the possibility of many-body localization without disorder. As an example, we construct a large class of one-dimensional lattice models where, despite the absence of asymptotic localization, the transient dynamics is exceptionally slow, i.e., the dynamics is indistinguishable from that of many-body localized systems for the system sizes and time scales accessible in experiments and numerical simulations.

Stability of large-scale systems with stable and unstable subsystems.

NASA Technical Reports Server (NTRS)

Grujic, Lj. T.; Siljak, D. D.

1972-01-01

The purpose of this paper is to develop new methods for constructing vector Liapunov functions and broaden the application of Liapunov's theory to stability analysis of large-scale dynamic systems. The application, so far limited by the assumption that the large-scale systems are composed of exponentially stable subsystems, is extended via the general concept of comparison functions to systems which can be decomposed into asymptotically stable subsystems. Asymptotic stability of the composite system is tested by a simple algebraic criterion. With minor technical adjustments, the same criterion can be used to determine connective asymptotic stability of large-scale systems subject to structural perturbations. By redefining the constraints imposed on the interconnections among the subsystems, the considered class of systems is broadened in an essential way to include composite systems with unstable subsystems. In this way, the theory is brought substantially closer to reality since stability of all subsystems is no longer a necessary assumption in establishing stability of the overall composite system.

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.

New approach to study mobility in the vicinity of dynamical arrest; exact application to a kinetically constrained model

NASA Astrophysics Data System (ADS)

DeGregorio, P.; Lawlor, A.; Dawson, K. A.

2006-04-01

We introduce a new method to describe systems in the vicinity of dynamical arrest. This involves a map that transforms mobile systems at one length scale to mobile systems at a longer length. This map is capable of capturing the singular behavior accrued across very large length scales, and provides a direct route to the dynamical correlation length and other related quantities. The ideas are immediately applicable in two spatial dimensions, and have been applied to a modified Kob-Andersen type model. For such systems the map may be derived in an exact form, and readily solved numerically. We obtain the asymptotic behavior across the whole physical domain of interest in dynamical arrest.

Towards the computation of time-periodic inertial range dynamics

NASA Astrophysics Data System (ADS)

van Veen, L.; Vela-Martín, A.; Kawahara, G.

2018-04-01

We explore the possibility of computing simple invariant solutions, like travelling waves or periodic orbits, in Large Eddy Simulation (LES) on a periodic domain with constant external forcing. The absence of material boundaries and the simple forcing mechanism make this system a comparatively simple target for the study of turbulent dynamics through invariant solutions. We show, that in spite of the application of eddy viscosity the computations are still rather challenging and must be performed on GPU cards rather than conventional coupled CPUs. We investigate the onset of turbulence in this system by means of bifurcation analysis, and present a long-period, large-amplitude unstable periodic orbit that is filtered from a turbulent time series. Although this orbit is computed on a coarse grid, with only a small separation between the integral scale and the LES filter length, the periodic dynamics seem to capture a regeneration process of the large-scale vortices.

Large-Scale Dynamics of the Magnetospheric Boundary: Comparisons between Global MHD Simulation Results and ISTP Observations

NASA Technical Reports Server (NTRS)

Berchem, J.; Raeder, J.; Ashour-Abdalla, M.; Frank, L. A.; Paterson, W. R.; Ackerson, K. L.; Kokubun, S.; Yamamoto, T.; Lepping, R. P.

1998-01-01

Understanding the large-scale dynamics of the magnetospheric boundary is an important step towards achieving the ISTP mission's broad objective of assessing the global transport of plasma and energy through the geospace environment. Our approach is based on three-dimensional global magnetohydrodynamic (MHD) simulations of the solar wind-magnetosphere- ionosphere system, and consists of using interplanetary magnetic field (IMF) and plasma parameters measured by solar wind monitors upstream of the bow shock as input to the simulations for predicting the large-scale dynamics of the magnetospheric boundary. The validity of these predictions is tested by comparing local data streams with time series measured by downstream spacecraft crossing the magnetospheric boundary. In this paper, we review results from several case studies which confirm that our MHD model reproduces very well the large-scale motion of the magnetospheric boundary. The first case illustrates the complexity of the magnetic field topology that can occur at the dayside magnetospheric boundary for periods of northward IMF with strong Bx and By components. The second comparison reviewed combines dynamic and topological aspects in an investigation of the evolution of the distant tail at 200 R(sub E) from the Earth.

Drivers and seasonal predictability of extreme wind speeds in the ECMWF System 4 and a statistical model

NASA Astrophysics Data System (ADS)

Walz, M. A.; Donat, M.; Leckebusch, G. C.

2017-12-01

As extreme wind speeds are responsible for large socio-economic losses in Europe, a skillful prediction would be of great benefit for disaster prevention as well as for the actuarial community. Here we evaluate patterns of large-scale atmospheric variability and the seasonal predictability of extreme wind speeds (e.g. >95th percentile) in the European domain in the dynamical seasonal forecast system ECMWF System 4, and compare to the predictability based on a statistical prediction model. The dominant patterns of atmospheric variability show distinct differences between reanalysis and ECMWF System 4, with most patterns in System 4 extended downstream in comparison to ERA-Interim. The dissimilar manifestations of the patterns within the two models lead to substantially different drivers associated with the occurrence of extreme winds in the respective model. While the ECMWF System 4 is shown to provide some predictive power over Scandinavia and the eastern Atlantic, only very few grid cells in the European domain have significant correlations for extreme wind speeds in System 4 compared to ERA-Interim. In contrast, a statistical model predicts extreme wind speeds during boreal winter in better agreement with the observations. Our results suggest that System 4 does not seem to capture the potential predictability of extreme winds that exists in the real world, and therefore fails to provide reliable seasonal predictions for lead months 2-4. This is likely related to the unrealistic representation of large-scale patterns of atmospheric variability. Hence our study points to potential improvements of dynamical prediction skill by improving the simulation of large-scale atmospheric dynamics.

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.

Dynamic security contingency screening and ranking using neural networks.

PubMed

Mansour, Y; Vaahedi, E; El-Sharkawi, M A

1997-01-01

This paper summarizes BC Hydro's experience in applying neural networks to dynamic security contingency screening and ranking. The idea is to use the information on the prevailing operating condition and directly provide contingency screening and ranking using a trained neural network. To train the two neural networks for the large scale systems of BC Hydro and Hydro Quebec, in total 1691 detailed transient stability simulation were conducted, 1158 for BC Hydro system and 533 for the Hydro Quebec system. The simulation program was equipped with the energy margin calculation module (second kick) to measure the energy margin in each run. The first set of results showed poor performance for the neural networks in assessing the dynamic security. However a number of corrective measures improved the results significantly. These corrective measures included: 1) the effectiveness of output; 2) the number of outputs; 3) the type of features (static versus dynamic); 4) the number of features; 5) system partitioning; and 6) the ratio of training samples to features. The final results obtained using the large scale systems of BC Hydro and Hydro Quebec demonstrates a good potential for neural network in dynamic security assessment contingency screening and ranking.

Decentralized adaptive neural control for high-order interconnected stochastic nonlinear time-delay systems with unknown system dynamics.

PubMed

Si, Wenjie; Dong, Xunde; Yang, Feifei

2018-03-01

This paper is concerned with the problem of decentralized adaptive backstepping state-feedback control for uncertain high-order large-scale stochastic nonlinear time-delay systems. For the control design of high-order large-scale nonlinear systems, only one adaptive parameter is constructed to overcome the over-parameterization, and neural networks are employed to cope with the difficulties raised by completely unknown system dynamics and stochastic disturbances. And then, the appropriate Lyapunov-Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions of high-order large-scale systems for the first time. At last, on the basis of Lyapunov stability theory, the decentralized adaptive neural controller was developed, and it decreases the number of learning parameters. The actual controller can be designed so as to ensure that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error converges in the small neighborhood of zero. The simulation example is used to further show the validity of the design method. Copyright © 2018 Elsevier Ltd. All rights reserved.

Large-scale systems: Complexity, stability, reliability

NASA Technical Reports Server (NTRS)

Siljak, D. D.

1975-01-01

After showing that a complex dynamic system with a competitive structure has highly reliable stability, a class of noncompetitive dynamic systems for which competitive models can be constructed is defined. It is shown that such a construction is possible in the context of the hierarchic stability analysis. The scheme is based on the comparison principle and vector Liapunov functions.

The Dynamic Earth.

ERIC Educational Resources Information Center

Siever, Raymond

1983-01-01

Discusses how the earth is a dynamic system that maintains itself in a steady state. Areas considered include large/small-scale earth motions, geologic time, rock and hydrologic cycles, and other aspects dealing with the changing face of the earth. (JN)

Investigating large-scale brain dynamics using field potential recordings: analysis and interpretation.

PubMed

Pesaran, Bijan; Vinck, Martin; Einevoll, Gaute T; Sirota, Anton; Fries, Pascal; Siegel, Markus; Truccolo, Wilson; Schroeder, Charles E; Srinivasan, Ramesh

2018-06-25

New technologies to record electrical activity from the brain on a massive scale offer tremendous opportunities for discovery. Electrical measurements of large-scale brain dynamics, termed field potentials, are especially important to understanding and treating the human brain. Here, our goal is to provide best practices on how field potential recordings (electroencephalograms, magnetoencephalograms, electrocorticograms and local field potentials) can be analyzed to identify large-scale brain dynamics, and to highlight critical issues and limitations of interpretation in current work. We focus our discussion of analyses around the broad themes of activation, correlation, communication and coding. We provide recommendations for interpreting the data using forward and inverse models. The forward model describes how field potentials are generated by the activity of populations of neurons. The inverse model describes how to infer the activity of populations of neurons from field potential recordings. A recurring theme is the challenge of understanding how field potentials reflect neuronal population activity given the complexity of the underlying brain systems.

Improving predictions of large scale soil carbon dynamics: Integration of fine-scale hydrological and biogeochemical processes, scaling, and benchmarking

NASA Astrophysics Data System (ADS)

Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.

2015-12-01

Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we contend that creating believable soil carbon predictions requires a robust, transparent, and community-available benchmarking framework. I will present an ILAMB evaluation of several of the above-mentioned approaches in ACME, and attempt to motivate community adoption of this evaluation approach.

HFSB-seeding for large-scale tomographic PIV in wind tunnels

NASA Astrophysics Data System (ADS)

Caridi, Giuseppe Carlo Alp; Ragni, Daniele; Sciacchitano, Andrea; Scarano, Fulvio

2016-12-01

A new system for large-scale tomographic particle image velocimetry in low-speed wind tunnels is presented. The system relies upon the use of sub-millimetre helium-filled soap bubbles as flow tracers, which scatter light with intensity several orders of magnitude higher than micron-sized droplets. With respect to a single bubble generator, the system increases the rate of bubbles emission by means of transient accumulation and rapid release. The governing parameters of the system are identified and discussed, namely the bubbles production rate, the accumulation and release times, the size of the bubble injector and its location with respect to the wind tunnel contraction. The relations between the above parameters, the resulting spatial concentration of tracers and measurement of dynamic spatial range are obtained and discussed. Large-scale experiments are carried out in a large low-speed wind tunnel with 2.85 × 2.85 m2 test section, where a vertical axis wind turbine of 1 m diameter is operated. Time-resolved tomographic PIV measurements are taken over a measurement volume of 40 × 20 × 15 cm3, allowing the quantitative analysis of the tip-vortex structure and dynamical evolution.

Large-Scale First-Principles Molecular Dynamics Simulations with Electrostatic Embedding: Application to Acetylcholinesterase Catalysis

DOE PAGES

Fattebert, Jean-Luc; Lau, Edmond Y.; Bennion, Brian J.; ...

2015-10-22

Enzymes are complicated solvated systems that typically require many atoms to simulate their function with any degree of accuracy. We have recently developed numerical techniques for large scale First-Principles molecular dynamics simulations and applied them to study the enzymatic reaction catalyzed by acetylcholinesterase. We carried out Density functional theory calculations for a quantum mechanical (QM) sub- system consisting of 612 atoms with an O(N) complexity finite-difference approach. The QM sub-system is embedded inside an external potential field representing the electrostatic effect due to the environment. We obtained finite temperature sampling by First-Principles molecular dynamics for the acylation reaction of acetylcholinemore » catalyzed by acetylcholinesterase. Our calculations shows two energies barriers along the reaction coordinate for the enzyme catalyzed acylation of acetylcholine. In conclusion, the second barrier (8.5 kcal/mole) is rate-limiting for the acylation reaction and in good agreement with experiment.« less

Preliminary design, analysis, and costing of a dynamic scale model of the NASA space station

NASA Technical Reports Server (NTRS)

Gronet, M. J.; Pinson, E. D.; Voqui, H. L.; Crawley, E. F.; Everman, M. R.

1987-01-01

The difficulty of testing the next generation of large flexible space structures on the ground places an emphasis on other means for validating predicted on-orbit dynamic behavior. Scale model technology represents one way of verifying analytical predictions with ground test data. This study investigates the preliminary design, scaling and cost trades for a Space Station dynamic scale model. The scaling of nonlinear joint behavior is studied from theoretical and practical points of view. Suspension system interaction trades are conducted for the ISS Dual Keel Configuration and Build-Up Stages suspended in the proposed NASA/LaRC Large Spacecraft Laboratory. Key issues addressed are scaling laws, replication vs. simulation of components, manufacturing, suspension interactions, joint behavior, damping, articulation capability, and cost. These issues are the subject of parametric trades versus the scale model factor. The results of these detailed analyses are used to recommend scale factors for four different scale model options, each with varying degrees of replication. Potential problems in constructing and testing the scale model are identified, and recommendations for further study are outlined.

Overcoming potential energy distortions in constrained internal coordinate molecular dynamics simulations.

PubMed

Kandel, Saugat; Salomon-Ferrer, Romelia; Larsen, Adrien B; Jain, Abhinandan; Vaidehi, Nagarajan

2016-01-28

The Internal Coordinate Molecular Dynamics (ICMD) method is an attractive molecular dynamics (MD) method for studying the dynamics of bonded systems such as proteins and polymers. It offers a simple venue for coarsening the dynamics model of a system at multiple hierarchical levels. For example, large scale protein dynamics can be studied using torsional dynamics, where large domains or helical structures can be treated as rigid bodies and the loops connecting them as flexible torsions. ICMD with such a dynamic model of the protein, combined with enhanced conformational sampling method such as temperature replica exchange, allows the sampling of large scale domain motion involving high energy barrier transitions. Once these large scale conformational transitions are sampled, all-torsion, or even all-atom, MD simulations can be carried out for the low energy conformations sampled via coarse grained ICMD to calculate the energetics of distinct conformations. Such hierarchical MD simulations can be carried out with standard all-atom forcefields without the need for compromising on the accuracy of the forces. Using constraints to treat bond lengths and bond angles as rigid can, however, distort the potential energy landscape of the system and reduce the number of dihedral transitions as well as conformational sampling. We present here a two-part solution to overcome such distortions of the potential energy landscape with ICMD models. To alleviate the intrinsic distortion that stems from the reduced phase space in torsional MD, we use the Fixman compensating potential. To additionally alleviate the extrinsic distortion that arises from the coupling between the dihedral angles and bond angles within a force field, we propose a hybrid ICMD method that allows the selective relaxing of bond angles. This hybrid ICMD method bridges the gap between all-atom MD and torsional MD. We demonstrate with examples that these methods together offer a solution to eliminate the potential energy distortions encountered in constrained ICMD simulations of peptide molecules.

Overcoming potential energy distortions in constrained internal coordinate molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Kandel, Saugat; Salomon-Ferrer, Romelia; Larsen, Adrien B.; Jain, Abhinandan; Vaidehi, Nagarajan

2016-01-01

The Internal Coordinate Molecular Dynamics (ICMD) method is an attractive molecular dynamics (MD) method for studying the dynamics of bonded systems such as proteins and polymers. It offers a simple venue for coarsening the dynamics model of a system at multiple hierarchical levels. For example, large scale protein dynamics can be studied using torsional dynamics, where large domains or helical structures can be treated as rigid bodies and the loops connecting them as flexible torsions. ICMD with such a dynamic model of the protein, combined with enhanced conformational sampling method such as temperature replica exchange, allows the sampling of large scale domain motion involving high energy barrier transitions. Once these large scale conformational transitions are sampled, all-torsion, or even all-atom, MD simulations can be carried out for the low energy conformations sampled via coarse grained ICMD to calculate the energetics of distinct conformations. Such hierarchical MD simulations can be carried out with standard all-atom forcefields without the need for compromising on the accuracy of the forces. Using constraints to treat bond lengths and bond angles as rigid can, however, distort the potential energy landscape of the system and reduce the number of dihedral transitions as well as conformational sampling. We present here a two-part solution to overcome such distortions of the potential energy landscape with ICMD models. To alleviate the intrinsic distortion that stems from the reduced phase space in torsional MD, we use the Fixman compensating potential. To additionally alleviate the extrinsic distortion that arises from the coupling between the dihedral angles and bond angles within a force field, we propose a hybrid ICMD method that allows the selective relaxing of bond angles. This hybrid ICMD method bridges the gap between all-atom MD and torsional MD. We demonstrate with examples that these methods together offer a solution to eliminate the potential energy distortions encountered in constrained ICMD simulations of peptide molecules.

The Dynamical Balance of the Brain at Rest

PubMed Central

Deco, Gustavo; Corbetta, Maurizio

2014-01-01

We review evidence that spontaneous, i.e. not stimulus- or task-driven, activity in the brain is not noise, but orderly organized at the level of large scale systems in a series of functional networks that maintain at all times a high level of coherence. These networks of spontaneous activity correlation or resting state networks (RSN) are closely related to the underlying anatomical connectivity, but their topography is also gated by the history of prior task activation. Network coherence does not depend on covert cognitive activity, but its strength and integrity relates to behavioral performance. Some RSN are functionally organized as dynamically competing systems both at rest and during tasks. Computational studies show that one of such dynamics, the anti-correlation between networks, depends on noise driven transitions between different multi-stable cluster synchronization states. These multi-stable states emerge because of transmission delays between regions that are modeled as coupled oscillators systems. Large-scale systems dynamics are useful for keeping different functional sub-networks in a state of heightened competition, which can be stabilized and fired by even small modulations of either sensory or internal signals. PMID:21196530

Local disturbance cycles and the maintenance of heterogeneity across scales in marine metapopulations.

PubMed

Gouhier, Tarik C; Guichard, Frédéric

2007-03-01

In marine systems, the occurrence and implications of disturbance-recovery cycles have been revealed at the landscape level, but only in demographically open or closed systems where landscape-level dynamics are assumed to have no feedback effect on regional dynamics. We present a mussel metapopulation model to elucidate the role of landscape-level disturbance cycles for regional response of mussel populations to onshore productivity and larval transport. Landscape dynamics are generated through spatially explicit rules, and each landscape is connected to its neighbor through unidirectional larval dispersal. The role of landscape disturbance cycles in the regional system behavior is elucidated (1) in demographically open vs. demographically coupled systems, in relation to (2) onshore reproductive output and (3) the temporal scale of landscape disturbance dynamics. By controlling for spatial structure at the landscape and metapopulation levels, we first demonstrate the interaction between landscape and oceanographic connectivity. The temporal scale of disturbance cycles, as controlled by mussel colonization rate, plays a critical role in the regional behavior of the system. Indeed, fast disturbance cycles are responsible for regional synchrony in relation to onshore reproductive output. Slow disturbance cycles, however, lead to increased robustness to changes in productivity and to demographic coupling. These testable predictions indicate that the occurrence and temporal scale of local disturbance-recovery dynamics can drive large-scale variability in demographically open systems, and the response of metapopulations to changes in nearshore productivity.

Trends in modern system theory

NASA Technical Reports Server (NTRS)

Athans, M.

1976-01-01

The topics considered are related to linear control system design, adaptive control, failure detection, control under failure, system reliability, and large-scale systems and decentralized control. It is pointed out that the design of a linear feedback control system which regulates a process about a desirable set point or steady-state condition in the presence of disturbances is a very important problem. The linearized dynamics of the process are used for design purposes. The typical linear-quadratic design involving the solution of the optimal control problem of a linear time-invariant system with respect to a quadratic performance criterion is considered along with gain reduction theorems and the multivariable phase margin theorem. The stumbling block in many adaptive design methodologies is associated with the amount of real time computation which is necessary. Attention is also given to the desperate need to develop good theories for large-scale systems, the beginning of a microprocessor revolution, the translation of the Wiener-Hopf theory into the time domain, and advances made in dynamic team theory, dynamic stochastic games, and finite memory stochastic control.

Evaluation of Kirkwood-Buff integrals via finite size scaling: a large scale molecular dynamics study

NASA Astrophysics Data System (ADS)

Dednam, W.; Botha, A. E.

2015-01-01

Solvation of bio-molecules in water is severely affected by the presence of co-solvent within the hydration shell of the solute structure. Furthermore, since solute molecules can range from small molecules, such as methane, to very large protein structures, it is imperative to understand the detailed structure-function relationship on the microscopic level. For example, it is useful know the conformational transitions that occur in protein structures. Although such an understanding can be obtained through large-scale molecular dynamic simulations, it is often the case that such simulations would require excessively large simulation times. In this context, Kirkwood-Buff theory, which connects the microscopic pair-wise molecular distributions to global thermodynamic properties, together with the recently developed technique, called finite size scaling, may provide a better method to reduce system sizes, and hence also the computational times. In this paper, we present molecular dynamics trial simulations of biologically relevant low-concentration solvents, solvated by aqueous co-solvent solutions. In particular we compare two different methods of calculating the relevant Kirkwood-Buff integrals. The first (traditional) method computes running integrals over the radial distribution functions, which must be obtained from large system-size NVT or NpT simulations. The second, newer method, employs finite size scaling to obtain the Kirkwood-Buff integrals directly by counting the particle number fluctuations in small, open sub-volumes embedded within a larger reservoir that can be well approximated by a much smaller simulation cell. In agreement with previous studies, which made a similar comparison for aqueous co-solvent solutions, without the additional solvent, we conclude that the finite size scaling method is also applicable to the present case, since it can produce computationally more efficient results which are equivalent to the more costly radial distribution function method.

Dynamic effective connectivity in cortically embedded systems of recurrently coupled synfire chains.

PubMed

Trengove, Chris; Diesmann, Markus; van Leeuwen, Cees

2016-02-01

As a candidate mechanism of neural representation, large numbers of synfire chains can efficiently be embedded in a balanced recurrent cortical network model. Here we study a model in which multiple synfire chains of variable strength are randomly coupled together to form a recurrent system. The system can be implemented both as a large-scale network of integrate-and-fire neurons and as a reduced model. The latter has binary-state pools as basic units but is otherwise isomorphic to the large-scale model, and provides an efficient tool for studying its behavior. Both the large-scale system and its reduced counterpart are able to sustain ongoing endogenous activity in the form of synfire waves, the proliferation of which is regulated by negative feedback caused by collateral noise. Within this equilibrium, diverse repertoires of ongoing activity are observed, including meta-stability and multiple steady states. These states arise in concert with an effective connectivity structure (ECS). The ECS admits a family of effective connectivity graphs (ECGs), parametrized by the mean global activity level. Of these graphs, the strongly connected components and their associated out-components account to a large extent for the observed steady states of the system. These results imply a notion of dynamic effective connectivity as governing neural computation with synfire chains, and related forms of cortical circuitry with complex topologies.

Design of distributed PID-type dynamic matrix controller for fractional-order systems

NASA Astrophysics Data System (ADS)

Wang, Dawei; Zhang, Ridong

2018-01-01

With the continuous requirements for product quality and safety operation in industrial production, it is difficult to describe the complex large-scale processes with integer-order differential equations. However, the fractional differential equations may precisely represent the intrinsic characteristics of such systems. In this paper, a distributed PID-type dynamic matrix control method based on fractional-order systems is proposed. First, the high-order approximate model of integer order is obtained by utilising the Oustaloup method. Then, the step response model vectors of the plant is obtained on the basis of the high-order model, and the online optimisation for multivariable processes is transformed into the optimisation of each small-scale subsystem that is regarded as a sub-plant controlled in the distributed framework. Furthermore, the PID operator is introduced into the performance index of each subsystem and the fractional-order PID-type dynamic matrix controller is designed based on Nash optimisation strategy. The information exchange among the subsystems is realised through the distributed control structure so as to complete the optimisation task of the whole large-scale system. Finally, the control performance of the designed controller in this paper is verified by an example.

The Nonlinear Magnetosphere: Expressions in MHD and in Kinetic Models

NASA Technical Reports Server (NTRS)

Hesse, Michael; Birn, Joachim

2011-01-01

Like most plasma systems, the magnetosphere of the Earth is governed by nonlinear dynamic evolution equations. The impact of nonlinearities ranges from large scales, where overall dynamics features are exhibiting nonlinear behavior, to small scale, kinetic, processes, where nonlinear behavior governs, among others, energy conversion and dissipation. In this talk we present a select set of examples of such behavior, with a specific emphasis on how nonlinear effects manifest themselves in MHD and in kinetic models of magnetospheric plasma dynamics.

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

From microscopic rules to macroscopic dynamics with active colloidal snakes

NASA Astrophysics Data System (ADS)

Zhang, Jie; Yan, Jing; Granick, Steve

Seeking to learn about self-assembly far from equilibrium, these imaging experiments inspect self-propelled colloidal particles whose heads and tails attract other particles reversibly as they swim. We observe processes akin to polymerization (short times) and chain scission and recombination (long times). The steady-state of dilute systems consists of discrete rings rotating in place with largely quenched dynamics, but when concentration is high, the system dynamics share features with turbulence. The dynamical rules of this model system appear to be scale-independent and hence potentially relevant more generally.

Limitations and tradeoffs in synchronization of large-scale networks with uncertain links

PubMed Central

Diwadkar, Amit; Vaidya, Umesh

2016-01-01

The synchronization of nonlinear systems connected over large-scale networks has gained popularity in a variety of applications, such as power grids, sensor networks, and biology. Stochastic uncertainty in the interconnections is a ubiquitous phenomenon observed in these physical and biological networks. We provide a size-independent network sufficient condition for the synchronization of scalar nonlinear systems with stochastic linear interactions over large-scale networks. This sufficient condition, expressed in terms of nonlinear dynamics, the Laplacian eigenvalues of the nominal interconnections, and the variance and location of the stochastic uncertainty, allows us to define a synchronization margin. We provide an analytical characterization of important trade-offs between the internal nonlinear dynamics, network topology, and uncertainty in synchronization. For nearest neighbour networks, the existence of an optimal number of neighbours with a maximum synchronization margin is demonstrated. An analytical formula for the optimal gain that produces the maximum synchronization margin allows us to compare the synchronization properties of various complex network topologies. PMID:27067994

On the Interactions Between Planetary and Mesoscale Dynamics in the Oceans

NASA Astrophysics Data System (ADS)

Grooms, I.; Julien, K. A.; Fox-Kemper, B.

2011-12-01

Multiple-scales asymptotic methods are used to investigate the interaction of planetary and mesoscale dynamics in the oceans. We find three regimes. In the first, the slow, large-scale planetary flow sets up a baroclinically unstable background which leads to vigorous mesoscale eddy generation, but the eddy dynamics do not affect the planetary dynamics. In the second, the planetary flow feels the effects of the eddies, but appears to be unable to generate them. The first two regimes rely on horizontally isotropic large-scale dynamics. In the third regime, large-scale anisotropy, as exists for example in the Antarctic Circumpolar Current and in western boundary currents, allows the large-scale dynamics to both generate and respond to mesoscale eddies. We also discuss how the investigation may be brought to bear on the problem of parameterization of unresolved mesoscale dynamics in ocean general circulation models.

Responses of Cloud Type Distributions to the Large-Scale Dynamical Circulation: Water Budget-Related Dynamical Phase Space and Dynamical Regimes

NASA Technical Reports Server (NTRS)

Wong, Sun; Del Genio, Anthony; Wang, Tao; Kahn, Brian; Fetzer, Eric J.; L'Ecuyer, Tristan S.

2015-01-01

Goals: Water budget-related dynamical phase space; Connect large-scale dynamical conditions to atmospheric water budget (including precipitation); Connect atmospheric water budget to cloud type distributions.

High performance computing in biology: multimillion atom simulations of nanoscale systems

PubMed Central

Sanbonmatsu, K. Y.; Tung, C.-S.

2007-01-01

Computational methods have been used in biology for sequence analysis (bioinformatics), all-atom simulation (molecular dynamics and quantum calculations), and more recently for modeling biological networks (systems biology). Of these three techniques, all-atom simulation is currently the most computationally demanding, in terms of compute load, communication speed, and memory load. Breakthroughs in electrostatic force calculation and dynamic load balancing have enabled molecular dynamics simulations of large biomolecular complexes. Here, we report simulation results for the ribosome, using approximately 2.64 million atoms, the largest all-atom biomolecular simulation published to date. Several other nanoscale systems with different numbers of atoms were studied to measure the performance of the NAMD molecular dynamics simulation program on the Los Alamos National Laboratory Q Machine. We demonstrate that multimillion atom systems represent a 'sweet spot' for the NAMD code on large supercomputers. NAMD displays an unprecedented 85% parallel scaling efficiency for the ribosome system on 1024 CPUs. We also review recent targeted molecular dynamics simulations of the ribosome that prove useful for studying conformational changes of this large biomolecular complex in atomic detail. PMID:17187988

Topological structure dynamics revealing collective evolution in active nematics

PubMed Central

Shi, Xia-qing; Ma, Yu-qiang

2013-01-01

Topological defects frequently emerge in active matter like bacterial colonies, cytoskeleton extracts on substrates, self-propelled granular or colloidal layers and so on, but their dynamical properties and the relations to large-scale organization and fluctuations in these active systems are seldom touched. Here we reveal, through a simple model for active nematics using self-driven hard elliptic rods, that the excitation, annihilation and transportation of topological defects differ markedly from those in non-active media. These dynamical processes exhibit strong irreversibility in active nematics in the absence of detailed balance. Moreover, topological defects are the key factors in organizing large-scale dynamic structures and collective flows, resulting in multi-spatial temporal effects. These findings allow us to control the self-organization of active matter through topological structures. PMID:24346733

Automatic Selection of Order Parameters in the Analysis of Large Scale Molecular Dynamics Simulations.

PubMed

Sultan, Mohammad M; Kiss, Gert; Shukla, Diwakar; Pande, Vijay S

2014-12-09

Given the large number of crystal structures and NMR ensembles that have been solved to date, classical molecular dynamics (MD) simulations have become powerful tools in the atomistic study of the kinetics and thermodynamics of biomolecular systems on ever increasing time scales. By virtue of the high-dimensional conformational state space that is explored, the interpretation of large-scale simulations faces difficulties not unlike those in the big data community. We address this challenge by introducing a method called clustering based feature selection (CB-FS) that employs a posterior analysis approach. It combines supervised machine learning (SML) and feature selection with Markov state models to automatically identify the relevant degrees of freedom that separate conformational states. We highlight the utility of the method in the evaluation of large-scale simulations and show that it can be used for the rapid and automated identification of relevant order parameters involved in the functional transitions of two exemplary cell-signaling proteins central to human disease states.

Decomposition-aggregation stability analysis. [for large scale dynamic systems with application to spinning Skylab control system

NASA Technical Reports Server (NTRS)

Siljak, D. D.; Weissenberger, S.; Cuk, S. M.

1973-01-01

This report presents the development and description of the decomposition aggregation approach to stability investigations of high dimension mathematical models of dynamic systems. The high dimension vector differential equation describing a large dynamic system is decomposed into a number of lower dimension vector differential equations which represent interconnected subsystems. Then a method is described by which the stability properties of each subsystem are aggregated into a single vector Liapunov function, representing the aggregate system model, consisting of subsystem Liapunov functions as components. A linear vector differential inequality is then formed in terms of the vector Liapunov function. The matrix of the model, which reflects the stability properties of the subsystems and the nature of their interconnections, is analyzed to conclude over-all system stability characteristics. The technique is applied in detail to investigate the stability characteristics of a dynamic model of a hypothetical spinning Skylab.

Spin diffusion from an inhomogeneous quench in an integrable system.

PubMed

Ljubotina, Marko; Žnidarič, Marko; Prosen, Tomaž

2017-07-13

Generalized hydrodynamics predicts universal ballistic transport in integrable lattice systems when prepared in generic inhomogeneous initial states. However, the ballistic contribution to transport can vanish in systems with additional discrete symmetries. Here we perform large scale numerical simulations of spin dynamics in the anisotropic Heisenberg XXZ spin 1/2 chain starting from an inhomogeneous mixed initial state which is symmetric with respect to a combination of spin reversal and spatial reflection. In the isotropic and easy-axis regimes we find non-ballistic spin transport which we analyse in detail in terms of scaling exponents of the transported magnetization and scaling profiles of the spin density. While in the easy-axis regime we find accurate evidence of normal diffusion, the spin transport in the isotropic case is clearly super-diffusive, with the scaling exponent very close to 2/3, but with universal scaling dynamics which obeys the diffusion equation in nonlinearly scaled time.

Evolution of wealth in a non-conservative economy driven by local Nash equilibria.

PubMed

Degond, Pierre; Liu, Jian-Guo; Ringhofer, Christian

2014-11-13

We develop a model for the evolution of wealth in a non-conservative economic environment, extending a theory developed in Degond et al. (2014 J. Stat. Phys. 154, 751-780 (doi:10.1007/s10955-013-0888-4)). The model considers a system of rational agents interacting in a game-theoretical framework. This evolution drives the dynamics of the agents in both wealth and economic configuration variables. The cost function is chosen to represent a risk-averse strategy of each agent. That is, the agent is more likely to interact with the market, the more predictable the market, and therefore the smaller its individual risk. This yields a kinetic equation for an effective single particle agent density with a Nash equilibrium serving as the local thermodynamic equilibrium. We consider a regime of scale separation where the large-scale dynamics is given by a hydrodynamic closure with this local equilibrium. A class of generalized collision invariants is developed to overcome the difficulty of the non-conservative property in the hydrodynamic closure derivation of the large-scale dynamics for the evolution of wealth distribution. The result is a system of gas dynamics-type equations for the density and average wealth of the agents on large scales. We recover the inverse Gamma distribution, which has been previously considered in the literature, as a local equilibrium for particular choices of the cost function. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Fuzzy Adaptive Decentralized Optimal Control for Strict Feedback Nonlinear Large-Scale Systems.

PubMed

Sun, Kangkang; Sui, Shuai; Tong, Shaocheng

2018-04-01

This paper considers the optimal decentralized fuzzy adaptive control design problem for a class of interconnected large-scale nonlinear systems in strict feedback form and with unknown nonlinear functions. The fuzzy logic systems are introduced to learn the unknown dynamics and cost functions, respectively, and a state estimator is developed. By applying the state estimator and the backstepping recursive design algorithm, a decentralized feedforward controller is established. By using the backstepping decentralized feedforward control scheme, the considered interconnected large-scale nonlinear system in strict feedback form is changed into an equivalent affine large-scale nonlinear system. Subsequently, an optimal decentralized fuzzy adaptive control scheme is constructed. The whole optimal decentralized fuzzy adaptive controller is composed of a decentralized feedforward control and an optimal decentralized control. It is proved that the developed optimal decentralized controller can ensure that all the variables of the control system are uniformly ultimately bounded, and the cost functions are the smallest. Two simulation examples are provided to illustrate the validity of the developed optimal decentralized fuzzy adaptive control scheme.

Large-scale hydropower system optimization using dynamic programming and object-oriented programming: the case of the Northeast China Power Grid.

PubMed

Li, Ji-Qing; Zhang, Yu-Shan; Ji, Chang-Ming; Wang, Ai-Jing; Lund, Jay R

2013-01-01

This paper examines long-term optimal operation using dynamic programming for a large hydropower system of 10 reservoirs in Northeast China. Besides considering flow and hydraulic head, the optimization explicitly includes time-varying electricity market prices to maximize benefit. Two techniques are used to reduce the 'curse of dimensionality' of dynamic programming with many reservoirs. Discrete differential dynamic programming (DDDP) reduces the search space and computer memory needed. Object-oriented programming (OOP) and the ability to dynamically allocate and release memory with the C++ language greatly reduces the cumulative effect of computer memory for solving multi-dimensional dynamic programming models. The case study shows that the model can reduce the 'curse of dimensionality' and achieve satisfactory results.

Architectural Visualization of C/C++ Source Code for Program Comprehension

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

Panas, T; Epperly, T W; Quinlan, D

2006-09-01

Structural and behavioral visualization of large-scale legacy systems to aid program comprehension is still a major challenge. The challenge is even greater when applications are implemented in flexible and expressive languages such as C and C++. In this paper, we consider visualization of static and dynamic aspects of large-scale scientific C/C++ applications. For our investigation, we reuse and integrate specialized analysis and visualization tools. Furthermore, we present a novel layout algorithm that permits a compressive architectural view of a large-scale software system. Our layout is unique in that it allows traditional program visualizations, i.e., graph structures, to be seen inmore » relation to the application's file structure.« less

Feasibility analysis of large length-scale thermocapillary flow experiment for the International Space Station

NASA Astrophysics Data System (ADS)

Alberts, Samantha J.

The investigation of microgravity fluid dynamics emerged out of necessity with the advent of space exploration. In particular, capillary research took a leap forward in the 1960s with regards to liquid settling and interfacial dynamics. Due to inherent temperature variations in large spacecraft liquid systems, such as fuel tanks, forces develop on gas-liquid interfaces which induce thermocapillary flows. To date, thermocapillary flows have been studied in small, idealized research geometries usually under terrestrial conditions. The 1 to 3m lengths in current and future large tanks and hardware are designed based on hardware rather than research, which leaves spaceflight systems designers without the technological tools to effectively create safe and efficient designs. This thesis focused on the design and feasibility of a large length-scale thermocapillary flow experiment, which utilizes temperature variations to drive a flow. The design of a helical channel geometry ranging from 1 to 2.5m in length permits a large length-scale thermocapillary flow experiment to fit in a seemingly small International Space Station (ISS) facility such as the Fluids Integrated Rack (FIR). An initial investigation determined the proposed experiment produced measurable data while adhering to the FIR facility limitations. The computational portion of this thesis focused on the investigation of functional geometries of fuel tanks and depots using Surface Evolver. This work outlines the design of a large length-scale thermocapillary flow experiment for the ISS FIR. The results from this work improve the understanding thermocapillary flows and thus improve technological tools for predicting heat and mass transfer in large length-scale thermocapillary flows. Without the tools to understand the thermocapillary flows in these systems, engineers are forced to design larger, heavier vehicles to assure safety and mission success.

SOLAR SYSTEM MOONS AS ANALOGS FOR COMPACT EXOPLANETARY SYSTEMS

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

Kane, Stephen R.; Hinkel, Natalie R.; Raymond, Sean N., E-mail: skane@ipac.caltech.edu

2013-11-01

The field of exoplanetary science has experienced a recent surge of new systems that is largely due to the precision photometry provided by the Kepler mission. The latest discoveries have included compact planetary systems in which the orbits of the planets all lie relatively close to the host star, which presents interesting challenges in terms of formation and dynamical evolution. The compact exoplanetary systems are analogous to the moons orbiting the giant planets in our solar system, in terms of their relative sizes and semimajor axes. We present a study that quantifies the scaled sizes and separations of the solarmore » system moons with respect to their hosts. We perform a similar study for a large sample of confirmed Kepler planets in multi-planet systems. We show that a comparison between the two samples leads to a similar correlation between their scaled sizes and separation distributions. The different gradients of the correlations may be indicative of differences in the formation and/or long-term dynamics of moon and planetary systems.« less

Simulation of FRET dyes allows quantitative comparison against experimental data

NASA Astrophysics Data System (ADS)

Reinartz, Ines; Sinner, Claude; Nettels, Daniel; Stucki-Buchli, Brigitte; Stockmar, Florian; Panek, Pawel T.; Jacob, Christoph R.; Nienhaus, Gerd Ulrich; Schuler, Benjamin; Schug, Alexander

2018-03-01

Fully understanding biomolecular function requires detailed insight into the systems' structural dynamics. Powerful experimental techniques such as single molecule Förster Resonance Energy Transfer (FRET) provide access to such dynamic information yet have to be carefully interpreted. Molecular simulations can complement these experiments but typically face limits in accessing slow time scales and large or unstructured systems. Here, we introduce a coarse-grained simulation technique that tackles these challenges. While requiring only few parameters, we maintain full protein flexibility and include all heavy atoms of proteins, linkers, and dyes. We are able to sufficiently reduce computational demands to simulate large or heterogeneous structural dynamics and ensembles on slow time scales found in, e.g., protein folding. The simulations allow for calculating FRET efficiencies which quantitatively agree with experimentally determined values. By providing atomically resolved trajectories, this work supports the planning and microscopic interpretation of experiments. Overall, these results highlight how simulations and experiments can complement each other leading to new insights into biomolecular dynamics and function.

Dynamical tuning for MPC using population games: A water supply network application.

PubMed

Barreiro-Gomez, Julian; Ocampo-Martinez, Carlos; Quijano, Nicanor

2017-07-01

Model predictive control (MPC) is a suitable strategy for the control of large-scale systems that have multiple design requirements, e.g., multiple physical and operational constraints. Besides, an MPC controller is able to deal with multiple control objectives considering them within the cost function, which implies to determine a proper prioritization for each of the objectives. Furthermore, when the system has time-varying parameters and/or disturbances, the appropriate prioritization might vary along the time as well. This situation leads to the need of a dynamical tuning methodology. This paper addresses the dynamical tuning issue by using evolutionary game theory. The advantages of the proposed method are highlighted and tested over a large-scale water supply network with periodic time-varying disturbances. Finally, results are analyzed with respect to a multi-objective MPC controller that uses static tuning. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Reaction dynamics analysis of a reconstituted Escherichia coli protein translation system by computational modeling

PubMed Central

Matsuura, Tomoaki; Tanimura, Naoki; Hosoda, Kazufumi; Yomo, Tetsuya; Shimizu, Yoshihiro

2017-01-01

To elucidate the dynamic features of a biologically relevant large-scale reaction network, we constructed a computational model of minimal protein synthesis consisting of 241 components and 968 reactions that synthesize the Met-Gly-Gly (MGG) peptide based on an Escherichia coli-based reconstituted in vitro protein synthesis system. We performed a simulation using parameters collected primarily from the literature and found that the rate of MGG peptide synthesis becomes nearly constant in minutes, thus achieving a steady state similar to experimental observations. In addition, concentration changes to 70% of the components, including intermediates, reached a plateau in a few minutes. However, the concentration change of each component exhibits several temporal plateaus, or a quasi-stationary state (QSS), before reaching the final plateau. To understand these complex dynamics, we focused on whether the components reached a QSS, mapped the arrangement of components in a QSS in the entire reaction network structure, and investigated time-dependent changes. We found that components in a QSS form clusters that grow over time but not in a linear fashion, and that this process involves the collapse and regrowth of clusters before the formation of a final large single cluster. These observations might commonly occur in other large-scale biological reaction networks. This developed analysis might be useful for understanding large-scale biological reactions by visualizing complex dynamics, thereby extracting the characteristics of the reaction network, including phase transitions. PMID:28167777

Linking crop yield anomalies to large-scale atmospheric circulation in Europe.

PubMed

Ceglar, Andrej; Turco, Marco; Toreti, Andrea; Doblas-Reyes, Francisco J

2017-06-15

Understanding the effects of climate variability and extremes on crop growth and development represents a necessary step to assess the resilience of agricultural systems to changing climate conditions. This study investigates the links between the large-scale atmospheric circulation and crop yields in Europe, providing the basis to develop seasonal crop yield forecasting and thus enabling a more effective and dynamic adaptation to climate variability and change. Four dominant modes of large-scale atmospheric variability have been used: North Atlantic Oscillation, Eastern Atlantic, Scandinavian and Eastern Atlantic-Western Russia patterns. Large-scale atmospheric circulation explains on average 43% of inter-annual winter wheat yield variability, ranging between 20% and 70% across countries. As for grain maize, the average explained variability is 38%, ranging between 20% and 58%. Spatially, the skill of the developed statistical models strongly depends on the large-scale atmospheric variability impact on weather at the regional level, especially during the most sensitive growth stages of flowering and grain filling. Our results also suggest that preceding atmospheric conditions might provide an important source of predictability especially for maize yields in south-eastern Europe. Since the seasonal predictability of large-scale atmospheric patterns is generally higher than the one of surface weather variables (e.g. precipitation) in Europe, seasonal crop yield prediction could benefit from the integration of derived statistical models exploiting the dynamical seasonal forecast of large-scale atmospheric circulation.

Impact of oceanic-scale interactions on the seasonal modulation of ocean dynamics by the atmosphere.

PubMed

Sasaki, Hideharu; Klein, Patrice; Qiu, Bo; Sasai, Yoshikazu

2014-12-15

Ocean eddies (with a size of 100-300 km), ubiquitous in satellite observations, are known to represent about 80% of the total ocean kinetic energy. Recent studies have pointed out the unexpected role of smaller oceanic structures (with 1-50 km scales) in generating and sustaining these eddies. The interpretation proposed so far invokes the internal instability resulting from the large-scale interaction between upper and interior oceanic layers. Here we show, using a new high-resolution simulation of the realistic North Pacific Ocean, that ocean eddies are instead sustained by a different process that involves small-scale mixed-layer instabilities set up by large-scale atmospheric forcing in winter. This leads to a seasonal evolution of the eddy kinetic energy in a very large part of this ocean, with an amplitude varying by a factor almost equal to 2. Perspectives in terms of the impacts on climate dynamics and future satellite observational systems are briefly discussed.

Impact of oceanic-scale interactions on the seasonal modulation of ocean dynamics by the atmosphere

PubMed Central

Sasaki, Hideharu; Klein, Patrice; Qiu, Bo; Sasai, Yoshikazu

2014-01-01

Ocean eddies (with a size of 100–300 km), ubiquitous in satellite observations, are known to represent about 80% of the total ocean kinetic energy. Recent studies have pointed out the unexpected role of smaller oceanic structures (with 1–50 km scales) in generating and sustaining these eddies. The interpretation proposed so far invokes the internal instability resulting from the large-scale interaction between upper and interior oceanic layers. Here we show, using a new high-resolution simulation of the realistic North Pacific Ocean, that ocean eddies are instead sustained by a different process that involves small-scale mixed-layer instabilities set up by large-scale atmospheric forcing in winter. This leads to a seasonal evolution of the eddy kinetic energy in a very large part of this ocean, with an amplitude varying by a factor almost equal to 2. Perspectives in terms of the impacts on climate dynamics and future satellite observational systems are briefly discussed. PMID:25501039

Static Analysis of Large-Scale Multibody System Using Joint Coordinates and Spatial Algebra Operator

PubMed Central

Omar, Mohamed A.

2014-01-01

Initial transient oscillations inhibited in the dynamic simulations responses of multibody systems can lead to inaccurate results, unrealistic load prediction, or simulation failure. These transients could result from incompatible initial conditions, initial constraints violation, and inadequate kinematic assembly. Performing static equilibrium analysis before the dynamic simulation can eliminate these transients and lead to stable simulation. Most exiting multibody formulations determine the static equilibrium position by minimizing the system potential energy. This paper presents a new general purpose approach for solving the static equilibrium in large-scale articulated multibody. The proposed approach introduces an energy drainage mechanism based on Baumgarte constraint stabilization approach to determine the static equilibrium position. The spatial algebra operator is used to express the kinematic and dynamic equations of the closed-loop multibody system. The proposed multibody system formulation utilizes the joint coordinates and modal elastic coordinates as the system generalized coordinates. The recursive nonlinear equations of motion are formulated using the Cartesian coordinates and the joint coordinates to form an augmented set of differential algebraic equations. Then system connectivity matrix is derived from the system topological relations and used to project the Cartesian quantities into the joint subspace leading to minimum set of differential equations. PMID:25045732

Static analysis of large-scale multibody system using joint coordinates and spatial algebra operator.

PubMed

Omar, Mohamed A

2014-01-01

Initial transient oscillations inhibited in the dynamic simulations responses of multibody systems can lead to inaccurate results, unrealistic load prediction, or simulation failure. These transients could result from incompatible initial conditions, initial constraints violation, and inadequate kinematic assembly. Performing static equilibrium analysis before the dynamic simulation can eliminate these transients and lead to stable simulation. Most exiting multibody formulations determine the static equilibrium position by minimizing the system potential energy. This paper presents a new general purpose approach for solving the static equilibrium in large-scale articulated multibody. The proposed approach introduces an energy drainage mechanism based on Baumgarte constraint stabilization approach to determine the static equilibrium position. The spatial algebra operator is used to express the kinematic and dynamic equations of the closed-loop multibody system. The proposed multibody system formulation utilizes the joint coordinates and modal elastic coordinates as the system generalized coordinates. The recursive nonlinear equations of motion are formulated using the Cartesian coordinates and the joint coordinates to form an augmented set of differential algebraic equations. Then system connectivity matrix is derived from the system topological relations and used to project the Cartesian quantities into the joint subspace leading to minimum set of differential equations.

Parallel Dynamics Simulation Using a Krylov-Schwarz Linear Solution Scheme

DOE PAGES

Abhyankar, Shrirang; Constantinescu, Emil M.; Smith, Barry F.; ...

2016-11-07

Fast dynamics simulation of large-scale power systems is a computational challenge because of the need to solve a large set of stiff, nonlinear differential-algebraic equations at every time step. The main bottleneck in dynamic simulations is the solution of a linear system during each nonlinear iteration of Newton’s method. In this paper, we present a parallel Krylov- Schwarz linear solution scheme that uses the Krylov subspacebased iterative linear solver GMRES with an overlapping restricted additive Schwarz preconditioner. As a result, performance tests of the proposed Krylov-Schwarz scheme for several large test cases ranging from 2,000 to 20,000 buses, including amore » real utility network, show good scalability on different computing architectures.« less

Parallel Dynamics Simulation Using a Krylov-Schwarz Linear Solution Scheme

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

Abhyankar, Shrirang; Constantinescu, Emil M.; Smith, Barry F.

Fast dynamics simulation of large-scale power systems is a computational challenge because of the need to solve a large set of stiff, nonlinear differential-algebraic equations at every time step. The main bottleneck in dynamic simulations is the solution of a linear system during each nonlinear iteration of Newton’s method. In this paper, we present a parallel Krylov- Schwarz linear solution scheme that uses the Krylov subspacebased iterative linear solver GMRES with an overlapping restricted additive Schwarz preconditioner. As a result, performance tests of the proposed Krylov-Schwarz scheme for several large test cases ranging from 2,000 to 20,000 buses, including amore » real utility network, show good scalability on different computing architectures.« less

Engineering large cartilage tissues using dynamic bioreactor culture at defined oxygen conditions.

PubMed

Daly, Andrew C; Sathy, Binulal N; Kelly, Daniel J

2018-01-01

Mesenchymal stem cells maintained in appropriate culture conditions are capable of producing robust cartilage tissue. However, gradients in nutrient availability that arise during three-dimensional culture can result in the development of spatially inhomogeneous cartilage tissues with core regions devoid of matrix. Previous attempts at developing dynamic culture systems to overcome these limitations have reported suppression of mesenchymal stem cell chondrogenesis compared to static conditions. We hypothesize that by modulating oxygen availability during bioreactor culture, it is possible to engineer cartilage tissues of scale. The objective of this study was to determine whether dynamic bioreactor culture, at defined oxygen conditions, could facilitate the development of large, spatially homogeneous cartilage tissues using mesenchymal stem cell laden hydrogels. A dynamic culture regime was directly compared to static conditions for its capacity to support chondrogenesis of mesenchymal stem cells in both small and large alginate hydrogels. The influence of external oxygen tension on the response to the dynamic culture conditions was explored by performing the experiment at 20% O 2 and 3% O 2 . At 20% O 2 , dynamic culture significantly suppressed chondrogenesis in engineered tissues of all sizes. In contrast, at 3% O 2 dynamic culture significantly enhanced the distribution and amount of cartilage matrix components (sulphated glycosaminoglycan and collagen II) in larger constructs compared to static conditions. Taken together, these results demonstrate that dynamic culture regimes that provide adequate nutrient availability and a low oxygen environment can be employed to engineer large homogeneous cartilage tissues. Such culture systems could facilitate the scaling up of cartilage tissue engineering strategies towards clinically relevant dimensions.

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.

Lightweight computational steering of very large scale molecular dynamics simulations

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

Beazley, D.M.; Lomdahl, P.S.

1996-09-01

We present a computational steering approach for controlling, analyzing, and visualizing very large scale molecular dynamics simulations involving tens to hundreds of millions of atoms. Our approach relies on extensible scripting languages and an easy to use tool for building extensions and modules. The system is extremely easy to modify, works with existing C code, is memory efficient, and can be used from inexpensive workstations and networks. We demonstrate how we have used this system to manipulate data from production MD simulations involving as many as 104 million atoms running on the CM-5 and Cray T3D. We also show howmore » this approach can be used to build systems that integrate common scripting languages (including Tcl/Tk, Perl, and Python), simulation code, user extensions, and commercial data analysis packages.« less

A variational approach to probing extreme events in turbulent dynamical systems

PubMed Central

Farazmand, Mohammad; Sapsis, Themistoklis P.

2017-01-01

Extreme events are ubiquitous in a wide range of dynamical systems, including turbulent fluid flows, nonlinear waves, large-scale networks, and biological systems. We propose a variational framework for probing conditions that trigger intermittent extreme events in high-dimensional nonlinear dynamical systems. We seek the triggers as the probabilistically feasible solutions of an appropriately constrained optimization problem, where the function to be maximized is a system observable exhibiting intermittent extreme bursts. The constraints are imposed to ensure the physical admissibility of the optimal solutions, that is, significant probability for their occurrence under the natural flow of the dynamical system. We apply the method to a body-forced incompressible Navier-Stokes equation, known as the Kolmogorov flow. We find that the intermittent bursts of the energy dissipation are independent of the external forcing and are instead caused by the spontaneous transfer of energy from large scales to the mean flow via nonlinear triad interactions. The global maximizer of the corresponding variational problem identifies the responsible triad, hence providing a precursor for the occurrence of extreme dissipation events. Specifically, monitoring the energy transfers within this triad allows us to develop a data-driven short-term predictor for the intermittent bursts of energy dissipation. We assess the performance of this predictor through direct numerical simulations. PMID:28948226

Engineering science and mechanics; Proceedings of the International Symposium, Tainan, Republic of China, December 29-31, 1981. Parts 1 & 2

NASA Astrophysics Data System (ADS)

Hsia, H.-M.; Chou, Y.-L.; Longman, R. W.

1983-07-01

The topics considered are related to measurements and controls in physical systems, the control of large scale and distributed parameter systems, chemical engineering systems, aerospace science and technology, thermodynamics and fluid mechanics, and computer applications. Subjects in structural dynamics are discussed, taking into account finite element approximations in transient analysis, buckling finite element analysis of flat plates, dynamic analysis of viscoelastic structures, the transient analysis of large frame structures by simple models, large amplitude vibration of an initially stressed thick plate, nonlinear aeroelasticity, a sensitivity analysis of a combined beam-spring-mass structure, and the optimal design and aeroelastic investigation of segmented windmill rotor blades. Attention is also given to dynamics and control of mechanical and civil engineering systems, composites, and topics in materials. For individual items see A83-44002 to A83-44061

Deciphering Dynamical Patterns of Growth Processes

ERIC Educational Resources Information Center

Kolakowska, A.

2009-01-01

Large systems of statistical physics often display properties that are independent of particulars that characterize their microscopic components. Universal dynamical patterns are manifested by the presence of scaling laws, which provides a common insight into governing physics of processes as vastly diverse as, e.g., growth of geological…

Stability and stabilisation of a class of networked dynamic systems

NASA Astrophysics Data System (ADS)

Liu, H. B.; Wang, D. Q.

2018-04-01

We investigate the stability and stabilisation of a linear time invariant networked heterogeneous system with arbitrarily connected subsystems. A new linear matrix inequality based sufficient and necessary condition for the stability is derived, based on which the stabilisation is provided. The obtained conditions efficiently utilise the block-diagonal characteristic of system parameter matrices and the sparseness of subsystem connection matrix. Moreover, a sufficient condition only dependent on each individual subsystem is also presented for the stabilisation of the networked systems with a large scale. Numerical simulations show that these conditions are computationally valid in the analysis and synthesis of a large-scale networked system.

Synchronization and Causality Across Time-scales: Complex Dynamics and Extremes in El Niño/Southern Oscillation

NASA Astrophysics Data System (ADS)

Jajcay, N.; Kravtsov, S.; Tsonis, A.; Palus, M.

2017-12-01

A better understanding of dynamics in complex systems, such as the Earth's climate is one of the key challenges for contemporary science and society. A large amount of experimental data requires new mathematical and computational approaches. Natural complex systems vary on many temporal and spatial scales, often exhibiting recurring patterns and quasi-oscillatory phenomena. The statistical inference of causal interactions and synchronization between dynamical phenomena evolving on different temporal scales is of vital importance for better understanding of underlying mechanisms and a key for modeling and prediction of such systems. This study introduces and applies information theory diagnostics to phase and amplitude time series of different wavelet components of the observed data that characterizes El Niño. A suite of significant interactions between processes operating on different time scales was detected, and intermittent synchronization among different time scales has been associated with the extreme El Niño events. The mechanisms of these nonlinear interactions were further studied in conceptual low-order and state-of-the-art dynamical, as well as statistical climate models. Observed and simulated interactions exhibit substantial discrepancies, whose understanding may be the key to an improved prediction. Moreover, the statistical framework which we apply here is suitable for direct usage of inferring cross-scale interactions in nonlinear time series from complex systems such as the terrestrial magnetosphere, solar-terrestrial interactions, seismic activity or even human brain dynamics.

Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding

PubMed Central

Tajima, Satohiro; Yanagawa, Toru; Fujii, Naotaka; Toyoizumi, Taro

2015-01-01

Brain-wide interactions generating complex neural dynamics are considered crucial for emergent cognitive functions. However, the irreducible nature of nonlinear and high-dimensional dynamical interactions challenges conventional reductionist approaches. We introduce a model-free method, based on embedding theorems in nonlinear state-space reconstruction, that permits a simultaneous characterization of complexity in local dynamics, directed interactions between brain areas, and how the complexity is produced by the interactions. We demonstrate this method in large-scale electrophysiological recordings from awake and anesthetized monkeys. The cross-embedding method captures structured interaction underlying cortex-wide dynamics that may be missed by conventional correlation-based analysis, demonstrating a critical role of time-series analysis in characterizing brain state. The method reveals a consciousness-related hierarchy of cortical areas, where dynamical complexity increases along with cross-area information flow. These findings demonstrate the advantages of the cross-embedding method in deciphering large-scale and heterogeneous neuronal systems, suggesting a crucial contribution by sensory-frontoparietal interactions to the emergence of complex brain dynamics during consciousness. PMID:26584045

Resting-State Functional Connectivity Emerges from Structurally and Dynamically Shaped Slow Linear Fluctuations

PubMed Central

Deco, Gustavo; Mantini, Dante; Romani, Gian Luca; Hagmann, Patric; Corbetta, Maurizio

2013-01-01

Brain fluctuations at rest are not random but are structured in spatial patterns of correlated activity across different brain areas. The question of how resting-state functional connectivity (FC) emerges from the brain's anatomical connections has motivated several experimental and computational studies to understand structure–function relationships. However, the mechanistic origin of resting state is obscured by large-scale models' complexity, and a close structure–function relation is still an open problem. Thus, a realistic but simple enough description of relevant brain dynamics is needed. Here, we derived a dynamic mean field model that consistently summarizes the realistic dynamics of a detailed spiking and conductance-based synaptic large-scale network, in which connectivity is constrained by diffusion imaging data from human subjects. The dynamic mean field approximates the ensemble dynamics, whose temporal evolution is dominated by the longest time scale of the system. With this reduction, we demonstrated that FC emerges as structured linear fluctuations around a stable low firing activity state close to destabilization. Moreover, the model can be further and crucially simplified into a set of motion equations for statistical moments, providing a direct analytical link between anatomical structure, neural network dynamics, and FC. Our study suggests that FC arises from noise propagation and dynamical slowing down of fluctuations in an anatomically constrained dynamical system. Altogether, the reduction from spiking models to statistical moments presented here provides a new framework to explicitly understand the building up of FC through neuronal dynamics underpinned by anatomical connections and to drive hypotheses in task-evoked studies and for clinical applications. PMID:23825427

Resting-state functional connectivity emerges from structurally and dynamically shaped slow linear fluctuations.

PubMed

Deco, Gustavo; Ponce-Alvarez, Adrián; Mantini, Dante; Romani, Gian Luca; Hagmann, Patric; Corbetta, Maurizio

2013-07-03

Brain fluctuations at rest are not random but are structured in spatial patterns of correlated activity across different brain areas. The question of how resting-state functional connectivity (FC) emerges from the brain's anatomical connections has motivated several experimental and computational studies to understand structure-function relationships. However, the mechanistic origin of resting state is obscured by large-scale models' complexity, and a close structure-function relation is still an open problem. Thus, a realistic but simple enough description of relevant brain dynamics is needed. Here, we derived a dynamic mean field model that consistently summarizes the realistic dynamics of a detailed spiking and conductance-based synaptic large-scale network, in which connectivity is constrained by diffusion imaging data from human subjects. The dynamic mean field approximates the ensemble dynamics, whose temporal evolution is dominated by the longest time scale of the system. With this reduction, we demonstrated that FC emerges as structured linear fluctuations around a stable low firing activity state close to destabilization. Moreover, the model can be further and crucially simplified into a set of motion equations for statistical moments, providing a direct analytical link between anatomical structure, neural network dynamics, and FC. Our study suggests that FC arises from noise propagation and dynamical slowing down of fluctuations in an anatomically constrained dynamical system. Altogether, the reduction from spiking models to statistical moments presented here provides a new framework to explicitly understand the building up of FC through neuronal dynamics underpinned by anatomical connections and to drive hypotheses in task-evoked studies and for clinical applications.

Overview of current research on atmospheric interactions with wildland fires

Treesearch

Warren E. Heilman

1996-01-01

Changes in the large-scale mean thermal structure of the atmosphere have the potential for affecting the dynamics of the atmosphere across the entire spectrum of scales that govern atmospheric processes. Inherent in these changes are interactions among the scales that could change, resulting in an alteration in the frequency of regional weather systems conducive to...

Current Scientific Issues in Large Scale Atmospheric Dynamics

NASA Technical Reports Server (NTRS)

Miller, T. L. (Compiler)

1986-01-01

Topics in large scale atmospheric dynamics are discussed. Aspects of atmospheric blocking, the influence of transient baroclinic eddies on planetary-scale waves, cyclogenesis, the effects of orography on planetary scale flow, small scale frontal structure, and simulations of gravity waves in frontal zones are discussed.

Analysis on the dynamic error for optoelectronic scanning coordinate measurement network

NASA Astrophysics Data System (ADS)

Shi, Shendong; Yang, Linghui; Lin, Jiarui; Guo, Siyang; Ren, Yongjie

2018-01-01

Large-scale dynamic three-dimension coordinate measurement technique is eagerly demanded in equipment manufacturing. Noted for advantages of high accuracy, scale expandability and multitask parallel measurement, optoelectronic scanning measurement network has got close attention. It is widely used in large components jointing, spacecraft rendezvous and docking simulation, digital shipbuilding and automated guided vehicle navigation. At present, most research about optoelectronic scanning measurement network is focused on static measurement capacity and research about dynamic accuracy is insufficient. Limited by the measurement principle, the dynamic error is non-negligible and restricts the application. The workshop measurement and positioning system is a representative which can realize dynamic measurement function in theory. In this paper we conduct deep research on dynamic error resources and divide them two parts: phase error and synchronization error. Dynamic error model is constructed. Based on the theory above, simulation about dynamic error is carried out. Dynamic error is quantized and the rule of volatility and periodicity has been found. Dynamic error characteristics are shown in detail. The research result lays foundation for further accuracy improvement.

Integrating legacy data to understand agroecosystem regional dynamics to catastrophic events

USDA-ARS?s Scientific Manuscript database

Multi-year extreme drought events are part of the history of the Earth system. Legacy data on the climate drivers, geomorphic features, and agroecosystem responses across a dynamically changing landscape throughout a region can provide important insights to a future where large-scale catastrophic ev...

Enhancements for a Dynamic Data Warehousing and Mining System for Large-scale HSCB Data

DTIC Science & Technology

2016-05-27

Page | 1 . . . . . . . . . . . . . . . . . . . Intelligent Automation Incorporated Enhancements for a Dynamic Data...301.294.4241, osavas@i-a-i.com) 1 Work Performed within This Reporting Period .................................................... 2 1.1 Top K User and...5 3 Work to be Performed in the Next Reporting Period

Quantum spin chains with multiple dynamics

NASA Astrophysics Data System (ADS)

Chen, Xiao; Fradkin, Eduardo; Witczak-Krempa, William

2017-11-01

Many-body systems with multiple emergent time scales arise in various contexts, including classical critical systems, correlated quantum materials, and ultracold atoms. We investigate such nontrivial quantum dynamics in a different setting: a spin-1 bilinear-biquadratic chain. It has a solvable entangled ground state, but a gapless excitation spectrum that is poorly understood. By using large-scale density matrix renormalization group simulations, we find that the lowest excitations have a dynamical exponent z that varies from 2 to 3.2 as we vary a coupling in the Hamiltonian. We find an additional gapless mode with a continuously varying exponent 2 ≤z <2.7 , which establishes the presence of multiple dynamics. In order to explain these striking properties, we construct a continuum wave function for the ground state, which correctly describes the correlations and entanglement properties. We also give a continuum parent Hamiltonian, but show that additional ingredients are needed to capture the excitations of the chain. By using an exact mapping to the nonequilibrium dynamics of a classical spin chain, we find that the large dynamical exponent is due to subdiffusive spin motion. Finally, we discuss the connections to other spin chains and to a family of quantum critical models in two dimensions.

Emergence of universal scaling in financial markets from mean-field dynamics

NASA Astrophysics Data System (ADS)

Vikram, S. V.; Sinha, Sitabhra

2011-01-01

Collective phenomena with universal properties have been observed in many complex systems with a large number of components. Here we present a microscopic model of the emergence of scaling behavior in such systems, where the interaction dynamics between individual components is mediated by a global variable making the mean-field description exact. Using the example of financial markets, we show that asset price can be such a global variable with the critical role of coordinating the actions of agents who are otherwise independent. The resulting model accurately reproduces empirical properties such as the universal scaling of the price fluctuation and volume distributions, long-range correlations in volatility, and multiscaling.

Multiple time step integrators in ab initio molecular dynamics.

PubMed

Luehr, Nathan; Markland, Thomas E; Martínez, Todd J

2014-02-28

Multiple time-scale algorithms exploit the natural separation of time-scales in chemical systems to greatly accelerate the efficiency of molecular dynamics simulations. Although the utility of these methods in systems where the interactions are described by empirical potentials is now well established, their application to ab initio molecular dynamics calculations has been limited by difficulties associated with splitting the ab initio potential into fast and slowly varying components. Here we present two schemes that enable efficient time-scale separation in ab initio calculations: one based on fragment decomposition and the other on range separation of the Coulomb operator in the electronic Hamiltonian. We demonstrate for both water clusters and a solvated hydroxide ion that multiple time-scale molecular dynamics allows for outer time steps of 2.5 fs, which are as large as those obtained when such schemes are applied to empirical potentials, while still allowing for bonds to be broken and reformed throughout the dynamics. This permits computational speedups of up to 4.4x, compared to standard Born-Oppenheimer ab initio molecular dynamics with a 0.5 fs time step, while maintaining the same energy conservation and accuracy.

DynamO: a free O(N) general event-driven molecular dynamics simulator.

PubMed

Bannerman, M N; Sargant, R; Lue, L

2011-11-30

Molecular dynamics algorithms for systems of particles interacting through discrete or "hard" potentials are fundamentally different to the methods for continuous or "soft" potential systems. Although many software packages have been developed for continuous potential systems, software for discrete potential systems based on event-driven algorithms are relatively scarce and specialized. We present DynamO, a general event-driven simulation package, which displays the optimal O(N) asymptotic scaling of the computational cost with the number of particles N, rather than the O(N) scaling found in most standard algorithms. DynamO provides reference implementations of the best available event-driven algorithms. These techniques allow the rapid simulation of both complex and large (>10(6) particles) systems for long times. The performance of the program is benchmarked for elastic hard sphere systems, homogeneous cooling and sheared inelastic hard spheres, and equilibrium Lennard-Jones fluids. This software and its documentation are distributed under the GNU General Public license and can be freely downloaded from http://marcusbannerman.co.uk/dynamo. Copyright © 2011 Wiley Periodicals, Inc.

Application of Dynamic Mode Decomposition: Temporal Evolution of Flow Structures in an Aneurysm

NASA Astrophysics Data System (ADS)

Conlin, William; Yu, Paulo; Durgesh, Vibhav

2017-11-01

An aneurysm is an enlargement of a weakened arterial wall that can be fatal or debilitating on rupture. Aneurysm hemodynamics is integral to developing an understanding of aneurysm formation, growth, and rupture. The flow in an aneurysm exhibits complex fluid dynamics behavior due to an inherent unsteady inflow condition and its interactions with large-scale flow structures present in the aneurysm. The objective of this study is to identify the large-scale structures in the aneurysm, study temporal behavior, and quantify their interaction with the inflow condition. For this purpose, detailed Particle Image Velocimetry (PIV) measurements were performed at the center plane of an idealized aneurysm model for a range of inflow conditions. Inflow conditions were precisely controlled using a ViVitro SuperPump system. Dynamic Modal Decomposition (DMD) of the velocity field was used to identify coherent structures and their temporal behavior. DMD was successful in capturing the large-scale flow structures and their temporal behavior. A low dimensional approximation to the flow field was obtained with the most relevant dynamic modes and was used to obtain temporal information about the coherent structures and their interaction with the inflow, formation, evolution, and growth.

Regional reanalysis without local data: Exploiting the downscaling paradigm

NASA Astrophysics Data System (ADS)

von Storch, Hans; Feser, Frauke; Geyer, Beate; Klehmet, Katharina; Li, Delei; Rockel, Burkhardt; Schubert-Frisius, Martina; Tim, Nele; Zorita, Eduardo

2017-08-01

This paper demonstrates two important aspects of regional dynamical downscaling of multidecadal atmospheric reanalysis. First, that in this way skillful regional descriptions of multidecadal climate variability may be constructed in regions with little or no local data. Second, that the concept of large-scale constraining allows global downscaling, so that global reanalyses may be completed by additions of consistent detail in all regions of the world. Global reanalyses suffer from inhomogeneities. However, their large-scale componenst are mostly homogeneous; Therefore, the concept of downscaling may be applied to homogeneously complement the large-scale state of the reanalyses with regional detail—wherever the condition of homogeneity of the description of large scales is fulfilled. Technically, this can be done by dynamical downscaling using a regional or global climate model, which's large scales are constrained by spectral nudging. This approach has been developed and tested for the region of Europe, and a skillful representation of regional weather risks—in particular marine risks—was identified. We have run this system in regions with reduced or absent local data coverage, such as Central Siberia, the Bohai and Yellow Sea, Southwestern Africa, and the South Atlantic. Also, a global simulation was computed, which adds regional features to prescribed global dynamics. Our cases demonstrate that spatially detailed reconstructions of the climate state and its change in the recent three to six decades add useful supplementary information to existing observational data for midlatitude and subtropical regions of the world.

Scaling of Multimillion-Atom Biological Molecular Dynamics Simulation on a Petascale Supercomputer

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

Schulz, Roland; Lindner, Benjamin; Petridis, Loukas

2009-01-01

A strategy is described for a fast all-atom molecular dynamics simulation of multimillion-atom biological systems on massively parallel supercomputers. The strategy is developed using benchmark systems of particular interest to bioenergy research, comprising models of cellulose and lignocellulosic biomass in an aqueous solution. The approach involves using the reaction field (RF) method for the computation of long-range electrostatic interactions, which permits efficient scaling on many thousands of cores. Although the range of applicability of the RF method for biomolecular systems remains to be demonstrated, for the benchmark systems the use of the RF produces molecular dipole moments, Kirkwood G factors,more » other structural properties, and mean-square fluctuations in excellent agreement with those obtained with the commonly used Particle Mesh Ewald method. With RF, three million- and five million atom biological systems scale well up to 30k cores, producing 30 ns/day. Atomistic simulations of very large systems for time scales approaching the microsecond would, therefore, appear now to be within reach.« less

Scaling of Multimillion-Atom Biological Molecular Dynamics Simulation on a Petascale Supercomputer.

PubMed

Schulz, Roland; Lindner, Benjamin; Petridis, Loukas; Smith, Jeremy C

2009-10-13

A strategy is described for a fast all-atom molecular dynamics simulation of multimillion-atom biological systems on massively parallel supercomputers. The strategy is developed using benchmark systems of particular interest to bioenergy research, comprising models of cellulose and lignocellulosic biomass in an aqueous solution. The approach involves using the reaction field (RF) method for the computation of long-range electrostatic interactions, which permits efficient scaling on many thousands of cores. Although the range of applicability of the RF method for biomolecular systems remains to be demonstrated, for the benchmark systems the use of the RF produces molecular dipole moments, Kirkwood G factors, other structural properties, and mean-square fluctuations in excellent agreement with those obtained with the commonly used Particle Mesh Ewald method. With RF, three million- and five million-atom biological systems scale well up to ∼30k cores, producing ∼30 ns/day. Atomistic simulations of very large systems for time scales approaching the microsecond would, therefore, appear now to be within reach.

The Ramifications of Meddling with Systems Governed by Self-organized Critical Dynamics

NASA Astrophysics Data System (ADS)

Carreras, B. A.; Newman, D. E.; Dobson, I.

2002-12-01

Complex natural, well as man-made, systems often exhibit characteristics similar to those seen in self-organized critical (SOC) systems. The concept of self-organized criticality brings together ideas of self-organization of nonlinear dynamical systems with the often-observed near critical behavior of many natural phenomena. These phenomena exhibit self-similarities over extended ranges of spatial and temporal scales. In those systems, scale lengths may be described by fractal geometry and time scales that lead to 1/f-like power spectra. Natural applications include modeling the motion of tectonics plates, forest fires, magnetospheric dynamics, spin glass systems, and turbulent transport. In man-made systems, applications have included traffic dynamics, power and communications networks, and financial markets among many others. Simple cellular automata models such as the running sandpile model have been very useful in reproducing the complexity and characteristics of these systems. One characteristic property of the SOC systems is that they relax through what we call events. These events can happen over all scales of the system. Examples of these events are: earthquakes in the case of plate tectonic; fires in forest evolution extinction in the co evolution of biological species; and blackouts in power transmission systems. In a time-averaged sense, these systems are subcritical (that is, they lie in an average state that should not trigger any events) and the relaxation events happen intermittently. The time spent in a subcritical state relative to the time of the events varies from one system to another. For instance, the chance of finding a forest on fire is very low with the frequency of fires being on the order of one fire every few years and with many of these fires small and inconsequential. Very large fires happen over time periods of decades or even centuries. However, because of their consequences, these large but infrequent events are the important ones to understand, control and minimize. The main thrust of this research is to understand how and when global events occur in such systems when we apply mitigation techniques and how this impacts risk assessment. As sample systems we investigate both forest fire models and electrical power transmission network models, though the results are probably applicable to a wide variety of systems. It is found, perhaps counter intuitively, that apparently sensible attempts to mitigate failures in such complex systems can have adverse effects and therefore must be approached with care. The success of mitigation efforts in SOC systems is strongly influenced by the dynamics of the system. Unless the mitigation efforts alter the self-organization forces driving the system, the system will in general be pushed toward criticality. To alter those forces with mitigation efforts may be quite difficult because the forces are an intrinsic part of the system. Moreover, in many cases, efforts to mitigate small disruptions will increase the frequency of large disruptions. This occurs because the large and small disruptions are not independent but are strongly coupled by the dynamics. Before discussing this in the more complicated case of power systems, we will illustrate this phenomenon with a forest fire model.

Simulation of all-scale atmospheric dynamics on unstructured meshes

NASA Astrophysics Data System (ADS)

Smolarkiewicz, Piotr K.; Szmelter, Joanna; Xiao, Feng

2016-10-01

The advance of massively parallel computing in the nineteen nineties and beyond encouraged finer grid intervals in numerical weather-prediction models. This has improved resolution of weather systems and enhanced the accuracy of forecasts, while setting the trend for development of unified all-scale atmospheric models. This paper first outlines the historical background to a wide range of numerical methods advanced in the process. Next, the trend is illustrated with a technical review of a versatile nonoscillatory forward-in-time finite-volume (NFTFV) approach, proven effective in simulations of atmospheric flows from small-scale dynamics to global circulations and climate. The outlined approach exploits the synergy of two specific ingredients: the MPDATA methods for the simulation of fluid flows based on the sign-preserving properties of upstream differencing; and the flexible finite-volume median-dual unstructured-mesh discretisation of the spatial differential operators comprising PDEs of atmospheric dynamics. The paper consolidates the concepts leading to a family of generalised nonhydrostatic NFTFV flow solvers that include soundproof PDEs of incompressible Boussinesq, anelastic and pseudo-incompressible systems, common in large-eddy simulation of small- and meso-scale dynamics, as well as all-scale compressible Euler equations. Such a framework naturally extends predictive skills of large-eddy simulation to the global atmosphere, providing a bottom-up alternative to the reverse approach pursued in the weather-prediction models. Theoretical considerations are substantiated by calculations attesting to the versatility and efficacy of the NFTFV approach. Some prospective developments are also discussed.

Liquidity crises on different time scales

NASA Astrophysics Data System (ADS)

Corradi, Francesco; Zaccaria, Andrea; Pietronero, Luciano

2015-12-01

We present an empirical analysis of the microstructure of financial markets and, in particular, of the static and dynamic properties of liquidity. We find that on relatively large time scales (15 min) large price fluctuations are connected to the failure of the subtle mechanism of compensation between the flows of market and limit orders: in other words, the missed revelation of the latent order book breaks the dynamical equilibrium between the flows, triggering the large price jumps. On smaller time scales (30 s), instead, the static depletion of the limit order book is an indicator of an intrinsic fragility of the system, which is related to a strongly nonlinear enhancement of the response. In order to quantify this phenomenon we introduce a measure of the liquidity imbalance present in the book and we show that it is correlated to both the sign and the magnitude of the next price movement. These findings provide a quantitative definition of the effective liquidity, which proves to be strongly dependent on the considered time scales.

Liquidity crises on different time scales.

PubMed

Corradi, Francesco; Zaccaria, Andrea; Pietronero, Luciano

2015-12-01

We present an empirical analysis of the microstructure of financial markets and, in particular, of the static and dynamic properties of liquidity. We find that on relatively large time scales (15 min) large price fluctuations are connected to the failure of the subtle mechanism of compensation between the flows of market and limit orders: in other words, the missed revelation of the latent order book breaks the dynamical equilibrium between the flows, triggering the large price jumps. On smaller time scales (30 s), instead, the static depletion of the limit order book is an indicator of an intrinsic fragility of the system, which is related to a strongly nonlinear enhancement of the response. In order to quantify this phenomenon we introduce a measure of the liquidity imbalance present in the book and we show that it is correlated to both the sign and the magnitude of the next price movement. These findings provide a quantitative definition of the effective liquidity, which proves to be strongly dependent on the considered time scales.

Transition from lognormal to χ2-superstatistics for financial time series

NASA Astrophysics Data System (ADS)

Xu, Dan; Beck, Christian

2016-07-01

Share price returns on different time scales can be well modelled by a superstatistical dynamics. Here we provide an investigation which type of superstatistics is most suitable to properly describe share price dynamics on various time scales. It is shown that while χ2-superstatistics works well on a time scale of days, on a much smaller time scale of minutes the price changes are better described by lognormal superstatistics. The system dynamics thus exhibits a transition from lognormal to χ2 superstatistics as a function of time scale. We discuss a more general model interpolating between both statistics which fits the observed data very well. We also present results on correlation functions of the extracted superstatistical volatility parameter, which exhibits exponential decay for returns on large time scales, whereas for returns on small time scales there are long-range correlations and power-law decay.

Generic solar photovoltaic system dynamic simulation model specification

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

Ellis, Abraham; Behnke, Michael Robert; Elliott, Ryan Thomas

This document is intended to serve as a specification for generic solar photovoltaic (PV) system positive-sequence dynamic models to be implemented by software developers and approved by the WECC MVWG for use in bulk system dynamic simulations in accordance with NERC MOD standards. Two specific dynamic models are included in the scope of this document. The first, a Central Station PV System model, is intended to capture the most important dynamic characteristics of large scale (> 10 MW) PV systems with a central Point of Interconnection (POI) at the transmission level. The second, a Distributed PV System model, is intendedmore » to represent an aggregation of smaller, distribution-connected systems that comprise a portion of a composite load that might be modeled at a transmission load bus.« less

Dynamics of the McDonnell Douglas Large Scale Dynamic Rig and Dynamic Calibration of the Rotor Balance

DOT National Transportation Integrated Search

1994-10-01

A shake test was performed on the Large Scale Dynamic Rig in the 40- by 80-Foot Wind Tunnel in support of the McDonnell Douglas Advanced Rotor Technology (MDART) Test Program. The shake test identifies the hub modes and the dynamic calibration matrix...

Intercomparison Project on Parameterizations of Large-Scale Dynamics for Simulations of Tropical Convection

NASA Astrophysics Data System (ADS)

Sobel, A. H.; Wang, S.; Bellon, G.; Sessions, S. L.; Woolnough, S.

2013-12-01

Parameterizations of large-scale dynamics have been developed in the past decade for studying the interaction between tropical convection and large-scale dynamics, based on our physical understanding of the tropical atmosphere. A principal advantage of these methods is that they offer a pathway to attack the key question of what controls large-scale variations of tropical deep convection. These methods have been used with both single column models (SCMs) and cloud-resolving models (CRMs) to study the interaction of deep convection with several kinds of environmental forcings. While much has been learned from these efforts, different groups' efforts are somewhat hard to compare. Different models, different versions of the large-scale parameterization methods, and experimental designs that differ in other ways are used. It is not obvious which choices are consequential to the scientific conclusions drawn and which are not. The methods have matured to the point that there is value in an intercomparison project. In this context, the Global Atmospheric Systems Study - Weak Temperature Gradient (GASS-WTG) project was proposed at the Pan-GASS meeting in September 2012. The weak temperature gradient approximation is one method to parameterize large-scale dynamics, and is used in the project name for historical reasons and simplicity, but another method, the damped gravity wave (DGW) method, will also be used in the project. The goal of the GASS-WTG project is to develop community understanding of the parameterization methods currently in use. Their strengths, weaknesses, and functionality in models with different physics and numerics will be explored in detail, and their utility to improve our understanding of tropical weather and climate phenomena will be further evaluated. This presentation will introduce the intercomparison project, including background, goals, and overview of the proposed experimental design. Interested groups will be invited to join (it will not be too late), and preliminary results will be presented.

Scaling laws of strategic behavior and size heterogeneity in agent dynamics

NASA Astrophysics Data System (ADS)

Vaglica, Gabriella; Lillo, Fabrizio; Moro, Esteban; Mantegna, Rosario N.

2008-03-01

We consider the financial market as a model system and study empirically how agents strategically adjust the properties of large orders in order to meet their preference and minimize their impact. We quantify this strategic behavior by detecting scaling relations between the variables characterizing the trading activity of different institutions. We also observe power-law distributions in the investment time horizon, in the number of transactions needed to execute a large order, and in the traded value exchanged by large institutions, and we show that heterogeneity of agents is a key ingredient for the emergence of some aggregate properties characterizing this complex system.

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

Climate Dynamics and Hysteresis at Low and High Obliquity

NASA Astrophysics Data System (ADS)

Colose, C.; Del Genio, A. D.; Way, M.

2017-12-01

We explore the large-scale climate dynamics at low and high obliquity for an Earth-like planet using the ROCKE-3D (Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics) 3-D General Circulation model being developed at NASA GISS as part of the Nexus for Exoplanet System Science (NExSS) initiative. We highlight the role of ocean heat storage and transport in determining the seasonal cycle at high obliquity, and describe the large-scale circulation and resulting regional climate patterns using both aquaplanet and Earth topographical boundary conditions. Finally, we contrast the hysteresis structure to varying CO2 concentration for a low and high obliquity planet near the outer edge of the habitable zone. We discuss the prospects for habitability for a high obliquity planet susceptible to global glaciation.

Coastal ocean forecasting with an unstructured grid model in the southern Adriatic and northern Ionian seas

NASA Astrophysics Data System (ADS)

Federico, Ivan; Pinardi, Nadia; Coppini, Giovanni; Oddo, Paolo; Lecci, Rita; Mossa, Michele

2017-01-01

SANIFS (Southern Adriatic Northern Ionian coastal Forecasting System) is a coastal-ocean operational system based on the unstructured grid finite-element three-dimensional hydrodynamic SHYFEM model, providing short-term forecasts. The operational chain is based on a downscaling approach starting from the large-scale system for the entire Mediterranean Basin (MFS, Mediterranean Forecasting System), which provides initial and boundary condition fields to the nested system. The model is configured to provide hydrodynamics and active tracer forecasts both in open ocean and coastal waters of southeastern Italy using a variable horizontal resolution from the open sea (3-4 km) to coastal areas (50-500 m). Given that the coastal fields are driven by a combination of both local (also known as coastal) and deep-ocean forcings propagating along the shelf, the performance of SANIFS was verified both in forecast and simulation mode, first (i) on the large and shelf-coastal scales by comparing with a large-scale survey CTD (conductivity-temperature-depth) in the Gulf of Taranto and then (ii) on the coastal-harbour scale (Mar Grande of Taranto) by comparison with CTD, ADCP (acoustic doppler current profiler) and tide gauge data. Sensitivity tests were performed on initialization conditions (mainly focused on spin-up procedures) and on surface boundary conditions by assessing the reliability of two alternative datasets at different horizontal resolution (12.5 and 6.5 km). The SANIFS forecasts at a lead time of 1 day were compared with the MFS forecasts, highlighting that SANIFS is able to retain the large-scale dynamics of MFS. The large-scale dynamics of MFS are correctly propagated to the shelf-coastal scale, improving the forecast accuracy (+17 % for temperature and +6 % for salinity compared to MFS). Moreover, the added value of SANIFS was assessed on the coastal-harbour scale, which is not covered by the coarse resolution of MFS, where the fields forecasted by SANIFS reproduced the observations well (temperature RMSE equal to 0.11 °C). Furthermore, SANIFS simulations were compared with hourly time series of temperature, sea level and velocity measured on the coastal-harbour scale, showing a good agreement. Simulations in the Gulf of Taranto described a circulation mainly characterized by an anticyclonic gyre with the presence of cyclonic vortexes in shelf-coastal areas. A surface water inflow from the open sea to Mar Grande characterizes the coastal-harbour scale.

A KPI-based process monitoring and fault detection framework for large-scale processes.

PubMed

Zhang, Kai; Shardt, Yuri A W; Chen, Zhiwen; Yang, Xu; Ding, Steven X; Peng, Kaixiang

2017-05-01

Large-scale processes, consisting of multiple interconnected subprocesses, are commonly encountered in industrial systems, whose performance needs to be determined. A common approach to this problem is to use a key performance indicator (KPI)-based approach. However, the different KPI-based approaches are not developed with a coherent and consistent framework. Thus, this paper proposes a framework for KPI-based process monitoring and fault detection (PM-FD) for large-scale industrial processes, which considers the static and dynamic relationships between process and KPI variables. For the static case, a least squares-based approach is developed that provides an explicit link with least-squares regression, which gives better performance than partial least squares. For the dynamic case, using the kernel representation of each subprocess, an instrument variable is used to reduce the dynamic case to the static case. This framework is applied to the TE benchmark process and the hot strip mill rolling process. The results show that the proposed method can detect faults better than previous methods. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Data Intensive Systems (DIS) Benchmark Performance Summary

DTIC Science & Technology

2003-08-01

models assumed by today’s conventional architectures. Such applications include model- based Automatic Target Recognition (ATR), synthetic aperture...radar (SAR) codes, large scale dynamic databases/battlefield integration, dynamic sensor- based processing, high-speed cryptanalysis, high speed...distributed interactive and data intensive simulations, data-oriented problems characterized by pointer- based and other highly irregular data structures

TRANSITION FROM KINETIC TO MHD BEHAVIOR IN A COLLISIONLESS PLASMA

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

Parashar, Tulasi N.; Matthaeus, William H.; Shay, Michael A.

The study of kinetic effects in heliospheric plasmas requires representation of dynamics at sub-proton scales, but in most cases the system is driven by magnetohydrodynamic (MHD) activity at larger scales. The latter requirement challenges available computational resources, which raises the question of how large such a system must be to exhibit MHD traits at large scales while kinetic behavior is accurately represented at small scales. Here we study this implied transition from kinetic to MHD-like behavior using particle-in-cell (PIC) simulations, initialized using an Orszag–Tang Vortex. The PIC code treats protons, as well as electrons, kinetically, and we address the questionmore » of interest by examining several different indicators of MHD-like behavior.« less

Advanced Kalman Filter for Real-Time Responsiveness in Complex Systems

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

Welch, Gregory Francis; Zhang, Jinghe

2014-06-10

Complex engineering systems pose fundamental challenges in real-time operations and control because they are highly dynamic systems consisting of a large number of elements with severe nonlinearities and discontinuities. Today’s tools for real-time complex system operations are mostly based on steady state models, unable to capture the dynamic nature and too slow to prevent system failures. We developed advanced Kalman filtering techniques and the formulation of dynamic state estimation using Kalman filtering techniques to capture complex system dynamics in aiding real-time operations and control. In this work, we looked at complex system issues including severe nonlinearity of system equations, discontinuitiesmore » caused by system controls and network switches, sparse measurements in space and time, and real-time requirements of power grid operations. We sought to bridge the disciplinary boundaries between Computer Science and Power Systems Engineering, by introducing methods that leverage both existing and new techniques. While our methods were developed in the context of electrical power systems, they should generalize to other large-scale scientific and engineering applications.« less

Dynamical heterogeneity in a glass-forming ideal gas.

PubMed

Charbonneau, Patrick; Das, Chinmay; Frenkel, Daan

2008-07-01

We conduct a numerical study of the dynamical behavior of a system of three-dimensional "crosses," particles that consist of three mutually perpendicular line segments of length sigma rigidly joined at their midpoints. In an earlier study [W. van Ketel, Phys. Rev. Lett. 94, 135703 (2005)] we showed that this model has the structural properties of an ideal gas, yet the dynamical properties of a strong glass former. In the present paper we report an extensive study of the dynamical heterogeneities that appear in this system in the regime where glassy behavior sets in. On the one hand, we find that the propensity of a particle to diffuse is determined by the structure of its local environment. The local density around mobile particles is significantly less than the average density, but there is little clustering of mobile particles, and the clusters observed tend to be small. On the other hand, dynamical susceptibility results indicate that a large dynamical length scale develops even at moderate densities. This suggests that propensity and other mobility measures are an incomplete measure of the dynamical length scales in this system.

Domain-area distribution anomaly in segregating multicomponent superfluids

NASA Astrophysics Data System (ADS)

Takeuchi, Hiromitsu

2018-01-01

The domain-area distribution in the phase transition dynamics of Z2 symmetry breaking is studied theoretically and numerically for segregating binary Bose-Einstein condensates in quasi-two-dimensional systems. Due to the dynamic-scaling law of the phase ordering kinetics, the domain-area distribution is described by a universal function of the domain area, rescaled by the mean distance between domain walls. The scaling theory for general coarsening dynamics in two dimensions hypothesizes that the distribution during the coarsening dynamics has a hierarchy with the two scaling regimes, the microscopic and macroscopic regimes with distinct power-law exponents. The power law in the macroscopic regime, where the domain size is larger than the mean distance, is universally represented with the Fisher's exponent of the percolation theory in two dimensions. On the other hand, the power-law exponent in the microscopic regime is sensitive to the microscopic dynamics of the system. This conjecture is confirmed by large-scale numerical simulations of the coupled Gross-Pitaevskii equation for binary condensates. In the numerical experiments of the superfluid system, the exponent in the microscopic regime anomalously reaches to its theoretical upper limit of the general scaling theory. The anomaly comes from the quantum-fluid effect in the presence of circular vortex sheets, described by the hydrodynamic approximation neglecting the fluid compressibility. It is also found that the distribution of superfluid circulation along vortex sheets obeys a dynamic-scaling law with different power-law exponents in the two regimes. An analogy to quantum turbulence on the hierarchy of vorticity distribution and the applicability to chiral superfluid 3He in a slab are also discussed.

A review of dynamic stability of repulsive-force maglev suspension systems

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

Cai, Y.; Rote, D.M.

1998-07-01

Vehicle dynamics and the need to satisfy ride quality requirements have long been recognized as crucial to the commercial success of passenger-carrying transportation systems. Design concepts for maglev systems are no exception. Early maglev investigators and designers were well aware of the importance of ride quality and took care to ensure that their designs would meet acceptable ride quality standards. In contrast, the dynamic stability of electrodynamic suspension (EDS) systems, which has obvious implications for system safety and cost as well as for ride quality, has not received nearly as much attention. Because of the well-known under-damped nature of EDSmore » suspension systems and the observation of instabilities in laboratory-scale model systems, it is prudent to develop a better understanding of vehicle stability characteristics. The work reported in this was undertaken with the intention of summarizing information that has been accumulated worldwide and that is relevant to dynamic stability of repulsive-force maglev suspension systems, assimilating that information, and gaining an understanding of the factors that influence that stability. Included in the paper is a discussion and comparison of results acquired from some representative tests of large-scale vehicles on linear test tracks, together with analytical and laboratory-scale investigations of stability and dynamics of EDS systems. This paper will also summarize the R and D activities at Argonne National Laboratory (ANL) since 1991 to study the nature of the forces that are operative in an EDS system and the dynamic stability of such systems.« less

Persistent model order reduction for complex dynamical systems using smooth orthogonal decomposition

NASA Astrophysics Data System (ADS)

Ilbeigi, Shahab; Chelidze, David

2017-11-01

Full-scale complex dynamic models are not effective for parametric studies due to the inherent constraints on available computational power and storage resources. A persistent reduced order model (ROM) that is robust, stable, and provides high-fidelity simulations for a relatively wide range of parameters and operating conditions can provide a solution to this problem. The fidelity of a new framework for persistent model order reduction of large and complex dynamical systems is investigated. The framework is validated using several numerical examples including a large linear system and two complex nonlinear systems with material and geometrical nonlinearities. While the framework is used for identifying the robust subspaces obtained from both proper and smooth orthogonal decompositions (POD and SOD, respectively), the results show that SOD outperforms POD in terms of stability, accuracy, and robustness.

Innovations in dynamic test restraint systems

NASA Technical Reports Server (NTRS)

Fuld, Christopher J.

1990-01-01

Recent launch system development programs have led to a new generation of large scale dynamic tests. The variety of test scenarios share one common requirement: restrain and capture massive high velocity flight hardware with no structural damage. The Space Systems Lab of McDonnell Douglas developed a remarkably simple and cost effective approach to such testing using ripstitch energy absorbers adapted from the sport of technical rockclimbing. The proven system reliability of the capture system concept has led to a wide variety of applications in test system design and in aerospace hardware design.

Dynamical Crossovers in Prethermal Critical States.

PubMed

Chiocchetta, Alessio; Gambassi, Andrea; Diehl, Sebastian; Marino, Jamir

2017-03-31

We study the prethermal dynamics of an interacting quantum field theory with an N-component order parameter and O(N) symmetry, suddenly quenched in the vicinity of a dynamical critical point. Depending on the initial conditions, the evolution of the order parameter, and of the response and correlation functions, can exhibit a temporal crossover between universal dynamical scaling regimes governed, respectively, by a quantum and a classical prethermal fixed point, as well as a crossover from a Gaussian to a non-Gaussian prethermal dynamical scaling. Together with a recent experiment, this suggests that quenches may be used in order to explore the rich variety of dynamical critical points occurring in the nonequilibrium dynamics of a quantum many-body system. We illustrate this fact by using a combination of renormalization group techniques and a nonperturbative large-N limit.

Criticality as a Set-Point for Adaptive Behavior in Neuromorphic Hardware

PubMed Central

Srinivasa, Narayan; Stepp, Nigel D.; Cruz-Albrecht, Jose

2015-01-01

Neuromorphic hardware are designed by drawing inspiration from biology to overcome limitations of current computer architectures while forging the development of a new class of autonomous systems that can exhibit adaptive behaviors. Several designs in the recent past are capable of emulating large scale networks but avoid complexity in network dynamics by minimizing the number of dynamic variables that are supported and tunable in hardware. We believe that this is due to the lack of a clear understanding of how to design self-tuning complex systems. It has been widely demonstrated that criticality appears to be the default state of the brain and manifests in the form of spontaneous scale-invariant cascades of neural activity. Experiment, theory and recent models have shown that neuronal networks at criticality demonstrate optimal information transfer, learning and information processing capabilities that affect behavior. In this perspective article, we argue that understanding how large scale neuromorphic electronics can be designed to enable emergent adaptive behavior will require an understanding of how networks emulated by such hardware can self-tune local parameters to maintain criticality as a set-point. We believe that such capability will enable the design of truly scalable intelligent systems using neuromorphic hardware that embrace complexity in network dynamics rather than avoiding it. PMID:26648839

Root structural and functional dynamics in terrestrial biosphere models--evaluation and recommendations.

PubMed

Warren, Jeffrey M; Hanson, Paul J; Iversen, Colleen M; Kumar, Jitendra; Walker, Anthony P; Wullschleger, Stan D

2015-01-01

There is wide breadth of root function within ecosystems that should be considered when modeling the terrestrial biosphere. Root structure and function are closely associated with control of plant water and nutrient uptake from the soil, plant carbon (C) assimilation, partitioning and release to the soils, and control of biogeochemical cycles through interactions within the rhizosphere. Root function is extremely dynamic and dependent on internal plant signals, root traits and morphology, and the physical, chemical and biotic soil environment. While plant roots have significant structural and functional plasticity to changing environmental conditions, their dynamics are noticeably absent from the land component of process-based Earth system models used to simulate global biogeochemical cycling. Their dynamic representation in large-scale models should improve model veracity. Here, we describe current root inclusion in models across scales, ranging from mechanistic processes of single roots to parameterized root processes operating at the landscape scale. With this foundation we discuss how existing and future root functional knowledge, new data compilation efforts, and novel modeling platforms can be leveraged to enhance root functionality in large-scale terrestrial biosphere models by improving parameterization within models, and introducing new components such as dynamic root distribution and root functional traits linked to resource extraction. No claim to original US Government works. New Phytologist © 2014 New Phytologist Trust.

DIALOG: An executive computer program for linking independent programs

NASA Technical Reports Server (NTRS)

Glatt, C. R.; Hague, D. S.; Watson, D. A.

1973-01-01

A very large scale computer programming procedure called the DIALOG executive system was developed for the CDC 6000 series computers. The executive computer program, DIALOG, controls the sequence of execution and data management function for a library of independent computer programs. Communication of common information is accomplished by DIALOG through a dynamically constructed and maintained data base of common information. Each computer program maintains its individual identity and is unaware of its contribution to the large scale program. This feature makes any computer program a candidate for use with the DIALOG executive system. The installation and uses of the DIALOG executive system are described.

Scale-invariance underlying the logistic equation and its social applications

NASA Astrophysics Data System (ADS)

Hernando, A.; Plastino, A.

2013-01-01

On the basis of dynamical principles we i) advance a derivation of the Logistic Equation (LE), widely employed (among multiple applications) in the simulation of population growth, and ii) demonstrate that scale-invariance and a mean-value constraint are sufficient and necessary conditions for obtaining it. We also generalize the LE to multi-component systems and show that the above dynamical mechanisms underlie a large number of scale-free processes. Examples are presented regarding city-populations, diffusion in complex networks, and popularity of technological products, all of them obeying the multi-component logistic equation in an either stochastic or deterministic way.

Gyrodampers for large space structures

NASA Technical Reports Server (NTRS)

Aubrun, J. N.; Margulies, G.

1979-01-01

The problem of controlling the vibrations of a large space structures by the use of actively augmented damping devices distributed throughout the structure is addressed. The gyrodamper which consists of a set of single gimbal control moment gyros which are actively controlled to extract the structural vibratory energy through the local rotational deformations of the structure, is described and analyzed. Various linear and nonlinear dynamic simulations of gyrodamped beams are shown, including results on self-induced vibrations due to sensor noise and rotor imbalance. The complete nonlinear dynamic equations are included. The problem of designing and sizing a system of gyrodampers for a given structure, or extrapolating results for one gyrodamped structure to another is solved in terms of scaling laws. Novel scaling laws for gyro systems are derived, based upon fundamental physical principles, and various examples are given.

Temperature for a dynamic spin ensemble

NASA Astrophysics Data System (ADS)

Ma, Pui-Wai; Dudarev, S. L.; Semenov, A. A.; Woo, C. H.

2010-09-01

In molecular dynamics simulations, temperature is evaluated, via the equipartition principle, by computing the mean kinetic energy of atoms. There is no similar recipe yet for evaluating temperature of a dynamic system of interacting spins. By solving semiclassical Langevin spin-dynamics equations, and applying the fluctuation-dissipation theorem, we derive an equation for the temperature of a spin ensemble, expressed in terms of dynamic spin variables. The fact that definitions for the kinetic and spin temperatures are fully consistent is illustrated using large-scale spin dynamics and spin-lattice dynamics simulations.

Efficient preconditioning of the electronic structure problem in large scale ab initio molecular dynamics simulations

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

Schiffmann, Florian; VandeVondele, Joost, E-mail: Joost.VandeVondele@mat.ethz.ch

2015-06-28

We present an improved preconditioning scheme for electronic structure calculations based on the orbital transformation method. First, a preconditioner is developed which includes information from the full Kohn-Sham matrix but avoids computationally demanding diagonalisation steps in its construction. This reduces the computational cost of its construction, eliminating a bottleneck in large scale simulations, while maintaining rapid convergence. In addition, a modified form of Hotelling’s iterative inversion is introduced to replace the exact inversion of the preconditioner matrix. This method is highly effective during molecular dynamics (MD), as the solution obtained in earlier MD steps is a suitable initial guess. Filteringmore » small elements during sparse matrix multiplication leads to linear scaling inversion, while retaining robustness, already for relatively small systems. For system sizes ranging from a few hundred to a few thousand atoms, which are typical for many practical applications, the improvements to the algorithm lead to a 2-5 fold speedup per MD step.« less

On the decentralized control of large-scale systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Chong, C.

1973-01-01

The decentralized control of stochastic large scale systems was considered. Particular emphasis was given to control strategies which utilize decentralized information and can be computed in a decentralized manner. The deterministic constrained optimization problem is generalized to the stochastic case when each decision variable depends on different information and the constraint is only required to be satisfied on the average. For problems with a particular structure, a hierarchical decomposition is obtained. For the stochastic control of dynamic systems with different information sets, a new kind of optimality is proposed which exploits the coupled nature of the dynamic system. The subsystems are assumed to be uncoupled and then certain constraints are required to be satisfied, either in a off-line or on-line fashion. For off-line coordination, a hierarchical approach of solving the problem is obtained. The lower level problems are all uncoupled. For on-line coordination, distinction is made between open loop feedback optimal coordination and closed loop optimal coordination.

Sensitivity of proxies on non-linear interactions in the climate system

PubMed Central

Schultz, Johannes A.; Beck, Christoph; Menz, Gunter; Neuwirth, Burkhard; Ohlwein, Christian; Philipp, Andreas

2015-01-01

Recent climate change is affecting the earth system to an unprecedented extent and intensity and has the potential to cause severe ecological and socioeconomic consequences. To understand natural and anthropogenic induced processes, feedbacks, trends, and dynamics in the climate system, it is also essential to consider longer timescales. In this context, annually resolved tree-ring data are often used to reconstruct past temperature or precipitation variability as well as atmospheric or oceanic indices such as the North Atlantic Oscillation (NAO) or the Atlantic Multidecadal Oscillation (AMO). The aim of this study is to assess weather-type sensitivity across the Northern Atlantic region based on two tree-ring width networks. Our results indicate that nonstationarities in superordinate space and time scales of the climate system (here synoptic- to global scale, NAO, AMO) can affect the climate sensitivity of tree-rings in subordinate levels of the system (here meso- to synoptic scale, weather-types). This scale bias effect has the capability to impact even large multiproxy networks and the ability of these networks to provide information about past climate conditions. To avoid scale biases in climate reconstructions, interdependencies between the different scales in the climate system must be considered, especially internal ocean/atmosphere dynamics. PMID:26686001

Unique Testing Capabilities of the NASA Langley Transonic Dynamics Tunnel, an Exercise in Aeroelastic Scaling

NASA Technical Reports Server (NTRS)

Ivanco, Thomas G.

2013-01-01

NASA Langley Research Center's Transonic Dynamics Tunnel (TDT) is the world's most capable aeroelastic test facility. Its large size, transonic speed range, variable pressure capability, and use of either air or R-134a heavy gas as a test medium enable unparalleled manipulation of flow-dependent scaling quantities. Matching these scaling quantities enables dynamic similitude of a full-scale vehicle with a sub-scale model, a requirement for proper characterization of any dynamic phenomenon, and many static elastic phenomena. Select scaling parameters are presented in order to quantify the scaling advantages of TDT and the consequence of testing in other facilities. In addition to dynamic testing, the TDT is uniquely well-suited for high risk testing or for those tests that require unusual model mount or support systems. Examples of recently conducted dynamic tests requiring unusual model support are presented. In addition to its unique dynamic test capabilities, the TDT is also evaluated in its capability to conduct aerodynamic performance tests as a result of its flow quality. Results of flow quality studies and a comparison to a many other transonic facilities are presented. Finally, the ability of the TDT to support future NASA research thrusts and likely vehicle designs is discussed.

Quantifying Km-scale Hydrological Exchange Flows under Dynamic Flows and Their Influences on River Corridor Biogeochemistry

NASA Astrophysics Data System (ADS)

Chen, X.; Song, X.; Shuai, P.; Hammond, G. E.; Ren, H.; Zachara, J. M.

2017-12-01

Hydrologic exchange flows (HEFs) in rivers play vital roles in watershed ecological and biogeochemical functions due to their strong capacity to attenuate contaminants and process significant quantities of carbon and nutrients. While most of existing HEF studies focus on headwater systems with the assumption of steady-state flow, there is lack of understanding of large-scale HEFs in high-order regulated rivers that experience high-frequency stage fluctuations. The large variability of HEFs is a result of interactions between spatial heterogeneity in hydrogeologic properties and temporal variation in river discharge induced by natural or anthropogenic perturbations. Our 9-year spatially distributed dataset (water elevation, specific conductance, and temperature) combined with mechanistic hydrobiogeochemical simulations have revealed complex spatial and temporal dynamics in km-scale HEFs and their significant impacts on contaminant plume mobility and hyporheic biogeochemical processes along the Hanford Reach. Extended multidirectional flow behaviors of unconfined, river corridor groundwater were observed hundreds of meters inland from the river shore resulting from discharge-dependent HEFs. An appropriately sized modeling domain to capture the impact of regional groundwater flow as well as knowledge of subsurface structures controlling intra-aquifer hydrologic connectivity were essential to realistically model transient storage in this large-scale river corridor. This work showed that both river water and mobile groundwater contaminants could serve as effective tracers of HEFs, thus providing valuable information for evaluating and validating the HEF models. Multimodal residence time distributions with long tails were resulted from the mixture of long and short exchange pathways, which consequently impact the carbon and nutrient cycling within the river corridor. Improved understanding of HEFs using integrated observational and modeling approaches sheds light on developing fundamental understanding of the influences of HEFs on water quality, nutrient dynamics, and ecosystem health in dynamic river corridor systems.

The Australian Computational Earth Systems Simulator

NASA Astrophysics Data System (ADS)

Mora, P.; Muhlhaus, H.; Lister, G.; Dyskin, A.; Place, D.; Appelbe, B.; Nimmervoll, N.; Abramson, D.

2001-12-01

Numerical simulation of the physics and dynamics of the entire earth system offers an outstanding opportunity for advancing earth system science and technology but represents a major challenge due to the range of scales and physical processes involved, as well as the magnitude of the software engineering effort required. However, new simulation and computer technologies are bringing this objective within reach. Under a special competitive national funding scheme to establish new Major National Research Facilities (MNRF), the Australian government together with a consortium of Universities and research institutions have funded construction of the Australian Computational Earth Systems Simulator (ACcESS). The Simulator or computational virtual earth will provide the research infrastructure to the Australian earth systems science community required for simulations of dynamical earth processes at scales ranging from microscopic to global. It will consist of thematic supercomputer infrastructure and an earth systems simulation software system. The Simulator models and software will be constructed over a five year period by a multi-disciplinary team of computational scientists, mathematicians, earth scientists, civil engineers and software engineers. The construction team will integrate numerical simulation models (3D discrete elements/lattice solid model, particle-in-cell large deformation finite-element method, stress reconstruction models, multi-scale continuum models etc) with geophysical, geological and tectonic models, through advanced software engineering and visualization technologies. When fully constructed, the Simulator aims to provide the software and hardware infrastructure needed to model solid earth phenomena including global scale dynamics and mineralisation processes, crustal scale processes including plate tectonics, mountain building, interacting fault system dynamics, and micro-scale processes that control the geological, physical and dynamic behaviour of earth systems. ACcESS represents a part of Australia's contribution to the APEC Cooperation for Earthquake Simulation (ACES) international initiative. Together with other national earth systems science initiatives including the Japanese Earth Simulator and US General Earthquake Model projects, ACcESS aims to provide a driver for scientific advancement and technological breakthroughs including: quantum leaps in understanding of earth evolution at global, crustal, regional and microscopic scales; new knowledge of the physics of crustal fault systems required to underpin the grand challenge of earthquake prediction; new understanding and predictive capabilities of geological processes such as tectonics and mineralisation.

Long-term spatial and temporal microbial community dynamics in a large-scale drinking water distribution system with multiple disinfectant regimes.

PubMed

Potgieter, Sarah; Pinto, Ameet; Sigudu, Makhosazana; du Preez, Hein; Ncube, Esper; Venter, Stephanus

2018-08-01

Long-term spatial-temporal investigations of microbial dynamics in full-scale drinking water distribution systems are scarce. These investigations can reveal the process, infrastructure, and environmental factors that influence the microbial community, offering opportunities to re-think microbial management in drinking water systems. Often, these insights are missed or are unreliable in short-term studies, which are impacted by stochastic variabilities inherent to large full-scale systems. In this two-year study, we investigated the spatial and temporal dynamics of the microbial community in a large, full scale South African drinking water distribution system that uses three successive disinfection strategies (i.e. chlorination, chloramination and hypochlorination). Monthly bulk water samples were collected from the outlet of the treatment plant and from 17 points in the distribution system spanning nearly 150 km and the bacterial community composition was characterised by Illumina MiSeq sequencing of the V4 hypervariable region of the 16S rRNA gene. Like previous studies, Alpha- and Betaproteobacteria dominated the drinking water bacterial communities, with an increase in Betaproteobacteria post-chloramination. In contrast with previous reports, the observed richness, diversity, and evenness of the bacterial communities were higher in the winter months as opposed to the summer months in this study. In addition to temperature effects, the seasonal variations were also likely to be influenced by changes in average water age in the distribution system and corresponding changes in disinfectant residual concentrations. Spatial dynamics of the bacterial communities indicated distance decay, with bacterial communities becoming increasingly dissimilar with increasing distance between sampling locations. These spatial effects dampened the temporal changes in the bulk water community and were the dominant factor when considering the entire distribution system. However, temporal variations were consistently stronger as compared to spatial changes at individual sampling locations and demonstrated seasonality. This study emphasises the need for long-term studies to comprehensively understand the temporal patterns that would otherwise be missed in short-term investigations. Furthermore, systematic long-term investigations are particularly critical towards determining the impact of changes in source water quality, environmental conditions, and process operations on the changes in microbial community composition in the drinking water distribution system. Copyright © 2018 Elsevier Ltd. All rights reserved.

Spatial synchrony of local populations has increased in association with the recent Northern Hemisphere climate trend.

PubMed

Post, Eric; Forchhammer, Mads C

2004-06-22

According to ecological theory, populations whose dynamics are entrained by environmental correlation face increased extinction risk as environmental conditions become more synchronized spatially. This prediction is highly relevant to the study of ecological consequences of climate change. Recent empirical studies have indicated, for example, that large-scale climate synchronizes trophic interactions and population dynamics over broad spatial scales in freshwater and terrestrial systems. Here, we present an analysis of century-scale, spatially replicated data on local weather and the population dynamics of caribou in Greenland. Our results indicate that spatial autocorrelation in local weather has increased with large-scale climatic warming. This increase in spatial synchrony of environmental conditions has been matched, in turn, by an increase in the spatial synchrony of local caribou populations toward the end of the 20th century. Our results indicate that spatial synchrony in environmental conditions and the populations influenced by them are highly variable through time and can increase with climatic warming. We suggest that if future warming can increase population synchrony, it may also increase extinction risk.

A Large Scale Dynamical System Immune Network Modelwith Finite Connectivity

NASA Astrophysics Data System (ADS)

Uezu, T.; Kadono, C.; Hatchett, J.; Coolen, A. C. C.

We study a model of an idiotypic immune network which was introduced by N. K. Jerne. It is known that in immune systems there generally exist several kinds of immune cells which can recognize any particular antigen. Taking this fact into account and assuming that each cell interacts with only a finite number of other cells, we analyze a large scale immune network via both numerical simulations and statistical mechanical methods, and show that the distribution of the concentrations of antibodies becomes non-trivial for a range of values of the strength of the interaction and the connectivity.

RE-Europe, a large-scale dataset for modeling a highly renewable European electricity system

PubMed Central

Jensen, Tue V.; Pinson, Pierre

2017-01-01

Future highly renewable energy systems will couple to complex weather and climate dynamics. This coupling is generally not captured in detail by the open models developed in the power and energy system communities, where such open models exist. To enable modeling such a future energy system, we describe a dedicated large-scale dataset for a renewable electric power system. The dataset combines a transmission network model, as well as information for generation and demand. Generation includes conventional generators with their technical and economic characteristics, as well as weather-driven forecasts and corresponding realizations for renewable energy generation for a period of 3 years. These may be scaled according to the envisioned degrees of renewable penetration in a future European energy system. The spatial coverage, completeness and resolution of this dataset, open the door to the evaluation, scaling analysis and replicability check of a wealth of proposals in, e.g., market design, network actor coordination and forecasting of renewable power generation. PMID:29182600

RE-Europe, a large-scale dataset for modeling a highly renewable European electricity system.

PubMed

Jensen, Tue V; Pinson, Pierre

2017-11-28

Future highly renewable energy systems will couple to complex weather and climate dynamics. This coupling is generally not captured in detail by the open models developed in the power and energy system communities, where such open models exist. To enable modeling such a future energy system, we describe a dedicated large-scale dataset for a renewable electric power system. The dataset combines a transmission network model, as well as information for generation and demand. Generation includes conventional generators with their technical and economic characteristics, as well as weather-driven forecasts and corresponding realizations for renewable energy generation for a period of 3 years. These may be scaled according to the envisioned degrees of renewable penetration in a future European energy system. The spatial coverage, completeness and resolution of this dataset, open the door to the evaluation, scaling analysis and replicability check of a wealth of proposals in, e.g., market design, network actor coordination and forecasting of renewable power generation.

RE-Europe, a large-scale dataset for modeling a highly renewable European electricity system

NASA Astrophysics Data System (ADS)

Jensen, Tue V.; Pinson, Pierre

2017-11-01

Future highly renewable energy systems will couple to complex weather and climate dynamics. This coupling is generally not captured in detail by the open models developed in the power and energy system communities, where such open models exist. To enable modeling such a future energy system, we describe a dedicated large-scale dataset for a renewable electric power system. The dataset combines a transmission network model, as well as information for generation and demand. Generation includes conventional generators with their technical and economic characteristics, as well as weather-driven forecasts and corresponding realizations for renewable energy generation for a period of 3 years. These may be scaled according to the envisioned degrees of renewable penetration in a future European energy system. The spatial coverage, completeness and resolution of this dataset, open the door to the evaluation, scaling analysis and replicability check of a wealth of proposals in, e.g., market design, network actor coordination and forecasting of renewable power generation.

System and Method for Dynamic Aeroelastic Control

NASA Technical Reports Server (NTRS)

Suh, Peter M. (Inventor)

2015-01-01

The present invention proposes a hardware and software architecture for dynamic modal structural monitoring that uses a robust modal filter to monitor a potentially very large-scale array of sensors in real time, and tolerant of asymmetric sensor noise and sensor failures, to achieve aircraft performance optimization such as minimizing aircraft flutter, drag and maximizing fuel efficiency.

Harnessing Big Data to Represent 30-meter Spatial Heterogeneity in Earth System Models

NASA Astrophysics Data System (ADS)

Chaney, N.; Shevliakova, E.; Malyshev, S.; Van Huijgevoort, M.; Milly, C.; Sulman, B. N.

2016-12-01

Terrestrial land surface processes play a critical role in the Earth system; they have a profound impact on the global climate, food and energy production, freshwater resources, and biodiversity. One of the most fascinating yet challenging aspects of characterizing terrestrial ecosystems is their field-scale (˜30 m) spatial heterogeneity. It has been observed repeatedly that the water, energy, and biogeochemical cycles at multiple temporal and spatial scales have deep ties to an ecosystem's spatial structure. Current Earth system models largely disregard this important relationship leading to an inadequate representation of ecosystem dynamics. In this presentation, we will show how existing global environmental datasets can be harnessed to explicitly represent field-scale spatial heterogeneity in Earth system models. For each macroscale grid cell, these environmental data are clustered according to their field-scale soil and topographic attributes to define unique sub-grid tiles. The state-of-the-art Geophysical Fluid Dynamics Laboratory (GFDL) land model is then used to simulate these tiles and their spatial interactions via the exchange of water, energy, and nutrients along explicit topographic gradients. Using historical simulations over the contiguous United States, we will show how a robust representation of field-scale spatial heterogeneity impacts modeled ecosystem dynamics including the water, energy, and biogeochemical cycles as well as vegetation composition and distribution.

Organizational Agility and Complex Enterprise System Innovations: A Mixed Methods Study of the Effects of Enterprise Systems on Organizational Agility

ERIC Educational Resources Information Center

Kharabe, Amol T.

2012-01-01

Over the last two decades, firms have operated in "increasingly" accelerated "high-velocity" dynamic markets, which require them to become "agile." During the same time frame, firms have increasingly deployed complex enterprise systems--large-scale packaged software "innovations" that integrate and automate…

Dynamic displacement measurement of large-scale structures based on the Lucas-Kanade template tracking algorithm

NASA Astrophysics Data System (ADS)

Guo, Jie; Zhu, Chang`an

2016-01-01

The development of optics and computer technologies enables the application of the vision-based technique that uses digital cameras to the displacement measurement of large-scale structures. Compared with traditional contact measurements, vision-based technique allows for remote measurement, has a non-intrusive characteristic, and does not necessitate mass introduction. In this study, a high-speed camera system is developed to complete the displacement measurement in real time. The system consists of a high-speed camera and a notebook computer. The high-speed camera can capture images at a speed of hundreds of frames per second. To process the captured images in computer, the Lucas-Kanade template tracking algorithm in the field of computer vision is introduced. Additionally, a modified inverse compositional algorithm is proposed to reduce the computing time of the original algorithm and improve the efficiency further. The modified algorithm can rapidly accomplish one displacement extraction within 1 ms without having to install any pre-designed target panel onto the structures in advance. The accuracy and the efficiency of the system in the remote measurement of dynamic displacement are demonstrated in the experiments on motion platform and sound barrier on suspension viaduct. Experimental results show that the proposed algorithm can extract accurate displacement signal and accomplish the vibration measurement of large-scale structures.

SQDFT: Spectral Quadrature method for large-scale parallel O(N) Kohn-Sham calculations at high temperature

NASA Astrophysics Data System (ADS)

Suryanarayana, Phanish; Pratapa, Phanisri P.; Sharma, Abhiraj; Pask, John E.

2018-03-01

We present SQDFT: a large-scale parallel implementation of the Spectral Quadrature (SQ) method for O(N) Kohn-Sham Density Functional Theory (DFT) calculations at high temperature. Specifically, we develop an efficient and scalable finite-difference implementation of the infinite-cell Clenshaw-Curtis SQ approach, in which results for the infinite crystal are obtained by expressing quantities of interest as bilinear forms or sums of bilinear forms, that are then approximated by spatially localized Clenshaw-Curtis quadrature rules. We demonstrate the accuracy of SQDFT by showing systematic convergence of energies and atomic forces with respect to SQ parameters to reference diagonalization results, and convergence with discretization to established planewave results, for both metallic and insulating systems. We further demonstrate that SQDFT achieves excellent strong and weak parallel scaling on computer systems consisting of tens of thousands of processors, with near perfect O(N) scaling with system size and wall times as low as a few seconds per self-consistent field iteration. Finally, we verify the accuracy of SQDFT in large-scale quantum molecular dynamics simulations of aluminum at high temperature.

VisIRR: A Visual Analytics System for Information Retrieval and Recommendation for Large-Scale Document Data

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

Choo, Jaegul; Kim, Hannah; Clarkson, Edward

In this paper, we present an interactive visual information retrieval and recommendation system, called VisIRR, for large-scale document discovery. VisIRR effectively combines the paradigms of (1) a passive pull through query processes for retrieval and (2) an active push that recommends items of potential interest to users based on their preferences. Equipped with an efficient dynamic query interface against a large-scale corpus, VisIRR organizes the retrieved documents into high-level topics and visualizes them in a 2D space, representing the relationships among the topics along with their keyword summary. In addition, based on interactive personalized preference feedback with regard to documents,more » VisIRR provides document recommendations from the entire corpus, which are beyond the retrieved sets. Such recommended documents are visualized in the same space as the retrieved documents, so that users can seamlessly analyze both existing and newly recommended ones. This article presents novel computational methods, which make these integrated representations and fast interactions possible for a large-scale document corpus. We illustrate how the system works by providing detailed usage scenarios. Finally, we present preliminary user study results for evaluating the effectiveness of the system.« less

VisIRR: A Visual Analytics System for Information Retrieval and Recommendation for Large-Scale Document Data

DOE PAGES

Choo, Jaegul; Kim, Hannah; Clarkson, Edward; ...

2018-01-31

In this paper, we present an interactive visual information retrieval and recommendation system, called VisIRR, for large-scale document discovery. VisIRR effectively combines the paradigms of (1) a passive pull through query processes for retrieval and (2) an active push that recommends items of potential interest to users based on their preferences. Equipped with an efficient dynamic query interface against a large-scale corpus, VisIRR organizes the retrieved documents into high-level topics and visualizes them in a 2D space, representing the relationships among the topics along with their keyword summary. In addition, based on interactive personalized preference feedback with regard to documents,more » VisIRR provides document recommendations from the entire corpus, which are beyond the retrieved sets. Such recommended documents are visualized in the same space as the retrieved documents, so that users can seamlessly analyze both existing and newly recommended ones. This article presents novel computational methods, which make these integrated representations and fast interactions possible for a large-scale document corpus. We illustrate how the system works by providing detailed usage scenarios. Finally, we present preliminary user study results for evaluating the effectiveness of the system.« less

Preliminary simulations of the large-scale environment during the FIRE cirrus IFO

NASA Technical Reports Server (NTRS)

Westphal, Douglas L.; Toon, Owen B.

1990-01-01

Large scale forcing (scales greater than 500 km) is the dominant factor in the generation, maintenance, and dissipation of cirrus cloud systems. However, the analyses of data acquired during the first Cirrus IFO have highlighted the importance of mesoscale processes (scales of 20 to 500 km) to the development of cirrus cloud systems. Unfortunately, Starr and Wylie found that the temporal and spatial resolution of the standard and supplemental rawinsonde data were insufficient to allow an explanation of all of the mesoscale cloud features that were present on the 27 to 28 Oct. 1986. It is described how dynamic initialization, or 4-D data assimilation (FDDA) can provide a method to address this problem. The first steps towards application of FDDA to FIRE are also described.

Model and Data Reduction for Control, Identification and Compressed Sensing

NASA Astrophysics Data System (ADS)

Kramer, Boris

This dissertation focuses on problems in design, optimization and control of complex, large-scale dynamical systems from different viewpoints. The goal is to develop new algorithms and methods, that solve real problems more efficiently, together with providing mathematical insight into the success of those methods. There are three main contributions in this dissertation. In Chapter 3, we provide a new method to solve large-scale algebraic Riccati equations, which arise in optimal control, filtering and model reduction. We present a projection based algorithm utilizing proper orthogonal decomposition, which is demonstrated to produce highly accurate solutions at low rank. The method is parallelizable, easy to implement for practitioners, and is a first step towards a matrix free approach to solve AREs. Numerical examples for n ≥ 106 unknowns are presented. In Chapter 4, we develop a system identification method which is motivated by tangential interpolation. This addresses the challenge of fitting linear time invariant systems to input-output responses of complex dynamics, where the number of inputs and outputs is relatively large. The method reduces the computational burden imposed by a full singular value decomposition, by carefully choosing directions on which to project the impulse response prior to assembly of the Hankel matrix. The identification and model reduction step follows from the eigensystem realization algorithm. We present three numerical examples, a mass spring damper system, a heat transfer problem, and a fluid dynamics system. We obtain error bounds and stability results for this method. Chapter 5 deals with control and observation design for parameter dependent dynamical systems. We address this by using local parametric reduced order models, which can be used online. Data available from simulations of the system at various configurations (parameters, boundary conditions) is used to extract a sparse basis to represent the dynamics (via dynamic mode decomposition). Subsequently, a new, compressed sensing based classification algorithm is developed which incorporates the extracted dynamic information into the sensing basis. We show that this augmented classification basis makes the method more robust to noise, and results in superior identification of the correct parameter. Numerical examples consist of a Navier-Stokes, as well as a Boussinesq flow application.

A large-scale circuit mechanism for hierarchical dynamical processing in the primate cortex

PubMed Central

Chaudhuri, Rishidev; Knoblauch, Kenneth; Gariel, Marie-Alice; Kennedy, Henry; Wang, Xiao-Jing

2015-01-01

We developed a large-scale dynamical model of the macaque neocortex, which is based on recently acquired directed- and weighted-connectivity data from tract-tracing experiments, and which incorporates heterogeneity across areas. A hierarchy of timescales naturally emerges from this system: sensory areas show brief, transient responses to input (appropriate for sensory processing), whereas association areas integrate inputs over time and exhibit persistent activity (suitable for decision-making and working memory). The model displays multiple temporal hierarchies, as evidenced by contrasting responses to visual versus somatosensory stimulation. Moreover, slower prefrontal and temporal areas have a disproportionate impact on global brain dynamics. These findings establish a circuit mechanism for “temporal receptive windows” that are progressively enlarged along the cortical hierarchy, suggest an extension of time integration in decision-making from local to large circuits, and should prompt a re-evaluation of the analysis of functional connectivity (measured by fMRI or EEG/MEG) by taking into account inter-areal heterogeneity. PMID:26439530

Ground-motion signature of dynamic ruptures on rough faults

NASA Astrophysics Data System (ADS)

Mai, P. Martin; Galis, Martin; Thingbaijam, Kiran K. S.; Vyas, Jagdish C.

2016-04-01

Natural earthquakes occur on faults characterized by large-scale segmentation and small-scale roughness. This multi-scale geometrical complexity controls the dynamic rupture process, and hence strongly affects the radiated seismic waves and near-field shaking. For a fault system with given segmentation, the question arises what are the conditions for producing large-magnitude multi-segment ruptures, as opposed to smaller single-segment events. Similarly, for variable degrees of roughness, ruptures may be arrested prematurely or may break the entire fault. In addition, fault roughness induces rupture incoherence that determines the level of high-frequency radiation. Using HPC-enabled dynamic-rupture simulations, we generate physically self-consistent rough-fault earthquake scenarios (M~6.8) and their associated near-source seismic radiation. Because these computations are too expensive to be conducted routinely for simulation-based seismic hazard assessment, we thrive to develop an effective pseudo-dynamic source characterization that produces (almost) the same ground-motion characteristics. Therefore, we examine how variable degrees of fault roughness affect rupture properties and the seismic wavefield, and develop a planar-fault kinematic source representation that emulates the observed dynamic behaviour. We propose an effective workflow for improved pseudo-dynamic source modelling that incorporates rough-fault effects and its associated high-frequency radiation in broadband ground-motion computation for simulation-based seismic hazard assessment.

Dynamical transitions in large systems of mean field-coupled Landau-Stuart oscillators: Extensive chaos and cluster states.

PubMed

Ku, Wai Lim; Girvan, Michelle; Ott, Edward

2015-12-01

In this paper, we study dynamical systems in which a large number N of identical Landau-Stuart oscillators are globally coupled via a mean-field. Previously, it has been observed that this type of system can exhibit a variety of different dynamical behaviors. These behaviors include time periodic cluster states in which each oscillator is in one of a small number of groups for which all oscillators in each group have the same state which is different from group to group, as well as a behavior in which all oscillators have different states and the macroscopic dynamics of the mean field is chaotic. We argue that this second type of behavior is "extensive" in the sense that the chaotic attractor in the full phase space of the system has a fractal dimension that scales linearly with N and that the number of positive Lyapunov exponents of the attractor also scales linearly with N. An important focus of this paper is the transition between cluster states and extensive chaos as the system is subjected to slow adiabatic parameter change. We observe discontinuous transitions between the cluster states (which correspond to low dimensional dynamics) and the extensively chaotic states. Furthermore, examining the cluster state, as the system approaches the discontinuous transition to extensive chaos, we find that the oscillator population distribution between the clusters continually evolves so that the cluster state is always marginally stable. This behavior is used to reveal the mechanism of the discontinuous transition. We also apply the Kaplan-Yorke formula to study the fractal structure of the extensively chaotic attractors.

Dynamical transitions in large systems of mean field-coupled Landau-Stuart oscillators: Extensive chaos and cluster states

NASA Astrophysics Data System (ADS)

Ku, Wai Lim; Girvan, Michelle; Ott, Edward

2015-12-01

In this paper, we study dynamical systems in which a large number N of identical Landau-Stuart oscillators are globally coupled via a mean-field. Previously, it has been observed that this type of system can exhibit a variety of different dynamical behaviors. These behaviors include time periodic cluster states in which each oscillator is in one of a small number of groups for which all oscillators in each group have the same state which is different from group to group, as well as a behavior in which all oscillators have different states and the macroscopic dynamics of the mean field is chaotic. We argue that this second type of behavior is "extensive" in the sense that the chaotic attractor in the full phase space of the system has a fractal dimension that scales linearly with N and that the number of positive Lyapunov exponents of the attractor also scales linearly with N. An important focus of this paper is the transition between cluster states and extensive chaos as the system is subjected to slow adiabatic parameter change. We observe discontinuous transitions between the cluster states (which correspond to low dimensional dynamics) and the extensively chaotic states. Furthermore, examining the cluster state, as the system approaches the discontinuous transition to extensive chaos, we find that the oscillator population distribution between the clusters continually evolves so that the cluster state is always marginally stable. This behavior is used to reveal the mechanism of the discontinuous transition. We also apply the Kaplan-Yorke formula to study the fractal structure of the extensively chaotic attractors.

Scaling Coastal Ecosystems to Oceanographic and Climatic Drivers: Making Sense of Community Variation on Rocky Shores Using the Comparative-Experimental Approach in Upwelling and Downwelling Systems

NASA Astrophysics Data System (ADS)

Menge, B. A.; Gouhier, T.; Chan, F.; Hacker, S.; Menge, D.; Nielsen, K. J.

2016-02-01

Ecology focuses increasingly on the issue of matching spatial and temporal scales responsible for ecosystem pattern and dynamics. Benthic coastal communities traditionally were studied at local scales using mostly short-term research, while environmental (oceanographic, climatic) drivers were investigated at large scales (e.g., regional to oceanic, mostly offshore) using combined snapshot and monitoring (time series) research. The comparative-experimental approach combines local-scale studies at multiple sites spanning large-scale environmental gradients in combination with monitoring of inner shelf oceanographic conditions including upwelling/downwelling wind forcing and their consequences (e.g., temperature), and inputs of subsidies (larvae, phytoplankton, detritus). Temporal scale varies depending on the questions, but can extend from years to decades. We discuss two examples of rocky intertidal ecosystem dynamics, one at a regional scale (California Current System, CCS) and one at an interhemispheric scale. In the upwelling-dominated CCS, 52% and 32% of the variance in local community structure (functional group abundances at 13 sites across 725 km) was explained by external factors (ecological subsidies, oceanographic conditions, geographic location), and species interactions, respectively. The interhemispheric study tested the intermittent upwelling hypothesis (IUH), which predicts that key ecological processes will vary unimodally along a persistent downwelling to persistent upwelling gradient. Using 14-22 sites, unimodal relationships between ecological subsidies (phytoplankton, prey recruitment), prey responses (barnacle colonization, mussel growth) and species interactions (competition rate, predation rate and effect) and the Bakun upwelling index calculated at each site accounted for 50% of the variance. Hence, external factors can account for about half of locally-expressed community structure and dynamics.

Requirements for a mobile communications satellite system. Volume 3: Large space structures measurements study

NASA Technical Reports Server (NTRS)

Akle, W.

1983-01-01

This study report defines a set of tests and measurements required to characterize the performance of a Large Space System (LSS), and to scale this data to other LSS satellites. Requirements from the Mobile Communication Satellite (MSAT) configurations derived in the parent study were used. MSAT utilizes a large, mesh deployable antenna, and encompasses a significant range of LSS technology issues in the areas of structural/dynamics, control, and performance predictability. In this study, performance requirements were developed for the antenna. Special emphasis was placed on antenna surface accuracy, and pointing stability. Instrumentation and measurement systems, applicable to LSS, were selected from existing or on-going technology developments. Laser ranging and angulation systems, presently in breadboard status, form the backbone of the measurements. Following this, a set of ground, STS, and GEO-operational were investigated. A third scale (15 meter) antenna system as selected for ground characterization followed by STS flight technology development. This selection ensures analytical scaling from ground-to-orbit, and size scaling. Other benefits are cost and ability to perform reasonable ground tests. Detail costing of the various tests and measurement systems were derived and are included in the report.

Large Scale Deformation of the Western US Cordillera

NASA Technical Reports Server (NTRS)

Bennett, Richard A.

2001-01-01

Destructive earthquakes occur throughout the western US Cordillera (WUSC), not just within the San Andreas fault zone. But because we do not understand the present-day large-scale deformations of the crust throughout the WUSC, our ability to assess the potential for seismic hazards in this region remains severely limited. To address this problem, we are using a large collection of Global Positioning System (GPS) networks which spans the WUSC to precisely quantify present-day large-scale crustal deformations in a single uniform reference frame. Our work can roughly be divided into an analysis of the GPS observations to infer the deformation field across and within the entire plate boundary zone and an investigation of the implications of this deformation field regarding plate boundary dynamics.

Finite-Time and -Size Scalings in the Evaluation of Large Deviation Functions. Numerical Analysis in Continuous Time

NASA Astrophysics Data System (ADS)

Guevara Hidalgo, Esteban; Nemoto, Takahiro; Lecomte, Vivien

Rare trajectories of stochastic systems are important to understand because of their potential impact. However, their properties are by definition difficult to sample directly. Population dynamics provide a numerical tool allowing their study, by means of simulating a large number of copies of the system, which are subjected to a selection rule that favors the rare trajectories of interest. However, such algorithms are plagued by finite simulation time- and finite population size- effects that can render their use delicate. Using the continuous-time cloning algorithm, we analyze the finite-time and finite-size scalings of estimators of the large deviation functions associated to the distribution of the rare trajectories. We use these scalings in order to propose a numerical approach which allows to extract the infinite-time and infinite-size limit of these estimators.

Characterizing and modeling the dynamics of online popularity.

PubMed

Ratkiewicz, Jacob; Fortunato, Santo; Flammini, Alessandro; Menczer, Filippo; Vespignani, Alessandro

2010-10-08

Online popularity has an enormous impact on opinions, culture, policy, and profits. We provide a quantitative, large scale, temporal analysis of the dynamics of online content popularity in two massive model systems: the Wikipedia and an entire country's Web space. We find that the dynamics of popularity are characterized by bursts, displaying characteristic features of critical systems such as fat-tailed distributions of magnitude and interevent time. We propose a minimal model combining the classic preferential popularity increase mechanism with the occurrence of random popularity shifts due to exogenous factors. The model recovers the critical features observed in the empirical analysis of the systems analyzed here, highlighting the key factors needed in the description of popularity dynamics.

"Structure and dynamics in complex chemical systems: Gaining new insights through recent advances in time-resolved spectroscopies.” ACS Division of Physical Chemistry Symposium presented at the Fall National ACS Meeting in Boston, MA, August 2015

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

Crawford, Daniel

8-Session Symposium on STRUCTURE AND DYNAMICS IN COMPLEX CHEMICAL SYSTEMS: GAINING NEW INSIGHTS THROUGH RECENT ADVANCES IN TIME-RESOLVED SPECTROSCOPIES. The intricacy of most chemical, biochemical, and material processes and their applications are underscored by the complex nature of the environments in which they occur. Substantial challenges for building a global understanding of a heterogeneous system include (1) identifying unique signatures associated with specific structural motifs within the heterogeneous distribution, and (2) resolving the significance of each of multiple time scales involved in both small- and large-scale nuclear reorganization. This symposium focuses on the progress in our understanding of dynamics inmore » complex systems driven by recent innovations in time-resolved spectroscopies and theoretical developments. Such advancement is critical for driving discovery at the molecular level facilitating new applications. Broad areas of interest include: Structural relaxation and the impact of structure on dynamics in liquids, interfaces, biochemical systems, materials, and other heterogeneous environments.« less

A Novel Method for Proximity Detection of Moving Targets Using a Large-Scale Planar Capacitive Sensor System

PubMed Central

Ye, Yong; Deng, Jiahao; Shen, Sanmin; Hou, Zhuo; Liu, Yuting

2016-01-01

A novel method for proximity detection of moving targets (with high dielectric constants) using a large-scale (the size of each sensor is 31 cm × 19 cm) planar capacitive sensor system (PCSS) is proposed. The capacitive variation with distance is derived, and a pair of electrodes in a planar capacitive sensor unit (PCSU) with a spiral shape is found to have better performance on sensitivity distribution homogeneity and dynamic range than three other shapes (comb shape, rectangular shape, and circular shape). A driving excitation circuit with a Clapp oscillator is proposed, and a capacitance measuring circuit with sensitivity of 0.21 Vp−p/pF is designed. The results of static experiments and dynamic experiments demonstrate that the voltage curves of static experiments are similar to those of dynamic experiments; therefore, the static data can be used to simulate the dynamic curves. The dynamic range of proximity detection for three projectiles is up to 60 cm, and the results of the following static experiments show that the PCSU with four neighboring units has the highest sensitivity (the sensitivities of other units are at least 4% lower); when the attack angle decreases, the intensity of sensor signal increases. This proposed method leads to the design of a feasible moving target detector with simple structure and low cost, which can be applied in the interception system. PMID:27196905

Simulating Large-Scale Earthquake Dynamic Rupture Scenarios On Natural Fault Zones Using the ADER-DG Method

NASA Astrophysics Data System (ADS)

Gabriel, Alice; Pelties, Christian

2014-05-01

In this presentation we will demonstrate the benefits of using modern numerical methods to support physic-based ground motion modeling and research. For this purpose, we utilize SeisSol an arbitrary high-order derivative Discontinuous Galerkin (ADER-DG) scheme to solve the spontaneous rupture problem with high-order accuracy in space and time using three-dimensional unstructured tetrahedral meshes. We recently verified the method in various advanced test cases of the 'SCEC/USGS Dynamic Earthquake Rupture Code Verification Exercise' benchmark suite, including branching and dipping fault systems, heterogeneous background stresses, bi-material faults and rate-and-state friction constitutive formulations. Now, we study the dynamic rupture process using 3D meshes of fault systems constructed from geological and geophysical constraints, such as high-resolution topography, 3D velocity models and fault geometries. Our starting point is a large scale earthquake dynamic rupture scenario based on the 1994 Northridge blind thrust event in Southern California. Starting from this well documented and extensively studied event, we intend to understand the ground-motion, including the relevant high frequency content, generated from complex fault systems and its variation arising from various physical constraints. For example, our results imply that the Northridge fault geometry favors a pulse-like rupture behavior.

Optimal estimation and scheduling in aquifer management using the rapid feedback control method

NASA Astrophysics Data System (ADS)

Ghorbanidehno, Hojat; Kokkinaki, Amalia; Kitanidis, Peter K.; Darve, Eric

2017-12-01

Management of water resources systems often involves a large number of parameters, as in the case of large, spatially heterogeneous aquifers, and a large number of "noisy" observations, as in the case of pressure observation in wells. Optimizing the operation of such systems requires both searching among many possible solutions and utilizing new information as it becomes available. However, the computational cost of this task increases rapidly with the size of the problem to the extent that textbook optimization methods are practically impossible to apply. In this paper, we present a new computationally efficient technique as a practical alternative for optimally operating large-scale dynamical systems. The proposed method, which we term Rapid Feedback Controller (RFC), provides a practical approach for combined monitoring, parameter estimation, uncertainty quantification, and optimal control for linear and nonlinear systems with a quadratic cost function. For illustration, we consider the case of a weakly nonlinear uncertain dynamical system with a quadratic objective function, specifically a two-dimensional heterogeneous aquifer management problem. To validate our method, we compare our results with the linear quadratic Gaussian (LQG) method, which is the basic approach for feedback control. We show that the computational cost of the RFC scales only linearly with the number of unknowns, a great improvement compared to the basic LQG control with a computational cost that scales quadratically. We demonstrate that the RFC method can obtain the optimal control values at a greatly reduced computational cost compared to the conventional LQG algorithm with small and controllable losses in the accuracy of the state and parameter estimation.

Identifiability of large-scale non-linear dynamic network models applied to the ADM1-case study.

PubMed

Nimmegeers, Philippe; Lauwers, Joost; Telen, Dries; Logist, Filip; Impe, Jan Van

2017-06-01

In this work, both the structural and practical identifiability of the Anaerobic Digestion Model no. 1 (ADM1) is investigated, which serves as a relevant case study of large non-linear dynamic network models. The structural identifiability is investigated using the probabilistic algorithm, adapted to deal with the specifics of the case study (i.e., a large-scale non-linear dynamic system of differential and algebraic equations). The practical identifiability is analyzed using a Monte Carlo parameter estimation procedure for a 'non-informative' and 'informative' experiment, which are heuristically designed. The model structure of ADM1 has been modified by replacing parameters by parameter combinations, to provide a generally locally structurally identifiable version of ADM1. This means that in an idealized theoretical situation, the parameters can be estimated accurately. Furthermore, the generally positive structural identifiability results can be explained from the large number of interconnections between the states in the network structure. This interconnectivity, however, is also observed in the parameter estimates, making uncorrelated parameter estimations in practice difficult. Copyright © 2017. Published by Elsevier Inc.

Heterogeneous dynamics of ionic liquids: A four-point time correlation function approach

NASA Astrophysics Data System (ADS)

Liu, Jiannan; Willcox, Jon A. L.; Kim, Hyung J.

2018-05-01

Many ionic liquids show behavior similar to that of glassy systems, e.g., large and long-lasted deviations from Gaussian dynamics and clustering of "mobile" and "immobile" groups of ions. Herein a time-dependent four-point density correlation function—typically used to characterize glassy systems—is implemented for the ionic liquids, choline acetate, and 1-butyl-3-methylimidazolium acetate. Dynamic correlation beyond the first ionic solvation shell on the time scale of nanoseconds is found in the ionic liquids, revealing the cooperative nature of ion motions. The traditional solvent, acetonitrile, on the other hand, shows a much shorter length-scale that decays after a few picoseconds.

Facilitating dynamo action via control of large-scale turbulence.

PubMed

Limone, A; Hatch, D R; Forest, C B; Jenko, F

2012-12-01

The magnetohydrodynamic dynamo effect is considered to be the major cause of magnetic field generation in geo- and astrophysical systems. Recent experimental and numerical results show that turbulence constitutes an obstacle to dynamos; yet its role in this context is not totally clear. Via numerical simulations, we identify large-scale turbulent vortices with a detrimental effect on the amplification of the magnetic field in a geometry of experimental interest and propose a strategy for facilitating the dynamo instability by manipulating these detrimental "hidden" dynamics.

Research of an emergency medical system for mass casualty incidents in Shanghai, China: a system dynamics model.

PubMed

Yu, Wenya; Lv, Yipeng; Hu, Chaoqun; Liu, Xu; Chen, Haiping; Xue, Chen; Zhang, Lulu

2018-01-01

Emergency medical system for mass casualty incidents (EMS-MCIs) is a global issue. However, China lacks such studies extremely, which cannot meet the requirement of rapid decision-support system. This study aims to realize modeling EMS-MCIs in Shanghai, to improve mass casualty incident (MCI) rescue efficiency in China, and to provide a possible method of making rapid rescue decisions during MCIs. This study established a system dynamics (SD) model of EMS-MCIs using the Vensim DSS program. Intervention scenarios were designed as adjusting scales of MCIs, allocation of ambulances, allocation of emergency medical staff, and efficiency of organization and command. Mortality increased with the increasing scale of MCIs, medical rescue capability of hospitals was relatively good, but the efficiency of organization and command was poor, and the prehospital time was too long. Mortality declined significantly when increasing ambulances and improving the efficiency of organization and command; triage and on-site first-aid time were shortened if increasing the availability of emergency medical staff. The effect was the most evident when 2,000 people were involved in MCIs; however, the influence was very small under the scale of 5,000 people. The keys to decrease the mortality of MCIs were shortening the prehospital time and improving the efficiency of organization and command. For small-scale MCIs, improving the utilization rate of health resources was important in decreasing the mortality. For large-scale MCIs, increasing the number of ambulances and emergency medical professionals was the core to decrease prehospital time and mortality. For super-large-scale MCIs, increasing health resources was the premise.

Exploring Cloud Computing for Large-scale Scientific Applications

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

Lin, Guang; Han, Binh; Yin, Jian

This paper explores cloud computing for large-scale data-intensive scientific applications. Cloud computing is attractive because it provides hardware and software resources on-demand, which relieves the burden of acquiring and maintaining a huge amount of resources that may be used only once by a scientific application. However, unlike typical commercial applications that often just requires a moderate amount of ordinary resources, large-scale scientific applications often need to process enormous amount of data in the terabyte or even petabyte range and require special high performance hardware with low latency connections to complete computation in a reasonable amount of time. To address thesemore » challenges, we build an infrastructure that can dynamically select high performance computing hardware across institutions and dynamically adapt the computation to the selected resources to achieve high performance. We have also demonstrated the effectiveness of our infrastructure by building a system biology application and an uncertainty quantification application for carbon sequestration, which can efficiently utilize data and computation resources across several institutions.« less

Molecular Dynamics Visualization (MDV): Stereoscopic 3D Display of Biomolecular Structure and Interactions Using the Unity Game Engine.

PubMed

Wiebrands, Michael; Malajczuk, Chris J; Woods, Andrew J; Rohl, Andrew L; Mancera, Ricardo L

2018-06-21

Molecular graphics systems are visualization tools which, upon integration into a 3D immersive environment, provide a unique virtual reality experience for research and teaching of biomolecular structure, function and interactions. We have developed a molecular structure and dynamics application, the Molecular Dynamics Visualization tool, that uses the Unity game engine combined with large scale, multi-user, stereoscopic visualization systems to deliver an immersive display experience, particularly with a large cylindrical projection display. The application is structured to separate the biomolecular modeling and visualization systems. The biomolecular model loading and analysis system was developed as a stand-alone C# library and provides the foundation for the custom visualization system built in Unity. All visual models displayed within the tool are generated using Unity-based procedural mesh building routines. A 3D user interface was built to allow seamless dynamic interaction with the model while being viewed in 3D space. Biomolecular structure analysis and display capabilities are exemplified with a range of complex systems involving cell membranes, protein folding and lipid droplets.

A novel representation of groundwater dynamics in large-scale land surface modelling

NASA Astrophysics Data System (ADS)

Rahman, Mostaquimur; Rosolem, Rafael; Kollet, Stefan

2017-04-01

Land surface processes are connected to groundwater dynamics via shallow soil moisture. For example, groundwater affects evapotranspiration (by influencing the variability of soil moisture) and runoff generation mechanisms. However, contemporary Land Surface Models (LSM) generally consider isolated soil columns and free drainage lower boundary condition for simulating hydrology. This is mainly due to the fact that incorporating detailed groundwater dynamics in LSMs usually requires considerable computing resources, especially for large-scale applications (e.g., continental to global). Yet, these simplifications undermine the potential effect of groundwater dynamics on land surface mass and energy fluxes. In this study, we present a novel approach of representing high-resolution groundwater dynamics in LSMs that is computationally efficient for large-scale applications. This new parameterization is incorporated in the Joint UK Land Environment Simulator (JULES) and tested at the continental-scale.

A statics-dynamics equivalence through the fluctuation–dissipation ratio provides a window into the spin-glass phase from nonequilibrium measurements

PubMed Central

Baity-Jesi, Marco; Calore, Enrico; Cruz, Andres; Fernandez, Luis Antonio; Gil-Narvión, José Miguel; Gordillo-Guerrero, Antonio; Iñiguez, David; Maiorano, Andrea; Marinari, Enzo; Martin-Mayor, Victor; Monforte-Garcia, Jorge; Muñoz Sudupe, Antonio; Navarro, Denis; Parisi, Giorgio; Perez-Gaviro, Sergio; Ricci-Tersenghi, Federico; Ruiz-Lorenzo, Juan Jesus; Schifano, Sebastiano Fabio; Tarancón, Alfonso; Tripiccione, Raffaele; Yllanes, David

2017-01-01

We have performed a very accurate computation of the nonequilibrium fluctuation–dissipation ratio for the 3D Edwards–Anderson Ising spin glass, by means of large-scale simulations on the special-purpose computers Janus and Janus II. This ratio (computed for finite times on very large, effectively infinite, systems) is compared with the equilibrium probability distribution of the spin overlap for finite sizes. Our main result is a quantitative statics-dynamics dictionary, which could allow the experimental exploration of important features of the spin-glass phase without requiring uncontrollable extrapolations to infinite times or system sizes. PMID:28174274

Supercomputer optimizations for stochastic optimal control applications

NASA Technical Reports Server (NTRS)

Chung, Siu-Leung; Hanson, Floyd B.; Xu, Huihuang

1991-01-01

Supercomputer optimizations for a computational method of solving stochastic, multibody, dynamic programming problems are presented. The computational method is valid for a general class of optimal control problems that are nonlinear, multibody dynamical systems, perturbed by general Markov noise in continuous time, i.e., nonsmooth Gaussian as well as jump Poisson random white noise. Optimization techniques for vector multiprocessors or vectorizing supercomputers include advanced data structures, loop restructuring, loop collapsing, blocking, and compiler directives. These advanced computing techniques and superconducting hardware help alleviate Bellman's curse of dimensionality in dynamic programming computations, by permitting the solution of large multibody problems. Possible applications include lumped flight dynamics models for uncertain environments, such as large scale and background random aerospace fluctuations.

Communication interval selection in distributed heterogeneous simulation of large-scale dynamical systems

NASA Astrophysics Data System (ADS)

Lucas, Charles E.; Walters, Eric A.; Jatskevich, Juri; Wasynczuk, Oleg; Lamm, Peter T.

2003-09-01

In this paper, a new technique useful for the numerical simulation of large-scale systems is presented. This approach enables the overall system simulation to be formed by the dynamic interconnection of the various interdependent simulations, each representing a specific component or subsystem such as control, electrical, mechanical, hydraulic, or thermal. Each simulation may be developed separately using possibly different commercial-off-the-shelf simulation programs thereby allowing the most suitable language or tool to be used based on the design/analysis needs. These subsystems communicate the required interface variables at specific time intervals. A discussion concerning the selection of appropriate communication intervals is presented herein. For the purpose of demonstration, this technique is applied to a detailed simulation of a representative aircraft power system, such as that found on the Joint Strike Fighter (JSF). This system is comprised of ten component models each developed using MATLAB/Simulink, EASY5, or ACSL. When the ten component simulations were distributed across just four personal computers (PCs), a greater than 15-fold improvement in simulation speed (compared to the single-computer implementation) was achieved.

Distributed Coordinated Control of Large-Scale Nonlinear Networks

DOE PAGES

Kundu, Soumya; Anghel, Marian

2015-11-08

We provide a distributed coordinated approach to the stability analysis and control design of largescale nonlinear dynamical systems by using a vector Lyapunov functions approach. In this formulation the large-scale system is decomposed into a network of interacting subsystems and the stability of the system is analyzed through a comparison system. However finding such comparison system is not trivial. In this work, we propose a sum-of-squares based completely decentralized approach for computing the comparison systems for networks of nonlinear systems. Moreover, based on the comparison systems, we introduce a distributed optimal control strategy in which the individual subsystems (agents) coordinatemore » with their immediate neighbors to design local control policies that can exponentially stabilize the full system under initial disturbances.We illustrate the control algorithm on a network of interacting Van der Pol systems.« less

Self-assembly of polyelectrolyte surfactant complexes using large scale MD simulation

NASA Astrophysics Data System (ADS)

Goswami, Monojoy; Sumpter, Bobby

2014-03-01

Polyelectrolytes (PE) and surfactants are known to form interesting structures with varied properties in aqueous solutions. The morphological details of the PE-surfactant complexes depend on a combination of polymer backbone, electrostatic interactions and hydrophobic interactions. We study the self-assembly of cationic PE and anionic surfactants complexes in dilute condition. The importance of such complexes of PE with oppositely charged surfactants can be found in biological systems, such as immobilization of enzymes in polyelectrolyte complexes or nonspecific association of DNA with protein. Many useful properties of PE surfactant complexes come from the highly ordered structures of surfactant self-assembly inside the PE aggregate which has applications in industry. We do large scale molecular dynamics simulation using LAMMPS to understand the structure and dynamics of PE-surfactant systems. Our investigation shows highly ordered pearl-necklace structures that have been observed experimentally in biological systems. We investigate many different properties of PE-surfactant complexation for different parameter ranges that are useful for pharmaceutical, engineering and biological applications.

Transport induced by large scale convective structures in a dipole-confined plasma.

PubMed

Grierson, B A; Mauel, M E; Worstell, M W; Klassen, M

2010-11-12

Convective structures characterized by E×B motion are observed in a dipole-confined plasma. Particle transport rates are calculated from density dynamics obtained from multipoint measurements and the reconstructed electrostatic potential. The calculated transport rates determined from the large-scale dynamics and local probe measurements agree in magnitude, show intermittency, and indicate that the particle transport is dominated by large-scale convective structures.

Determination of functional collective motions in a protein at atomic resolution using coherent neutron scattering

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

Hong, Liang; Jain, Nitin; Cheng, Xiaolin

Protein function often depends on global, collective internal motions. However, the simultaneous quantitative experimental determination of the forms, amplitudes, and time scales of these motions has remained elusive. We demonstrate that a complete description of these large-scale dynamic modes can be obtained using coherent neutron-scattering experiments on perdeuterated samples. With this approach, a microscopic relationship between the structure, dynamics, and function in a protein, cytochrome P450cam, is established. The approach developed here should be of general applicability to protein systems.

Determination of functional collective motions in a protein at atomic resolution using coherent neutron scattering

DOE PAGES

Hong, Liang; Jain, Nitin; Cheng, Xiaolin; ...

2016-10-14

Protein function often depends on global, collective internal motions. However, the simultaneous quantitative experimental determination of the forms, amplitudes, and time scales of these motions has remained elusive. We demonstrate that a complete description of these large-scale dynamic modes can be obtained using coherent neutron-scattering experiments on perdeuterated samples. With this approach, a microscopic relationship between the structure, dynamics, and function in a protein, cytochrome P450cam, is established. The approach developed here should be of general applicability to protein systems.

Modal resonant dynamics of cables with a flexible support: A modulated diffraction problem

NASA Astrophysics Data System (ADS)

Guo, Tieding; Kang, Houjun; Wang, Lianhua; Liu, Qijian; Zhao, Yueyu

2018-06-01

Modal resonant dynamics of cables with a flexible support is defined as a modulated (wave) diffraction problem, and investigated by asymptotic expansions of the cable-support coupled system. The support-cable mass ratio, which is usually very large, turns out to be the key parameter for characterizing cable-support dynamic interactions. By treating the mass ratio's inverse as a small perturbation parameter and scaling the cable tension properly, both cable's modal resonant dynamics and the flexible support dynamics are asymptotically reduced by using multiple scale expansions, leading finally to a reduced cable-support coupled model (i.e., on a slow time scale). After numerical validations of the reduced coupled model, cable-support coupled responses and the flexible support induced coupling effects on the cable, are both fully investigated, based upon the reduced model. More explicitly, the dynamic effects on the cable's nonlinear frequency and force responses, caused by the support-cable mass ratio, the resonant detuning parameter and the support damping, are carefully evaluated.

Scaling effects in the static and dynamic response of graphite-epoxy beam-columns. Ph.D. Thesis - Virginia Polytechnic Inst. and State Univ.

NASA Technical Reports Server (NTRS)

Jackson, Karen E.

1990-01-01

Scale model technology represents one method of investigating the behavior of advanced, weight-efficient composite structures under a variety of loading conditions. It is necessary, however, to understand the limitations involved in testing scale model structures before the technique can be fully utilized. These limitations, or scaling effects, are characterized. in the large deflection response and failure of composite beams. Scale model beams were loaded with an eccentric axial compressive load designed to produce large bending deflections and global failure. A dimensional analysis was performed on the composite beam-column loading configuration to determine a model law governing the system response. An experimental program was developed to validate the model law under both static and dynamic loading conditions. Laminate stacking sequences including unidirectional, angle ply, cross ply, and quasi-isotropic were tested to examine a diversity of composite response and failure modes. The model beams were loaded under scaled test conditions until catastrophic failure. A large deflection beam solution was developed to compare with the static experimental results and to analyze beam failure. Also, the finite element code DYCAST (DYnamic Crash Analysis of STructure) was used to model both the static and impulsive beam response. Static test results indicate that the unidirectional and cross ply beam responses scale as predicted by the model law, even under severe deformations. In general, failure modes were consistent between scale models within a laminate family; however, a significant scale effect was observed in strength. The scale effect in strength which was evident in the static tests was also observed in the dynamic tests. Scaling of load and strain time histories between the scale model beams and the prototypes was excellent for the unidirectional beams, but inconsistent results were obtained for the angle ply, cross ply, and quasi-isotropic beams. Results show that valuable information can be obtained from testing on scale model composite structures, especially in the linear elastic response region. However, due to scaling effects in the strength behavior of composite laminates, caution must be used in extrapolating data taken from a scale model test when that test involves failure of the structure.

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

Large Scale Water Vapor Sources Relative to the October 2000 Piedmont Flood

NASA Technical Reports Server (NTRS)

Turato, Barbara; Reale, Oreste; Siccardi, Franco

2003-01-01

Very intense mesoscale or synoptic-scale rainfall events can occasionally be observed in the Mediterranean region without any deep cyclone developing over the areas affected by precipitation. In these perplexing cases the synoptic situation can superficially look similar to cases in which very little precipitation occurs. These situations could possibly baffle the operational weather forecasters. In this article, the major precipitation event that affected Piedmont (Italy) between 13 and 16 October 2000 is investigated. This is one of the cases in which no intense cyclone was observed within the Mediterranean region at any time, only a moderate system was present, and yet exceptional rainfall and flooding occurred. The emphasis of this study is on the moisture origin and transport. Moisture and energy balances are computed on different space- and time-scales, revealing that precipitation exceeds evaporation over an area inclusive of Piedmont and the northwestern Mediterranean region, on a time-scale encompassing the event and about two weeks preceding it. This is suggestive of an important moisture contribution originating from outside the region. A synoptic and dynamic analysis is then performed to outline the potential mechanisms that could have contributed to the large-scale moisture transport. The central part of the work uses a quasi-isentropic water-vapor back trajectory technique. The moisture sources obtained by this technique are compared with the results of the balances and with the synoptic situation, to unveil possible dynamic mechanisms and physical processes involved. It is found that moisture sources on a variety of atmospheric scales contribute to this event. First, an important contribution is caused by the extratropical remnants of former tropical storm Leslie. The large-scale environment related to this system allows a significant amount of moisture to be carried towards Europe. This happens on a time- scale of about 5-15 days preceding the Piedmont event. Second, water-vapor intrusions from the African Inter-Tropical Convergence Zone and evaporation from the eastern Atlantic contribute on the 2-5 day time-scale. The large-scale moist dynamics appears therefore to be one important factor enabling a moderate Mediterranean cyclone to produce heavy precipitation. Finally, local evaporation from the Mediterranean, water-vapor recycling, and orographically-induced low-level convergence enhance and concentrate the moisture over the area where heavy precipitation occurs. This happens on a 12-72 hour time-scale.

Assessing Northern Hemisphere Land-Atmosphere Hotspots Using Dynamical Adjustment

NASA Astrophysics Data System (ADS)

Merrifield, Anna; Lehner, Flavio; Deser, Clara; Xie, Shang-Ping

2017-04-01

Understanding the influence of soil moisture on surface air temperature (SAT) is made more challenging by large-scale, internal atmospheric variability present in the midlatitude summer atmosphere. In this study, dynamical adjustment is used to characterize and remove summer SAT variability associated with large-scale circulation patterns in the Community Earth System Model large ensemble (CESM-LE). The adjustment is performed over North America and Europe with two different circulation indicators: sea level pressure (SLP) and 500mb height (Z500). The removal of dynamical "noise" leaves residual SAT variability in the central U.S. and Mediterranean regions identified as hotspots of land-atmosphere interaction (e.g. Koster et al. 2004, Seneviratne et al. 2006). The residual SAT variability "signal" is not clearly related to modes of sea surface temperature (SST) variability, but is related to local soil moisture, evaporative fraction, and radiation availability. These local relationships suggest that residual SAT variability is representative of the aggregate land surface signal. SLP dynamical adjustment removes ˜15% more variability in the central U.S. hotspot region than Z500 dynamical adjustment. Similar amounts of variability are removed by SLP and Z500 in the Mediterranean region. Differences in SLP and Z500 signal magnitude in the central U.S. are likely due to the modification of SLP by local land surface conditions, while the proximity of European hotspots to the Mediterranean sea mitigates the land surface influence. Variations in the Z500 field more closely resemble large-scale midlatitude circulation patterns and therefore Z500 may be a more suitable circulation indicator for summer dynamical adjustment. Changes in the residual SAT variability signal under increased greenhouse gas forcing will also be explored.

Structural Similitude and Scaling Laws

NASA Technical Reports Server (NTRS)

Simitses, George J.

1998-01-01

Aircraft and spacecraft comprise the class of aerospace structures that require efficiency and wisdom in design, sophistication and accuracy in analysis and numerous and careful experimental evaluations of components and prototype, in order to achieve the necessary system reliability, performance and safety. Preliminary and/or concept design entails the assemblage of system mission requirements, system expected performance and identification of components and their connections as well as of manufacturing and system assembly techniques. This is accomplished through experience based on previous similar designs, and through the possible use of models to simulate the entire system characteristics. Detail design is heavily dependent on information and concepts derived from the previous steps. This information identifies critical design areas which need sophisticated analyses, and design and redesign procedures to achieve the expected component performance. This step may require several independent analysis models, which, in many instances, require component testing. The last step in the design process, before going to production, is the verification of the design. This step necessitates the production of large components and prototypes in order to test component and system analytical predictions and verify strength and performance requirements under the worst loading conditions that the system is expected to encounter in service. Clearly then, full-scale testing is in many cases necessary and always very expensive. In the aircraft industry, in addition to full-scale tests, certification and safety necessitate large component static and dynamic testing. Such tests are extremely difficult, time consuming and definitely absolutely necessary. Clearly, one should not expect that prototype testing will be totally eliminated in the aircraft industry. It is hoped, though, that we can reduce full-scale testing to a minimum. Full-scale large component testing is necessary in other industries as well, Ship building, automobile and railway car construction all rely heavily on testing. Regardless of the application, a scaled-down (by a large factor) model (scale model) which closely represents the structural behavior of the full-scale system (prototype) can prove to be an extremely beneficial tool. This possible development must be based on the existence of certain structural parameters that control the behavior of a structural system when acted upon by static and/or dynamic loads. If such structural parameters exist, a scaled-down replica can be built, which will duplicate the response of the full-scale system. The two systems are then said to be structurally similar. The term, then, that best describes this similarity is structural similitude. Similarity of systems requires that the relevant system parameters be identical and these systems be governed by a unique set of characteristic equations. Thus, if a relation or equation of variables is written for a system, it is valid for all systems which are similar to it. Each variable in a model is proportional to the corresponding variable of the prototype. This ratio, which plays an essential role in predicting the relationship between the model and its prototype, is called the scale factor.

Large-Scale Test of Dynamic Correlation Processors: Implications for Correlation-Based Seismic Pipelines

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

Dodge, D. A.; Harris, D. B.

Correlation detectors are of considerable interest to the seismic monitoring communities because they offer reduced detection thresholds and combine detection, location and identification functions into a single operation. They appear to be ideal for applications requiring screening of frequent repeating events. However, questions remain about how broadly empirical correlation methods are applicable. We describe the effectiveness of banks of correlation detectors in a system that combines traditional power detectors with correlation detectors in terms of efficiency, which we define to be the fraction of events detected by the correlators. This paper elaborates and extends the concept of a dynamic correlationmore » detection framework – a system which autonomously creates correlation detectors from event waveforms detected by power detectors; and reports observed performance on a network of arrays in terms of efficiency. We performed a large scale test of dynamic correlation processors on an 11 terabyte global dataset using 25 arrays in the single frequency band 1-3 Hz. The system found over 3.2 million unique signals and produced 459,747 screened detections. A very satisfying result is that, on average, efficiency grows with time and, after nearly 16 years of operation, exceeds 47% for events observed over all distance ranges and approaches 70% for near regional and 90% for local events. This observation suggests that future pipeline architectures should make extensive use of correlation detectors, principally for decluttering observations of local and near-regional events. Our results also suggest that future operations based on correlation detection will require commodity large-scale computing infrastructure, since the numbers of correlators in an autonomous system can grow into the hundreds of thousands.« less

Large-Scale Test of Dynamic Correlation Processors: Implications for Correlation-Based Seismic Pipelines

DOE PAGES

Dodge, D. A.; Harris, D. B.

2016-03-15

Correlation detectors are of considerable interest to the seismic monitoring communities because they offer reduced detection thresholds and combine detection, location and identification functions into a single operation. They appear to be ideal for applications requiring screening of frequent repeating events. However, questions remain about how broadly empirical correlation methods are applicable. We describe the effectiveness of banks of correlation detectors in a system that combines traditional power detectors with correlation detectors in terms of efficiency, which we define to be the fraction of events detected by the correlators. This paper elaborates and extends the concept of a dynamic correlationmore » detection framework – a system which autonomously creates correlation detectors from event waveforms detected by power detectors; and reports observed performance on a network of arrays in terms of efficiency. We performed a large scale test of dynamic correlation processors on an 11 terabyte global dataset using 25 arrays in the single frequency band 1-3 Hz. The system found over 3.2 million unique signals and produced 459,747 screened detections. A very satisfying result is that, on average, efficiency grows with time and, after nearly 16 years of operation, exceeds 47% for events observed over all distance ranges and approaches 70% for near regional and 90% for local events. This observation suggests that future pipeline architectures should make extensive use of correlation detectors, principally for decluttering observations of local and near-regional events. Our results also suggest that future operations based on correlation detection will require commodity large-scale computing infrastructure, since the numbers of correlators in an autonomous system can grow into the hundreds of thousands.« less

Component Cost Analysis of Large Scale Systems

NASA Technical Reports Server (NTRS)

Skelton, R. E.; Yousuff, A.

1982-01-01

The ideas of cost decomposition is summarized to aid in the determination of the relative cost (or 'price') of each component of a linear dynamic system using quadratic performance criteria. In addition to the insights into system behavior that are afforded by such a component cost analysis CCA, these CCA ideas naturally lead to a theory for cost-equivalent realizations.

The Dynamic Brain: From Spiking Neurons to Neural Masses and Cortical Fields

PubMed Central

Deco, Gustavo; Jirsa, Viktor K.; Robinson, Peter A.; Breakspear, Michael; Friston, Karl

2008-01-01

The cortex is a complex system, characterized by its dynamics and architecture, which underlie many functions such as action, perception, learning, language, and cognition. Its structural architecture has been studied for more than a hundred years; however, its dynamics have been addressed much less thoroughly. In this paper, we review and integrate, in a unifying framework, a variety of computational approaches that have been used to characterize the dynamics of the cortex, as evidenced at different levels of measurement. Computational models at different space–time scales help us understand the fundamental mechanisms that underpin neural processes and relate these processes to neuroscience data. Modeling at the single neuron level is necessary because this is the level at which information is exchanged between the computing elements of the brain; the neurons. Mesoscopic models tell us how neural elements interact to yield emergent behavior at the level of microcolumns and cortical columns. Macroscopic models can inform us about whole brain dynamics and interactions between large-scale neural systems such as cortical regions, the thalamus, and brain stem. Each level of description relates uniquely to neuroscience data, from single-unit recordings, through local field potentials to functional magnetic resonance imaging (fMRI), electroencephalogram (EEG), and magnetoencephalogram (MEG). Models of the cortex can establish which types of large-scale neuronal networks can perform computations and characterize their emergent properties. Mean-field and related formulations of dynamics also play an essential and complementary role as forward models that can be inverted given empirical data. This makes dynamic models critical in integrating theory and experiments. We argue that elaborating principled and informed models is a prerequisite for grounding empirical neuroscience in a cogent theoretical framework, commensurate with the achievements in the physical sciences. PMID:18769680

Graph-based linear scaling electronic structure theory.

PubMed

Niklasson, Anders M N; Mniszewski, Susan M; Negre, Christian F A; Cawkwell, Marc J; Swart, Pieter J; Mohd-Yusof, Jamal; Germann, Timothy C; Wall, Michael E; Bock, Nicolas; Rubensson, Emanuel H; Djidjev, Hristo

2016-06-21

We show how graph theory can be combined with quantum theory to calculate the electronic structure of large complex systems. The graph formalism is general and applicable to a broad range of electronic structure methods and materials, including challenging systems such as biomolecules. The methodology combines well-controlled accuracy, low computational cost, and natural low-communication parallelism. This combination addresses substantial shortcomings of linear scaling electronic structure theory, in particular with respect to quantum-based molecular dynamics simulations.

Graph-based linear scaling electronic structure theory

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

Niklasson, Anders M. N., E-mail: amn@lanl.gov; Negre, Christian F. A.; Cawkwell, Marc J.

2016-06-21

We show how graph theory can be combined with quantum theory to calculate the electronic structure of large complex systems. The graph formalism is general and applicable to a broad range of electronic structure methods and materials, including challenging systems such as biomolecules. The methodology combines well-controlled accuracy, low computational cost, and natural low-communication parallelism. This combination addresses substantial shortcomings of linear scaling electronic structure theory, in particular with respect to quantum-based molecular dynamics simulations.

Vortex dynamics and Lagrangian statistics in a model for active turbulence.

PubMed

James, Martin; Wilczek, Michael

2018-02-14

Cellular suspensions such as dense bacterial flows exhibit a turbulence-like phase under certain conditions. We study this phenomenon of "active turbulence" statistically by using numerical tools. Following Wensink et al. (Proc. Natl. Acad. Sci. U.S.A. 109, 14308 (2012)), we model active turbulence by means of a generalized Navier-Stokes equation. Two-point velocity statistics of active turbulence, both in the Eulerian and the Lagrangian frame, is explored. We characterize the scale-dependent features of two-point statistics in this system. Furthermore, we extend this statistical study with measurements of vortex dynamics in this system. Our observations suggest that the large-scale statistics of active turbulence is close to Gaussian with sub-Gaussian tails.

An Implicit Solver on A Parallel Block-Structured Adaptive Mesh Grid for FLASH

NASA Astrophysics Data System (ADS)

Lee, D.; Gopal, S.; Mohapatra, P.

2012-07-01

We introduce a fully implicit solver for FLASH based on a Jacobian-Free Newton-Krylov (JFNK) approach with an appropriate preconditioner. The main goal of developing this JFNK-type implicit solver is to provide efficient high-order numerical algorithms and methodology for simulating stiff systems of differential equations on large-scale parallel computer architectures. A large number of natural problems in nonlinear physics involve a wide range of spatial and time scales of interest. A system that encompasses such a wide magnitude of scales is described as "stiff." A stiff system can arise in many different fields of physics, including fluid dynamics/aerodynamics, laboratory/space plasma physics, low Mach number flows, reactive flows, radiation hydrodynamics, and geophysical flows. One of the big challenges in solving such a stiff system using current-day computational resources lies in resolving time and length scales varying by several orders of magnitude. We introduce FLASH's preliminary implementation of a time-accurate JFNK-based implicit solver in the framework of FLASH's unsplit hydro solver.

Network-scale spatial and temporal variation in Chinook salmon (Oncorhynchus tshawytscha) redd distributions: patterns inferred from spatially continuous replicate surveys

Treesearch

Daniel J. Isaak; Russell F. Thurow

2006-01-01

Spatially continuous sampling designs, when temporally replicated, provide analytical flexibility and are unmatched in their ability to provide a dynamic system view. We have compiled such a data set by georeferencing the network-scale distribution of Chinook salmon (Oncorhynchus tshawytscha) redds across a large wilderness basin (7330 km2) in...

Response of a 2-story test-bed structure for the seismic evaluation of nonstructural systems

NASA Astrophysics Data System (ADS)

Soroushian, Siavash; Maragakis, E. "Manos"; Zaghi, Arash E.; Rahmanishamsi, Esmaeel; Itani, Ahmad M.; Pekcan, Gokhan

2016-03-01

A full-scale, two-story, two-by-one bay, steel braced-frame was subjected to a number of unidirectional ground motions using three shake tables at the UNR-NEES site. The test-bed frame was designed to study the seismic performance of nonstructural systems including steel-framed gypsum partition walls, suspended ceilings and fire sprinkler systems. The frame can be configured to perform as an elastic or inelastic system to generate large floor accelerations or large inter story drift, respectively. In this study, the dynamic performance of the linear and nonlinear test-beds was comprehensively studied. The seismic performance of nonstructural systems installed in the linear and nonlinear test-beds were assessed during extreme excitations. In addition, the dynamic interactions of the test-bed and installed nonstructural systems are investigated.

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.

Large fluctuations in anti-coordination games on scale-free graphs

NASA Astrophysics Data System (ADS)

Sabsovich, Daniel; Mobilia, Mauro; Assaf, Michael

2017-05-01

We study the influence of the complex topology of scale-free graphs on the dynamics of anti-coordination games (e.g. snowdrift games). These reference models are characterized by the coexistence (evolutionary stable mixed strategy) of two competing species, say ‘cooperators’ and ‘defectors’, and, in finite systems, by metastability and large-fluctuation-driven fixation. In this work, we use extensive computer simulations and an effective diffusion approximation (in the weak selection limit) to determine under which circumstances, depending on the individual-based update rules, the topology drastically affects the long-time behavior of anti-coordination games. In particular, we compute the variance of the number of cooperators in the metastable state and the mean fixation time when the dynamics is implemented according to the voter model (death-first/birth-second process) and the link dynamics (birth/death or death/birth at random). For the voter update rule, we show that the scale-free topology effectively renormalizes the population size and as a result the statistics of observables depend on the network’s degree distribution. In contrast, such a renormalization does not occur with the link dynamics update rule and we recover the same behavior as on complete graphs.

Hierarchic spatio-temporal dynamics in glycolysis

NASA Astrophysics Data System (ADS)

Shinjyo, Takahiro; Nakagawa, Yoshiyuki; Ueda, Tetsuo

Yeast extracts exhibit oscillations when the glycolytic system is far away from equilibrium. Spatio-temporal dynamics in this system was studied in the newly developed gel as well as in the solution. Small regions (about 10 um) with very complex shape with high or low concentrations of NADH appeared, and upon these small structures large-scale dynamics were superimposed. Concentration waves propagated, and the source of wave was induced by contact with high ADP. Sink of waves was generated by contacting the reaction gel to two small gels rich in ADP. Upon these spatio-temporal dynamics were superimposed much slower global oscillations throughout the system with a period of about 40 min. Similar dynamics was seen in a solution of yeast extract, but the size of domains was about ten times larger than that in the gel. In this way, the multi-enzyme system of glycolysis exhibits self-organization of hierarchy in spatio-temporal dynamics.

Two-Level Chebyshev Filter Based Complementary Subspace Method: Pushing the Envelope of Large-Scale Electronic Structure Calculations.

PubMed

Banerjee, Amartya S; Lin, Lin; Suryanarayana, Phanish; Yang, Chao; Pask, John E

2018-06-12

We describe a novel iterative strategy for Kohn-Sham density functional theory calculations aimed at large systems (>1,000 electrons), applicable to metals and insulators alike. In lieu of explicit diagonalization of the Kohn-Sham Hamiltonian on every self-consistent field (SCF) iteration, we employ a two-level Chebyshev polynomial filter based complementary subspace strategy to (1) compute a set of vectors that span the occupied subspace of the Hamiltonian; (2) reduce subspace diagonalization to just partially occupied states; and (3) obtain those states in an efficient, scalable manner via an inner Chebyshev filter iteration. By reducing the necessary computation to just partially occupied states and obtaining these through an inner Chebyshev iteration, our approach reduces the cost of large metallic calculations significantly, while eliminating subspace diagonalization for insulating systems altogether. We describe the implementation of the method within the framework of the discontinuous Galerkin (DG) electronic structure method and show that this results in a computational scheme that can effectively tackle bulk and nano systems containing tens of thousands of electrons, with chemical accuracy, within a few minutes or less of wall clock time per SCF iteration on large-scale computing platforms. We anticipate that our method will be instrumental in pushing the envelope of large-scale ab initio molecular dynamics. As a demonstration of this, we simulate a bulk silicon system containing 8,000 atoms at finite temperature, and obtain an average SCF step wall time of 51 s on 34,560 processors; thus allowing us to carry out 1.0 ps of ab initio molecular dynamics in approximately 28 h (of wall time).

Reach-scale characterization of large woody debris in a low-gradient, Midwestern U.S.A. river system

NASA Astrophysics Data System (ADS)

Martin, Derek J.; Pavlowsky, Robert T.; Harden, Carol P.

2016-06-01

Addition of large woody debris (LWD) to rivers has increasingly become a popular stream restoration strategy, particularly in river systems of the Midwestern United States. However, our knowledge of LWD dynamics is mostly limited to high gradient montane river systems, or coastal river systems. The LWD-related management of low-gradient, Midwestern river systems is thus largely based on higher gradient analogs of LWD dynamics. This research characterizes fluvial wood loads and investigates the relationships between fluvial wood, channel morphology, and sediment deposition in a relatively low-gradient, semiconfined, alluvial river. The LWD and channel morphology were surveyed at nine reaches along the Big River in southeastern Missouri to investigate those relationships in comparison to other regions. Wood loads in the Big River are low (3-114 m3/100 m) relative to those of higher gradient river systems of the Pacific Northwest, but high relative to lower-gradient river systems of the Eastern United States. Wood characteristics such as size and orientation suggest that the dominant LWD recruitment mechanism in the Big River is bank erosion. Also, ratios of wood geometry to channel geometry show that the Big River maintains a relatively high wood transport capacity for most of its length. Although LWD creates sites for sediment storage, the overall impact on reach-scale sediment storage in the Big River is low (< 4.2% of total in-channel storage). However, wood loads, and thus opportunities for sediment storage, have the potential to grow in the future as Midwestern riparian forests mature. This study represents the first of its kind within this particular type of river system and within this region and thus serves as a basis for understanding fluvial wood dynamics in low-gradient river systems of the Midwestern United States.

Networked dynamical systems with linear coupling: synchronisation patterns, coherence and other behaviours.

PubMed

Judd, Kevin

2013-12-01

Many physical and biochemical systems are well modelled as a network of identical non-linear dynamical elements with linear coupling between them. An important question is how network structure affects chaotic dynamics, for example, by patterns of synchronisation and coherence. It is shown that small networks can be characterised precisely into patterns of exact synchronisation and large networks characterised by partial synchronisation at the local and global scale. Exact synchronisation modes are explained using tools of symmetry groups and invariance, and partial synchronisation is explained by finite-time shadowing of exact synchronisation modes.

Self-homodyne measurement of a dynamic Mollow triplet in the solid state

NASA Astrophysics Data System (ADS)

Fischer, Kevin A.; Müller, Kai; Rundquist, Armand; Sarmiento, Tomas; Piggott, Alexander Y.; Kelaita, Yousif; Dory, Constantin; Lagoudakis, Konstantinos G.; Vučković, Jelena

2016-03-01

The study of the light-matter interaction at the quantum scale has been enabled by the cavity quantum electrodynamics (CQED) architecture, in which a quantum two-level system strongly couples to a single cavity mode. Originally implemented with atoms in optical cavities, CQED effects are now also observed with artificial atoms in solid-state environments. Such realizations of these systems exhibit fast dynamics, making them attractive candidates for devices including modulators and sources in high-throughput communications. However, these systems possess large photon out-coupling rates that obscure any quantum behaviour at large excitation powers. Here, we have used a self-homodyning interferometric technique that fully employs the complex mode structure of our nanofabricated cavity to observe a quantum phenomenon known as the dynamic Mollow triplet. We expect this interference to facilitate the development of arbitrary on-chip quantum state generators, thereby strongly influencing quantum lithography, metrology and imaging.

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

Considering Complex Objectives and Scarce Resources in Information Systems' Analysis.

ERIC Educational Resources Information Center

Crowther, Warren

The low efficacy of many of the library and large-scale information systems that have been implemented in the developing countries has been disappointing, and their appropriateness is often questioned in the governmental and educational institutions of more industrialized countries beset by budget-crunching and a very dynamic transformation of…

Universal self-similar dynamics of relativistic and nonrelativistic field theories near nonthermal fixed points

NASA Astrophysics Data System (ADS)

Piñeiro Orioli, Asier; Boguslavski, Kirill; Berges, Jürgen

2015-07-01

We investigate universal behavior of isolated many-body systems far from equilibrium, which is relevant for a wide range of applications from ultracold quantum gases to high-energy particle physics. The universality is based on the existence of nonthermal fixed points, which represent nonequilibrium attractor solutions with self-similar scaling behavior. The corresponding dynamic universality classes turn out to be remarkably large, encompassing both relativistic as well as nonrelativistic quantum and classical systems. For the examples of nonrelativistic (Gross-Pitaevskii) and relativistic scalar field theory with quartic self-interactions, we demonstrate that infrared scaling exponents as well as scaling functions agree. We perform two independent nonperturbative calculations, first by using classical-statistical lattice simulation techniques and second by applying a vertex-resummed kinetic theory. The latter extends kinetic descriptions to the nonperturbative regime of overoccupied modes. Our results open new perspectives to learn from experiments with cold atoms aspects about the dynamics during the early stages of our universe.

New Challenges in Computational Thermal Hydraulics

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

Yadigaroglu, George; Lakehal, Djamel

New needs and opportunities drive the development of novel computational methods for the design and safety analysis of light water reactors (LWRs). Some new methods are likely to be three dimensional. Coupling is expected between system codes, computational fluid dynamics (CFD) modules, and cascades of computations at scales ranging from the macro- or system scale to the micro- or turbulence scales, with the various levels continuously exchanging information back and forth. The ISP-42/PANDA and the international SETH project provide opportunities for testing applications of single-phase CFD methods to LWR safety problems. Although industrial single-phase CFD applications are commonplace, computational multifluidmore » dynamics is still under development. However, first applications are appearing; the state of the art and its potential uses are discussed. The case study of condensation of steam/air mixtures injected from a downward-facing vent into a pool of water is a perfect illustration of a simulation cascade: At the top of the hierarchy of scales, system behavior can be modeled with a system code; at the central level, the volume-of-fluid method can be applied to predict large-scale bubbling behavior; at the bottom of the cascade, direct-contact condensation can be treated with direct numerical simulation, in which turbulent flow (in both the gas and the liquid), interfacial dynamics, and heat/mass transfer are directly simulated without resorting to models.« less

An intercomparison of GCM and RCM dynamical downscaling for characterizing the hydroclimatology of California and Nevada

NASA Astrophysics Data System (ADS)

Xu, Z.; Rhoades, A.; Johansen, H.; Ullrich, P. A.; Collins, W. D.

2017-12-01

Dynamical downscaling is widely used to properly characterize regional surface heterogeneities that shape the local hydroclimatology. However, the factors in dynamical downscaling, including the refinement of model horizontal resolution, large-scale forcing datasets and dynamical cores, have not been fully evaluated. Two cutting-edge global-to-regional downscaling methods are used to assess these, specifically the variable-resolution Community Earth System Model (VR-CESM) and the Weather Research & Forecasting (WRF) regional climate model, under different horizontal resolutions (28, 14, and 7 km). Two groups of WRF simulations are driven by either the NCEP reanalysis dataset (WRF_NCEP) or VR-CESM outputs (WRF_VRCESM) to evaluate the effects of the large-scale forcing datasets. The impacts of dynamical core are assessed by comparing the VR-CESM simulations to the coupled WRF_VRCESM simulations with the same physical parameterizations and similar grid domains. The simulated hydroclimatology (i.e., total precipitation, snow cover, snow water equivalent and surface temperature) are compared with the reference datasets. The large-scale forcing datasets are critical to the WRF simulations in more accurately simulating total precipitation, SWE and snow cover, but not surface temperature. Both the WRF and VR-CESM results highlight that no significant benefit is found in the simulated hydroclimatology by just increasing horizontal resolution refinement from 28 to 7 km. Simulated surface temperature is sensitive to the choice of dynamical core. WRF generally simulates higher temperatures than VR-CESM, alleviates the systematic cold bias of DJF temperatures over the California mountain region, but overestimates the JJA temperature in California's Central Valley.

Asymmetric noise-induced large fluctuations in coupled systems

NASA Astrophysics Data System (ADS)

Schwartz, Ira B.; Szwaykowska, Klimka; Carr, Thomas W.

2017-10-01

Networks of interacting, communicating subsystems are common in many fields, from ecology, biology, and epidemiology to engineering and robotics. In the presence of noise and uncertainty, interactions between the individual components can lead to unexpected complex system-wide behaviors. In this paper, we consider a generic model of two weakly coupled dynamical systems, and we show how noise in one part of the system is transmitted through the coupling interface. Working synergistically with the coupling, the noise on one system drives a large fluctuation in the other, even when there is no noise in the second system. Moreover, the large fluctuation happens while the first system exhibits only small random oscillations. Uncertainty effects are quantified by showing how characteristic time scales of noise-induced switching scale as a function of the coupling between the two coupled parts of the experiment. In addition, our results show that the probability of switching in the noise-free system scales inversely as the square of reduced noise intensity amplitude, rendering the virtual probability of switching an extremely rare event. Our results showing the interplay between transmitted noise and coupling are also confirmed through simulations, which agree quite well with analytic theory.

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

Zitney, S.E.

This presentation will examine process systems engineering R&D needs for application to advanced fossil energy (FE) systems and highlight ongoing research activities at the National Energy Technology Laboratory (NETL) under the auspices of a recently launched Collaboratory for Process & Dynamic Systems Research. The three current technology focus areas include: 1) High-fidelity systems with NETL's award-winning Advanced Process Engineering Co-Simulator (APECS) technology for integrating process simulation with computational fluid dynamics (CFD) and virtual engineering concepts, 2) Dynamic systems with R&D on plant-wide IGCC dynamic simulation, control, and real-time training applications, and 3) Systems optimization including large-scale process optimization, stochastic simulationmore » for risk/uncertainty analysis, and cost estimation. Continued R&D aimed at these and other key process systems engineering models, methods, and tools will accelerate the development of advanced gasification-based FE systems and produce increasingly valuable outcomes for DOE and the Nation.« less

A Network Thermodynamic Framework for the Analysis and Control Design of Large-Scale Dynamical Systems

DTIC Science & Technology

2006-03-31

Nonnegative Dynamical Sys- tems................................................. 18 2.10. Adaptive Control for General Anesthesia and Intensive Care...Unit Sedation 20 2.11. Neural Network Adaptive Control for Intensive Care Unit Sedation and In- traoperative Anesthesia ...control for operating room hypnosis and intefisive care unit sedation. 1.3. Goals of this Report The main goal of this report is to summarize the

Dynamical transitions in large systems of mean field-coupled Landau-Stuart oscillators: Extensive chaos and cluster states

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

Ku, Wai Lim; Girvan, Michelle; Ott, Edward

In this paper, we study dynamical systems in which a large number N of identical Landau-Stuart oscillators are globally coupled via a mean-field. Previously, it has been observed that this type of system can exhibit a variety of different dynamical behaviors. These behaviors include time periodic cluster states in which each oscillator is in one of a small number of groups for which all oscillators in each group have the same state which is different from group to group, as well as a behavior in which all oscillators have different states and the macroscopic dynamics of the mean field ismore » chaotic. We argue that this second type of behavior is “extensive” in the sense that the chaotic attractor in the full phase space of the system has a fractal dimension that scales linearly with N and that the number of positive Lyapunov exponents of the attractor also scales linearly with N. An important focus of this paper is the transition between cluster states and extensive chaos as the system is subjected to slow adiabatic parameter change. We observe discontinuous transitions between the cluster states (which correspond to low dimensional dynamics) and the extensively chaotic states. Furthermore, examining the cluster state, as the system approaches the discontinuous transition to extensive chaos, we find that the oscillator population distribution between the clusters continually evolves so that the cluster state is always marginally stable. This behavior is used to reveal the mechanism of the discontinuous transition. We also apply the Kaplan-Yorke formula to study the fractal structure of the extensively chaotic attractors.« less

Reduced linear noise approximation for biochemical reaction networks with time-scale separation: The stochastic tQSSA+

NASA Astrophysics Data System (ADS)

Herath, Narmada; Del Vecchio, Domitilla

2018-03-01

Biochemical reaction networks often involve reactions that take place on different time scales, giving rise to "slow" and "fast" system variables. This property is widely used in the analysis of systems to obtain dynamical models with reduced dimensions. In this paper, we consider stochastic dynamics of biochemical reaction networks modeled using the Linear Noise Approximation (LNA). Under time-scale separation conditions, we obtain a reduced-order LNA that approximates both the slow and fast variables in the system. We mathematically prove that the first and second moments of this reduced-order model converge to those of the full system as the time-scale separation becomes large. These mathematical results, in particular, provide a rigorous justification to the accuracy of LNA models derived using the stochastic total quasi-steady state approximation (tQSSA). Since, in contrast to the stochastic tQSSA, our reduced-order model also provides approximations for the fast variable stochastic properties, we term our method the "stochastic tQSSA+". Finally, we demonstrate the application of our approach on two biochemical network motifs found in gene-regulatory and signal transduction networks.

SQDFT: Spectral Quadrature method for large-scale parallel O ( N ) Kohn–Sham calculations at high temperature

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

Suryanarayana, Phanish; Pratapa, Phanisri P.; Sharma, Abhiraj

We present SQDFT: a large-scale parallel implementation of the Spectral Quadrature (SQ) method formore » $$\\mathscr{O}(N)$$ Kohn–Sham Density Functional Theory (DFT) calculations at high temperature. Specifically, we develop an efficient and scalable finite-difference implementation of the infinite-cell Clenshaw–Curtis SQ approach, in which results for the infinite crystal are obtained by expressing quantities of interest as bilinear forms or sums of bilinear forms, that are then approximated by spatially localized Clenshaw–Curtis quadrature rules. We demonstrate the accuracy of SQDFT by showing systematic convergence of energies and atomic forces with respect to SQ parameters to reference diagonalization results, and convergence with discretization to established planewave results, for both metallic and insulating systems. Here, we further demonstrate that SQDFT achieves excellent strong and weak parallel scaling on computer systems consisting of tens of thousands of processors, with near perfect $$\\mathscr{O}(N)$$ scaling with system size and wall times as low as a few seconds per self-consistent field iteration. Finally, we verify the accuracy of SQDFT in large-scale quantum molecular dynamics simulations of aluminum at high temperature.« less

SQDFT: Spectral Quadrature method for large-scale parallel O ( N ) Kohn–Sham calculations at high temperature

DOE PAGES

Suryanarayana, Phanish; Pratapa, Phanisri P.; Sharma, Abhiraj; ...

2017-12-07

We present SQDFT: a large-scale parallel implementation of the Spectral Quadrature (SQ) method formore » $$\\mathscr{O}(N)$$ Kohn–Sham Density Functional Theory (DFT) calculations at high temperature. Specifically, we develop an efficient and scalable finite-difference implementation of the infinite-cell Clenshaw–Curtis SQ approach, in which results for the infinite crystal are obtained by expressing quantities of interest as bilinear forms or sums of bilinear forms, that are then approximated by spatially localized Clenshaw–Curtis quadrature rules. We demonstrate the accuracy of SQDFT by showing systematic convergence of energies and atomic forces with respect to SQ parameters to reference diagonalization results, and convergence with discretization to established planewave results, for both metallic and insulating systems. Here, we further demonstrate that SQDFT achieves excellent strong and weak parallel scaling on computer systems consisting of tens of thousands of processors, with near perfect $$\\mathscr{O}(N)$$ scaling with system size and wall times as low as a few seconds per self-consistent field iteration. Finally, we verify the accuracy of SQDFT in large-scale quantum molecular dynamics simulations of aluminum at high temperature.« less

Towards a comprehensive understanding of emerging dynamics and function of pancreatic islets: A complex network approach. Comment on "Network science of biological systems at different scales: A review" by Gosak et al.

NASA Astrophysics Data System (ADS)

Loppini, Alessandro

2018-03-01

Complex network theory represents a comprehensive mathematical framework to investigate biological systems, ranging from sub-cellular and cellular scales up to large-scale networks describing species interactions and ecological systems. In their exhaustive and comprehensive work [1], Gosak et al. discuss several scenarios in which the network approach was able to uncover general properties and underlying mechanisms of cells organization and regulation, tissue functions and cell/tissue failure in pathology, by the study of chemical reaction networks, structural networks and functional connectivities.

Drivers of forest cover dynamics in smallholder farming systems: the case of northwestern Vietnam.

PubMed

Jadin, Isaline; Vanacker, Veerle; Hoang, Huong Thi Thu

2013-04-01

The national-scale forest recovery of Vietnam started in the early 1990s and is associated with a shift from net deforestation to net reforestation. Large disparities in forest cover dynamics are, however, observed at the local scale. This study aims to unravel the mechanisms driving forest cover change for a mountainous region located in northwest Vietnam. Statistical analyses were used to explore the association between forest cover change and household characteristics. In Sa Pa district, deforestation rates are decreasing, but forest degradation continues at similar rates. Deforestation is not necessarily associated with impoverished ethnic communities or high levels of subsistence farming, and the largest forest cover dynamics are found in villages with the best socio-economic conditions. Our empirical study does not provide strong evidence of a dominant role of agriculture in forest cover dynamics. It shows that empirical studies on local-scale forest dynamics remain important to unravel the complexity of human-environment interactions.

Mean Field Analysis of Large-Scale Interacting Populations of Stochastic Conductance-Based Spiking Neurons Using the Klimontovich Method

NASA Astrophysics Data System (ADS)

Gandolfo, Daniel; Rodriguez, Roger; Tuckwell, Henry C.

2017-03-01

We investigate the dynamics of large-scale interacting neural populations, composed of conductance based, spiking model neurons with modifiable synaptic connection strengths, which are possibly also subjected to external noisy currents. The network dynamics is controlled by a set of neural population probability distributions (PPD) which are constructed along the same lines as in the Klimontovich approach to the kinetic theory of plasmas. An exact non-closed, nonlinear, system of integro-partial differential equations is derived for the PPDs. As is customary, a closing procedure leads to a mean field limit. The equations we have obtained are of the same type as those which have been recently derived using rigorous techniques of probability theory. The numerical solutions of these so called McKean-Vlasov-Fokker-Planck equations, which are only valid in the limit of infinite size networks, actually shows that the statistical measures as obtained from PPDs are in good agreement with those obtained through direct integration of the stochastic dynamical system for large but finite size networks. Although numerical solutions have been obtained for networks of Fitzhugh-Nagumo model neurons, which are often used to approximate Hodgkin-Huxley model neurons, the theory can be readily applied to networks of general conductance-based model neurons of arbitrary dimension.

Research of an emergency medical system for mass casualty incidents in Shanghai, China: a system dynamics model

PubMed Central

Liu, Xu; Chen, Haiping; Xue, Chen

2018-01-01

Objectives Emergency medical system for mass casualty incidents (EMS-MCIs) is a global issue. However, China lacks such studies extremely, which cannot meet the requirement of rapid decision-support system. This study aims to realize modeling EMS-MCIs in Shanghai, to improve mass casualty incident (MCI) rescue efficiency in China, and to provide a possible method of making rapid rescue decisions during MCIs. Methods This study established a system dynamics (SD) model of EMS-MCIs using the Vensim DSS program. Intervention scenarios were designed as adjusting scales of MCIs, allocation of ambulances, allocation of emergency medical staff, and efficiency of organization and command. Results Mortality increased with the increasing scale of MCIs, medical rescue capability of hospitals was relatively good, but the efficiency of organization and command was poor, and the prehospital time was too long. Mortality declined significantly when increasing ambulances and improving the efficiency of organization and command; triage and on-site first-aid time were shortened if increasing the availability of emergency medical staff. The effect was the most evident when 2,000 people were involved in MCIs; however, the influence was very small under the scale of 5,000 people. Conclusion The keys to decrease the mortality of MCIs were shortening the prehospital time and improving the efficiency of organization and command. For small-scale MCIs, improving the utilization rate of health resources was important in decreasing the mortality. For large-scale MCIs, increasing the number of ambulances and emergency medical professionals was the core to decrease prehospital time and mortality. For super-large-scale MCIs, increasing health resources was the premise. PMID:29440876

DIALOG: An executive computer program for linking independent programs

NASA Technical Reports Server (NTRS)

Glatt, C. R.; Hague, D. S.; Watson, D. A.

1973-01-01

A very large scale computer programming procedure called the DIALOG Executive System has been developed for the Univac 1100 series computers. The executive computer program, DIALOG, controls the sequence of execution and data management function for a library of independent computer programs. Communication of common information is accomplished by DIALOG through a dynamically constructed and maintained data base of common information. The unique feature of the DIALOG Executive System is the manner in which computer programs are linked. Each program maintains its individual identity and as such is unaware of its contribution to the large scale program. This feature makes any computer program a candidate for use with the DIALOG Executive System. The installation and use of the DIALOG Executive System are described at Johnson Space Center.

Data-driven Climate Modeling and Prediction

NASA Astrophysics Data System (ADS)

Kondrashov, D. A.; Chekroun, M.

2016-12-01

Global climate models aim to simulate a broad range of spatio-temporal scales of climate variability with state vector having many millions of degrees of freedom. On the other hand, while detailed weather prediction out to a few days requires high numerical resolution, it is fairly clear that a major fraction of large-scale climate variability can be predicted in a much lower-dimensional phase space. Low-dimensional models can simulate and predict this fraction of climate variability, provided they are able to account for linear and nonlinear interactions between the modes representing large scales of climate dynamics, as well as their interactions with a much larger number of modes representing fast and small scales. This presentation will highlight several new applications by Multilayered Stochastic Modeling (MSM) [Kondrashov, Chekroun and Ghil, 2015] framework that has abundantly proven its efficiency in the modeling and real-time forecasting of various climate phenomena. MSM is a data-driven inverse modeling technique that aims to obtain a low-order nonlinear system of prognostic equations driven by stochastic forcing, and estimates both the dynamical operator and the properties of the driving noise from multivariate time series of observations or a high-end model's simulation. MSM leads to a system of stochastic differential equations (SDEs) involving hidden (auxiliary) variables of fast-small scales ranked by layers, which interact with the macroscopic (observed) variables of large-slow scales to model the dynamics of the latter, and thus convey memory effects. New MSM climate applications focus on development of computationally efficient low-order models by using data-adaptive decomposition methods that convey memory effects by time-embedding techniques, such as Multichannel Singular Spectrum Analysis (M-SSA) [Ghil et al. 2002] and recently developed Data-Adaptive Harmonic (DAH) decomposition method [Chekroun and Kondrashov, 2016]. In particular, new results by DAH-MSM modeling and prediction of Arctic Sea Ice, as well as decadal predictions of near-surface Earth temperatures will be presented.

Broken detailed balance and non-equilibrium dynamics in living systems: a review

NASA Astrophysics Data System (ADS)

Gnesotto, F. S.; Mura, F.; Gladrow, J.; Broedersz, C. P.

2018-06-01

Living systems operate far from thermodynamic equilibrium. Enzymatic activity can induce broken detailed balance at the molecular scale. This molecular scale breaking of detailed balance is crucial to achieve biological functions such as high-fidelity transcription and translation, sensing, adaptation, biochemical patterning, and force generation. While biological systems such as motor enzymes violate detailed balance at the molecular scale, it remains unclear how non-equilibrium dynamics manifests at the mesoscale in systems that are driven through the collective activity of many motors. Indeed, in several cellular systems the presence of non-equilibrium dynamics is not always evident at large scales. For example, in the cytoskeleton or in chromosomes one can observe stationary stochastic processes that appear at first glance thermally driven. This raises the question how non-equilibrium fluctuations can be discerned from thermal noise. We discuss approaches that have recently been developed to address this question, including methods based on measuring the extent to which the system violates the fluctuation-dissipation theorem. We also review applications of this approach to reconstituted cytoskeletal networks, the cytoplasm of living cells, and cell membranes. Furthermore, we discuss a more recent approach to detect actively driven dynamics, which is based on inferring broken detailed balance. This constitutes a non-invasive method that uses time-lapse microscopy data, and can be applied to a broad range of systems in cells and tissue. We discuss the ideas underlying this method and its application to several examples including flagella, primary cilia, and cytoskeletal networks. Finally, we briefly discuss recent developments in stochastic thermodynamics and non-equilibrium statistical mechanics, which offer new perspectives to understand the physics of living systems.

Broken detailed balance and non-equilibrium dynamics in living systems: a review.

PubMed

Gnesotto, F S; Mura, F; Gladrow, J; Broedersz, C P

2018-06-01

Living systems operate far from thermodynamic equilibrium. Enzymatic activity can induce broken detailed balance at the molecular scale. This molecular scale breaking of detailed balance is crucial to achieve biological functions such as high-fidelity transcription and translation, sensing, adaptation, biochemical patterning, and force generation. While biological systems such as motor enzymes violate detailed balance at the molecular scale, it remains unclear how non-equilibrium dynamics manifests at the mesoscale in systems that are driven through the collective activity of many motors. Indeed, in several cellular systems the presence of non-equilibrium dynamics is not always evident at large scales. For example, in the cytoskeleton or in chromosomes one can observe stationary stochastic processes that appear at first glance thermally driven. This raises the question how non-equilibrium fluctuations can be discerned from thermal noise. We discuss approaches that have recently been developed to address this question, including methods based on measuring the extent to which the system violates the fluctuation-dissipation theorem. We also review applications of this approach to reconstituted cytoskeletal networks, the cytoplasm of living cells, and cell membranes. Furthermore, we discuss a more recent approach to detect actively driven dynamics, which is based on inferring broken detailed balance. This constitutes a non-invasive method that uses time-lapse microscopy data, and can be applied to a broad range of systems in cells and tissue. We discuss the ideas underlying this method and its application to several examples including flagella, primary cilia, and cytoskeletal networks. Finally, we briefly discuss recent developments in stochastic thermodynamics and non-equilibrium statistical mechanics, which offer new perspectives to understand the physics of living systems.

Dynamic Simulation of AN Helium Refrigerator

NASA Astrophysics Data System (ADS)

Deschildre, C.; Barraud, A.; Bonnay, P.; Briend, P.; Girard, A.; Poncet, J. M.; Roussel, P.; Sequeira, S. E.

2008-03-01

A dynamic simulation of a large scale existing refrigerator has been performed using the software Aspen Hysys®. The model comprises the typical equipments of a cryogenic system: heat exchangers, expanders, helium phase separators and cold compressors. It represents the 400 W @ 1.8 K Test Facility located at CEA—Grenoble. This paper describes the model development and shows the possibilities and limitations of the dynamic module of Aspen Hysys®. Then, comparison between simulation results and experimental data are presented; the simulation of cooldown process was also performed.

Quantum measurement-induced dynamics of many-body ultracold bosonic and fermionic systems in optical lattices

NASA Astrophysics Data System (ADS)

Mazzucchi, Gabriel; Kozlowski, Wojciech; Caballero-Benitez, Santiago F.; Elliott, Thomas J.; Mekhov, Igor B.

2016-02-01

Trapping ultracold atoms in optical lattices enabled numerous breakthroughs uniting several disciplines. Coupling these systems to quantized light leads to a plethora of new phenomena and has opened up a new field of study. Here we introduce an unusual additional source of competition in a many-body strongly correlated system: We prove that quantum backaction of global measurement is able to efficiently compete with intrinsic short-range dynamics of an atomic system. The competition becomes possible due to the ability to change the spatial profile of a global measurement at a microscopic scale comparable to the lattice period without the need of single site addressing. In coherence with a general physical concept, where new competitions typically lead to new phenomena, we demonstrate nontrivial dynamical effects such as large-scale multimode oscillations, long-range entanglement, and correlated tunneling, as well as selective suppression and enhancement of dynamical processes beyond the projective limit of the quantum Zeno effect. We demonstrate both the breakup and protection of strongly interacting fermion pairs by measurement. Such a quantum optical approach introduces into many-body physics novel processes, objects, and methods of quantum engineering, including the design of many-body entangled environments for open systems.

Development and Application of a Structural Health Monitoring System Based on Wireless Smart Aggregates

PubMed Central

Ma, Haoyan; Li, Peng; Song, Gangbing; Wu, Jianxin

2017-01-01

Structural health monitoring (SHM) systems can improve the safety and reliability of structures, reduce maintenance costs, and extend service life. Research on concrete SHMs using piezoelectric-based smart aggregates have reached great achievements. However, the newly developed techniques have not been widely applied in practical engineering, largely due to the wiring problems associated with large-scale structural health monitoring. The cumbersome wiring requires much material and labor work, and more importantly, the associated maintenance work is also very heavy. Targeting a practical large scale concrete crack detection (CCD) application, a smart aggregates-based wireless sensor network system is proposed for the CCD application. The developed CCD system uses Zigbee 802.15.4 protocols, and is able to perform dynamic stress monitoring, structural impact capturing, and internal crack detection. The system has been experimentally validated, and the experimental results demonstrated the effectiveness of the proposed system. This work provides important support for practical CCD applications using wireless smart aggregates. PMID:28714927

Development and Application of a Structural Health Monitoring System Based on Wireless Smart Aggregates.

PubMed

Yan, Shi; Ma, Haoyan; Li, Peng; Song, Gangbing; Wu, Jianxin

2017-07-17

Structural health monitoring (SHM) systems can improve the safety and reliability of structures, reduce maintenance costs, and extend service life. Research on concrete SHMs using piezoelectric-based smart aggregates have reached great achievements. However, the newly developed techniques have not been widely applied in practical engineering, largely due to the wiring problems associated with large-scale structural health monitoring. The cumbersome wiring requires much material and labor work, and more importantly, the associated maintenance work is also very heavy. Targeting a practical large scale concrete crack detection (CCD) application, a smart aggregates-based wireless sensor network system is proposed for the CCD application. The developed CCD system uses Zigbee 802.15.4 protocols, and is able to perform dynamic stress monitoring, structural impact capturing, and internal crack detection. The system has been experimentally validated, and the experimental results demonstrated the effectiveness of the proposed system. This work provides important support for practical CCD applications using wireless smart aggregates.

pycola: N-body COLA method code

NASA Astrophysics Data System (ADS)

Tassev, Svetlin; Eisenstein, Daniel J.; Wandelt, Benjamin D.; Zaldarriagag, Matias

2015-09-01

pycola is a multithreaded Python/Cython N-body code, implementing the Comoving Lagrangian Acceleration (COLA) method in the temporal and spatial domains, which trades accuracy at small-scales to gain computational speed without sacrificing accuracy at large scales. This is especially useful for cheaply generating large ensembles of accurate mock halo catalogs required to study galaxy clustering and weak lensing. The COLA method achieves its speed by calculating the large-scale dynamics exactly using LPT while letting the N-body code solve for the small scales, without requiring it to capture exactly the internal dynamics of halos.

Asynchronous Two-Level Checkpointing Scheme for Large-Scale Adjoints in the Spectral-Element Solver Nek5000

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

Schanen, Michel; Marin, Oana; Zhang, Hong

Adjoints are an important computational tool for large-scale sensitivity evaluation, uncertainty quantification, and derivative-based optimization. An essential component of their performance is the storage/recomputation balance in which efficient checkpointing methods play a key role. We introduce a novel asynchronous two-level adjoint checkpointing scheme for multistep numerical time discretizations targeted at large-scale numerical simulations. The checkpointing scheme combines bandwidth-limited disk checkpointing and binomial memory checkpointing. Based on assumptions about the target petascale systems, which we later demonstrate to be realistic on the IBM Blue Gene/Q system Mira, we create a model of the expected performance of our checkpointing approach and validatemore » it using the highly scalable Navier-Stokes spectralelement solver Nek5000 on small to moderate subsystems of the Mira supercomputer. In turn, this allows us to predict optimal algorithmic choices when using all of Mira. We also demonstrate that two-level checkpointing is significantly superior to single-level checkpointing when adjoining a large number of time integration steps. To our knowledge, this is the first time two-level checkpointing had been designed, implemented, tuned, and demonstrated on fluid dynamics codes at large scale of 50k+ cores.« less

Regional Climate Simulations over North America: Interaction of Local Processes with Improved Large-Scale Flow.

NASA Astrophysics Data System (ADS)

Miguez-Macho, Gonzalo; Stenchikov, Georgiy L.; Robock, Alan

2005-04-01

The reasons for biases in regional climate simulations were investigated in an attempt to discern whether they arise from deficiencies in the model parameterizations or are due to dynamical problems. Using the Regional Atmospheric Modeling System (RAMS) forced by the National Centers for Environmental Prediction-National Center for Atmospheric Research reanalysis, the detailed climate over North America at 50-km resolution for June 2000 was simulated. First, the RAMS equations were modified to make them applicable to a large region, and its turbulence parameterization was corrected. The initial simulations showed large biases in the location of precipitation patterns and surface air temperatures. By implementing higher-resolution soil data, soil moisture and soil temperature initialization, and corrections to the Kain-Fritch convective scheme, the temperature biases and precipitation amount errors could be removed, but the precipitation location errors remained. The precipitation location biases could only be improved by implementing spectral nudging of the large-scale (wavelength of 2500 km) dynamics in RAMS. This corrected for circulation errors produced by interactions and reflection of the internal domain dynamics with the lateral boundaries where the model was forced by the reanalysis.

Rediscovery of the doldrums in storm-resolving simulations over the tropical Atlantic

NASA Astrophysics Data System (ADS)

Klocke, Daniel; Brueck, Matthias; Hohenegger, Cathy; Stevens, Bjorn

2017-12-01

The doldrums — a zone of calm and variable winds in the deep tropics between the trades — were of key importance to nineteenth century maritime travel. As a result, the region was a focus in atmospheric science at that time. However, as sailing ships were replaced by steamboats, scientific interest shifted to the heavy precipitating storms within the doldrums: the deep convective systems of the intertropical convergence zone. Now, in storm-system-resolving simulations over a period of two months that cover a large part of the tropical Atlantic, the doldrums are one of the most prominent features. The doldrums are substantially less pronounced in coarser-resolution simulations that use a parameterization for convection, despite their large-scale extent. We conclude that explicitly representing the storm scale dynamics and their coupling to the surface wind on the storm-system scales helps to maintain the systems of winds that define the doldrums. We suggest that the lack of these wind systems could explain the persistent tropical precipitation biases in climate models.

The cross-over to magnetostrophic convection in planetary dynamo systems

PubMed Central

King, E. M.

2017-01-01

Global scale magnetostrophic balance, in which Lorentz and Coriolis forces comprise the leading-order force balance, has long been thought to describe the natural state of planetary dynamo systems. This argument arises from consideration of the linear theory of rotating magnetoconvection. Here we test this long-held tenet by directly comparing linear predictions against dynamo modelling results. This comparison shows that dynamo modelling results are not typically in the global magnetostrophic state predicted by linear theory. Then, in order to estimate at what scale (if any) magnetostrophic balance will arise in nonlinear dynamo systems, we carry out a simple scaling analysis of the Elsasser number Λ, yielding an improved estimate of the ratio of Lorentz and Coriolis forces. From this, we deduce that there is a magnetostrophic cross-over length scale, LX≈(Λo2/Rmo)D, where Λo is the linear (or traditional) Elsasser number, Rmo is the system scale magnetic Reynolds number and D is the length scale of the system. On scales well above LX, magnetostrophic convection dynamics should not be possible. Only on scales smaller than LX should it be possible for the convective behaviours to follow the predictions for the magnetostrophic branch of convection. Because LX is significantly smaller than the system scale in most dynamo models, their large-scale flows should be quasi-geostrophic, as is confirmed in many dynamo simulations. Estimating Λo≃1 and Rmo≃103 in Earth’s core, the cross-over scale is approximately 1/1000 that of the system scale, suggesting that magnetostrophic convection dynamics exists in the core only on small scales below those that can be characterized by geomagnetic observations. PMID:28413338

The cross-over to magnetostrophic convection in planetary dynamo systems.

PubMed

Aurnou, J M; King, E M

2017-03-01

Global scale magnetostrophic balance, in which Lorentz and Coriolis forces comprise the leading-order force balance, has long been thought to describe the natural state of planetary dynamo systems. This argument arises from consideration of the linear theory of rotating magnetoconvection. Here we test this long-held tenet by directly comparing linear predictions against dynamo modelling results. This comparison shows that dynamo modelling results are not typically in the global magnetostrophic state predicted by linear theory. Then, in order to estimate at what scale (if any) magnetostrophic balance will arise in nonlinear dynamo systems, we carry out a simple scaling analysis of the Elsasser number Λ , yielding an improved estimate of the ratio of Lorentz and Coriolis forces. From this, we deduce that there is a magnetostrophic cross-over length scale, [Formula: see text], where Λ o is the linear (or traditional) Elsasser number, Rm o is the system scale magnetic Reynolds number and D is the length scale of the system. On scales well above [Formula: see text], magnetostrophic convection dynamics should not be possible. Only on scales smaller than [Formula: see text] should it be possible for the convective behaviours to follow the predictions for the magnetostrophic branch of convection. Because [Formula: see text] is significantly smaller than the system scale in most dynamo models, their large-scale flows should be quasi-geostrophic, as is confirmed in many dynamo simulations. Estimating Λ o ≃1 and Rm o ≃10 3 in Earth's core, the cross-over scale is approximately 1/1000 that of the system scale, suggesting that magnetostrophic convection dynamics exists in the core only on small scales below those that can be characterized by geomagnetic observations.

Accelerated molecular dynamics: A promising and efficient simulation method for biomolecules

NASA Astrophysics Data System (ADS)

Hamelberg, Donald; Mongan, John; McCammon, J. Andrew

2004-06-01

Many interesting dynamic properties of biological molecules cannot be simulated directly using molecular dynamics because of nanosecond time scale limitations. These systems are trapped in potential energy minima with high free energy barriers for large numbers of computational steps. The dynamic evolution of many molecular systems occurs through a series of rare events as the system moves from one potential energy basin to another. Therefore, we have proposed a robust bias potential function that can be used in an efficient accelerated molecular dynamics approach to simulate the transition of high energy barriers without any advance knowledge of the location of either the potential energy wells or saddle points. In this method, the potential energy landscape is altered by adding a bias potential to the true potential such that the escape rates from potential wells are enhanced, which accelerates and extends the time scale in molecular dynamics simulations. Our definition of the bias potential echoes the underlying shape of the potential energy landscape on the modified surface, thus allowing for the potential energy minima to be well defined, and hence properly sampled during the simulation. We have shown that our approach, which can be extended to biomolecules, samples the conformational space more efficiently than normal molecular dynamics simulations, and converges to the correct canonical distribution.

The problem of ecological scaling in spatially complex, nonequilibrium ecological systems [chapter 3

Treesearch

Samuel A. Cushman; Jeremy Littell; Kevin McGarigal

2010-01-01

In the previous chapter we reviewed the challenges posed by spatial complexity and temporal disequilibrium to efforts to understand and predict the structure and dynamics of ecological systems. The central theme was that spatial variability in the environment and population processes fundamentally alters the interactions between species and their environments, largely...

Parameter identification of civil engineering structures

NASA Technical Reports Server (NTRS)

Juang, J. N.; Sun, C. T.

1980-01-01

This paper concerns the development of an identification method required in determining structural parameter variations for systems subjected to an extended exposure to the environment. The concept of structural identifiability of a large scale structural system in the absence of damping is presented. Three criteria are established indicating that a large number of system parameters (the coefficient parameters of the differential equations) can be identified by a few actuators and sensors. An eight-bay-fifteen-story frame structure is used as example. A simple model is employed for analyzing the dynamic response of the frame structure.

Review of Aerosol–Cloud Interactions: Mechanisms, Significance, and Challenges

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

Fan, Jiwen; Wang, Yuan; Rosenfeld, Daniel

2016-11-01

Over the past decade, the number of studies that investigate aerosol-cloud interactions has increased considerably. Although tremendous progress has been made to improve our understanding of basic physical mechanisms of aerosol-cloud interactions and reduce their uncertainties in climate forcing, we are still in poor understanding of (1) some of the mechanisms that interact with each other over multiple spatial and temporal scales, (2) the feedback between microphysical and dynamical processes and between local-scale processes and large-scale circulations, and (3) the significance of cloud-aerosol interactions on weather systems as well as regional and global climate. This review focuses on recent theoreticalmore » studies and important mechanisms on aerosol-cloud interactions, and discusses the significances of aerosol impacts on raditative forcing and precipitation extremes associated with different cloud systems. Despite significant understanding has been gained about aerosol impacts on the main cloud types, there are still many unknowns especially associated with various deep convective systems. Therefore, large efforts are needed to escalate our understanding. Future directions should focus on obtaining concurrent measurements of aerosol properties, cloud microphysical and dynamic properties over a range of temporal and spatial scales collected over typical climate regimes and closure studies, as well as improving understanding and parameterizations of cloud microphysics such as ice nucleation, mixed-phase properties, and hydrometeor size and fall speed« less

Phase-relationships between scales in the perturbed turbulent boundary layer

NASA Astrophysics Data System (ADS)

Jacobi, I.; McKeon, B. J.

2017-12-01

The phase-relationship between large-scale motions and small-scale fluctuations in a non-equilibrium turbulent boundary layer was investigated. A zero-pressure-gradient flat plate turbulent boundary layer was perturbed by a short array of two-dimensional roughness elements, both statically, and under dynamic actuation. Within the compound, dynamic perturbation, the forcing generated a synthetic very-large-scale motion (VLSM) within the flow. The flow was decomposed by phase-locking the flow measurements to the roughness forcing, and the phase-relationship between the synthetic VLSM and remaining fluctuating scales was explored by correlation techniques. The general relationship between large- and small-scale motions in the perturbed flow, without phase-locking, was also examined. The synthetic large scale cohered with smaller scales in the flow via a phase-relationship that is similar to that of natural large scales in an unperturbed flow, but with a much stronger organizing effect. Cospectral techniques were employed to describe the physical implications of the perturbation on the relative orientation of large- and small-scale structures in the flow. The correlation and cospectral techniques provide tools for designing more efficient control strategies that can indirectly control small-scale motions via the large scales.

Energetic Consistency and Coupling of the Mean and Covariance Dynamics

NASA Technical Reports Server (NTRS)

Cohn, Stephen E.

2008-01-01

The dynamical state of the ocean and atmosphere is taken to be a large dimensional random vector in a range of large-scale computational applications, including data assimilation, ensemble prediction, sensitivity analysis, and predictability studies. In each of these applications, numerical evolution of the covariance matrix of the random state plays a central role, because this matrix is used to quantify uncertainty in the state of the dynamical system. Since atmospheric and ocean dynamics are nonlinear, there is no closed evolution equation for the covariance matrix, nor for the mean state. Therefore approximate evolution equations must be used. This article studies theoretical properties of the evolution equations for the mean state and covariance matrix that arise in the second-moment closure approximation (third- and higher-order moment discard). This approximation was introduced by EPSTEIN [1969] in an early effort to introduce a stochastic element into deterministic weather forecasting, and was studied further by FLEMING [1971a,b], EPSTEIN and PITCHER [1972], and PITCHER [1977], also in the context of atmospheric predictability. It has since fallen into disuse, with a simpler one being used in current large-scale applications. The theoretical results of this article make a case that this approximation should be reconsidered for use in large-scale applications, however, because the second moment closure equations possess a property of energetic consistency that the approximate equations now in common use do not possess. A number of properties of solutions of the second-moment closure equations that result from this energetic consistency will be established.

Parameter estimation in large-scale systems biology models: a parallel and self-adaptive cooperative strategy.

PubMed

Penas, David R; González, Patricia; Egea, Jose A; Doallo, Ramón; Banga, Julio R

2017-01-21

The development of large-scale kinetic models is one of the current key issues in computational systems biology and bioinformatics. Here we consider the problem of parameter estimation in nonlinear dynamic models. Global optimization methods can be used to solve this type of problems but the associated computational cost is very large. Moreover, many of these methods need the tuning of a number of adjustable search parameters, requiring a number of initial exploratory runs and therefore further increasing the computation times. Here we present a novel parallel method, self-adaptive cooperative enhanced scatter search (saCeSS), to accelerate the solution of this class of problems. The method is based on the scatter search optimization metaheuristic and incorporates several key new mechanisms: (i) asynchronous cooperation between parallel processes, (ii) coarse and fine-grained parallelism, and (iii) self-tuning strategies. The performance and robustness of saCeSS is illustrated by solving a set of challenging parameter estimation problems, including medium and large-scale kinetic models of the bacterium E. coli, bakerés yeast S. cerevisiae, the vinegar fly D. melanogaster, Chinese Hamster Ovary cells, and a generic signal transduction network. The results consistently show that saCeSS is a robust and efficient method, allowing very significant reduction of computation times with respect to several previous state of the art methods (from days to minutes, in several cases) even when only a small number of processors is used. The new parallel cooperative method presented here allows the solution of medium and large scale parameter estimation problems in reasonable computation times and with small hardware requirements. Further, the method includes self-tuning mechanisms which facilitate its use by non-experts. We believe that this new method can play a key role in the development of large-scale and even whole-cell dynamic models.

Mathematical and Computational Challenges in Population Biology and Ecosystems Science

NASA Technical Reports Server (NTRS)

Levin, Simon A.; Grenfell, Bryan; Hastings, Alan; Perelson, Alan S.

1997-01-01

Mathematical and computational approaches provide powerful tools in the study of problems in population biology and ecosystems science. The subject has a rich history intertwined with the development of statistics and dynamical systems theory, but recent analytical advances, coupled with the enhanced potential of high-speed computation, have opened up new vistas and presented new challenges. Key challenges involve ways to deal with the collective dynamics of heterogeneous ensembles of individuals, and to scale from small spatial regions to large ones. The central issues-understanding how detail at one scale makes its signature felt at other scales, and how to relate phenomena across scales-cut across scientific disciplines and go to the heart of algorithmic development of approaches to high-speed computation. Examples are given from ecology, genetics, epidemiology, and immunology.

An Optimization Code for Nonlinear Transient Problems of a Large Scale Multidisciplinary Mathematical Model

NASA Astrophysics Data System (ADS)

Takasaki, Koichi

This paper presents a program for the multidisciplinary optimization and identification problem of the nonlinear model of large aerospace vehicle structures. The program constructs the global matrix of the dynamic system in the time direction by the p-version finite element method (pFEM), and the basic matrix for each pFEM node in the time direction is described by a sparse matrix similarly to the static finite element problem. The algorithm used by the program does not require the Hessian matrix of the objective function and so has low memory requirements. It also has a relatively low computational cost, and is suited to parallel computation. The program was integrated as a solver module of the multidisciplinary analysis system CUMuLOUS (Computational Utility for Multidisciplinary Large scale Optimization of Undense System) which is under development by the Aerospace Research and Development Directorate (ARD) of the Japan Aerospace Exploration Agency (JAXA).

Modeling, Analysis and Mitigation of Sub-Synchronous Interactions between Full- and Partial-Scale Voltage-Source Converters and Power Networks

NASA Astrophysics Data System (ADS)

Alawasa, Khaled Mohammad

Voltage-source converters (VSCs) have gained widespread acceptance in modern power systems. The stability and dynamics of power systems involving these devices have recently become salient issues. In the small-signal sense, the dynamics of VSC-based systems is dictated by its incremental output impedance, which is formed by a combination of 'passive' circuit components and 'active' control elements. Control elements such as control parameters, control loops, and control topologies play a significant role in shaping the impedance profile. Depending on the control schemes and strategies used, VSC-based systems can exhibit different incremental impedance dynamics. As the control elements and dynamics are involved in the impedance structure, the frequency-dependent output impedance might have a negative real-part (i.e., a negative resistance). In the grid-connected mode, the negative resistance degrades the system damping and negatively impacts the stability. In high-voltage networks where high-power VSC-based systems are usually employed and where sub-synchronous dynamics usually exist, integrating large VSC-based systems might reduce the overall damping and results in unstable dynamics. The objectives of this thesis are to (1) investigate and analyze the output impedance properties under different control strategies and control functions, (2) identify and characterize the key contributors to the impedance and sub-synchronous damping profiles, and (3) propose mitigation techniques to minimize and eliminate the negative impact associated with integrating VSC-based systems into power systems. Different VSC configurations are considered in this thesis; in particular, the full-scale and partial-scale topologies (doubly fed-induction generators) are addressed. Additionally, the impedance and system damping profiles are studied under two different control strategies: the standard vector control strategy and the recently-developed power synchronization control strategy. Furthermore, this thesis proposes a simple and robust technique for damping the sub-synchronous resonance in a power system.

ArI/ArII laser induced fluorescence system for measurement of neutral and ion dynamics in a large scale helicon plasma

NASA Astrophysics Data System (ADS)

Kelly, R. F.; Meaney, K. D.; Gilmore, M.; Desjardins, T. R.; Zhang, Y.

2016-11-01

In order to investigate the role of both neutral and ion dynamics in large-scale helicon discharges, a laser induced fluorescence (LIF) system capable of measuring both ArI and ArII fluorescence using a single tunable laser is being developed. The system is based on a >250 mW solid state laser. For ArI measurements, the laser pumps the metastable (2P03/2)4s level to the (2P01/2)4p level using 696.7352 nm light, and fluorescence radiation from decay to the (2P01/2)4s level at 772.6333 nm is observed. For ArII, currently in development, the metastable (3P)3d 4F7/2 level will be pumped to the (3P)4p 4D07/2 level using 688.8511 nm, and decay fluorescence to the (3P)4s 4P5/2 level at 434.9285 nm measured. Here all wavelengths are in a vacuum.

ArI/ArII laser induced fluorescence system for measurement of neutral and ion dynamics in a large scale helicon plasma.

PubMed

Kelly, R F; Meaney, K D; Gilmore, M; Desjardins, T R; Zhang, Y

2016-11-01

In order to investigate the role of both neutral and ion dynamics in large-scale helicon discharges, a laser induced fluorescence (LIF) system capable of measuring both ArI and ArII fluorescence using a single tunable laser is being developed. The system is based on a >250 mW solid state laser. For ArI measurements, the laser pumps the metastable ( 2 P 0 3/2 )4s level to the ( 2 P 0 1/2 )4p level using 696.7352 nm light, and fluorescence radiation from decay to the ( 2 P 0 1/2 )4s level at 772.6333 nm is observed. For ArII, currently in development, the metastable ( 3 P)3d 4 F 7/2 level will be pumped to the ( 3 P)4p 4 D 0 7/2 level using 688.8511 nm, and decay fluorescence to the ( 3 P)4s 4 P 5/2 level at 434.9285 nm measured. Here all wavelengths are in a vacuum.

A microkernel design for component-based parallel numerical software systems.

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

Balay, S.

1999-01-13

What is the minimal software infrastructure and what type of conventions are needed to simplify development of sophisticated parallel numerical application codes using a variety of software components that are not necessarily available as source code? We propose an opaque object-based model where the objects are dynamically loadable from the file system or network. The microkernel required to manage such a system needs to include, at most: (1) a few basic services, namely--a mechanism for loading objects at run time via dynamic link libraries, and consistent schemes for error handling and memory management; and (2) selected methods that all objectsmore » share, to deal with object life (destruction, reference counting, relationships), and object observation (viewing, profiling, tracing). We are experimenting with these ideas in the context of extensible numerical software within the ALICE (Advanced Large-scale Integrated Computational Environment) project, where we are building the microkernel to manage the interoperability among various tools for large-scale scientific simulations. This paper presents some preliminary observations and conclusions from our work with microkernel design.« less

Three pillars for achieving quantum mechanical molecular dynamics simulations of huge systems: Divide-and-conquer, density-functional tight-binding, and massively parallel computation.

PubMed

Nishizawa, Hiroaki; Nishimura, Yoshifumi; Kobayashi, Masato; Irle, Stephan; Nakai, Hiromi

2016-08-05

The linear-scaling divide-and-conquer (DC) quantum chemical methodology is applied to the density-functional tight-binding (DFTB) theory to develop a massively parallel program that achieves on-the-fly molecular reaction dynamics simulations of huge systems from scratch. The functions to perform large scale geometry optimization and molecular dynamics with DC-DFTB potential energy surface are implemented to the program called DC-DFTB-K. A novel interpolation-based algorithm is developed for parallelizing the determination of the Fermi level in the DC method. The performance of the DC-DFTB-K program is assessed using a laboratory computer and the K computer. Numerical tests show the high efficiency of the DC-DFTB-K program, a single-point energy gradient calculation of a one-million-atom system is completed within 60 s using 7290 nodes of the K computer. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Computer-aided software development process design

NASA Technical Reports Server (NTRS)

Lin, Chi Y.; Levary, Reuven R.

1989-01-01

The authors describe an intelligent tool designed to aid managers of software development projects in planning, managing, and controlling the development process of medium- to large-scale software projects. Its purpose is to reduce uncertainties in the budget, personnel, and schedule planning of software development projects. It is based on dynamic model for the software development and maintenance life-cycle process. This dynamic process is composed of a number of time-varying, interacting developmental phases, each characterized by its intended functions and requirements. System dynamics is used as a modeling methodology. The resulting Software LIfe-Cycle Simulator (SLICS) and the hybrid expert simulation system of which it is a subsystem are described.

High-speed inlet research program and supporting analysis

NASA Technical Reports Server (NTRS)

Coltrin, Robert E.

1990-01-01

The technology challenges faced by the high speed inlet designer are discussed by describing the considerations that went into the design of the Mach 5 research inlet. It is shown that the emerging three dimensional viscous computational fluid dynamics (CFD) flow codes, together with small scale experiments, can be used to guide larger scale full inlet systems research. Then, in turn, the results of the large scale research, if properly instrumented, can be used to validate or at least to calibrate the CFD codes.

A reduced basis method for molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Vincent-Finley, Rachel Elisabeth

In this dissertation, we develop a method for molecular simulation based on principal component analysis (PCA) of a molecular dynamics trajectory and least squares approximation of a potential energy function. Molecular dynamics (MD) simulation is a computational tool used to study molecular systems as they evolve through time. With respect to protein dynamics, local motions, such as bond stretching, occur within femtoseconds, while rigid body and large-scale motions, occur within a range of nanoseconds to seconds. To capture motion at all levels, time steps on the order of a femtosecond are employed when solving the equations of motion and simulations must continue long enough to capture the desired large-scale motion. To date, simulations of solvated proteins on the order of nanoseconds have been reported. It is typically the case that simulations of a few nanoseconds do not provide adequate information for the study of large-scale motions. Thus, the development of techniques that allow longer simulation times can advance the study of protein function and dynamics. In this dissertation we use principal component analysis (PCA) to identify the dominant characteristics of an MD trajectory and to represent the coordinates with respect to these characteristics. We augment PCA with an updating scheme based on a reduced representation of a molecule and consider equations of motion with respect to the reduced representation. We apply our method to butane and BPTI and compare the results to standard MD simulations of these molecules. Our results indicate that the molecular activity with respect to our simulation method is analogous to that observed in the standard MD simulation with simulations on the order of picoseconds.

Ecological hierarchies and self-organisation - Pattern analysis, modelling and process integration across scales

USGS Publications Warehouse

Reuter, H.; Jopp, F.; Blanco-Moreno, J. M.; Damgaard, C.; Matsinos, Y.; DeAngelis, D.L.

2010-01-01

A continuing discussion in applied and theoretical ecology focuses on the relationship of different organisational levels and on how ecological systems interact across scales. We address principal approaches to cope with complex across-level issues in ecology by applying elements of hierarchy theory and the theory of complex adaptive systems. A top-down approach, often characterised by the use of statistical techniques, can be applied to analyse large-scale dynamics and identify constraints exerted on lower levels. Current developments are illustrated with examples from the analysis of within-community spatial patterns and large-scale vegetation patterns. A bottom-up approach allows one to elucidate how interactions of individuals shape dynamics at higher levels in a self-organisation process; e.g., population development and community composition. This may be facilitated by various modelling tools, which provide the distinction between focal levels and resulting properties. For instance, resilience in grassland communities has been analysed with a cellular automaton approach, and the driving forces in rodent population oscillations have been identified with an agent-based model. Both modelling tools illustrate the principles of analysing higher level processes by representing the interactions of basic components.The focus of most ecological investigations on either top-down or bottom-up approaches may not be appropriate, if strong cross-scale relationships predominate. Here, we propose an 'across-scale-approach', closely interweaving the inherent potentials of both approaches. This combination of analytical and synthesising approaches will enable ecologists to establish a more coherent access to cross-level interactions in ecological systems. ?? 2010 Gesellschaft f??r ??kologie.

Analysis of Large Scale Spatial Variability of Soil Moisture Using a Geostatistical Method

DTIC Science & Technology

2010-01-25

2010 / Accepted: 19 January 2010 / Published: 25 January 2010 Abstract: Spatial and temporal soil moisture dynamics are critically needed to...scale observed and simulated estimates of soil moisture under pre- and post-precipitation event conditions. This large scale variability is a crucial... dynamics is essential in the hydrological and meteorological modeling, improves our understanding of land surface–atmosphere interactions. Spatial and

Extension to the dynamic modeling of the large angle magnetic suspension test fixture. M.S. Thesis - Old Dominion Univ., May 1995 Progress Report, 1 Nov. 1994 - 30 Apr. 1995

NASA Technical Reports Server (NTRS)

Foster, Lucas E.; Britcher, Colin P.

1995-01-01

The Large Angle Magnetic Suspension Test Fixture (LAMSTF) is a laboratory scale proof-of-concept system. The configuration is unique in that the electromagnets are mounted in a circular planar array. A mathematical model of the system had previously been developed, but was shown to have inaccuracies. These inaccuracies showed up in the step responses. Eddy currents were found to be the major cause of the modeling errors. In the original system, eddy currents existed in the aluminum baseplate, iron cores, and the sensor support frame. An attempt to include the eddy current dynamics in the system model is presented. The dynamics of a dummy sensor ring were added to the system. Adding the eddy current dynamics to the simulation improves the way it compares to the actual experiment. Also presented is a new method of determining the yaw angle of the suspended element. From the coil currents the yaw angle can be determined and the controller can be updated to suspend at the new current. This method has been used to demonstrate a 360 degree yaw angle rotation.

Decentralized regulation of dynamic systems. [for controlling large scale linear systems

NASA Technical Reports Server (NTRS)

Chu, K. C.

1975-01-01

A special class of decentralized control problem is discussed in which the objectives of the control agents are to steer the state of the system to desired levels. Each agent is concerned about certain aspects of the state of the entire system. The state and control equations are given for linear time-invariant systems. Stability and coordination, and the optimization of decentralized control are analyzed, and the information structure design is presented.

Finite-time and finite-size scalings in the evaluation of large-deviation functions: Numerical approach in continuous time.

PubMed

Guevara Hidalgo, Esteban; Nemoto, Takahiro; Lecomte, Vivien

2017-06-01

Rare trajectories of stochastic systems are important to understand because of their potential impact. However, their properties are by definition difficult to sample directly. Population dynamics provides a numerical tool allowing their study, by means of simulating a large number of copies of the system, which are subjected to selection rules that favor the rare trajectories of interest. Such algorithms are plagued by finite simulation time and finite population size, effects that can render their use delicate. In this paper, we present a numerical approach which uses the finite-time and finite-size scalings of estimators of the large deviation functions associated to the distribution of rare trajectories. The method we propose allows one to extract the infinite-time and infinite-size limit of these estimators, which-as shown on the contact process-provides a significant improvement of the large deviation function estimators compared to the standard one.

Topological Principles of Control in Dynamical Networks

NASA Astrophysics Data System (ADS)

Kim, Jason; Pasqualetti, Fabio; Bassett, Danielle

Networked biological systems, such as the brain, feature complex patterns of interactions. To predict and correct the dynamic behavior of such systems, it is imperative to understand how the underlying topological structure affects and limits the function of the system. Here, we use network control theory to extract topological features that favor or prevent network controllability, and to understand the network-wide effect of external stimuli on large-scale brain systems. Specifically, we treat each brain region as a dynamic entity with real-valued state, and model the time evolution of all interconnected regions using linear, time-invariant dynamics. We propose a simplified feed-forward scheme where the effect of upstream regions (drivers) on the connected downstream regions (non-drivers) is characterized in closed-form. Leveraging this characterization of the simplified model, we derive topological features that predict the controllability properties of non-simplified networks. We show analytically and numerically that these predictors are accurate across a large range of parameters. Among other contributions, our analysis shows that heterogeneity in the network weights facilitate controllability, and allows us to implement targeted interventions that profoundly improve controllability. By assuming an underlying dynamical mechanism, we are able to understand the complex topology of networked biological systems in a functionally meaningful way.

From Lattice Boltzmann to hydrodynamics in dissipative relativistic fluids

NASA Astrophysics Data System (ADS)

Gabbana, Alessandro; Mendoza, Miller; Succi, Sauro; Tripiccione, Raffaele

2017-11-01

Relativistic fluid dynamics is currently applied to several fields of modern physics, covering many physical scales, from astrophysics, to atomic scales (e.g. in the study of effective 2D systems such as graphene) and further down to subnuclear scales (e.g. quark-gluon plasmas). This talk focuses on recent progress in the largely debated connection between kinetic transport coefficients and macroscopic hydrodynamic parameters in dissipative relativistic fluid dynamics. We use a new relativistic Lattice Boltzmann method (RLBM), able to handle from ultra-relativistic to almost non-relativistic flows, and obtain strong evidence that the Chapman-Enskog expansion provides the correct pathway from kinetic theory to hydrodynamics. This analysis confirms recently obtained theoretical results, which can be used to obtain accurate calibrations for RLBM methods applied to realistic physics systems in the relativistic regime. Using this calibration methodology, RLBM methods are able to deliver improved physical accuracy in the simulation of the physical systems described above. European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 642069.

Recent (1999-2003) Canadian research on contemporary processes of river erosion and sedimentation, and river mechanics

NASA Astrophysics Data System (ADS)

de Boer, D. H.; Hassan, M. A.; MacVicar, B.; Stone, M.

2005-01-01

Contributions by Canadian fluvial geomorphologists between 1999 and 2003 are discussed under four major themes: sediment yield and sediment dynamics of large rivers; cohesive sediment transport; turbulent flow structure and sediment transport; and bed material transport and channel morphology. The paper concludes with a section on recent technical advances. During the review period, substantial progress has been made in investigating the details of fluvial processes at relatively small scales. Examples of this emphasis are the studies of flow structure, turbulence characteristics and bedload transport, which continue to form central themes in fluvial research in Canada. Translating the knowledge of small-scale, process-related research to an understanding of the behaviour of large-scale fluvial systems, however, continues to be a formidable challenge. Models play a prominent role in elucidating the link between small-scale processes and large-scale fluvial geomorphology, and, as a result, a number of papers describing models and modelling results have been published during the review period. In addition, a number of investigators are now approaching the problem by directly investigating changes in the system of interest at larger scales, e.g. a channel reach over tens of years, and attempting to infer what processes may have led to the result. It is to be expected that these complementary approaches will contribute to an increased understanding of fluvial systems at a variety of spatial and temporal scales. Copyright

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.

Charge and energy migration in molecular clusters: A stochastic Schrödinger equation approach.

PubMed

Plehn, Thomas; May, Volkhard

2017-01-21

The performance of stochastic Schrödinger equations for simulating dynamic phenomena in large scale open quantum systems is studied. Going beyond small system sizes, commonly used master equation approaches become inadequate. In this regime, wave function based methods profit from their inherent scaling benefit and present a promising tool to study, for example, exciton and charge carrier dynamics in huge and complex molecular structures. In the first part of this work, a strict analytic derivation is presented. It starts with the finite temperature reduced density operator expanded in coherent reservoir states and ends up with two linear stochastic Schrödinger equations. Both equations are valid in the weak and intermediate coupling limit and can be properly related to two existing approaches in literature. In the second part, we focus on the numerical solution of these equations. The main issue is the missing norm conservation of the wave function propagation which may lead to numerical discrepancies. To illustrate this, we simulate the exciton dynamics in the Fenna-Matthews-Olson complex in direct comparison with the data from literature. Subsequently a strategy for the proper computational handling of the linear stochastic Schrödinger equation is exposed particularly with regard to large systems. Here, we study charge carrier transfer kinetics in realistic hybrid organic/inorganic para-sexiphenyl/ZnO systems of different extension.

Charge and energy migration in molecular clusters: A stochastic Schrödinger equation approach

NASA Astrophysics Data System (ADS)

Plehn, Thomas; May, Volkhard

2017-01-01

The performance of stochastic Schrödinger equations for simulating dynamic phenomena in large scale open quantum systems is studied. Going beyond small system sizes, commonly used master equation approaches become inadequate. In this regime, wave function based methods profit from their inherent scaling benefit and present a promising tool to study, for example, exciton and charge carrier dynamics in huge and complex molecular structures. In the first part of this work, a strict analytic derivation is presented. It starts with the finite temperature reduced density operator expanded in coherent reservoir states and ends up with two linear stochastic Schrödinger equations. Both equations are valid in the weak and intermediate coupling limit and can be properly related to two existing approaches in literature. In the second part, we focus on the numerical solution of these equations. The main issue is the missing norm conservation of the wave function propagation which may lead to numerical discrepancies. To illustrate this, we simulate the exciton dynamics in the Fenna-Matthews-Olson complex in direct comparison with the data from literature. Subsequently a strategy for the proper computational handling of the linear stochastic Schrödinger equation is exposed particularly with regard to large systems. Here, we study charge carrier transfer kinetics in realistic hybrid organic/inorganic para-sexiphenyl/ZnO systems of different extension.

A scalable double-barcode sequencing platform for characterization of dynamic protein-protein interactions.

PubMed

Schlecht, Ulrich; Liu, Zhimin; Blundell, Jamie R; St Onge, Robert P; Levy, Sasha F

2017-05-25

Several large-scale efforts have systematically catalogued protein-protein interactions (PPIs) of a cell in a single environment. However, little is known about how the protein interactome changes across environmental perturbations. Current technologies, which assay one PPI at a time, are too low throughput to make it practical to study protein interactome dynamics. Here, we develop a highly parallel protein-protein interaction sequencing (PPiSeq) platform that uses a novel double barcoding system in conjunction with the dihydrofolate reductase protein-fragment complementation assay in Saccharomyces cerevisiae. PPiSeq detects PPIs at a rate that is on par with current assays and, in contrast with current methods, quantitatively scores PPIs with enough accuracy and sensitivity to detect changes across environments. Both PPI scoring and the bulk of strain construction can be performed with cell pools, making the assay scalable and easily reproduced across environments. PPiSeq is therefore a powerful new tool for large-scale investigations of dynamic PPIs.

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

Environmentally induced amplitude death and firing provocation in large-scale networks of neuronal systems

NASA Astrophysics Data System (ADS)

Pankratova, Evgeniya V.; Kalyakulina, Alena I.

2016-12-01

We study the dynamics of multielement neuronal systems taking into account both the direct interaction between the cells via linear coupling and nondiffusive cell-to-cell communication via common environment. For the cells exhibiting individual bursting behavior, we have revealed the dependence of the network activity on its scale. Particularly, we show that small-scale networks demonstrate the inability to maintain complicated oscillations: for a small number of elements in an ensemble, the phenomenon of amplitude death is observed. The existence of threshold network scales and mechanisms causing firing in artificial and real multielement neural networks, as well as their significance for biological applications, are discussed.

Discrete Event Modeling and Massively Parallel Execution of Epidemic Outbreak Phenomena

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

Perumalla, Kalyan S; Seal, Sudip K

2011-01-01

In complex phenomena such as epidemiological outbreaks, the intensity of inherent feedback effects and the significant role of transients in the dynamics make simulation the only effective method for proactive, reactive or post-facto analysis. The spatial scale, runtime speed, and behavioral detail needed in detailed simulations of epidemic outbreaks make it necessary to use large-scale parallel processing. Here, an optimistic parallel execution of a new discrete event formulation of a reaction-diffusion simulation model of epidemic propagation is presented to facilitate in dramatically increasing the fidelity and speed by which epidemiological simulations can be performed. Rollback support needed during optimistic parallelmore » execution is achieved by combining reverse computation with a small amount of incremental state saving. Parallel speedup of over 5,500 and other runtime performance metrics of the system are observed with weak-scaling execution on a small (8,192-core) Blue Gene / P system, while scalability with a weak-scaling speedup of over 10,000 is demonstrated on 65,536 cores of a large Cray XT5 system. Scenarios representing large population sizes exceeding several hundreds of millions of individuals in the largest cases are successfully exercised to verify model scalability.« less

Evaluation of the scale dependent dynamic SGS model in the open source code caffa3d.MBRi in wall-bounded flows

NASA Astrophysics Data System (ADS)

Draper, Martin; Usera, Gabriel

2015-04-01

The Scale Dependent Dynamic Model (SDDM) has been widely validated in large-eddy simulations using pseudo-spectral codes [1][2][3]. The scale dependency, particularly the potential law, has been proved also in a priori studies [4][5]. To the authors' knowledge there have been only few attempts to use the SDDM in finite difference (FD) and finite volume (FV) codes [6][7], finding some improvements with the dynamic procedures (scale independent or scale dependent approach), but not showing the behavior of the scale-dependence parameter when using the SDDM. The aim of the present paper is to evaluate the SDDM in the open source code caffa3d.MBRi, an updated version of the code presented in [8]. caffa3d.MBRi is a FV code, second-order accurate, parallelized with MPI, in which the domain is divided in unstructured blocks of structured grids. To accomplish this, 2 cases are considered: flow between flat plates and flow over a rough surface with the presence of a model wind turbine, taking for this case the experimental data presented in [9]. In both cases the standard Smagorinsky Model (SM), the Scale Independent Dynamic Model (SIDM) and the SDDM are tested. As presented in [6][7] slight improvements are obtained with the SDDM. Nevertheless, the behavior of the scale-dependence parameter supports the generalization of the dynamic procedure proposed in the SDDM, particularly taking into account that no explicit filter is used (the implicit filter is unknown). [1] F. Porté-Agel, C. Meneveau, M.B. Parlange. "A scale-dependent dynamic model for large-eddy simulation: application to a neutral atmospheric boundary layer". Journal of Fluid Mechanics, 2000, 415, 261-284. [2] E. Bou-Zeid, C. Meneveau, M. Parlante. "A scale-dependent Lagrangian dynamic model for large eddy simulation of complex turbulent flows". Physics of Fluids, 2005, 17, 025105 (18p). [3] R. Stoll, F. Porté-Agel. "Dynamic subgrid-scale models for momentum and scalar fluxes in large-eddy simulations of neutrally stratified atmospheric boundary layers over heterogeneous terrain". Water Resources Research, 2006, 42, WO1409 (18 p). [4] J. Keissl, M. Parlange, C. Meneveau. "Field experimental study of dynamic Smagorinsky models in the atmospheric surface layer". Journal of the Atmospheric Science, 2004, 61, 2296-2307. [5] E. Bou-Zeid, N. Vercauteren, M.B. Parlange, C. Meneveau. "Scale dependence of subgrid-scale model coefficients: An a priori study". Physics of Fluids, 2008, 20, 115106. [6] G. Kirkil, J. Mirocha, E. Bou-Zeid, F.K. Chow, B. Kosovic, "Implementation and evaluation of dynamic subfilter - scale stress models for large - eddy simulation using WRF". Monthly Weather Review, 2012, 140, 266-284. [7] S. Radhakrishnan, U. Piomelli. "Large-eddy simulation of oscillating boundary layers: model comparison and validation". Journal of Geophysical Research, 2008, 113, C02022. [8] G. Usera, A. Vernet, J.A. Ferré. "A parallel block-structured finite volume method for flows in complex geometry with sliding interfaces". Flow, Turbulence and Combustion, 2008, 81, 471-495. [9] Y-T. Wu, F. Porté-Agel. "Large-eddy simulation of wind-turbine wakes: evaluation of turbine parametrisations". BoundaryLayerMeteorology, 2011, 138, 345-366.

Water circulation and global mantle dynamics: Insight from numerical modeling

NASA Astrophysics Data System (ADS)

Nakagawa, Takashi; Nakakuki, Tomoeki; Iwamori, Hikaru

2015-05-01

We investigate water circulation and its dynamical effects on global-scale mantle dynamics in numerical thermochemical mantle convection simulations. Both dehydration-hydration processes and dehydration melting are included. We also assume the rheological properties of hydrous minerals and density reduction caused by hydrous minerals. Heat transfer due to mantle convection seems to be enhanced more effectively than water cycling in the mantle convection system when reasonable water dependence of viscosity is assumed, due to effective slab dehydration at shallow depths. Water still affects significantly the global dynamics by weakening the near-surface oceanic crust and lithosphere, enhancing the activity of surface plate motion compared to dry mantle case. As a result, including hydrous minerals, the more viscous mantle is expected with several orders of magnitude compared to the dry mantle. The average water content in the whole mantle is regulated by the dehydration-hydration process. The large-scale thermochemical anomalies, as is observed in the deep mantle, is found when a large density contrast between basaltic material and ambient mantle is assumed (4-5%), comparable to mineral physics measurements. Through this study, the effects of hydrous minerals in mantle dynamics are very important for interpreting the observational constraints on mantle convection.

NASA Goddard Earth Sciences Graduate Student Program. [FIRE CIRRUS-II examination of coupling between an upper tropospheric cloud system and synoptic-scale dynamics

NASA Technical Reports Server (NTRS)

Ackerman, Thomas P.

1994-01-01

The evolution of synoptic-scale dynamics associated with a middle and upper tropospheric cloud event that occurred on 26 November 1991 is examined. The case under consideration occurred during the FIRE CIRRUS-II Intensive Field Observing Period held in Coffeyville, KS during Nov. and Dec., 1991. Using data from the wind profiler demonstration network and a temporally and spatially augmented radiosonde array, emphasis is given to explaining the evolution of the kinematically-derived ageostrophic vertical circulations and correlating the circulation with the forcing of an extensively sampled cloud field. This is facilitated by decomposing the horizontal divergence into its component parts through a natural coordinate representation of the flow. Ageostrophic vertical circulations are inferred and compared to the circulation forcing arising from geostrophic confluence and shearing deformation derived from the Sawyer-Eliassen Equation. It is found that a thermodynamically indirect vertical circulation existed in association with a jet streak exit region. The circulation was displaced to the cyclonic side of the jet axis due to the orientation of the jet exit between a deepening diffluent trough and building ridge. The cloud line formed in the ascending branch of the vertical circulation with the most concentrated cloud development occurring in conjunction with the maximum large-scale vertical motion. The relationship between the large scale dynamics and the parameterization of middle and upper tropospheric clouds in large-scale models is discussed and an example of ice water contents derived from a parameterization forced by the diagnosed vertical motions and observed water vapor contents is presented.

System Dynamics Modeling of Transboundary Systems: The Bear River Basin Model

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

Gerald Sehlke; Jake Jacobson

2005-09-01

System dynamics is a computer-aided approach to evaluating the interrelationships of different components and activities within complex systems. Recently, system dynamics models have been developed in areas such as policy design, biological and medical modeling, energy and the environmental analysis, and in various other areas in the natural and social sciences. The Idaho National Engineering and Environmental Laboratory, a multi-purpose national laboratory managed by the Department of Energy, has developed a systems dynamics model in order to evaluate its utility for modeling large complex hydrological systems. We modeled the Bear River Basin, a transboundary basin that includes portions of Idaho,more » Utah and Wyoming. We found that system dynamics modeling is very useful for integrating surface water and groundwater data and for simulating the interactions between these sources within a given basin. In addition, we also found system dynamics modeling is useful for integrating complex hydrologic data with other information (e.g., policy, regulatory and management criteria) to produce a decision support system. Such decision support systems can allow managers and stakeholders to better visualize the key hydrologic elements and management constraints in the basin, which enables them to better understand the system via the simulation of multiple “what-if” scenarios. Although system dynamics models can be developed to conduct traditional hydraulic/hydrologic surface water or groundwater modeling, we believe that their strength lies in their ability to quickly evaluate trends and cause–effect relationships in large-scale hydrological systems; for integrating disparate data; for incorporating output from traditional hydraulic/hydrologic models; and for integration of interdisciplinary data, information and criteria to support better management decisions.« less

System Dynamics Modeling of Transboundary Systems: the Bear River Basin Model

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

Gerald Sehlke; Jacob J. Jacobson

2005-09-01

System dynamics is a computer-aided approach to evaluating the interrelationships of different components and activities within complex systems. Recently, system dynamics models have been developed in areas such as policy design, biological and medical modeling, energy and the environmental analysis, and in various other areas in the natural and social sciences. The Idaho National Engineering and Environmental Laboratory, a multi-purpose national laboratory managed by the Department of Energy, has developed a systems dynamics model in order to evaluate its utility for modeling large complex hydrological systems. We modeled the Bear River Basin, a transboundary basin that includes portions of Idaho,more » Utah and Wyoming. We found that system dynamics modeling is very useful for integrating surface water and ground water data and for simulating the interactions between these sources within a given basin. In addition, we also found system dynamics modeling is useful for integrating complex hydrologic data with other information (e.g., policy, regulatory and management criteria) to produce a decision support system. Such decision support systems can allow managers and stakeholders to better visualize the key hydrologic elements and management constraints in the basin, which enables them to better understand the system via the simulation of multiple “what-if” scenarios. Although system dynamics models can be developed to conduct traditional hydraulic/hydrologic surface water or ground water modeling, we believe that their strength lies in their ability to quickly evaluate trends and cause–effect relationships in large-scale hydrological systems; for integrating disparate data; for incorporating output from traditional hydraulic/hydrologic models; and for integration of interdisciplinary data, information and criteria to support better management decisions.« less

Pattern formation in individual-based systems with time-varying parameters

NASA Astrophysics Data System (ADS)

Ashcroft, Peter; Galla, Tobias

2013-12-01

We study the patterns generated in finite-time sweeps across symmetry-breaking bifurcations in individual-based models. Similar to the well-known Kibble-Zurek scenario of defect formation, large-scale patterns are generated when model parameters are varied slowly, whereas fast sweeps produce a large number of small domains. The symmetry breaking is triggered by intrinsic noise, originating from the discrete dynamics at the microlevel. Based on a linear-noise approximation, we calculate the characteristic length scale of these patterns. We demonstrate the applicability of this approach in a simple model of opinion dynamics, a model in evolutionary game theory with a time-dependent fitness structure, and a model of cell differentiation. Our theoretical estimates are confirmed in simulations. In further numerical work, we observe a similar phenomenon when the symmetry-breaking bifurcation is triggered by population growth.

Large-Scale Operations Management Test of Use of the White Amur for Control of Problem Aquatic Plants. Report 2. First Year Poststocking Results. Volume IV. Nitrogen and Phosphorus Dynamics of the Lake Conway Ecosystem: Loading Budgets and a Dynamic Hydrologic Phosphorus Model.

DTIC Science & Technology

1982-08-01

AD-AIA 700 FLORIDA UN1V GAINESVILLE DEPT OF ENVIRONMENTAL ENGIN -ETC F/G 6/6 LARGE-SCALE OPERATIONS MANAGEMENT TEST OF USE OF THE WHITE AMOR--ENL...Conway ecosystem and is part of the Large- Scale Operations Management Test (LSOMT) of the Aquatic Plant Control Research Program (APCRP) at the WES...should be cited as follows: Blancher, E. C., II, and Fellows, C. R. 1982. "Large-Scale Operations Management Test of Use of the White Amur for Control

A Historical Perspective on Dynamics Testing at the Langley Research Center

NASA Technical Reports Server (NTRS)

Horta, Lucas G.; Kvaternik, Raymond G.

2000-01-01

The history of structural dynamics testing research over the past four decades at the Langley Research Center of the National Aeronautics and Space Administration is reviewed. Beginning in the early sixties, Langley investigated several scale model and full-scale spacecraft including the NIMBUS and various concepts for Apollo and Viking landers. Langley engineers pioneered the use of scaled models to study the dynamics of launch vehicles including Saturn I, Saturn V, and Titan III. In the seventies, work emphasized the Space Shuttle and advanced test and data analysis methods. In the eighties, the possibility of delivering large structures to orbit by the Space Shuttle shifted focus towards understanding the interaction of flexible space structures with attitude control systems. Although Langley has maintained a tradition of laboratory-based research, some flight experiments were supported. This review emphasizes work that, in some way, advanced the state of knowledge at the time.

Decentralized Adaptive Neural Output-Feedback DSC for Switched Large-Scale Nonlinear Systems.

PubMed

Lijun Long; Jun Zhao

2017-04-01

In this paper, for a class of switched large-scale uncertain nonlinear systems with unknown control coefficients and unmeasurable states, a switched-dynamic-surface-based decentralized adaptive neural output-feedback control approach is developed. The approach proposed extends the classical dynamic surface control (DSC) technique for nonswitched version to switched version by designing switched first-order filters, which overcomes the problem of multiple "explosion of complexity." Also, a dual common coordinates transformation of all subsystems is exploited to avoid individual coordinate transformations for subsystems that are required when applying the backstepping recursive design scheme. Nussbaum-type functions are utilized to handle the unknown control coefficients, and a switched neural network observer is constructed to estimate the unmeasurable states. Combining with the average dwell time method and backstepping and the DSC technique, decentralized adaptive neural controllers of subsystems are explicitly designed. It is proved that the approach provided can guarantee the semiglobal uniformly ultimately boundedness for all the signals in the closed-loop system under a class of switching signals with average dwell time, and the tracking errors to a small neighborhood of the origin. A two inverted pendulums system is provided to demonstrate the effectiveness of the method proposed.

NEMS (Nanoelectromechanicsl Systems) Networks: A Novel Validation Platform for Controlling Interconnected Dynamical Networks

DTIC Science & Technology

2015-08-01

power   power  grids  to...both  an   ultralow  intrinsic  dissipation   (high  Q)  and  a  low  threshold  onset  of  nonlinear  dynamics.  Q...of   nodes,   we  will   have   in   effect   a   powerful   simulator   for   large-­‐scale   real   world  

Development of Dynamic Flow Field Pressure Probes Suitable for Use in Large Scale Supersonic Wind Tunnels

NASA Technical Reports Server (NTRS)

Porro, A. Robert

2000-01-01

A series of dynamic flow field pressure probes were developed for use in large-scale supersonic wind tunnels at NASA Glenn Research Center. These flow field probes include pitot, static, and five-hole conical pressure probes that are capable of capturing fast acting flow field pressure transients that occur on a millisecond time scale. The pitot and static probes can be used to determine local Mach number time histories during a transient event. The five-hole conical pressure probes are used primarily to determine local flow angularity, but can also determine local Mach number. These probes were designed, developed, and tested at the NASA Glenn Research Center. They were also used in a NASA Glenn 10-by 10-Foot Supersonic Wind Tunnel (SWT) test program where they successfully acquired flow field pressure data in the vicinity of a propulsion system during an engine compressor staff and inlet unstart transient event. Details of the design, development, and subsequent use of these probes are discussed in this report.

Sign: large-scale gene network estimation environment for high performance computing.

PubMed

Tamada, Yoshinori; Shimamura, Teppei; Yamaguchi, Rui; Imoto, Seiya; Nagasaki, Masao; Miyano, Satoru

2011-01-01

Our research group is currently developing software for estimating large-scale gene networks from gene expression data. The software, called SiGN, is specifically designed for the Japanese flagship supercomputer "K computer" which is planned to achieve 10 petaflops in 2012, and other high performance computing environments including Human Genome Center (HGC) supercomputer system. SiGN is a collection of gene network estimation software with three different sub-programs: SiGN-BN, SiGN-SSM and SiGN-L1. In these three programs, five different models are available: static and dynamic nonparametric Bayesian networks, state space models, graphical Gaussian models, and vector autoregressive models. All these models require a huge amount of computational resources for estimating large-scale gene networks and therefore are designed to be able to exploit the speed of 10 petaflops. The software will be available freely for "K computer" and HGC supercomputer system users. The estimated networks can be viewed and analyzed by Cell Illustrator Online and SBiP (Systems Biology integrative Pipeline). The software project web site is available at http://sign.hgc.jp/ .

Regional Simulations of Stratospheric Lofting of Smoke Plumes

NASA Astrophysics Data System (ADS)

Stenchikov, G. L.; Fromm, M.; Robock, A.

2006-12-01

The lifetime and spatial distribution of sooty aerosols from multiple fires that would cause major climate impact were debated in studies of climatic and environmental consequences of a nuclear war in the 1980s. The Kuwait oil fires in 1991 did not show a cumulative effect of multiple smoke plumes on large-scale circulation systems and smoke was mainly dispersed in the middle troposphere. However, recent observations show that smoke from large forest fires can be directly injected into the lower stratosphere by strong pyro-convective storms. Smoke plumes in the upper troposphere can be partially mixed into the lower stratosphere because of the same heating and lofting effect that was simulated in large-scale nuclear winter simulations with interactive aerosols. However nuclear winter simulations were conducted using climate models with grid spacing of more than 100 km, which do not account for the fine-scale dynamic processes. Therefore in this study we conduct fine-scale regional simulations of the aerosol plume using the Regional Atmospheric Modeling System (RAMS) mesoscale model which was modified to account for radiatively interactive tracers. To resolve fine-scale dynamic processes we use horizontal grid spacing of 25 km and 60 vertical layers, and initiate simulations with the NCEP reanalysis fields. We find that dense aerosol layers could be lofted from 1 to a few km per day, but this critically depends on the optical depth of aerosol layer, single scatter albedo, and how fast the plume is being diluted. Kuwaiti plumes from different small-area fires reached only 5-6 km altitude and were probably diffused and diluted in the lower and middle troposphere. A plume of 100 km spatial scale initially developed in the upper troposphere tends to penetrate into the stratosphere. Short-term cloud resolving simulations of such a plume show that aerosol heating intensifies small-scale motions that tend to mix smoke polluted air into the lower stratosphere. Regional simulations allow us to more accurately estimate the rate of lifting and spreading of aerosol clouds. But they do not reveal any dynamic processes that could prevent heating and lofting of absorbing aerosols.

Universal statistics of vortex tangles in three-dimensional random waves

NASA Astrophysics Data System (ADS)

Taylor, Alexander J.

2018-02-01

The tangled nodal lines (wave vortices) in random, three-dimensional wavefields are studied as an exemplar of a fractal loop soup. Their statistics are a three-dimensional counterpart to the characteristic random behaviour of nodal domains in quantum chaos, but in three dimensions the filaments can wind around one another to give distinctly different large scale behaviours. By tracing numerically the structure of the vortices, their conformations are shown to follow recent analytical predictions for random vortex tangles with periodic boundaries, where the local disorder of the model ‘averages out’ to produce large scale power law scaling relations whose universality classes do not depend on the local physics. These results explain previous numerical measurements in terms of an explicit effect of the periodic boundaries, where the statistics of the vortices are strongly affected by the large scale connectedness of the system even at arbitrarily high energies. The statistics are investigated primarily for static (monochromatic) wavefields, but the analytical results are further shown to directly describe the reconnection statistics of vortices evolving in certain dynamic systems, or occurring during random perturbations of the static configuration.

Dynamics of coupled human-landscape systems

NASA Astrophysics Data System (ADS)

Werner, B. T.; McNamara, D. E.

2007-11-01

A preliminary dynamical analysis of landscapes and humans as hierarchical complex systems suggests that strong coupling between the two that spreads to become regionally or globally pervasive should be focused at multi-year to decadal time scales. At these scales, landscape dynamics is dominated by water, sediment and biological routing mediated by fluvial, oceanic, atmospheric processes and human dynamics is dominated by simplifying, profit-maximizing market forces and political action based on projection of economic effect. Also at these scales, landscapes impact humans through patterns of natural disasters and trends such as sea level rise; humans impact landscapes by the effect of economic activity and changes meant to mitigate natural disasters and longer term trends. Based on this analysis, human-landscape coupled systems can be modeled using heterogeneous agents employing prediction models to determine actions to represent the nonlinear behavior of economic and political systems and rule-based routing algorithms to represent landscape processes. A cellular model for the development of New Orleans illustrates this approach, with routing algorithms for river and hurricane-storm surge determining flood extent, five markets (home, labor, hotel, tourism and port services) connecting seven types of economic agents (home buyers/laborers, home developers, hotel owners/ employers, hotel developers, tourists, port services developer and port services owners/employers), building of levees or a river spillway by political agents and damage to homes, hotels or port services within cells determined by the passage or depth of flood waters. The model reproduces historical aspects of New Orleans economic development and levee construction and the filtering of frequent small-scale floods at the expense of large disasters.

Servo-hydraulic actuator in controllable canonical form: Identification and experimental validation

NASA Astrophysics Data System (ADS)

Maghareh, Amin; Silva, Christian E.; Dyke, Shirley J.

2018-02-01

Hydraulic actuators have been widely used to experimentally examine structural behavior at multiple scales. Real-time hybrid simulation (RTHS) is one innovative testing method that largely relies on such servo-hydraulic actuators. In RTHS, interface conditions must be enforced in real time, and controllers are often used to achieve tracking of the desired displacements. Thus, neglecting the dynamics of hydraulic transfer system may result either in system instability or sub-optimal performance. Herein, we propose a nonlinear dynamical model for a servo-hydraulic actuator (a.k.a. hydraulic transfer system) coupled with a nonlinear physical specimen. The nonlinear dynamical model is transformed into controllable canonical form for further tracking control design purposes. Through a number of experiments, the controllable canonical model is validated.

Electrokinetic and hydrodynamic properties of charged-particles systems. From small electrolyte ions to large colloids

NASA Astrophysics Data System (ADS)

Nägele, G.; Heinen, M.; Banchio, A. J.; Contreras-Aburto, C.

2013-11-01

Dynamic processes in dispersions of charged spherical particles are of importance both in fundamental science, and in technical and bio-medical applications. There exists a large variety of charged-particles systems, ranging from nanometer-sized electrolyte ions to micron-sized charge-stabilized colloids. We review recent advances in theoretical methods for the calculation of linear transport coefficients in concentrated particulate systems, with the focus on hydrodynamic interactions and electrokinetic effects. Considered transport properties are the dispersion viscosity, self- and collective diffusion coefficients, sedimentation coefficients, and electrophoretic mobilities and conductivities of ionic particle species in an external electric field. Advances by our group are also discussed, including a novel mode-coupling-theory method for conduction-diffusion and viscoelastic properties of strong electrolyte solutions. Furthermore, results are presented for dispersions of solvent-permeable particles, and particles with non-zero hydrodynamic surface slip. The concentration-dependent swelling of ionic microgels is discussed, as well as a far-reaching dynamic scaling behavior relating colloidal long- to short-time dynamics.

High-Performance Monitoring Architecture for Large-Scale Distributed Systems Using Event Filtering

NASA Technical Reports Server (NTRS)

Maly, K.

1998-01-01

Monitoring is an essential process to observe and improve the reliability and the performance of large-scale distributed (LSD) systems. In an LSD environment, a large number of events is generated by the system components during its execution or interaction with external objects (e.g. users or processes). Monitoring such events is necessary for observing the run-time behavior of LSD systems and providing status information required for debugging, tuning and managing such applications. However, correlated events are generated concurrently and could be distributed in various locations in the applications environment which complicates the management decisions process and thereby makes monitoring LSD systems an intricate task. We propose a scalable high-performance monitoring architecture for LSD systems to detect and classify interesting local and global events and disseminate the monitoring information to the corresponding end- points management applications such as debugging and reactive control tools to improve the application performance and reliability. A large volume of events may be generated due to the extensive demands of the monitoring applications and the high interaction of LSD systems. The monitoring architecture employs a high-performance event filtering mechanism to efficiently process the large volume of event traffic generated by LSD systems and minimize the intrusiveness of the monitoring process by reducing the event traffic flow in the system and distributing the monitoring computation. Our architecture also supports dynamic and flexible reconfiguration of the monitoring mechanism via its Instrumentation and subscription components. As a case study, we show how our monitoring architecture can be utilized to improve the reliability and the performance of the Interactive Remote Instruction (IRI) system which is a large-scale distributed system for collaborative distance learning. The filtering mechanism represents an Intrinsic component integrated with the monitoring architecture to reduce the volume of event traffic flow in the system, and thereby reduce the intrusiveness of the monitoring process. We are developing an event filtering architecture to efficiently process the large volume of event traffic generated by LSD systems (such as distributed interactive applications). This filtering architecture is used to monitor collaborative distance learning application for obtaining debugging and feedback information. Our architecture supports the dynamic (re)configuration and optimization of event filters in large-scale distributed systems. Our work represents a major contribution by (1) survey and evaluating existing event filtering mechanisms In supporting monitoring LSD systems and (2) devising an integrated scalable high- performance architecture of event filtering that spans several kev application domains, presenting techniques to improve the functionality, performance and scalability. This paper describes the primary characteristics and challenges of developing high-performance event filtering for monitoring LSD systems. We survey existing event filtering mechanisms and explain key characteristics for each technique. In addition, we discuss limitations with existing event filtering mechanisms and outline how our architecture will improve key aspects of event filtering.

Continuous data assimilation for downscaling large-footprint soil moisture retrievals

NASA Astrophysics Data System (ADS)

Altaf, Muhammad U.; Jana, Raghavendra B.; Hoteit, Ibrahim; McCabe, Matthew F.

2016-10-01

Soil moisture is a key component of the hydrologic cycle, influencing processes leading to runoff generation, infiltration and groundwater recharge, evaporation and transpiration. Generally, the measurement scale for soil moisture is found to be different from the modeling scales for these processes. Reducing this mismatch between observation and model scales in necessary for improved hydrological modeling. An innovative approach to downscaling coarse resolution soil moisture data by combining continuous data assimilation and physically based modeling is presented. In this approach, we exploit the features of Continuous Data Assimilation (CDA) which was initially designed for general dissipative dynamical systems and later tested numerically on the incompressible Navier-Stokes equation, and the Benard equation. A nudging term, estimated as the misfit between interpolants of the assimilated coarse grid measurements and the fine grid model solution, is added to the model equations to constrain the model's large scale variability by available measurements. Soil moisture fields generated at a fine resolution by a physically-based vadose zone model (HYDRUS) are subjected to data assimilation conditioned upon coarse resolution observations. This enables nudging of the model outputs towards values that honor the coarse resolution dynamics while still being generated at the fine scale. Results show that the approach is feasible to generate fine scale soil moisture fields across large extents, based on coarse scale observations. Application of this approach is likely in generating fine and intermediate resolution soil moisture fields conditioned on the radiometerbased, coarse resolution products from remote sensing satellites.

Cytology of DNA Replication Reveals Dynamic Plasticity of Large-Scale Chromatin Fibers.

PubMed

Deng, Xiang; Zhironkina, Oxana A; Cherepanynets, Varvara D; Strelkova, Olga S; Kireev, Igor I; Belmont, Andrew S

2016-09-26

In higher eukaryotic interphase nuclei, the 100- to >1,000-fold linear compaction of chromatin is difficult to reconcile with its function as a template for transcription, replication, and repair. It is challenging to imagine how DNA and RNA polymerases with their associated molecular machinery would move along the DNA template without transient decondensation of observed large-scale chromatin "chromonema" fibers [1]. Transcription or "replication factory" models [2], in which polymerases remain fixed while DNA is reeled through, are similarly difficult to conceptualize without transient decondensation of these chromonema fibers. Here, we show how a dynamic plasticity of chromatin folding within large-scale chromatin fibers allows DNA replication to take place without significant changes in the global large-scale chromatin compaction or shape of these large-scale chromatin fibers. Time-lapse imaging of lac-operator-tagged chromosome regions shows no major change in the overall compaction of these chromosome regions during their DNA replication. Improved pulse-chase labeling of endogenous interphase chromosomes yields a model in which the global compaction and shape of large-Mbp chromatin domains remains largely invariant during DNA replication, with DNA within these domains undergoing significant movements and redistribution as they move into and then out of adjacent replication foci. In contrast to hierarchical folding models, this dynamic plasticity of large-scale chromatin organization explains how localized changes in DNA topology allow DNA replication to take place without an accompanying global unfolding of large-scale chromatin fibers while suggesting a possible mechanism for maintaining epigenetic programming of large-scale chromatin domains throughout DNA replication. Copyright © 2016 Elsevier Ltd. All rights reserved.

Making automated computer program documentation a feature of total system design

NASA Technical Reports Server (NTRS)

Wolf, A. W.

1970-01-01

It is pointed out that in large-scale computer software systems, program documents are too often fraught with errors, out of date, poorly written, and sometimes nonexistent in whole or in part. The means are described by which many of these typical system documentation problems were overcome in a large and dynamic software project. A systems approach was employed which encompassed such items as: (1) configuration management; (2) standards and conventions; (3) collection of program information into central data banks; (4) interaction among executive, compiler, central data banks, and configuration management; and (5) automatic documentation. A complete description of the overall system is given.

Supportive-Expressive Dynamic Psychotherapy in the Community Mental Health System: A Pilot Effectiveness Trial for the Treatment of Depression

PubMed Central

Connolly Gibbons, Mary Beth; Thompson, Sarah M.; Scott, Kelli; Schauble, Lindsay A.; Mooney, Tessa; Thompson, Donald; Green, Patricia; MacArthur, Mary Jo; Crits-Christoph, Paul

2013-01-01

The goal of the current article is to present the results of a randomized pilot investigation of a brief dynamic psychotherapy compared with treatment-as-usual (TAU) in the treatment of moderate-to-severe depression in the community mental health system. Forty patients seeking services for moderate-to-severe depression in the community mental health system were randomized to 12 weeks of psychotherapy, with either a community therapist trained in brief dynamic psychotherapy or a TAU therapist. Results indicated that blind judges could discriminate the dynamic sessions from the TAU sessions on adherence to dynamic interventions. The results indicate moderate-to-large effect sizes in favor of the dynamic psychotherapy over the TAU therapy in the treatment of depression. The Behavior and Symptom Identification Scale-24 showed that 50% of patients treated with dynamic therapy moved into a normative range compared with only 29% of patients treated with TAU. PMID:22962971

Large-scale fabrication of micro-lens array by novel end-fly-cutting-servo diamond machining.

PubMed

Zhu, Zhiwei; To, Suet; Zhang, Shaojian

2015-08-10

Fast/slow tool servo (FTS/STS) diamond turning is a very promising technique for the generation of micro-lens array (MLA). However, it is still a challenge to process MLA in large scale due to certain inherent limitations of this technique. In the present study, a novel ultra-precision diamond cutting method, as the end-fly-cutting-servo (EFCS) system, is adopted and investigated for large-scale generation of MLA. After a detailed discussion of the characteristic advantages for processing MLA, the optimal toolpath generation strategy for the EFCS is developed with consideration of the geometry and installation pose of the diamond tool. A typical aspheric MLA over a large area is experimentally fabricated, and the resulting form accuracy, surface micro-topography and machining efficiency are critically investigated. The result indicates that the MLA with homogeneous quality over the whole area is obtained. Besides, high machining efficiency, extremely small volume of control points for the toolpath, and optimal usage of system dynamics of the machine tool during the whole cutting can be simultaneously achieved.

Stability analysis and backward whirl investigation of cracked rotors with time-varying stiffness

NASA Astrophysics Data System (ADS)

AL-Shudeifat, Mohammad A.

2015-07-01

The dynamic stability of dynamical systems with time-periodic stiffness is addressed here. Cracked rotor systems with time-periodic stiffness are well-known examples of such systems. Time-varying area moments of inertia at the cracked element cross-section of a cracked rotor have been used to formulate the time-periodic finite element stiffness matrix. The semi-infinite coefficient matrix obtained by applying the harmonic balance (HB) solution to the finite element (FE) equations of motion is employed here to study the dynamic stability of the system. Consequently, the sign of the determinant of a scaled version of a sub-matrix of this semi-infinite coefficient matrix at a finite number of harmonics in the HB solution is found to be sufficient for identifying the major unstable zones of the system in the parameter plane. Specifically, it is found that the negative determinant always corresponds to unstable zones in all of the systems considered. This approach is applied to a parametrically excited Mathieu's equation, a two degree-of-freedom linear time-periodic dynamical system, a cracked Jeffcott rotor and a finite element model of the cracked rotor system. Compared to the corresponding results obtained by Floquet's theory, the sign of the determinant of the scaled sub-matrix is found to be an efficient tool for identifying the major unstable zones of the linear time-periodic parametrically excited systems, especially large-scale FE systems. Moreover, it is found that the unstable zones for a FE cracked rotor with an open transverse crack model only appear at the backward whirl. The theoretical and experimental results have been found to agree well for verifying that the open crack model excites the backward whirl amplitudes at the critical backward whirling rotational speeds.

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

Linking Assessment and School Success.

ERIC Educational Resources Information Center

Raham, Helen

1999-01-01

School systems have recently experienced a dramatic shift toward the use of large-scale assessment to improve school performance. Discusses the ways in which external assessment may benefit education, the need for multiple measures of various dimensions of school success, and guidelines for using assessment to create a dynamic cycle of continuous…

Hypertext: Behind the Hype. ERIC Digest.

ERIC Educational Resources Information Center

Bevilacqua, Ann F.

This digest begins by defining the concept of hypertext and describing the two types of hypertext--static and dynamic. Three prototype applications are then discussed: (1) Intermedia, a large-scale multimedia system at Brown University; (2) the Perseus Project at Harvard University, which is developing interactive courseware on classical Greek…

Numerical study of anomalous dynamic scaling behaviour of (1+1)-dimensional Das Sarma-Tamborenea model

NASA Astrophysics Data System (ADS)

Xun, Zhi-Peng; Tang, Gang; Han, Kui; Hao, Da-Peng; Xia, Hui; Zhou, Wei; Yang, Xi-Quan; Wen, Rong-Ji; Chen, Yu-Ling

2010-07-01

In order to discuss the finite-size effect and the anomalous dynamic scaling behaviour of Das Sarma-Tamborenea growth model, the (1+1)-dimensional Das Sarma-Tamborenea model is simulated on a large length scale by using the kinetic Monte-Carlo method. In the simulation, noise reduction technique is used in order to eliminate the crossover effect. Our results show that due to the existence of the finite-size effect, the effective global roughness exponent of the (1+1)-dimensional Das Sarma-Tamborenea model systematically decreases with system size L increasing when L > 256. This finding proves the conjecture by Aarao Reis[Aarao Reis F D A 2004 Phys. Rev. E 70 031607]. In addition, our simulation results also show that the Das Sarma-Tamborenea model in 1+1 dimensions indeed exhibits intrinsic anomalous scaling behaviour.

Solving large-scale dynamic systems using band Lanczos method in Rockwell NASTRAN on CRAY X-MP

NASA Technical Reports Server (NTRS)

Gupta, V. K.; Zillmer, S. D.; Allison, R. E.

1986-01-01

The improved cost effectiveness using better models, more accurate and faster algorithms and large scale computing offers more representative dynamic analyses. The band Lanczos eigen-solution method was implemented in Rockwell's version of 1984 COSMIC-released NASTRAN finite element structural analysis computer program to effectively solve for structural vibration modes including those of large complex systems exceeding 10,000 degrees of freedom. The Lanczos vectors were re-orthogonalized locally using the Lanczos Method and globally using the modified Gram-Schmidt method for sweeping rigid-body modes and previously generated modes and Lanczos vectors. The truncated band matrix was solved for vibration frequencies and mode shapes using Givens rotations. Numerical examples are included to demonstrate the cost effectiveness and accuracy of the method as implemented in ROCKWELL NASTRAN. The CRAY version is based on RPK's COSMIC/NASTRAN. The band Lanczos method was more reliable and accurate and converged faster than the single vector Lanczos Method. The band Lanczos method was comparable to the subspace iteration method which was a block version of the inverse power method. However, the subspace matrix tended to be fully populated in the case of subspace iteration and not as sparse as a band matrix.

Effect of turbulence modelling to predict combustion and nanoparticle production in the flame assisted spray dryer based on computational fluid dynamics

NASA Astrophysics Data System (ADS)

Septiani, Eka Lutfi; Widiyastuti, W.; Winardi, Sugeng; Machmudah, Siti; Nurtono, Tantular; Kusdianto

2016-02-01

Flame assisted spray dryer are widely uses for large-scale production of nanoparticles because of it ability. Numerical approach is needed to predict combustion and particles production in scale up and optimization process due to difficulty in experimental observation and relatively high cost. Computational Fluid Dynamics (CFD) can provide the momentum, energy and mass transfer, so that CFD more efficient than experiment due to time and cost. Here, two turbulence models, k-ɛ and Large Eddy Simulation were compared and applied in flame assisted spray dryer system. The energy sources for particle drying was obtained from combustion between LPG as fuel and air as oxidizer and carrier gas that modelled by non-premixed combustion in simulation. Silica particles was used to particle modelling from sol silica solution precursor. From the several comparison result, i.e. flame contour, temperature distribution and particle size distribution, Large Eddy Simulation turbulence model can provide the closest data to the experimental result.

3D ion-scale dynamics of BBFs and their associated emissions in Earth's magnetotail using 3D hybrid simulations and MMS multi-spacecraft observations

NASA Astrophysics Data System (ADS)

Breuillard, H.; Aunai, N.; Le Contel, O.; Catapano, F.; Alexandrova, A.; Retino, A.; Cozzani, G.; Gershman, D. J.; Giles, B. L.; Khotyaintsev, Y. V.; Lindqvist, P. A.; Ergun, R.; Strangeway, R. J.; Russell, C. T.; Magnes, W.; Plaschke, F.; Nakamura, R.; Fuselier, S. A.; Turner, D. L.; Schwartz, S. J.; Torbert, R. B.; Burch, J.

2017-12-01

Transient and localized jets of hot plasma, also known as Bursty Bulk Flows (BBFs), play a crucial role in Earth's magnetotail dynamics because the energy input from the solar wind is partly dissipated in their vicinity, notably in their embedded dipolarization front (DF). This dissipation is in the form of strong low-frequency waves that can heat and accelerate energetic particles up to the high-latitude plasma sheet. The ion-scale dynamics of BBFs have been revealed by the Cluster and THEMIS multi-spacecraft missions. However, the dynamics of BBF propagation in the magnetotail are still under debate due to instrumental limitations and spacecraft separation distances, as well as simulation limitations. The NASA/MMS fleet, which features unprecedented high time resolution instruments and four spacecraft separated by kinetic-scale distances, has also shown recently that the DF normal dynamics and its associated emissions are below the ion gyroradius scale in this region. Large variations in the dawn-dusk direction were also observed. However, most of large-scale simulations are using the MHD approach and are assumed 2D in the XZ plane. Thus, in this study we take advantage of both multi-spacecraft observations by MMS and large-scale 3D hybrid simulations to investigate the 3D dynamics of BBFs and their associated emissions at ion-scale in Earth's magnetotail, and their impact on particle heating and acceleration.

Wavelet Monte Carlo dynamics: A new algorithm for simulating the hydrodynamics of interacting Brownian particles

NASA Astrophysics Data System (ADS)

Dyer, Oliver T.; Ball, Robin C.

2017-03-01

We develop a new algorithm for the Brownian dynamics of soft matter systems that evolves time by spatially correlated Monte Carlo moves. The algorithm uses vector wavelets as its basic moves and produces hydrodynamics in the low Reynolds number regime propagated according to the Oseen tensor. When small moves are removed, the correlations closely approximate the Rotne-Prager tensor, itself widely used to correct for deficiencies in Oseen. We also include plane wave moves to provide the longest range correlations, which we detail for both infinite and periodic systems. The computational cost of the algorithm scales competitively with the number of particles simulated, N, scaling as N In N in homogeneous systems and as N in dilute systems. In comparisons to established lattice Boltzmann and Brownian dynamics algorithms, the wavelet method was found to be only a factor of order 1 times more expensive than the cheaper lattice Boltzmann algorithm in marginally semi-dilute simulations, while it is significantly faster than both algorithms at large N in dilute simulations. We also validate the algorithm by checking that it reproduces the correct dynamics and equilibrium properties of simple single polymer systems, as well as verifying the effect of periodicity on the mobility tensor.

Morphological communication: exploiting coupled dynamics in a complex mechanical structure to achieve locomotion

PubMed Central

Rieffel, John A.; Valero-Cuevas, Francisco J.; Lipson, Hod

2010-01-01

Traditional engineering approaches strive to avoid, or actively suppress, nonlinear dynamic coupling among components. Biological systems, in contrast, are often rife with these dynamics. Could there be, in some cases, a benefit to high degrees of dynamical coupling? Here we present a distributed robotic control scheme inspired by the biological phenomenon of tensegrity-based mechanotransduction. This emergence of morphology-as-information-conduit or ‘morphological communication’, enabled by time-sensitive spiking neural networks, presents a new paradigm for the decentralized control of large, coupled, modular systems. These results significantly bolster, both in magnitude and in form, the idea of morphological computation in robotic control. Furthermore, they lend further credence to ideas of embodied anatomical computation in biological systems, on scales ranging from cellular structures up to the tendinous networks of the human hand. PMID:19776146

Neural Computations in a Dynamical System with Multiple Time Scales.

PubMed

Mi, Yuanyuan; Lin, Xiaohan; Wu, Si

2016-01-01

Neural systems display rich short-term dynamics at various levels, e.g., spike-frequency adaptation (SFA) at the single-neuron level, and short-term facilitation (STF) and depression (STD) at the synapse level. These dynamical features typically cover a broad range of time scales and exhibit large diversity in different brain regions. It remains unclear what is the computational benefit for the brain to have such variability in short-term dynamics. In this study, we propose that the brain can exploit such dynamical features to implement multiple seemingly contradictory computations in a single neural circuit. To demonstrate this idea, we use continuous attractor neural network (CANN) as a working model and include STF, SFA and STD with increasing time constants in its dynamics. Three computational tasks are considered, which are persistent activity, adaptation, and anticipative tracking. These tasks require conflicting neural mechanisms, and hence cannot be implemented by a single dynamical feature or any combination with similar time constants. However, with properly coordinated STF, SFA and STD, we show that the network is able to implement the three computational tasks concurrently. We hope this study will shed light on the understanding of how the brain orchestrates its rich dynamics at various levels to realize diverse cognitive functions.

Variational Assimilation of Global Microwave Rainfall Retrievals: Physical and Dynamical Impact on GEOS Analyses and Forecasts

NASA Technical Reports Server (NTRS)

Lin, Xin; Zhang, Sara Q.; Hou, Arthur Y.

2006-01-01

Global microwave rainfall retrievals from a 5-satellite constellation, including TMI from TRMM, SSWI from DMSP F13, F14 and F15, and AMSR-E from EOS-AQUA, are assimilated into the NASA Goddard Earth Observing System (GEOS) Data Assimilation System (DAS) using a 1-D variational continuous assimilation (VCA) algorithm. The physical and dynamical impact of rainfall assimilation on GEOS analyses and forecasts is examined at various temporal and spatial scales. This study demonstrates that the 1-D VCA algorithm, which was originally developed and evaluated for rainfall assimilations over tropical oceans, can effectively assimilate satellite microwave rainfall retrievals and improve GEOS analyses over both the Tropics and the extratropics where the atmospheric processes are dominated by different large-scale dynamics and moist physics, and also over the land, where rainfall estimates from passive microwave radiometers are believed to be less accurate. Results show that rainfall assimilation renders the GEOS analysis physically and dynamically more consistent with the observed precipitation at the monthly-mean and 6-hour time scales. Over regions where the model precipitation tends to misbehave in distinctly different rainy regimes, the 1-D VCA algorithm, by compensating for errors in the model s moist time-tendency in a 6-h analysis window, is able to bring the rainfall analysis closer to the observed. The radiation and cloud fields also tend to be in better agreement with independent satellite observations in the rainfall-assimilation m especially over regions where rainfall analyses indicate large improvements. Assimilation experiments with and without rainfall data for a midlatitude frontal system clearly indicates that the GEOS analysis is improved through changes in the thermodynamic and dynamic fields that respond to the rainfall assimilation. The synoptic structures of temperature, moisture, winds, divergence, and vertical motion, as well as vorticity are more realistically captured across the front. Short-term forecasts using initial conditions assimilated with rainfall data also show slight improvements. 1

Steps Towards Understanding Large-scale Deformation of Gas Hydrate-bearing Sediments

NASA Astrophysics Data System (ADS)

Gupta, S.; Deusner, C.; Haeckel, M.; Kossel, E.

2016-12-01

Marine sediments bearing gas hydrates are typically characterized by heterogeneity in the gas hydrate distribution and anisotropy in the sediment-gas hydrate fabric properties. Gas hydrates also contribute to the strength and stiffness of the marine sediment, and any disturbance in the thermodynamic stability of the gas hydrates is likely to affect the geomechanical stability of the sediment. Understanding mechanisms and triggers of large-strain deformation and failure of marine gas hydrate-bearing sediments is an area of extensive research, particularly in the context of marine slope-stability and industrial gas production. The ultimate objective is to predict severe deformation events such as regional-scale slope failure or excessive sand production by using numerical simulation tools. The development of such tools essentially requires a careful analysis of thermo-hydro-chemo-mechanical behavior of gas hydrate-bearing sediments at lab-scale, and its stepwise integration into reservoir-scale simulators through definition of effective variables, use of suitable constitutive relations, and application of scaling laws. One of the focus areas of our research is to understand the bulk coupled behavior of marine gas hydrate systems with contributions from micro-scale characteristics, transport-reaction dynamics, and structural heterogeneity through experimental flow-through studies using high-pressure triaxial test systems and advanced tomographical tools (CT, ERT, MRI). We combine these studies to develop mathematical model and numerical simulation tools which could be used to predict the coupled hydro-geomechanical behavior of marine gas hydrate reservoirs in a large-strain framework. Here we will present some of our recent results from closely co-ordinated experimental and numerical simulation studies with an objective to capture the large-deformation behavior relevant to different gas production scenarios. We will also report on a variety of mechanically relevant test scenarios focusing on effects of dynamic changes in gas hydrate saturation, highly uneven gas hydrate distributions, focused fluid migration and gas hydrate production through depressurization and CO2 injection.

Scale criticality in estimating ecosystem carbon dynamics

USGS Publications Warehouse

Zhao, Shuqing; Liu, Shuguang

2014-01-01

Scaling is central to ecology and Earth system sciences. However, the importance of scale (i.e. resolution and extent) for understanding carbon dynamics across scales is poorly understood and quantified. We simulated carbon dynamics under a wide range of combinations of resolution (nine spatial resolutions of 250 m, 500 m, 1 km, 2 km, 5 km, 10 km, 20 km, 50 km, and 100 km) and extent (57 geospatial extents ranging from 108 to 1 247 034 km2) in the southeastern United States to explore the existence of scale dependence of the simulated regional carbon balance. Results clearly show the existence of a critical threshold resolution for estimating carbon sequestration within a given extent and an error limit. Furthermore, an invariant power law scaling relationship was found between the critical resolution and the spatial extent as the critical resolution is proportional to An (n is a constant, and A is the extent). Scale criticality and the power law relationship might be driven by the power law probability distributions of land surface and ecological quantities including disturbances at landscape to regional scales. The current overwhelming practices without considering scale criticality might have largely contributed to difficulties in balancing carbon budgets at regional and global scales.

Space Weather Research at the National Science Foundation

NASA Astrophysics Data System (ADS)

Moretto, T.

2015-12-01

There is growing recognition that the space environment can have substantial, deleterious, impacts on society. Consequently, research enabling specification and forecasting of hazardous space effects has become of great importance and urgency. This research requires studying the entire Sun-Earth system to understand the coupling of regions all the way from the source of disturbances in the solar atmosphere to the Earth's upper atmosphere. The traditional, region-based structure of research programs in Solar and Space physics is ill suited to fully support the change in research directions that the problem of space weather dictates. On the observational side, dense, distributed networks of observations are required to capture the full large-scale dynamics of the space environment. However, the cost of implementing these is typically prohibitive, especially for measurements in space. Thus, by necessity, the implementation of such new capabilities needs to build on creative and unconventional solutions. A particularly powerful idea is the utilization of new developments in data engineering and informatics research (big data). These new technologies make it possible to build systems that can collect and process huge amounts of noisy and inaccurate data and extract from them useful information. The shift in emphasis towards system level science for geospace also necessitates the development of large-scale and multi-scale models. The development of large-scale models capable of capturing the global dynamics of the Earth's space environment requires investment in research team efforts that go beyond what can typically be funded under the traditional grants programs. This calls for effective interdisciplinary collaboration and efficient leveraging of resources both nationally and internationally. This presentation will provide an overview of current and planned initiatives, programs, and activities at the National Science Foundation pertaining to space weathe research.

Probing aerosol indirect effect on deep convection using idealized cloud-resolving simulations with parameterized large-scale dynamics.

NASA Astrophysics Data System (ADS)

Anber, U.; Wang, S.; Gentine, P.; Jensen, M. P.

2017-12-01

A framework is introduced to investigate the indirect impact of aerosol loading on tropical deep convection using 3-dimentional idealized cloud-system resolving simulations with coupled large-scale circulation. The large scale dynamics is parameterized using a spectral weak temperature gradient approximation that utilizes the dominant balance in the tropics between adiabatic cooling and diabatic heating. Aerosol loading effect is examined by varying the number concentration of nuclei (CCN) to form cloud droplets in the bulk microphysics scheme over a wide range from 30 to 5000 without including any radiative effect as the radiative cooling is prescribed at a constant rate, to isolate the microphysical effect. Increasing aerosol number concentration causes mean precipitation to decrease monotonically, despite the increase in cloud condensates. Such reduction in precipitation efficiency is attributed to reduction in the surface enthalpy fluxes, and not to the divergent circulation, as the gross moist stability remains unchanged. We drive a simple scaling argument based on the moist static energy budget, that enables a direct estimation of changes in precipitation given known changes in surfaces enthalpy fluxes and the constant gross moist stability. The impact on cloud hydrometers and microphysical properties is also examined and is consistent with the macro-physical picture.

Micron-scale coherence in interphase chromatin dynamics

PubMed Central

Zidovska, Alexandra; Weitz, David A.; Mitchison, Timothy J.

2013-01-01

Chromatin structure and dynamics control all aspects of DNA biology yet are poorly understood, especially at large length scales. We developed an approach, displacement correlation spectroscopy based on time-resolved image correlation analysis, to map chromatin dynamics simultaneously across the whole nucleus in cultured human cells. This method revealed that chromatin movement was coherent across large regions (4–5 µm) for several seconds. Regions of coherent motion extended beyond the boundaries of single-chromosome territories, suggesting elastic coupling of motion over length scales much larger than those of genes. These large-scale, coupled motions were ATP dependent and unidirectional for several seconds, perhaps accounting for ATP-dependent directed movement of single genes. Perturbation of major nuclear ATPases such as DNA polymerase, RNA polymerase II, and topoisomerase II eliminated micron-scale coherence, while causing rapid, local movement to increase; i.e., local motions accelerated but became uncoupled from their neighbors. We observe similar trends in chromatin dynamics upon inducing a direct DNA damage; thus we hypothesize that this may be due to DNA damage responses that physically relax chromatin and block long-distance communication of forces. PMID:24019504

Obtaining Arbitrary Prescribed Mean Field Dynamics for Recurrently Coupled Networks of Type-I Spiking Neurons with Analytically Determined Weights

PubMed Central

Nicola, Wilten; Tripp, Bryan; Scott, Matthew

2016-01-01

A fundamental question in computational neuroscience is how to connect a network of spiking neurons to produce desired macroscopic or mean field dynamics. One possible approach is through the Neural Engineering Framework (NEF). The NEF approach requires quantities called decoders which are solved through an optimization problem requiring large matrix inversion. Here, we show how a decoder can be obtained analytically for type I and certain type II firing rates as a function of the heterogeneity of its associated neuron. These decoders generate approximants for functions that converge to the desired function in mean-squared error like 1/N, where N is the number of neurons in the network. We refer to these decoders as scale-invariant decoders due to their structure. These decoders generate weights for a network of neurons through the NEF formula for weights. These weights force the spiking network to have arbitrary and prescribed mean field dynamics. The weights generated with scale-invariant decoders all lie on low dimensional hypersurfaces asymptotically. We demonstrate the applicability of these scale-invariant decoders and weight surfaces by constructing networks of spiking theta neurons that replicate the dynamics of various well known dynamical systems such as the neural integrator, Van der Pol system and the Lorenz system. As these decoders are analytically determined and non-unique, the weights are also analytically determined and non-unique. We discuss the implications for measured weights of neuronal networks. PMID:26973503

Obtaining Arbitrary Prescribed Mean Field Dynamics for Recurrently Coupled Networks of Type-I Spiking Neurons with Analytically Determined Weights.

PubMed

Nicola, Wilten; Tripp, Bryan; Scott, Matthew

2016-01-01

A fundamental question in computational neuroscience is how to connect a network of spiking neurons to produce desired macroscopic or mean field dynamics. One possible approach is through the Neural Engineering Framework (NEF). The NEF approach requires quantities called decoders which are solved through an optimization problem requiring large matrix inversion. Here, we show how a decoder can be obtained analytically for type I and certain type II firing rates as a function of the heterogeneity of its associated neuron. These decoders generate approximants for functions that converge to the desired function in mean-squared error like 1/N, where N is the number of neurons in the network. We refer to these decoders as scale-invariant decoders due to their structure. These decoders generate weights for a network of neurons through the NEF formula for weights. These weights force the spiking network to have arbitrary and prescribed mean field dynamics. The weights generated with scale-invariant decoders all lie on low dimensional hypersurfaces asymptotically. We demonstrate the applicability of these scale-invariant decoders and weight surfaces by constructing networks of spiking theta neurons that replicate the dynamics of various well known dynamical systems such as the neural integrator, Van der Pol system and the Lorenz system. As these decoders are analytically determined and non-unique, the weights are also analytically determined and non-unique. We discuss the implications for measured weights of neuronal networks.

Perspectives on the role of mobility, behavior, and time scales in the spread of diseases.

PubMed

Castillo-Chavez, Carlos; Bichara, Derdei; Morin, Benjamin R

2016-12-20

The dynamics, control, and evolution of communicable and vector-borne diseases are intimately connected to the joint dynamics of epidemiological, behavioral, and mobility processes that operate across multiple spatial, temporal, and organizational scales. The identification of a theoretical explanatory framework that accounts for the pattern regularity exhibited by a large number of host-parasite systems, including those sustained by host-vector epidemiological dynamics, is but one of the challenges facing the coevolving fields of computational, evolutionary, and theoretical epidemiology. Host-parasite epidemiological patterns, including epidemic outbreaks and endemic recurrent dynamics, are characteristic to well-identified regions of the world; the result of processes and constraints such as strain competition, host and vector mobility, and population structure operating over multiple scales in response to recurrent disturbances (like El Niño) and climatological and environmental perturbations over thousands of years. It is therefore important to identify and quantify the processes responsible for observed epidemiological macroscopic patterns: the result of individual interactions in changing social and ecological landscapes. In this perspective, we touch on some of the issues calling for the identification of an encompassing theoretical explanatory framework by identifying some of the limitations of existing theory, in the context of particular epidemiological systems. Fostering the reenergizing of research that aims at disentangling the role of epidemiological and socioeconomic forces on disease dynamics, better understood as complex adaptive systems, is a key aim of this perspective.

SPATIAL SCALE OF AUTOCORRELATION IN WISCONSIN FROG AND TOAD SURVEY DATA

EPA Science Inventory

The degree to which local population dynamics are correlated with nearby sites has important implications for metapopulation dynamics and landscape management. Spatially extensive monitoring data can be used to evaluate large-scale population dynamic processes. Our goals in this ...

Dynamic system simulation of small satellite projects

NASA Astrophysics Data System (ADS)

Raif, Matthias; Walter, Ulrich; Bouwmeester, Jasper

2010-11-01

A prerequisite to accomplish a system simulation is to have a system model holding all necessary project information in a centralized repository that can be accessed and edited by all parties involved. At the Institute of Astronautics of the Technische Universitaet Muenchen a modular approach for modeling and dynamic simulation of satellite systems has been developed called dynamic system simulation (DySyS). DySyS is based on the platform independent description language SysML to model a small satellite project with respect to the system composition and dynamic behavior. A library of specific building blocks and possible relations between these blocks have been developed. From this library a system model of the satellite of interest can be created. A mapping into a C++ simulation allows the creation of an executable system model with which simulations are performed to observe the dynamic behavior of the satellite. In this paper DySyS is used to model and simulate the dynamic behavior of small satellites, because small satellite projects can act as a precursor to demonstrate the feasibility of a system model since they are less complex compared to a large scale satellite project.

Regional turbulence patterns driven by meso- and submesoscale processes in the Caribbean Sea

NASA Astrophysics Data System (ADS)

C. Pérez, Juan G.; R. Calil, Paulo H.

2017-09-01

The surface ocean circulation in the Caribbean Sea is characterized by the interaction between anticyclonic eddies and the Caribbean Upwelling System (CUS). These interactions lead to instabilities that modulate the transfer of kinetic energy up- or down-cascade. The interaction of North Brazil Current rings with the islands leads to the formation of submesoscale vorticity filaments leeward of the Lesser Antilles, thus transferring kinetic energy from large to small scales. Within the Caribbean, the upper ocean dynamic ranges from large-scale currents to coastal upwelling filaments and allow the vertical exchange of physical properties and supply KE to larger scales. In this study, we use a regional model with different spatial resolutions (6, 3, and 1 km), focusing on the Guajira Peninsula and the Lesser Antilles in the Caribbean Sea, in order to evaluate the impact of submesoscale processes on the regional KE energy cascade. Ageostrophic velocities emerge as the Rossby number becomes O(1). As model resolution is increased submesoscale motions are more energetic, as seen by the flatter KE spectra when compared to the lower resolution run. KE injection at the large scales is greater in the Guajira region than in the others regions, being more effectively transferred to smaller scales, thus showing that submesoscale dynamics is key in modulating eddy kinetic energy and the energy cascade within the Caribbean Sea.

On the time arrows, and randomness in cosmological signals

NASA Astrophysics Data System (ADS)

Gurzadyan, V. G.; Sargsyan, S.; Yegorian, G.

2013-09-01

Arrows of time - thermodynamical, cosmological, electromagnetic, quantum mechanical, psychological - are basic properties of Nature. For a quantum system-bath closed system the de-correlated initial conditions and no-memory (Markovian) dynamics are outlined as necessary conditions for the appearance of the thermodynamical arrow. The emergence of the arrow for the system evolving according to non-unitary dynamics due to the presence of the bath, then, is a result of limited observability, and we conjecture the arrow in the observable Universe as determined by the dark sector acting as a bath. The voids in the large scale matter distribution induce hyperbolicity of the null geodesics, with possible observational consequences.

From cosmology to cold atoms: observation of Sakharov oscillations in a quenched atomic superfluid.

PubMed

Hung, Chen-Lung; Gurarie, Victor; Chin, Cheng

2013-09-13

Predicting the dynamics of many-body systems far from equilibrium is a challenging theoretical problem. A long-predicted phenomenon in hydrodynamic nonequilibrium systems is the occurrence of Sakharov oscillations, which manifest in the anisotropy of the cosmic microwave background and the large-scale correlations of galaxies. Here, we report the observation of Sakharov oscillations in the density fluctuations of a quenched atomic superfluid through a systematic study in both space and time domains and with tunable interaction strengths. Our work suggests a different approach to the study of nonequilibrium dynamics of quantum many-body systems and the exploration of their analogs in cosmology and astrophysics.

A Life-Cycle Model of Human Social Groups Produces a U-Shaped Distribution in Group Size.

PubMed

Salali, Gul Deniz; Whitehouse, Harvey; Hochberg, Michael E

2015-01-01

One of the central puzzles in the study of sociocultural evolution is how and why transitions from small-scale human groups to large-scale, hierarchically more complex ones occurred. Here we develop a spatially explicit agent-based model as a first step towards understanding the ecological dynamics of small and large-scale human groups. By analogy with the interactions between single-celled and multicellular organisms, we build a theory of group lifecycles as an emergent property of single cell demographic and expansion behaviours. We find that once the transition from small-scale to large-scale groups occurs, a few large-scale groups continue expanding while small-scale groups gradually become scarcer, and large-scale groups become larger in size and fewer in number over time. Demographic and expansion behaviours of groups are largely influenced by the distribution and availability of resources. Our results conform to a pattern of human political change in which religions and nation states come to be represented by a few large units and many smaller ones. Future enhancements of the model should include decision-making rules and probabilities of fragmentation for large-scale societies. We suggest that the synthesis of population ecology and social evolution will generate increasingly plausible models of human group dynamics.

A Life-Cycle Model of Human Social Groups Produces a U-Shaped Distribution in Group Size

PubMed Central

Salali, Gul Deniz; Whitehouse, Harvey; Hochberg, Michael E.

2015-01-01

One of the central puzzles in the study of sociocultural evolution is how and why transitions from small-scale human groups to large-scale, hierarchically more complex ones occurred. Here we develop a spatially explicit agent-based model as a first step towards understanding the ecological dynamics of small and large-scale human groups. By analogy with the interactions between single-celled and multicellular organisms, we build a theory of group lifecycles as an emergent property of single cell demographic and expansion behaviours. We find that once the transition from small-scale to large-scale groups occurs, a few large-scale groups continue expanding while small-scale groups gradually become scarcer, and large-scale groups become larger in size and fewer in number over time. Demographic and expansion behaviours of groups are largely influenced by the distribution and availability of resources. Our results conform to a pattern of human political change in which religions and nation states come to be represented by a few large units and many smaller ones. Future enhancements of the model should include decision-making rules and probabilities of fragmentation for large-scale societies. We suggest that the synthesis of population ecology and social evolution will generate increasingly plausible models of human group dynamics. PMID:26381745

Transfer of movement sequences: bigger is better.

PubMed

Dean, Noah J; Kovacs, Attila J; Shea, Charles H

2008-02-01

Experiment 1 was conducted to determine if proportional transfer from "small to large" scale movements is as effective as transferring from "large to small." We hypothesize that the learning of larger scale movement will require the participant to learn to manage the generation, storage, and dissipation of forces better than when practicing smaller scale movements. Thus, we predict an advantage for transfer of larger scale movements to smaller scale movements relative to transfer from smaller to larger scale movements. Experiment 2 was conducted to determine if adding a load to a smaller scale movement would enhance later transfer to a larger scale movement sequence. It was hypothesized that the added load would require the participants to consider the dynamics of the movement to a greater extent than without the load. The results replicated earlier findings of effective transfer from large to small movements, but consistent with our hypothesis, transfer was less effective from small to large (Experiment 1). However, when a load was added during acquisition transfer from small to large was enhanced even though the load was removed during the transfer test. These results are consistent with the notion that the transfer asymmetry noted in Experiment 1 was due to factors related to movement dynamics that were enhanced during practice of the larger scale movement sequence, but not during the practice of the smaller scale movement sequence. The findings that the movement structure is unaffected by transfer direction but the movement dynamics are influenced by transfer direction is consistent with hierarchal models of sequence production.

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.

General Entanglement Scaling Laws from Time Evolution

NASA Astrophysics Data System (ADS)

Eisert, Jens; Osborne, Tobias J.

2006-10-01

We establish a general scaling law for the entanglement of a large class of ground states and dynamically evolving states of quantum spin chains: we show that the geometric entropy of a distinguished block saturates, and hence follows an entanglement-boundary law. These results apply to any ground state of a gapped model resulting from dynamics generated by a local Hamiltonian, as well as, dually, to states that are generated via a sudden quench of an interaction as recently studied in the case of dynamics of quantum phase transitions. We achieve these results by exploiting ideas from quantum information theory and tools provided by Lieb-Robinson bounds. We also show that there exist noncritical fermionic systems and equivalent spin chains with rapidly decaying interactions violating this entanglement-boundary law. Implications for the classical simulatability are outlined.

Cirrus cloud development in a mobile upper tropospheric trough: The November 26th FIRE cirrus case study

NASA Technical Reports Server (NTRS)

Mace, Gerald G.; Ackerman, Thomas P.

1993-01-01

The period from 18 UTC 26 Nov. 1991 to roughly 23 UTC 26 Nov. 1991 is one of the study periods of the FIRE (First International Satellite Cloud Climatology Regional Experiment) 2 field campaign. The middle and upper tropospheric cloud data that was collected during this time allowed FIRE scientists to learn a great deal about the detailed structure, microphysics, and radiative characteristics of the mid latitude cirrus that occurred during that time. Modeling studies that range from the microphysical to the mesoscale are now underway attempting to piece the detailed knowledge of this cloud system into a coherent picture of the atmospheric processes important to cirrus cloud development and maintenance. An important component of the modeling work, either as an input parameter in the case of cloud-scale models, or as output in the case of meso and larger scale models, is the large scale forcing of the cloud system. By forcing we mean the synoptic scale vertical motions and moisture budget that initially send air parcels ascending and supply the water vapor to allow condensation during ascent. Defining this forcing from the synoptic scale to the cloud scale is one of the stated scientific objectives of the FIRE program. From the standpoint of model validation, it is also necessary that the vertical motions and large scale moisture budget of the case studies be derived from observations. It is considered important that the models used to simulate the observed cloud fields begin with the correct dynamics and that the dynamics be in the right place for the right reasons.

Optimal Control Modification Adaptive Law for Time-Scale Separated Systems

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2010-01-01

Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.

Optimal Control Modification for Time-Scale Separated Systems

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2012-01-01

Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.

Toward a theoretical framework for trustworthy cyber sensing

NASA Astrophysics Data System (ADS)

Xu, Shouhuai

2010-04-01

Cyberspace is an indispensable part of the economy and society, but has been "polluted" with many compromised computers that can be abused to launch further attacks against the others. Since it is likely that there always are compromised computers, it is important to be aware of the (dynamic) cyber security-related situation, which is however challenging because cyberspace is an extremely large-scale complex system. Our project aims to investigate a theoretical framework for trustworthy cyber sensing. With the perspective of treating cyberspace as a large-scale complex system, the core question we aim to address is: What would be a competent theoretical (mathematical and algorithmic) framework for designing, analyzing, deploying, managing, and adapting cyber sensor systems so as to provide trustworthy information or input to the higher layer of cyber situation-awareness management, even in the presence of sophisticated malicious attacks against the cyber sensor systems?

Exploiting multi-scale parallelism for large scale numerical modelling of laser wakefield accelerators

NASA Astrophysics Data System (ADS)

Fonseca, R. A.; Vieira, J.; Fiuza, F.; Davidson, A.; Tsung, F. S.; Mori, W. B.; Silva, L. O.

2013-12-01

A new generation of laser wakefield accelerators (LWFA), supported by the extreme accelerating fields generated in the interaction of PW-Class lasers and underdense targets, promises the production of high quality electron beams in short distances for multiple applications. Achieving this goal will rely heavily on numerical modelling to further understand the underlying physics and identify optimal regimes, but large scale modelling of these scenarios is computationally heavy and requires the efficient use of state-of-the-art petascale supercomputing systems. We discuss the main difficulties involved in running these simulations and the new developments implemented in the OSIRIS framework to address these issues, ranging from multi-dimensional dynamic load balancing and hybrid distributed/shared memory parallelism to the vectorization of the PIC algorithm. We present the results of the OASCR Joule Metric program on the issue of large scale modelling of LWFA, demonstrating speedups of over 1 order of magnitude on the same hardware. Finally, scalability to over ˜106 cores and sustained performance over ˜2 P Flops is demonstrated, opening the way for large scale modelling of LWFA scenarios.

Geospatial Optimization of Siting Large-Scale Solar Projects

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

Macknick, Jordan; Quinby, Ted; Caulfield, Emmet

2014-03-01

Recent policy and economic conditions have encouraged a renewed interest in developing large-scale solar projects in the U.S. Southwest. However, siting large-scale solar projects is complex. In addition to the quality of the solar resource, solar developers must take into consideration many environmental, social, and economic factors when evaluating a potential site. This report describes a proof-of-concept, Web-based Geographical Information Systems (GIS) tool that evaluates multiple user-defined criteria in an optimization algorithm to inform discussions and decisions regarding the locations of utility-scale solar projects. Existing siting recommendations for large-scale solar projects from governmental and non-governmental organizations are not consistent withmore » each other, are often not transparent in methods, and do not take into consideration the differing priorities of stakeholders. The siting assistance GIS tool we have developed improves upon the existing siting guidelines by being user-driven, transparent, interactive, capable of incorporating multiple criteria, and flexible. This work provides the foundation for a dynamic siting assistance tool that can greatly facilitate siting decisions among multiple stakeholders.« less

Moon-based Earth Observation for Large Scale Geoscience Phenomena

NASA Astrophysics Data System (ADS)

Guo, Huadong; Liu, Guang; Ding, Yixing

2016-07-01

The capability of Earth observation for large-global-scale natural phenomena needs to be improved and new observing platform are expected. We have studied the concept of Moon as an Earth observation in these years. Comparing with manmade satellite platform, Moon-based Earth observation can obtain multi-spherical, full-band, active and passive information,which is of following advantages: large observation range, variable view angle, long-term continuous observation, extra-long life cycle, with the characteristics of longevity ,consistency, integrity, stability and uniqueness. Moon-based Earth observation is suitable for monitoring the large scale geoscience phenomena including large scale atmosphere change, large scale ocean change,large scale land surface dynamic change,solid earth dynamic change,etc. For the purpose of establishing a Moon-based Earth observation platform, we already have a plan to study the five aspects as follows: mechanism and models of moon-based observing earth sciences macroscopic phenomena; sensors' parameters optimization and methods of moon-based Earth observation; site selection and environment of moon-based Earth observation; Moon-based Earth observation platform; and Moon-based Earth observation fundamental scientific framework.

Aeroelastic Stability Investigations for Large-scale Vertical Axis Wind Turbines

NASA Astrophysics Data System (ADS)

Owens, B. C.; Griffith, D. T.

2014-06-01

The availability of offshore wind resources in coastal regions, along with a high concentration of load centers in these areas, makes offshore wind energy an attractive opportunity for clean renewable electricity production. High infrastructure costs such as the offshore support structure and operation and maintenance costs for offshore wind technology, however, are significant obstacles that need to be overcome to make offshore wind a more cost-effective option. A vertical-axis wind turbine (VAWT) rotor configuration offers a potential transformative technology solution that significantly lowers cost of energy for offshore wind due to its inherent advantages for the offshore market. However, several potential challenges exist for VAWTs and this paper addresses one of them with an initial investigation of dynamic aeroelastic stability for large-scale, multi-megawatt VAWTs. The aeroelastic formulation and solution method from the BLade Aeroelastic STability Tool (BLAST) for HAWT blades was employed to extend the analysis capability of a newly developed structural dynamics design tool for VAWTs. This investigation considers the effect of configuration geometry, material system choice, and number of blades on the aeroelastic stability of a VAWT, and provides an initial scoping for potential aeroelastic instabilities in large-scale VAWT designs.

Improvement of CFD Methods for Modeling Full Scale Circulating Fluidized Bed Combustion Systems

NASA Astrophysics Data System (ADS)

Shah, Srujal; Klajny, Marcin; Myöhänen, Kari; Hyppänen, Timo

With the currently available methods of computational fluid dynamics (CFD), the task of simulating full scale circulating fluidized bed combustors is very challenging. In order to simulate the complex fluidization process, the size of calculation cells should be small and the calculation should be transient with small time step size. For full scale systems, these requirements lead to very large meshes and very long calculation times, so that the simulation in practice is difficult. This study investigates the requirements of cell size and the time step size for accurate simulations, and the filtering effects caused by coarser mesh and longer time step. A modeling study of a full scale CFB furnace is presented and the model results are compared with experimental data.

Integrated view of internal friction in unfolded proteins from single-molecule FRET, contact quenching, theory, and simulations

PubMed Central

Soranno, Andrea; Holla, Andrea; Dingfelder, Fabian; Nettels, Daniel; Makarov, Dmitrii E.; Schuler, Benjamin

2017-01-01

Internal friction is an important contribution to protein dynamics at all stages along the folding reaction. Even in unfolded and intrinsically disordered proteins, internal friction has a large influence, as demonstrated with several experimental techniques and in simulations. However, these methods probe different facets of internal friction and have been applied to disparate molecular systems, raising questions regarding the compatibility of the results. To obtain an integrated view, we apply here the combination of two complementary experimental techniques, simulations, and theory to the same system: unfolded protein L. We use single-molecule Förster resonance energy transfer (FRET) to measure the global reconfiguration dynamics of the chain, and photoinduced electron transfer (PET), a contact-based method, to quantify the rate of loop formation between two residues. This combination enables us to probe unfolded-state dynamics on different length scales, corresponding to different parts of the intramolecular distance distribution. Both FRET and PET measurements show that internal friction dominates unfolded-state dynamics at low denaturant concentration, and the results are in remarkable agreement with recent large-scale molecular dynamics simulations using a new water model. The simulations indicate that intrachain interactions and dihedral angle rotation correlate with the presence of internal friction, and theoretical models of polymer dynamics provide a framework for interrelating the contribution of internal friction observed in the two types of experiments and in the simulations. The combined results thus provide a coherent and quantitative picture of internal friction in unfolded proteins that could not be attained from the individual techniques. PMID:28223518

Integrated view of internal friction in unfolded proteins from single-molecule FRET, contact quenching, theory, and simulations.

PubMed

Soranno, Andrea; Holla, Andrea; Dingfelder, Fabian; Nettels, Daniel; Makarov, Dmitrii E; Schuler, Benjamin

2017-03-07

Internal friction is an important contribution to protein dynamics at all stages along the folding reaction. Even in unfolded and intrinsically disordered proteins, internal friction has a large influence, as demonstrated with several experimental techniques and in simulations. However, these methods probe different facets of internal friction and have been applied to disparate molecular systems, raising questions regarding the compatibility of the results. To obtain an integrated view, we apply here the combination of two complementary experimental techniques, simulations, and theory to the same system: unfolded protein L. We use single-molecule Förster resonance energy transfer (FRET) to measure the global reconfiguration dynamics of the chain, and photoinduced electron transfer (PET), a contact-based method, to quantify the rate of loop formation between two residues. This combination enables us to probe unfolded-state dynamics on different length scales, corresponding to different parts of the intramolecular distance distribution. Both FRET and PET measurements show that internal friction dominates unfolded-state dynamics at low denaturant concentration, and the results are in remarkable agreement with recent large-scale molecular dynamics simulations using a new water model. The simulations indicate that intrachain interactions and dihedral angle rotation correlate with the presence of internal friction, and theoretical models of polymer dynamics provide a framework for interrelating the contribution of internal friction observed in the two types of experiments and in the simulations. The combined results thus provide a coherent and quantitative picture of internal friction in unfolded proteins that could not be attained from the individual techniques.

Strongly enhanced thermal transport in a lightly doped Mott insulator at low temperature.

PubMed

Zlatić, V; Freericks, J K

2012-12-28

We show how a lightly doped Mott insulator has hugely enhanced electronic thermal transport at low temperature. It displays universal behavior independent of the interaction strength when the carriers can be treated as nondegenerate fermions and a nonuniversal "crossover" region where the Lorenz number grows to large values, while still maintaining a large thermoelectric figure of merit. The electron dynamics are described by the Falicov-Kimball model which is solved for arbitrary large on-site correlation with a dynamical mean-field theory algorithm on a Bethe lattice. We show how these results are generic for lightly doped Mott insulators as long as the renormalized Fermi liquid scale is pushed to very low temperature and the system is not magnetically ordered.

A high-throughput assay for quantifying appetite and digestive dynamics.

PubMed

Jordi, Josua; Guggiana-Nilo, Drago; Soucy, Edward; Song, Erin Yue; Lei Wee, Caroline; Engert, Florian

2015-08-15

Food intake and digestion are vital functions, and their dysregulation is fundamental for many human diseases. Current methods do not support their dynamic quantification on large scales in unrestrained vertebrates. Here, we combine an infrared macroscope with fluorescently labeled food to quantify feeding behavior and intestinal nutrient metabolism with high temporal resolution, sensitivity, and throughput in naturally behaving zebrafish larvae. Using this method and rate-based modeling, we demonstrate that zebrafish larvae match nutrient intake to their bodily demand and that larvae adjust their digestion rate, according to the ingested meal size. Such adaptive feedback mechanisms make this model system amenable to identify potential chemical modulators. As proof of concept, we demonstrate that nicotine, l-lysine, ghrelin, and insulin have analogous impact on food intake as in mammals. Consequently, the method presented here will promote large-scale translational research of food intake and digestive function in a naturally behaving vertebrate. Copyright © 2015 the American Physiological Society.

A high-throughput assay for quantifying appetite and digestive dynamics

PubMed Central

Guggiana-Nilo, Drago; Soucy, Edward; Song, Erin Yue; Lei Wee, Caroline; Engert, Florian

2015-01-01

Food intake and digestion are vital functions, and their dysregulation is fundamental for many human diseases. Current methods do not support their dynamic quantification on large scales in unrestrained vertebrates. Here, we combine an infrared macroscope with fluorescently labeled food to quantify feeding behavior and intestinal nutrient metabolism with high temporal resolution, sensitivity, and throughput in naturally behaving zebrafish larvae. Using this method and rate-based modeling, we demonstrate that zebrafish larvae match nutrient intake to their bodily demand and that larvae adjust their digestion rate, according to the ingested meal size. Such adaptive feedback mechanisms make this model system amenable to identify potential chemical modulators. As proof of concept, we demonstrate that nicotine, l-lysine, ghrelin, and insulin have analogous impact on food intake as in mammals. Consequently, the method presented here will promote large-scale translational research of food intake and digestive function in a naturally behaving vertebrate. PMID:26108871

Scalable Cloning on Large-Scale GPU Platforms with Application to Time-Stepped Simulations on Grids

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

Yoginath, Srikanth B.; Perumalla, Kalyan S.

Cloning is a technique to efficiently simulate a tree of multiple what-if scenarios that are unraveled during the course of a base simulation. However, cloned execution is highly challenging to realize on large, distributed memory computing platforms, due to the dynamic nature of the computational load across clones, and due to the complex dependencies spanning the clone tree. In this paper, we present the conceptual simulation framework, algorithmic foundations, and runtime interface of CloneX, a new system we designed for scalable simulation cloning. It efficiently and dynamically creates whole logical copies of a dynamic tree of simulations across a largemore » parallel system without full physical duplication of computation and memory. The performance of a prototype implementation executed on up to 1,024 graphical processing units of a supercomputing system has been evaluated with three benchmarks—heat diffusion, forest fire, and disease propagation models—delivering a speed up of over two orders of magnitude compared to replicated runs. Finally, the results demonstrate a significantly faster and scalable way to execute many what-if scenario ensembles of large simulations via cloning using the CloneX interface.« less

Scalable Cloning on Large-Scale GPU Platforms with Application to Time-Stepped Simulations on Grids

DOE PAGES

Yoginath, Srikanth B.; Perumalla, Kalyan S.

2018-01-31

Cloning is a technique to efficiently simulate a tree of multiple what-if scenarios that are unraveled during the course of a base simulation. However, cloned execution is highly challenging to realize on large, distributed memory computing platforms, due to the dynamic nature of the computational load across clones, and due to the complex dependencies spanning the clone tree. In this paper, we present the conceptual simulation framework, algorithmic foundations, and runtime interface of CloneX, a new system we designed for scalable simulation cloning. It efficiently and dynamically creates whole logical copies of a dynamic tree of simulations across a largemore » parallel system without full physical duplication of computation and memory. The performance of a prototype implementation executed on up to 1,024 graphical processing units of a supercomputing system has been evaluated with three benchmarks—heat diffusion, forest fire, and disease propagation models—delivering a speed up of over two orders of magnitude compared to replicated runs. Finally, the results demonstrate a significantly faster and scalable way to execute many what-if scenario ensembles of large simulations via cloning using the CloneX interface.« less

Self-consistency tests of large-scale dynamics parameterizations for single-column modeling

DOE PAGES

Edman, Jacob P.; Romps, David M.

2015-03-18

Large-scale dynamics parameterizations are tested numerically in cloud-resolving simulations, including a new version of the weak-pressure-gradient approximation (WPG) introduced by Edman and Romps (2014), the weak-temperature-gradient approximation (WTG), and a prior implementation of WPG. We perform a series of self-consistency tests with each large-scale dynamics parameterization, in which we compare the result of a cloud-resolving simulation coupled to WTG or WPG with an otherwise identical simulation with prescribed large-scale convergence. In self-consistency tests based on radiative-convective equilibrium (RCE; i.e., no large-scale convergence), we find that simulations either weakly coupled or strongly coupled to either WPG or WTG are self-consistent, butmore » WPG-coupled simulations exhibit a nonmonotonic behavior as the strength of the coupling to WPG is varied. We also perform self-consistency tests based on observed forcings from two observational campaigns: the Tropical Warm Pool International Cloud Experiment (TWP-ICE) and the ARM Southern Great Plains (SGP) Summer 1995 IOP. In these tests, we show that the new version of WPG improves upon prior versions of WPG by eliminating a potentially troublesome gravity-wave resonance.« less

The Equations of Oceanic Motions

NASA Astrophysics Data System (ADS)

Müller, Peter

2006-10-01

Modeling and prediction of oceanographic phenomena and climate is based on the integration of dynamic equations. The Equations of Oceanic Motions derives and systematically classifies the most common dynamic equations used in physical oceanography, from large scale thermohaline circulations to those governing small scale motions and turbulence. After establishing the basic dynamical equations that describe all oceanic motions, M|ller then derives approximate equations, emphasizing the assumptions made and physical processes eliminated. He distinguishes between geometric, thermodynamic and dynamic approximations and between the acoustic, gravity, vortical and temperature-salinity modes of motion. Basic concepts and formulae of equilibrium thermodynamics, vector and tensor calculus, curvilinear coordinate systems, and the kinematics of fluid motion and wave propagation are covered in appendices. Providing the basic theoretical background for graduate students and researchers of physical oceanography and climate science, this book will serve as both a comprehensive text and an essential reference.

Dynamics and Control of a Disordered System in Space

NASA Technical Reports Server (NTRS)

Quadrelli, Marco B.

2013-01-01

In this paper, we present some ideas regarding the modeling, dynamics and control aspects of granular spacecraft. Granular spacecraft are complex multibody systems composed of a spatially disordered distribution of a large number of elements, for instance a cloud of N grains in orbit, with N greater than 10(exp 3). These grains can be large (Cubesat-size) or small (mm-size), and can be active, i.e., a fully equipped vehicle capable sensing their own position and attitude, and enabled with propulsion means, or entirely passive. The ultimate objective would be to study the behavior of the single grains and of large ensembles of grains in orbit and to identify ways to guide and control the shape of a cloud composed of these grains so that it can perform a useful function in space, for instance, as an element of an optical imaging system for astrophysical applications. This concept, in which the aperture does not need to be continuous and monolithic, would increase the aperture size several times compared to large NASA observatories such as ATLAST, allowing for a true Terrestrial Planet Imager that would be able to resolve exo-planet details and do meaningful spectroscopy on distant world. In the paper, we address the modeling and autonomous operation of a distributed assembly (the cloud) of large numbers of highly miniaturized space-borne elements (the grains). A multi-scale, multi-physics model is proposed of the dynamics of the cloud in orbit, as well as a control law for cloud shape maintenance, and preliminary simulation studies yield an estimate of the computational effort, indicating a scale factor of approximately N(exp 1.4) as a function of the number of grains. A granular spacecraft can be defined as a collection of a large number of space-borne elements (in the 1000s) designed and controlled such that a desirable collective behavior emerges, either from the interactions among neighboring grains, and/or between the grains and the environment. In this paper, each grain is considered to be a highly miniaturized spacecraft which has limited size and mass, hence it has limited actuation, limited propulsive capability, limited power, limited sensing, limited communication, limited computational resources, limited range of motion, limited lifetime, and may be expendable. The modeling and dynamics of clouds of vehicles is more challenging than with conventional vehicles because we are faced with a probabilistic vehicle composed of a large number of physically disconnected vehicles. First, different scales of motion occur simultaneously in a cloud: translations and rotations of the cloud as a whole (macro-dynamics), relative rotation and translation of one cloud member with respect to another (meso-dynamics), and individual cloud member dynamics (micro-dynamics). Second, the control design needs to be tolerant of the system complexity, of the system architecture (centralized vs. decentralized large scale system control) as well as robust to un-modeled dynamics and noise sources. Figure 1, top left, shows the kinematic parameters of a 1000 element cloud in orbit. The motion of the system is described with respect to a local vertical-local horizontal (LV-LH) orbiting reference frame (x,y,z)=F(sub ORF) of origin O(sub ORF) which rotates with mean motion omega and orbital semi-major axis R(sub 0). The orbital geometry at the initial time is defined in terms of its six orbital elements, and the orbital dynamics equation for point O(sub ORF) is propagated forward in time under the influence of the gravitational field of the primary and other external perturbations, described below. The origin of this frame coincides with the initial position of the center of mass of the system, and the coordinate axes are z along the local vertical, x toward the flight direction, and y in the orbit normal direction. The assumptions we used to model the dynamics are as follows: 1) The inertial frame is fixed at Earth's center. 2) The orbiting Frame ORF follows Keplerian orbit. 3) the cloud system dynamics is referred to ORF. 4) the attitude of each grain uses the principal body frame as body fixed frame. 5) the atmosphere is assumed to be rigidly rotating with the Earth. Regarding the grains forming the cloud: 1) each grain is modeled as a rigid body; 2) a simple attitude estimator provides attitude estimates, 3) a simple guidance logic commands the position and attitude of each grain, 4) a simple local feedback controller based on PD control of local states is used to stabilize the attitude of the vehicle. Regarding the cloud: 1) the cloud as a whole is modeled as an equivalent rigid body in orbit, and 2) an associated graph establishes agent connectivity and enables coupling between modes of motion at the micro and macro scales; 3) a simple guidance and estimation logic is modeled to estimate and command the attitude of this equivalent rigid body; 4) a cloud shape maintenance controller is based on the dynamics of a stable virtual truss in the orbiting frame. Regarding the environmental perturbations acting on the cloud: 1) a non-spherical gravity field including JO (Earth's spherical field) zonal component, J2 (Earth's oblateness) and J3 zonal components is implemented; 2) atmospheric drag is modeled with an exponential model; 3) solar pressure is modeled assuming the Sun is inertially fixed; and 4) the Earth's magnetic field is model using an equivalent dipole model. The equations of motion are written in a referential system with respect to the origin of the orbiting frame and the state is propagated forward in time using an incremental predictor-corrector scheme. A representative cloud with varying number of grains is simulated to identify the limitations in computation time as the number of grains grows. We derive a control law to track a desired surface in the ORF (equivalently to maintain a reference cloud shape) by defining an error from a desired surface shape, and designing a control law that is exponentially stable and reduces the tracking error to zero. Figure 1 (top right) shows a comparison of various requirements for simulation of single spacecraft vs. granular spacecraft, indicating the high degree of complexity that needs to be taken into consideration. The ORF components of control force required by one of the grains is, for this particular case, in the micro-Newton range. However, no attempt has been made yet to reconfigure (or re-orient) the cloud configuration internally, for which forces in the milli-Newton level are expected, depending on the time required to do the reconfiguration. Figure 1, bottom, shows the computation time as a function of the number of grains, indicating an order N(exp 1.43) scaling on a 8 Gb, 1067 MHz RAM MacOSX computer with a 3.06 GHz Intel Core 2 Duo processor. With this metric, the same simulation for a system of N=1000 grains would take 5.4 hours, and 146 hours (i.e., 6 days) for a system with N=10,000 grains. Therefore, efficient ways to simulate this complex system, where not only the time scales of natural system dynamics, but also the sampling times of the Guidance, Navigation, and Control are included, remain to be explored. Additional details on the cloud modeling, dynamics, and control will be described in the paper.

Constraining Centennial-Scale Ecosystem-Climate Interactions with a Pre-colonial Forest Reconstruction across the Upper Midwest and Northeastern United States

NASA Astrophysics Data System (ADS)

Matthes, J. H.; Dietze, M.; Fox, A. M.; Goring, S. J.; McLachlan, J. S.; Moore, D. J.; Poulter, B.; Quaife, T. L.; Schaefer, K. M.; Steinkamp, J.; Williams, J. W.

2014-12-01

Interactions between ecological systems and the atmosphere are the result of dynamic processes with system memories that persist from seconds to centuries. Adequately capturing long-term biosphere-atmosphere exchange within earth system models (ESMs) requires an accurate representation of changes in plant functional types (PFTs) through time and space, particularly at timescales associated with ecological succession. However, most model parameterization and development has occurred using datasets than span less than a decade. We tested the ability of ESMs to capture the ecological dynamics observed in paleoecological and historical data spanning the last millennium. Focusing on an area from the Upper Midwest to New England, we examined differences in the magnitude and spatial pattern of PFT distributions and ecotones between historic datasets and the CMIP5 inter-comparison project's large-scale ESMs. We then conducted a 1000-year model inter-comparison using six state-of-the-art biosphere models at sites that bridged regional temperature and precipitation gradients. The distribution of ecosystem characteristics in modeled climate space reveals widely disparate relationships between modeled climate and vegetation that led to large differences in long-term biosphere-atmosphere fluxes for this region. Model simulations revealed that both the interaction between climate and vegetation and the representation of ecosystem dynamics within models were important controls on biosphere-atmosphere exchange.

Microbial Activity and Depositional System Dynamics: Linking Scales With The Aid of New Technology

NASA Astrophysics Data System (ADS)

Defew, E. C.; Hagerthey, S. E.; Honeywill, C.; Perkins, R. G.; Black, K. S.; Paterson, D. M.

The dynamics of estuarine depositional systems are influenced by sediment-dwelling microphytobenthic assemblages. These assemblages produce extracellular polymeric substances (EPS), which are known to be important in the process of sediment biosta- bilisation. However, these communities are generally studied on very small spatial scales making the prediction of primary productivity and their importance in terms of sediment stability over large areas uncertain. Recent advances in our knowledge of the biostabilisation process have allowed the establishment of links between EPS produc- tion, spatial distribution of algal biomass and their primary productivity over much larger spatial scales. For example, during the multidisciplinary BIOPTIS project, re- mote sensing (RS) was combined with ground-truthing measurements of physical and biological parameters to produce synoptic maps leading to a better understanding of system dynamics and the potential effects of environmental perturbations such as cli- mate change. Recent work using low-temperature scanning electron microscopy (LT- SEM) and in-line laser holography has measured the influence of EPS on the erosional behaviour of sediment flocs and particles and has shown that an increase in the con- centration of EPS determines the nature of the eroded floc material and the critical threshold for sediment erosion. This provides the mechanistic link required between EPS concentration and sediment stability. Whilst it is not yet possible to discern EPS concentration directly by RS studies, we know that EPS concentrations in sediments co-vary with chlorophyll a content, and are closely related to algal productivity. There- fore, RS studies which provide large-scale spatial information of chlorophyll a distri- bution may be used to model the stability and productivity of intertidal depositional systems. This paper introduces the basis of these linkages from the cellular level (in situ chlorophyll fluorescence), the ground-truthing approach (sediment stability, struc- ture, pigment distribution, in situ chlorophyll fluorescence) and investigates the poten- tial of a RS approach in a case study of a Scottish Estuary.

Using stroboscopic flow imaging to validate large-scale computational fluid dynamics simulations

NASA Astrophysics Data System (ADS)

Laurence, Ted A.; Ly, Sonny; Fong, Erika; Shusteff, Maxim; Randles, Amanda; Gounley, John; Draeger, Erik

2017-02-01

The utility and accuracy of computational modeling often requires direct validation against experimental measurements. The work presented here is motivated by taking a combined experimental and computational approach to determine the ability of large-scale computational fluid dynamics (CFD) simulations to understand and predict the dynamics of circulating tumor cells in clinically relevant environments. We use stroboscopic light sheet fluorescence imaging to track the paths and measure the velocities of fluorescent microspheres throughout a human aorta model. Performed over complex physiologicallyrealistic 3D geometries, large data sets are acquired with microscopic resolution over macroscopic distances.

Theory of rumour spreading in complex social networks

NASA Astrophysics Data System (ADS)

Nekovee, M.; Moreno, Y.; Bianconi, G.; Marsili, M.

2007-01-01

We introduce a general stochastic model for the spread of rumours, and derive mean-field equations that describe the dynamics of the model on complex social networks (in particular, those mediated by the Internet). We use analytical and numerical solutions of these equations to examine the threshold behaviour and dynamics of the model on several models of such networks: random graphs, uncorrelated scale-free networks and scale-free networks with assortative degree correlations. We show that in both homogeneous networks and random graphs the model exhibits a critical threshold in the rumour spreading rate below which a rumour cannot propagate in the system. In the case of scale-free networks, on the other hand, this threshold becomes vanishingly small in the limit of infinite system size. We find that the initial rate at which a rumour spreads is much higher in scale-free networks than in random graphs, and that the rate at which the spreading proceeds on scale-free networks is further increased when assortative degree correlations are introduced. The impact of degree correlations on the final fraction of nodes that ever hears a rumour, however, depends on the interplay between network topology and the rumour spreading rate. Our results show that scale-free social networks are prone to the spreading of rumours, just as they are to the spreading of infections. They are relevant to the spreading dynamics of chain emails, viral advertising and large-scale information dissemination algorithms on the Internet.

Introduction: demography and cultural macroevolution.

PubMed

Steele, James; Shennan, Stephen

2009-04-01

The papers in this special issue of Human Biology, which derive from a conference sponsored by the Arts and Humanities Research Council (AHRC) Center for the Evolution of Cultural Diversity, lay some of the foundations for an empirical macroevolutionary analysis of cultural dynamics. Our premise here is that cultural dynamics-including the stability of traditions and the rate of origination of new variants-are influenced by independently occurring demographic processes (population size, structure, and distribution as these vary over time as a result of changes in rates of fertility, mortality, and migration). The contributors focus on three sets of problems relevant to empirical studies of cultural macroevolution: large-scale reconstruction of past population dynamics from archaeological and genetic data; juxtaposition of models and evidence of cultural dynamics using large-scale archaeological and historical data sets; and juxtaposition of models and evidence of cultural dynamics from large-scale linguistic data sets. In this introduction we outline some of the theoretical and methodological issues and briefly summarize the individual contributions.

Effects of Ensemble Configuration on Estimates of Regional Climate Uncertainties

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

Goldenson, N.; Mauger, G.; Leung, L. R.

Internal variability in the climate system can contribute substantial uncertainty in climate projections, particularly at regional scales. Internal variability can be quantified using large ensembles of simulations that are identical but for perturbed initial conditions. Here we compare methods for quantifying internal variability. Our study region spans the west coast of North America, which is strongly influenced by El Niño and other large-scale dynamics through their contribution to large-scale internal variability. Using a statistical framework to simultaneously account for multiple sources of uncertainty, we find that internal variability can be quantified consistently using a large ensemble or an ensemble ofmore » opportunity that includes small ensembles from multiple models and climate scenarios. The latter also produce estimates of uncertainty due to model differences. We conclude that projection uncertainties are best assessed using small single-model ensembles from as many model-scenario pairings as computationally feasible, which has implications for ensemble design in large modeling efforts.« less

A framework for modeling and optimizing dynamic systems under uncertainty

DOE PAGES

Nicholson, Bethany; Siirola, John

2017-11-11

Algebraic modeling languages (AMLs) have drastically simplified the implementation of algebraic optimization problems. However, there are still many classes of optimization problems that are not easily represented in most AMLs. These classes of problems are typically reformulated before implementation, which requires significant effort and time from the modeler and obscures the original problem structure or context. In this work we demonstrate how the Pyomo AML can be used to represent complex optimization problems using high-level modeling constructs. We focus on the operation of dynamic systems under uncertainty and demonstrate the combination of Pyomo extensions for dynamic optimization and stochastic programming.more » We use a dynamic semibatch reactor model and a large-scale bubbling fluidized bed adsorber model as test cases.« less

A framework for modeling and optimizing dynamic systems under uncertainty

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

Nicholson, Bethany; Siirola, John

Algebraic modeling languages (AMLs) have drastically simplified the implementation of algebraic optimization problems. However, there are still many classes of optimization problems that are not easily represented in most AMLs. These classes of problems are typically reformulated before implementation, which requires significant effort and time from the modeler and obscures the original problem structure or context. In this work we demonstrate how the Pyomo AML can be used to represent complex optimization problems using high-level modeling constructs. We focus on the operation of dynamic systems under uncertainty and demonstrate the combination of Pyomo extensions for dynamic optimization and stochastic programming.more » We use a dynamic semibatch reactor model and a large-scale bubbling fluidized bed adsorber model as test cases.« less

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

Design Aspects of the Rayleigh Convection Code

NASA Astrophysics Data System (ADS)

Featherstone, N. A.

2017-12-01

Understanding the long-term generation of planetary or stellar magnetic field requires complementary knowledge of the large-scale fluid dynamics pervading large fractions of the object's interior. Such large-scale motions are sensitive to the system's geometry which, in planets and stars, is spherical to a good approximation. As a result, computational models designed to study such systems often solve the MHD equations in spherical geometry, frequently employing a spectral approach involving spherical harmonics. We present computational and user-interface design aspects of one such modeling tool, the Rayleigh convection code, which is suitable for deployment on desktop and petascale-hpc architectures alike. In this poster, we will present an overview of this code's parallel design and its built-in diagnostics-output package. Rayleigh has been developed with NSF support through the Computational Infrastructure for Geodynamics and is expected to be released as open-source software in winter 2017/2018.

Handling Big Data in Medical Imaging: Iterative Reconstruction with Large-Scale Automated Parallel Computation

PubMed Central

Lee, Jae H.; Yao, Yushu; Shrestha, Uttam; Gullberg, Grant T.; Seo, Youngho

2014-01-01

The primary goal of this project is to implement the iterative statistical image reconstruction algorithm, in this case maximum likelihood expectation maximum (MLEM) used for dynamic cardiac single photon emission computed tomography, on Spark/GraphX. This involves porting the algorithm to run on large-scale parallel computing systems. Spark is an easy-to- program software platform that can handle large amounts of data in parallel. GraphX is a graph analytic system running on top of Spark to handle graph and sparse linear algebra operations in parallel. The main advantage of implementing MLEM algorithm in Spark/GraphX is that it allows users to parallelize such computation without any expertise in parallel computing or prior knowledge in computer science. In this paper we demonstrate a successful implementation of MLEM in Spark/GraphX and present the performance gains with the goal to eventually make it useable in clinical setting. PMID:27081299

Handling Big Data in Medical Imaging: Iterative Reconstruction with Large-Scale Automated Parallel Computation.

PubMed

Lee, Jae H; Yao, Yushu; Shrestha, Uttam; Gullberg, Grant T; Seo, Youngho

2014-11-01

The primary goal of this project is to implement the iterative statistical image reconstruction algorithm, in this case maximum likelihood expectation maximum (MLEM) used for dynamic cardiac single photon emission computed tomography, on Spark/GraphX. This involves porting the algorithm to run on large-scale parallel computing systems. Spark is an easy-to- program software platform that can handle large amounts of data in parallel. GraphX is a graph analytic system running on top of Spark to handle graph and sparse linear algebra operations in parallel. The main advantage of implementing MLEM algorithm in Spark/GraphX is that it allows users to parallelize such computation without any expertise in parallel computing or prior knowledge in computer science. In this paper we demonstrate a successful implementation of MLEM in Spark/GraphX and present the performance gains with the goal to eventually make it useable in clinical setting.

The “unreasonable effectiveness” of stratigraphic and geomorphic experiments

NASA Astrophysics Data System (ADS)

Paola, Chris; Straub, Kyle; Mohrig, David; Reinhardt, Liam

2009-12-01

The growth of quantitative analysis and prediction in Earth-surface science has been accompanied by growth in experimental stratigraphy and geomorphology. Experimenters have grown increasingly bold in targeting landscape elements from channel reaches up to the entire erosional networks and depositional basins, often using very small facilities. The experiments produce spatial structure and kinematics that, although imperfect, compare well with natural systems despite differences of spatial scale, time scale, material properties, and number of active processes. Experiments have been particularly useful in studying a wide range of forms of self-organized (autogenic) complexity that occur in morphodynamic systems. Autogenic dynamics creates much of the spatial structure we see in the landscape and in preserved strata, and is strongly associated with sediment storage and release. The observed consistency between experimental and field systems despite large differences in governing dimensionless numbers is what we mean by "unreasonable effectiveness". We suggest that unreasonable experimental effectiveness arises from natural scale independence. We generalize existing ideas to relate internal similarity, in which a small part of a system is similar to the larger system, to external similarity, in which a small copy of a system is similar to the larger system. We propose that internal similarity implies external similarity, though not the converse. The external similarity of landscape experiments to natural landscapes suggests that natural scale independence may be even more characteristic of morphodynamics than it is of better studied cases such as turbulence. We urge a shift in emphasis in experimental stratigraphy and geomorphology away from classical dynamical scaling and towards a quantitative understanding of the origins and limits of scale independence. Other research areas with strong growth potential in experimental surface dynamics include physical-biotic interactions, cohesive effects, stochastic processes, the interplay of structural and geomorphic self-organization, extraction of quantitative process information from landscape and stratigraphic records, and closer interaction between experimentation and theory.

Wetlands as large-scale nature-based solutions: status and future challenges for research and management

NASA Astrophysics Data System (ADS)

Thorslund, Josefin; Jarsjö, Jerker; Destouni, Georgia

2017-04-01

Wetlands are often considered as nature-based solutions that can provide a multitude of services of great social, economic and environmental value to humankind. The services may include recreation, greenhouse gas sequestration, contaminant retention, coastal protection, groundwater level and soil moisture regulation, flood regulation and biodiversity support. Changes in land-use, water use and climate can all impact wetland functions and occur at scales extending well beyond the local scale of an individual wetland. However, in practical applications, management decisions usually regard and focus on individual wetland sites and local conditions. To understand the potential usefulness and services of wetlands as larger-scale nature-based solutions, e.g. for mitigating negative impacts from large-scale change pressures, one needs to understand the combined function multiple wetlands at the relevant large scales. We here systematically investigate if and to what extent research so far has addressed the large-scale dynamics of landscape systems with multiple wetlands, which are likely to be relevant for understanding impacts of regional to global change. Our investigation regards key changes and impacts of relevance for nature-based solutions, such as large-scale nutrient and pollution retention, flow regulation and coastal protection. Although such large-scale knowledge is still limited, evidence suggests that the aggregated functions and effects of multiple wetlands in the landscape can differ considerably from those observed at individual wetlands. Such scale differences may have important implications for wetland function-effect predictability and management under large-scale change pressures and impacts, such as those of climate change.

Correlated motion of protein subdomains and large-scale conformational flexibility of RecA protein filament

NASA Astrophysics Data System (ADS)

Yu, Garmay; A, Shvetsov; D, Karelov; D, Lebedev; A, Radulescu; M, Petukhov; V, Isaev-Ivanov

2012-02-01

Based on X-ray crystallographic data available at Protein Data Bank, we have built molecular dynamics (MD) models of homologous recombinases RecA from E. coli and D. radiodurans. Functional form of RecA enzyme, which is known to be a long helical filament, was approximated by a trimer, simulated in periodic water box. The MD trajectories were analyzed in terms of large-scale conformational motions that could be detectable by neutron and X-ray scattering techniques. The analysis revealed that large-scale RecA monomer dynamics can be described in terms of relative motions of 7 subdomains. Motion of C-terminal domain was the major contributor to the overall dynamics of protein. Principal component analysis (PCA) of the MD trajectories in the atom coordinate space showed that rotation of C-domain is correlated with the conformational changes in the central domain and N-terminal domain, that forms the monomer-monomer interface. Thus, even though C-terminal domain is relatively far from the interface, its orientation is correlated with large-scale filament conformation. PCA of the trajectories in the main chain dihedral angle coordinate space implicates a co-existence of a several different large-scale conformations of the modeled trimer. In order to clarify the relationship of independent domain orientation with large-scale filament conformation, we have performed analysis of independent domain motion and its implications on the filament geometry.

Quadratic partial eigenvalue assignment in large-scale stochastic dynamic systems for resilient and economic design

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

Das, Sonjoy; Goswami, Kundan; Datta, Biswa N.

2014-12-10

Failure of structural systems under dynamic loading can be prevented via active vibration control which shifts the damped natural frequencies of the systems away from the dominant range of loading spectrum. The damped natural frequencies and the dynamic load typically show significant variations in practice. A computationally efficient methodology based on quadratic partial eigenvalue assignment technique and optimization under uncertainty has been formulated in the present work that will rigorously account for these variations and result in an economic and resilient design of structures. A novel scheme based on hierarchical clustering and importance sampling is also developed in this workmore » for accurate and efficient estimation of probability of failure to guarantee the desired resilience level of the designed system. Numerical examples are presented to illustrate the proposed methodology.« less

A modeling study of the thermosphere-ionosphere interactions during the boreal winter and spring 2015-2016: Tidal and planetary-scale waves effect on the ionospheric structure.

NASA Astrophysics Data System (ADS)

Sassi, F.; McDonald, S. E.; McCormack, J. P.; Tate, J.; Liu, H.; Kuhl, D.

2017-12-01

The 2015-2016 boreal winter and spring is a dynamically very interesting time in the lower atmosphere: a minor high latitude stratospheric warming occurred in February 2016; an interrupted descent of the QBO was found in the tropical stratosphere; and a large warm ENSO took place in the tropical Pacific Ocean. The stratospheric warming, the QBO and ENSO are known to affect in different ways the meteorology of the upper atmosphere in different ways: low latitude solar tides and high latitude planetary-scale waves have potentially important implications on the structure of the ionosphere. In this study, we use global atmospheric analyses from a high-altitude version of the High-Altitude Navy Global Environmental Model (HA-NAVGEM) to constrain the meteorology of numerical simulations of the Specified Dynamics Whole Atmosphere Community Climate Model, extended version (SD-WACCM-X). We describe the large-scale behavior of tropical tides and mid-latitude planetary waves that emerge in the lower thermosphere. The effect on the ionosphere is captured by numerical simulations of the Navy Highly Integrated Thermosphere Ionosphere Demonstration System (Navy-HITIDES) that uses the meteorology generated by SD-WACCM-X to drive ionospheric simulations during this time period. We will analyze the impact of various dynamical fields on the zonal behavior of the ionosphere by selectively filtering the relevant dynamical modes.

Assessing Groundwater Depletion and Dynamics Using GRACE and InSAR: Potential and Limitations.

PubMed

Castellazzi, Pascal; Martel, Richard; Galloway, Devin L; Longuevergne, Laurent; Rivera, Alfonso

2016-11-01

In the last decade, remote sensing of the temporal variation of ground level and gravity has improved our understanding of groundwater dynamics and storage. Mass changes are measured by GRACE (Gravity Recovery and Climate Experiment) satellites, whereas ground deformation is measured by processing synthetic aperture radar satellites data using the InSAR (Interferometry of Synthetic Aperture Radar) techniques. Both methods are complementary and offer different sensitivities to aquifer system processes. GRACE is sensitive to mass changes over large spatial scales (more than 100,000 km 2 ). As such, it fails in providing groundwater storage change estimates at local or regional scales relevant to most aquifer systems, and at which most groundwater management schemes are applied. However, InSAR measures ground displacement due to aquifer response to fluid-pressure changes. InSAR applications to groundwater depletion assessments are limited to aquifer systems susceptible to measurable deformation. Furthermore, the inversion of InSAR-derived displacement maps into volume of depleted groundwater storage (both reversible and largely irreversible) is confounded by vertical and horizontal variability of sediment compressibility. During the last decade, both techniques have shown increasing interest in the scientific community to complement available in situ observations where they are insufficient. In this review, we present the theoretical and conceptual bases of each method, and present idealized scenarios to highlight the potential benefits and challenges of combining these techniques to remotely assess groundwater storage changes and other aspects of the dynamics of aquifer systems. © 2016, National Ground Water Association.

Assessing groundwater depletion and dynamics using GRACE and InSAR: Potential and limitations

USGS Publications Warehouse

Castellazzi, Pascal; Martel, Richard; Galloway, Devin L.; Longuevergne, Laurent; Rivera, Alfonso

2016-01-01

In the last decade, remote sensing of the temporal variation of ground level and gravity has improved our understanding of groundwater dynamics and storage. Mass changes are measured by GRACE (Gravity Recovery and Climate Experiment) satellites, whereas ground deformation is measured by processing synthetic aperture radar satellites data using the InSAR (Interferometry of Synthetic Aperture Radar) techniques. Both methods are complementary and offer different sensitivities to aquifer system processes. GRACE is sensitive to mass changes over large spatial scales (more than 100,000 km2). As such, it fails in providing groundwater storage change estimates at local or regional scales relevant to most aquifer systems, and at which most groundwater management schemes are applied. However, InSAR measures ground displacement due to aquifer response to fluid-pressure changes. InSAR applications to groundwater depletion assessments are limited to aquifer systems susceptible to measurable deformation. Furthermore, the inversion of InSAR-derived displacement maps into volume of depleted groundwater storage (both reversible and largely irreversible) is confounded by vertical and horizontal variability of sediment compressibility. During the last decade, both techniques have shown increasing interest in the scientific community to complement available in situ observations where they are insufficient. In this review, we present the theoretical and conceptual bases of each method, and present idealized scenarios to highlight the potential benefits and challenges of combining these techniques to remotely assess groundwater storage changes and other aspects of the dynamics of aquifer systems.

From Large-scale to Protostellar Disk Fragmentation into Close Binary Stars

NASA Astrophysics Data System (ADS)

Sigalotti, Leonardo Di G.; Cruz, Fidel; Gabbasov, Ruslan; Klapp, Jaime; Ramírez-Velasquez, José

2018-04-01

Recent observations of young stellar systems with the Atacama Large Millimeter/submillimeter Array (ALMA) and the Karl G. Jansky Very Large Array are helping to cement the idea that close companion stars form via fragmentation of a gravitationally unstable disk around a protostar early in the star formation process. As the disk grows in mass, it eventually becomes gravitationally unstable and fragments, forming one or more new protostars in orbit with the first at mean separations of 100 au or even less. Here, we report direct numerical calculations down to scales as small as ∼0.1 au, using a consistent Smoothed Particle Hydrodynamics code, that show the large-scale fragmentation of a cloud core into two protostars accompanied by small-scale fragmentation of their circumstellar disks. Our results demonstrate the two dominant mechanisms of star formation, where the disk forming around a protostar (which in turn results from the large-scale fragmentation of the cloud core) undergoes eccentric (m = 1) fragmentation to produce a close binary. We generate two-dimensional emission maps and simulated ALMA 1.3 mm continuum images of the structure and fragmentation of the disks that can help explain the dynamical processes occurring within collapsing cloud cores.

Strategies for Energy Efficient Resource Management of Hybrid Programming Models

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

Li, Dong; Supinski, Bronis de; Schulz, Martin

2013-01-01

Many scientific applications are programmed using hybrid programming models that use both message-passing and shared-memory, due to the increasing prevalence of large-scale systems with multicore, multisocket nodes. Previous work has shown that energy efficiency can be improved using software-controlled execution schemes that consider both the programming model and the power-aware execution capabilities of the system. However, such approaches have focused on identifying optimal resource utilization for one programming model, either shared-memory or message-passing, in isolation. The potential solution space, thus the challenge, increases substantially when optimizing hybrid models since the possible resource configurations increase exponentially. Nonetheless, with the accelerating adoptionmore » of hybrid programming models, we increasingly need improved energy efficiency in hybrid parallel applications on large-scale systems. In this work, we present new software-controlled execution schemes that consider the effects of dynamic concurrency throttling (DCT) and dynamic voltage and frequency scaling (DVFS) in the context of hybrid programming models. Specifically, we present predictive models and novel algorithms based on statistical analysis that anticipate application power and time requirements under different concurrency and frequency configurations. We apply our models and methods to the NPB MZ benchmarks and selected applications from the ASC Sequoia codes. Overall, we achieve substantial energy savings (8.74% on average and up to 13.8%) with some performance gain (up to 7.5%) or negligible performance loss.« less

Large-Scale Economic Change and Youth Development: The Case of Urban China

ERIC Educational Resources Information Center

Yoshikawa, Hirokazu; Way, Niobe; Chen, Xinyin

2012-01-01

Social ecological and dynamic systems theories propose that human development is shaped by the cumulative impact of social interactions in proximal and distal settings, which are themselves influenced by social and economic forces. The understanding of the links between microsystem-level factors (such as parenting styles and parent-child…

Performing a Large-Scale Modal Test on the B2 Stand Crane at NASA's Stennis Space Center

NASA Technical Reports Server (NTRS)

Stasiunas, Eric C.; Parks, Russel A.

2018-01-01

A modal test of NASA’s Space Launch System (SLS) Core Stage is scheduled to occur prior to propulsion system verification testing at the Stennis Space Center B2 test stand. A derrick crane with a 180-ft long boom, located at the top of the stand, will be used to suspend the Core Stage in order to achieve defined boundary conditions. During this suspended modal test, it is expected that dynamic coupling will occur between the crane and the Core Stage. Therefore, a separate modal test was performed on the B2 crane itself, in order to evaluate the varying dynamic characteristics and correlate math models of the crane. Performing a modal test on such a massive structure was challenging and required creative test setup and procedures, including implementing both AC and DC accelerometers, and performing both classical hammer and operational modal analysis. This paper describes the logistics required to perform this large-scale test, as well as details of the test setup, the modal test methods used, and an overview of the results.

Research on an optoelectronic measurement system of dynamic envelope measurement for China Railway high-speed train

NASA Astrophysics Data System (ADS)

Zhao, Ziyue; Gan, Xiaochuan; Zou, Zhi; Ma, Liqun

2018-01-01

The dynamic envelope measurement plays very important role in the external dimension design for high-speed train. Recently there is no digital measurement system to solve this problem. This paper develops an optoelectronic measurement system by using monocular digital camera, and presents the research of measurement theory, visual target design, calibration algorithm design, software programming and so on. This system consists of several CMOS digital cameras, several luminous targets for measuring, a scale bar, data processing software and a terminal computer. The system has such advantages as large measurement scale, high degree of automation, strong anti-interference ability, noise rejection and real-time measurement. In this paper, we resolve the key technology such as the transformation, storage and calculation of multiple cameras' high resolution digital image. The experimental data show that the repeatability of the system is within 0.02mm and the distance error of the system is within 0.12mm in the whole workspace. This experiment has verified the rationality of the system scheme, the correctness, the precision and effectiveness of the relevant methods.

Iterative learning-based decentralized adaptive tracker for large-scale systems: a digital redesign approach.

PubMed

Tsai, Jason Sheng-Hong; Du, Yan-Yi; Huang, Pei-Hsiang; Guo, Shu-Mei; Shieh, Leang-San; Chen, Yuhua

2011-07-01

In this paper, a digital redesign methodology of the iterative learning-based decentralized adaptive tracker is proposed to improve the dynamic performance of sampled-data linear large-scale control systems consisting of N interconnected multi-input multi-output subsystems, so that the system output will follow any trajectory which may not be presented by the analytic reference model initially. To overcome the interference of each sub-system and simplify the controller design, the proposed model reference decentralized adaptive control scheme constructs a decoupled well-designed reference model first. Then, according to the well-designed model, this paper develops a digital decentralized adaptive tracker based on the optimal analog control and prediction-based digital redesign technique for the sampled-data large-scale coupling system. In order to enhance the tracking performance of the digital tracker at specified sampling instants, we apply the iterative learning control (ILC) to train the control input via continual learning. As a result, the proposed iterative learning-based decentralized adaptive tracker not only has robust closed-loop decoupled property but also possesses good tracking performance at both transient and steady state. Besides, evolutionary programming is applied to search for a good learning gain to speed up the learning process of ILC. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Investigating the Role of Large-Scale Domain Dynamics in Protein-Protein Interactions.

PubMed

Delaforge, Elise; Milles, Sigrid; Huang, Jie-Rong; Bouvier, Denis; Jensen, Malene Ringkjøbing; Sattler, Michael; Hart, Darren J; Blackledge, Martin

2016-01-01

Intrinsically disordered linkers provide multi-domain proteins with degrees of conformational freedom that are often essential for function. These highly dynamic assemblies represent a significant fraction of all proteomes, and deciphering the physical basis of their interactions represents a considerable challenge. Here we describe the difficulties associated with mapping the large-scale domain dynamics and describe two recent examples where solution state methods, in particular NMR spectroscopy, are used to investigate conformational exchange on very different timescales.

Investigating the Role of Large-Scale Domain Dynamics in Protein-Protein Interactions

PubMed Central

Delaforge, Elise; Milles, Sigrid; Huang, Jie-rong; Bouvier, Denis; Jensen, Malene Ringkjøbing; Sattler, Michael; Hart, Darren J.; Blackledge, Martin

2016-01-01

Intrinsically disordered linkers provide multi-domain proteins with degrees of conformational freedom that are often essential for function. These highly dynamic assemblies represent a significant fraction of all proteomes, and deciphering the physical basis of their interactions represents a considerable challenge. Here we describe the difficulties associated with mapping the large-scale domain dynamics and describe two recent examples where solution state methods, in particular NMR spectroscopy, are used to investigate conformational exchange on very different timescales. PMID:27679800

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.

Classification of time series patterns from complex dynamic systems

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

Schryver, J.C.; Rao, N.

1998-07-01

An increasing availability of high-performance computing and data storage media at decreasing cost is making possible the proliferation of large-scale numerical databases and data warehouses. Numeric warehousing enterprises on the order of hundreds of gigabytes to terabytes are a reality in many fields such as finance, retail sales, process systems monitoring, biomedical monitoring, surveillance and transportation. Large-scale databases are becoming more accessible to larger user communities through the internet, web-based applications and database connectivity. Consequently, most researchers now have access to a variety of massive datasets. This trend will probably only continue to grow over the next several years. Unfortunately,more » the availability of integrated tools to explore, analyze and understand the data warehoused in these archives is lagging far behind the ability to gain access to the same data. In particular, locating and identifying patterns of interest in numerical time series data is an increasingly important problem for which there are few available techniques. Temporal pattern recognition poses many interesting problems in classification, segmentation, prediction, diagnosis and anomaly detection. This research focuses on the problem of classification or characterization of numerical time series data. Highway vehicles and their drivers are examples of complex dynamic systems (CDS) which are being used by transportation agencies for field testing to generate large-scale time series datasets. Tools for effective analysis of numerical time series in databases generated by highway vehicle systems are not yet available, or have not been adapted to the target problem domain. However, analysis tools from similar domains may be adapted to the problem of classification of numerical time series data.« less

Clustering and heterogeneous dynamics in a kinetic Monte Carlo model of self-propelled hard disks

NASA Astrophysics Data System (ADS)

Levis, Demian; Berthier, Ludovic

2014-06-01

We introduce a kinetic Monte Carlo model for self-propelled hard disks to capture with minimal ingredients the interplay between thermal fluctuations, excluded volume, and self-propulsion in large assemblies of active particles. We analyze in detail the resulting (density, self-propulsion) nonequilibrium phase diagram over a broad range of parameters. We find that purely repulsive hard disks spontaneously aggregate into fractal clusters as self-propulsion is increased and rationalize the evolution of the average cluster size by developing a kinetic model of reversible aggregation. As density is increased, the nonequilibrium clusters percolate to form a ramified structure reminiscent of a physical gel. We show that the addition of a finite amount of noise is needed to trigger a nonequilibrium phase separation, showing that demixing in active Brownian particles results from a delicate balance between noise, interparticle interactions, and self-propulsion. We show that self-propulsion has a profound influence on the dynamics of the active fluid. We find that the diffusion constant has a nonmonotonic behavior as self-propulsion is increased at finite density and that activity produces strong deviations from Fickian diffusion that persist over large time scales and length scales, suggesting that systems of active particles generically behave as dynamically heterogeneous systems.

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

Zhang, S.; Wang, Minghuai; Ghan, Steven J.

Aerosol-cloud interactions continue to constitute a major source of uncertainty for the estimate of climate radiative forcing. The variation of aerosol indirect effects (AIE) in climate models is investigated across different dynamical regimes, determined by monthly mean 500 hPa vertical pressure velocity (ω500), lower-tropospheric stability (LTS) and large-scale surface precipitation rate derived from several global climate models (GCMs), with a focus on liquid water path (LWP) response to cloud condensation nuclei (CCN) concentrations. The LWP sensitivity to aerosol perturbation within dynamic regimes is found to exhibit a large spread among these GCMs. It is in regimes of strong large-scale ascendmore » (ω500 < -25 hPa/d) and low clouds (stratocumulus and trade wind cumulus) where the models differ most. Shortwave aerosol indirect forcing is also found to differ significantly among different regimes. Shortwave aerosol indirect forcing in ascending regimes is as large as that in stratocumulus regimes, which indicates that regimes with strong large-scale ascend are as important as stratocumulus regimes in studying AIE. 42" It is further shown that shortwave aerosol indirect forcing over regions with high monthly large-scale surface precipitation rate (> 0.1 mm/d) contributes the most to the total aerosol indirect forcing (from 64% to nearly 100%). Results show that the uncertainty in AIE is even larger within specific dynamical regimes than that globally, pointing to the need to reduce the uncertainty in AIE in different dynamical regimes.« less

Mass balances for a biological life support system simulation model

NASA Technical Reports Server (NTRS)

Volk, Tyler; Rummel, John D.

1987-01-01

Design decisions to aid the development of future space based biological life support systems (BLSS) can be made with simulation models. The biochemistry stoichiometry was developed for: (1) protein, carbohydrate, fat, fiber, and lignin production in the edible and inedible parts of plants; (2) food consumption and production of organic solids in urine, feces, and wash water by the humans; and (3) operation of the waste processor. Flux values for all components are derived for a steady state system with wheat as the sole food source. The large scale dynamics of a materially closed (BLSS) computer model is described in a companion paper. An extension of this methodology can explore multifood systems and more complex biochemical dynamics while maintaining whole system closure as a focus.

Stochastic thermodynamics across scales: Emergent inter-attractoral discrete Markov jump process and its underlying continuous diffusion

NASA Astrophysics Data System (ADS)

Santillán, Moisés; Qian, Hong

2013-01-01

We investigate the internal consistency of a recently developed mathematical thermodynamic structure across scales, between a continuous stochastic nonlinear dynamical system, i.e., a diffusion process with Langevin and Fokker-Planck equations, and its emergent discrete, inter-attractoral Markov jump process. We analyze how the system’s thermodynamic state functions, e.g. free energy F, entropy S, entropy production ep, free energy dissipation Ḟ, etc., are related when the continuous system is described with coarse-grained discrete variables. It is shown that the thermodynamics derived from the underlying, detailed continuous dynamics gives rise to exactly the free-energy representation of Gibbs and Helmholtz. That is, the system’s thermodynamic structure is the same as if one only takes a middle road and starts with the natural discrete description, with the corresponding transition rates empirically determined. By natural we mean in the thermodynamic limit of a large system, with an inherent separation of time scales between inter- and intra-attractoral dynamics. This result generalizes a fundamental idea from chemistry, and the theory of Kramers, by incorporating thermodynamics: while a mechanical description of a molecule is in terms of continuous bond lengths and angles, chemical reactions are phenomenologically described by a discrete representation, in terms of exponential rate laws and a stochastic thermodynamics.

Effects of diversity on multiagent systems: Minority games

NASA Astrophysics Data System (ADS)

Wong, K. Y. Michael; Lim, S. W.; Gao, Zhuo

2005-06-01

We consider a version of large population games whose agents compete for resources using strategies with adaptable preferences. The games can be used to model economic markets, ecosystems, or distributed control. Diversity of initial preferences of strategies is introduced by randomly assigning biases to the strategies of different agents. We find that diversity among the agents reduces their maladaptive behavior. We find interesting scaling relations with diversity for the variance and other parameters such as the convergence time, the fraction of fickle agents, and the variance of wealth, illustrating their dynamical origin. When diversity increases, the scaling dynamics is modified by kinetic sampling and waiting effects. Analyses yield excellent agreement with simulations.

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.

Tropical warming and the dynamics of endangered primates.

PubMed

Wiederholt, Ruscena; Post, Eric

2010-04-23

Many primate species are severely threatened, but little is known about the effects of global warming and the associated intensification of El Niño events on primate populations. Here, we document the influences of the El Niño southern oscillation (ENSO) and hemispheric climatic variability on the population dynamics of four genera of ateline (neotropical, large-bodied) primates. All ateline genera experienced either an immediate or a lagged negative effect of El Niño events. ENSO events were also found to influence primate resource levels through neotropical arboreal phenology. Furthermore, frugivorous primates showed a high degree of interspecific population synchrony over large scales across Central and South America attributable to the recent trends in large-scale climate. These results highlight the role of large-scale climatic variation and trends in ateline primate population dynamics, and emphasize that global warming could pose additional threats to the persistence of multiple species of endangered primates.

Statistical Ensemble of Large Eddy Simulations

NASA Technical Reports Server (NTRS)

Carati, Daniele; Rogers, Michael M.; Wray, Alan A.; Mansour, Nagi N. (Technical Monitor)

2001-01-01

A statistical ensemble of large eddy simulations (LES) is run simultaneously for the same flow. The information provided by the different large scale velocity fields is used to propose an ensemble averaged version of the dynamic model. This produces local model parameters that only depend on the statistical properties of the flow. An important property of the ensemble averaged dynamic procedure is that it does not require any spatial averaging and can thus be used in fully inhomogeneous flows. Also, the ensemble of LES's provides statistics of the large scale velocity that can be used for building new models for the subgrid-scale stress tensor. The ensemble averaged dynamic procedure has been implemented with various models for three flows: decaying isotropic turbulence, forced isotropic turbulence, and the time developing plane wake. It is found that the results are almost independent of the number of LES's in the statistical ensemble provided that the ensemble contains at least 16 realizations.

Causal inference between bioavailability of heavy metals and environmental factors in a large-scale region.

PubMed

Liu, Yuqiong; Du, Qingyun; Wang, Qi; Yu, Huanyun; Liu, Jianfeng; Tian, Yu; Chang, Chunying; Lei, Jing

2017-07-01

The causation between bioavailability of heavy metals and environmental factors are generally obtained from field experiments at local scales at present, and lack sufficient evidence from large scales. However, inferring causation between bioavailability of heavy metals and environmental factors across large-scale regions is challenging. Because the conventional correlation-based approaches used for causation assessments across large-scale regions, at the expense of actual causation, can result in spurious insights. In this study, a general approach framework, Intervention calculus when the directed acyclic graph (DAG) is absent (IDA) combined with the backdoor criterion (BC), was introduced to identify causation between the bioavailability of heavy metals and the potential environmental factors across large-scale regions. We take the Pearl River Delta (PRD) in China as a case study. The causal structures and effects were identified based on the concentrations of heavy metals (Zn, As, Cu, Hg, Pb, Cr, Ni and Cd) in soil (0-20 cm depth) and vegetable (lettuce) and 40 environmental factors (soil properties, extractable heavy metals and weathering indices) in 94 samples across the PRD. Results show that the bioavailability of heavy metals (Cd, Zn, Cr, Ni and As) was causally influenced by soil properties and soil weathering factors, whereas no causal factor impacted the bioavailability of Cu, Hg and Pb. No latent factor was found between the bioavailability of heavy metals and environmental factors. The causation between the bioavailability of heavy metals and environmental factors at field experiments is consistent with that on a large scale. The IDA combined with the BC provides a powerful tool to identify causation between the bioavailability of heavy metals and environmental factors across large-scale regions. Causal inference in a large system with the dynamic changes has great implications for system-based risk management. Copyright © 2017 Elsevier Ltd. All rights reserved.

Transmission of chirality through space and across length scales

NASA Astrophysics Data System (ADS)

Morrow, Sarah M.; Bissette, Andrew J.; Fletcher, Stephen P.

2017-05-01

Chirality is a fundamental property and vital to chemistry, biology, physics and materials science. The ability to use asymmetry to operate molecular-level machines or macroscopically functional devices, or to give novel properties to materials, may address key challenges at the heart of the physical sciences. However, how chirality at one length scale can be translated to asymmetry at a different scale is largely not well understood. In this Review, we discuss systems where chiral information is translated across length scales and through space. A variety of synthetic systems involve the transmission of chiral information between the molecular-, meso- and macroscales. We show how fundamental stereochemical principles may be used to design and understand nanoscale chiral phenomena and highlight important recent advances relevant to nanotechnology. The survey reveals that while the study of stereochemistry on the nanoscale is a rich and dynamic area, our understanding of how to control and harness it and dial-up specific properties is still in its infancy. The long-term goal of controlling nanoscale chirality promises to be an exciting journey, revealing insight into biological mechanisms and providing new technologies based on dynamic physical properties.

Effects of topology on network evolution

NASA Astrophysics Data System (ADS)

Oikonomou, Panos; Cluzel, Philippe

2006-08-01

The ubiquity of scale-free topology in nature raises the question of whether this particular network design confers an evolutionary advantage. A series of studies has identified key principles controlling the growth and the dynamics of scale-free networks. Here, we use neuron-based networks of boolean components as a framework for modelling a large class of dynamical behaviours in both natural and artificial systems. Applying a training algorithm, we characterize how networks with distinct topologies evolve towards a pre-established target function through a process of random mutations and selection. We find that homogeneous random networks and scale-free networks exhibit drastically different evolutionary paths. Whereas homogeneous random networks accumulate neutral mutations and evolve by sparse punctuated steps, scale-free networks evolve rapidly and continuously. Remarkably, this latter property is robust to variations of the degree exponent. In contrast, homogeneous random networks require a specific tuning of their connectivity to optimize their ability to evolve. These results highlight an organizing principle that governs the evolution of complex networks and that can improve the design of engineered systems.

Living in a network of scaling cities and finite resources.

PubMed

Qubbaj, Murad R; Shutters, Shade T; Muneepeerakul, Rachata

2015-02-01

Many urban phenomena exhibit remarkable regularity in the form of nonlinear scaling behaviors, but their implications on a system of networked cities has never been investigated. Such knowledge is crucial for our ability to harness the complexity of urban processes to further sustainability science. In this paper, we develop a dynamical modeling framework that embeds population-resource dynamics-a generalized Lotka-Volterra system with modifications to incorporate the urban scaling behaviors-in complex networks in which cities may be linked to the resources of other cities and people may migrate in pursuit of higher welfare. We find that isolated cities (i.e., no migration) are susceptible to collapse if they do not have access to adequate resources. Links to other cities may help cities that would otherwise collapse due to insufficient resources. The effects of inter-city links, however, can vary due to the interplay between the nonlinear scaling behaviors and network structure. The long-term population level of a city is, in many settings, largely a function of the city's access to resources over which the city has little or no competition. Nonetheless, careful investigation of dynamics is required to gain mechanistic understanding of a particular city-resource network because cities and resources may collapse and the scaling behaviors may influence the effects of inter-city links, thereby distorting what topological metrics really measure.

Draft De Novo Transcriptome of the Rat Kangaroo Potorous tridactylus as a Tool for Cell Biology

PubMed Central

Udy, Dylan B.; Voorhies, Mark; Chan, Patricia P.; Lowe, Todd M.; Dumont, Sophie

2015-01-01

The rat kangaroo (long-nosed potoroo, Potorous tridactylus) is a marsupial native to Australia. Cultured rat kangaroo kidney epithelial cells (PtK) are commonly used to study cell biological processes. These mammalian cells are large, adherent, and flat, and contain large and few chromosomes—and are thus ideal for imaging intra-cellular dynamics such as those of mitosis. Despite this, neither the rat kangaroo genome nor transcriptome have been sequenced, creating a challenge for probing the molecular basis of these cellular dynamics. Here, we present the sequencing, assembly and annotation of the draft rat kangaroo de novo transcriptome. We sequenced 679 million reads that mapped to 347,323 Trinity transcripts and 20,079 Unigenes. We present statistics emerging from transcriptome-wide analyses, and analyses suggesting that the transcriptome covers full-length sequences of most genes, many with multiple isoforms. We also validate our findings with a proof-of-concept gene knockdown experiment. We expect that this high quality transcriptome will make rat kangaroo cells a more tractable system for linking molecular-scale function and cellular-scale dynamics. PMID:26252667

Draft De Novo Transcriptome of the Rat Kangaroo Potorous tridactylus as a Tool for Cell Biology.

PubMed

Udy, Dylan B; Voorhies, Mark; Chan, Patricia P; Lowe, Todd M; Dumont, Sophie

2015-01-01

The rat kangaroo (long-nosed potoroo, Potorous tridactylus) is a marsupial native to Australia. Cultured rat kangaroo kidney epithelial cells (PtK) are commonly used to study cell biological processes. These mammalian cells are large, adherent, and flat, and contain large and few chromosomes-and are thus ideal for imaging intra-cellular dynamics such as those of mitosis. Despite this, neither the rat kangaroo genome nor transcriptome have been sequenced, creating a challenge for probing the molecular basis of these cellular dynamics. Here, we present the sequencing, assembly and annotation of the draft rat kangaroo de novo transcriptome. We sequenced 679 million reads that mapped to 347,323 Trinity transcripts and 20,079 Unigenes. We present statistics emerging from transcriptome-wide analyses, and analyses suggesting that the transcriptome covers full-length sequences of most genes, many with multiple isoforms. We also validate our findings with a proof-of-concept gene knockdown experiment. We expect that this high quality transcriptome will make rat kangaroo cells a more tractable system for linking molecular-scale function and cellular-scale dynamics.

Fast "Feast/Famine" Cycles for Studying Microbial Physiology Under Dynamic Conditions: A Case Study with Saccharomyces cerevisiae.

PubMed

Suarez-Mendez, Camilo A; Sousa, Andre; Heijnen, Joseph J; Wahl, Aljoscha

2014-05-15

Microorganisms are constantly exposed to rapidly changing conditions, under natural as well as industrial production scale environments, especially due to large-scale substrate mixing limitations. In this work, we present an experimental approach based on a dynamic feast/famine regime (400 s) that leads to repetitive cycles with moderate changes in substrate availability in an aerobic glucose cultivation of Saccharomyces cerevisiae. After a few cycles, the feast/famine produced a stable and repetitive pattern with a reproducible metabolic response in time, thus providing a robust platform for studying the microorganism's physiology under dynamic conditions. We found that the biomass yield was slightly reduced (-5%) under the feast/famine regime, while the averaged substrate and oxygen consumption as well as the carbon dioxide production rates were comparable. The dynamic response of the intracellular metabolites showed specific differences in comparison to other dynamic experiments (especially stimulus-response experiments, SRE). Remarkably, the frequently reported ATP paradox observed in single pulse experiments was not present during the repetitive perturbations applied here. We found that intracellular dynamic accumulations led to an uncoupling of the substrate uptake rate (up to 9-fold change at 20 s.) Moreover, the dynamic profiles of the intracellular metabolites obtained with the feast/famine suggest the presence of regulatory mechanisms that resulted in a delayed response. With the feast famine setup many cellular states can be measured at high frequency given the feature of reproducible cycles. The feast/famine regime is thus a versatile platform for systems biology approaches, which can help us to identify and investigate metabolite regulations under realistic conditions (e.g., large-scale bioreactors or natural environments).

Fast “Feast/Famine” Cycles for Studying Microbial Physiology Under Dynamic Conditions: A Case Study with Saccharomyces cerevisiae

PubMed Central

Suarez-Mendez, Camilo A.; Sousa, Andre; Heijnen, Joseph J.; Wahl, Aljoscha

2014-01-01

Microorganisms are constantly exposed to rapidly changing conditions, under natural as well as industrial production scale environments, especially due to large-scale substrate mixing limitations. In this work, we present an experimental approach based on a dynamic feast/famine regime (400 s) that leads to repetitive cycles with moderate changes in substrate availability in an aerobic glucose cultivation of Saccharomyces cerevisiae. After a few cycles, the feast/famine produced a stable and repetitive pattern with a reproducible metabolic response in time, thus providing a robust platform for studying the microorganism’s physiology under dynamic conditions. We found that the biomass yield was slightly reduced (−5%) under the feast/famine regime, while the averaged substrate and oxygen consumption as well as the carbon dioxide production rates were comparable. The dynamic response of the intracellular metabolites showed specific differences in comparison to other dynamic experiments (especially stimulus-response experiments, SRE). Remarkably, the frequently reported ATP paradox observed in single pulse experiments was not present during the repetitive perturbations applied here. We found that intracellular dynamic accumulations led to an uncoupling of the substrate uptake rate (up to 9-fold change at 20 s.) Moreover, the dynamic profiles of the intracellular metabolites obtained with the feast/famine suggest the presence of regulatory mechanisms that resulted in a delayed response. With the feast famine setup many cellular states can be measured at high frequency given the feature of reproducible cycles. The feast/famine regime is thus a versatile platform for systems biology approaches, which can help us to identify and investigate metabolite regulations under realistic conditions (e.g., large-scale bioreactors or natural environments). PMID:24957030

Computer Science Techniques Applied to Parallel Atomistic Simulation

NASA Astrophysics Data System (ADS)

Nakano, Aiichiro

1998-03-01

Recent developments in parallel processing technology and multiresolution numerical algorithms have established large-scale molecular dynamics (MD) simulations as a new research mode for studying materials phenomena such as fracture. However, this requires large system sizes and long simulated times. We have developed: i) Space-time multiresolution schemes; ii) fuzzy-clustering approach to hierarchical dynamics; iii) wavelet-based adaptive curvilinear-coordinate load balancing; iv) multilevel preconditioned conjugate gradient method; and v) spacefilling-curve-based data compression for parallel I/O. Using these techniques, million-atom parallel MD simulations are performed for the oxidation dynamics of nanocrystalline Al. The simulations take into account the effect of dynamic charge transfer between Al and O using the electronegativity equalization scheme. The resulting long-range Coulomb interaction is calculated efficiently with the fast multipole method. Results for temperature and charge distributions, residual stresses, bond lengths and bond angles, and diffusivities of Al and O will be presented. The oxidation of nanocrystalline Al is elucidated through immersive visualization in virtual environments. A unique dual-degree education program at Louisiana State University will also be discussed in which students can obtain a Ph.D. in Physics & Astronomy and a M.S. from the Department of Computer Science in five years. This program fosters interdisciplinary research activities for interfacing High Performance Computing and Communications with large-scale atomistic simulations of advanced materials. This work was supported by NSF (CAREER Program), ARO, PRF, and Louisiana LEQSF.

Propagation, cascades, and agreement dynamics in complex communication and social networks

NASA Astrophysics Data System (ADS)

Lu, Qiming

Many modern and important technological, social, information and infrastructure systems can be viewed as complex systems with a large number of interacting components. Models of complex networks and dynamical interactions, as well as their applications are of fundamental interests in many aspects. Here, several stylized models of multiplex propagation and opinion dynamics are investigated on complex and empirical social networks. We first investigate cascade dynamics in threshold-controlled (multiplex) propagation on random geometric networks. We find that such local dynamics can serve as an efficient, robust, and reliable prototypical activation protocol in sensor networks in responding to various alarm scenarios. We also consider the same dynamics on a modified network by adding a few long-range communication links, resulting in a small-world network. We find that such construction can further enhance and optimize the speed of the network's response, while keeping energy consumption at a manageable level. We also investigate a prototypical agent-based model, the Naming Game, on two-dimensional random geometric networks. The Naming Game [A. Baronchelli et al., J. Stat. Mech.: Theory Exp. (2006) P06014.] is a minimal model, employing local communications that captures the emergence of shared communication schemes (languages) in a population of autonomous semiotic agents. Implementing the Naming Games with local broadcasts on random geometric graphs, serves as a model for agreement dynamics in large-scale, autonomously operating wireless sensor networks. Further, it captures essential features of the scaling properties of the agreement process for spatially-embedded autonomous agents. Among the relevant observables capturing the temporal properties of the agreement process, we investigate the cluster-size distribution and the distribution of the agreement times, both exhibiting dynamic scaling. We also present results for the case when a small density of long-range communication links are added on top of the random geometric graph, resulting in a "small-world"-like network and yielding a significantly reduced time to reach global agreement. We construct a finite-size scaling analysis for the agreement times in this case. When applying the model of Naming Game on empirical social networks, this stylized agent-based model captures essential features of agreement dynamics in a network of autonomous agents, corresponding to the development of shared classification schemes in a network of artificial agents or opinion spreading and social dynamics in social networks. Our study focuses on the impact that communities in the underlying social graphs have on the outcome of the agreement process. We find that networks with strong community structure hinder the system from reaching global agreement; the evolution of the Naming Game in these networks maintains clusters of coexisting opinions indefinitely. Further, we investigate agent-based network strategies to facilitate convergence to global consensus.

A Holistic Management Architecture for Large-Scale Adaptive Networks

DTIC Science & Technology

2007-09-01

transmission and processing overhead required for management. The challenges of building models to describe dynamic systems are well-known to the field of...increases the challenge of finding a simple approach to assessing the state of the network. Moreover, the performance state of one network link may be... challenging . These obstacles indicate the need for a less comprehensive-analytical, more systemic-holistic approach to managing networks. This approach might

Multiple-basin energy landscapes for large-amplitude conformational motions of proteins: Structure-based molecular dynamics simulations

PubMed Central

Okazaki, Kei-ichi; Koga, Nobuyasu; Takada, Shoji; Onuchic, Jose N.; Wolynes, Peter G.

2006-01-01

Biomolecules often undergo large-amplitude motions when they bind or release other molecules. Unlike macroscopic machines, these biomolecular machines can partially disassemble (unfold) and then reassemble (fold) during such transitions. Here we put forward a minimal structure-based model, the “multiple-basin model,” that can directly be used for molecular dynamics simulation of even very large biomolecular systems so long as the endpoints of the conformational change are known. We investigate the model by simulating large-scale motions of four proteins: glutamine-binding protein, S100A6, dihydrofolate reductase, and HIV-1 protease. The mechanisms of conformational transition depend on the protein basin topologies and change with temperature near the folding transition. The conformational transition rate varies linearly with driving force over a fairly large range. This linearity appears to be a consequence of partial unfolding during the conformational transition. PMID:16877541

Genomic analysis of regulatory network dynamics reveals large topological changes

NASA Astrophysics Data System (ADS)

Luscombe, Nicholas M.; Madan Babu, M.; Yu, Haiyuan; Snyder, Michael; Teichmann, Sarah A.; Gerstein, Mark

2004-09-01

Network analysis has been applied widely, providing a unifying language to describe disparate systems ranging from social interactions to power grids. It has recently been used in molecular biology, but so far the resulting networks have only been analysed statically. Here we present the dynamics of a biological network on a genomic scale, by integrating transcriptional regulatory information and gene-expression data for multiple conditions in Saccharomyces cerevisiae. We develop an approach for the statistical analysis of network dynamics, called SANDY, combining well-known global topological measures, local motifs and newly derived statistics. We uncover large changes in underlying network architecture that are unexpected given current viewpoints and random simulations. In response to diverse stimuli, transcription factors alter their interactions to varying degrees, thereby rewiring the network. A few transcription factors serve as permanent hubs, but most act transiently only during certain conditions. By studying sub-network structures, we show that environmental responses facilitate fast signal propagation (for example, with short regulatory cascades), whereas the cell cycle and sporulation direct temporal progression through multiple stages (for example, with highly inter-connected transcription factors). Indeed, to drive the latter processes forward, phase-specific transcription factors inter-regulate serially, and ubiquitously active transcription factors layer above them in a two-tiered hierarchy. We anticipate that many of the concepts presented here-particularly the large-scale topological changes and hub transience-will apply to other biological networks, including complex sub-systems in higher eukaryotes.

Modeling the MJO rain rates using parameterized large scale dynamics: vertical structure, radiation, and horizontal advection of dry air

NASA Astrophysics Data System (ADS)

Wang, S.; Sobel, A. H.; Nie, J.

2015-12-01

Two Madden Julian Oscillation (MJO) events were observed during October and November 2011 in the equatorial Indian Ocean during the DYNAMO field campaign. Precipitation rates and large-scale vertical motion profiles derived from the DYNAMO northern sounding array are simulated in a small-domain cloud-resolving model using parameterized large-scale dynamics. Three parameterizations of large-scale dynamics --- the conventional weak temperature gradient (WTG) approximation, vertical mode based spectral WTG (SWTG), and damped gravity wave coupling (DGW) --- are employed. The target temperature profiles and radiative heating rates are taken from a control simulation in which the large-scale vertical motion is imposed (rather than directly from observations), and the model itself is significantly modified from that used in previous work. These methodological changes lead to significant improvement in the results.Simulations using all three methods, with imposed time -dependent radiation and horizontal moisture advection, capture the time variations in precipitation associated with the two MJO events well. The three methods produce significant differences in the large-scale vertical motion profile, however. WTG produces the most top-heavy and noisy profiles, while DGW's is smoother with a peak in midlevels. SWTG produces a smooth profile, somewhere between WTG and DGW, and in better agreement with observations than either of the others. Numerical experiments without horizontal advection of moisture suggest that that process significantly reduces the precipitation and suppresses the top-heaviness of large-scale vertical motion during the MJO active phases, while experiments in which the effect of cloud on radiation are disabled indicate that cloud-radiative interaction significantly amplifies the MJO. Experiments in which interactive radiation is used produce poorer agreement with observation than those with imposed time-varying radiative heating. Our results highlight the importance of both horizontal advection of moisture and cloud-radiative feedback to the dynamics of the MJO, as well as to accurate simulation and prediction of it in models.

Revisiting Cholera-Climate Teleconnections in the Native Homeland: ENSO and other Extremes through the Regional Hydroclimatic Drivers

NASA Astrophysics Data System (ADS)

Akanda, A. S.; Jutla, A.; Huq, A.; Colwell, R. R.

2014-12-01

Cholera is a global disease, with significantly large outbreaks occurring since the 1990s, notably in Sub-Saharan Africa and South Asia and recently in Haiti, in the Caribbean. Critical knowledge gaps remain in the understanding of the annual recurrence in endemic areas and the nature of epidemic outbreaks, especially those that follow extreme hydroclimatic events. Teleconnections with large-scale climate phenomena affecting regional scale hydroclimatic drivers of cholera dynamics remain largely unexplained. For centuries, the Bengal delta region has been strongly influenced by the asymmetric availability of water in the rivers Ganges and the Brahmaputra. As these two major rivers are known to have strong contrasting affects on local cholera dynamics in the region, we argue that the role of El Nino-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), or other phenomena needs to be interpreted in the context of the seasonal role of individual rivers and subsequent impact on local environmental processes, not as a teleconnection having a remote and unified effect. We present a modified hypothesis that the influences of large-scale climate phenomena such as ENSO and IOD on Bengal cholera can be explicitly identified and incorporated through regional scale hydroclimatic drivers. Here, we provide an analytical review of the literature addressing cholera and climate linkages and present hypotheses, based on recent evidence, and quantification on the role of regional scale hydroclimatic drivers of cholera. We argue that the seasonal changes in precipitation and temperature, and resulting river discharge in the GBM basin region during ENSO and IOD events have a dominant combined effect on the endemic persistence and the epidemic vulnerability to cholera outbreaks in spring and fall seasons, respectively, that is stronger than the effect of localized hydrological and socio-economic sensitivities in Bangladesh. In addition, systematic identification of underlying seasonal hydroclimatic drivers will allow us to harness the inherent system memory of these processes to develop early warning systems and strengthen prevention measures.

The scientific targets of the SCOPE mission

NASA Astrophysics Data System (ADS)

Fujimoto, M.; Saito, Y.; Tsuda, Y.; Shinohara, I.; Kojima, H.

Future Japanese magnetospheric mission "SCOPE" is now under study (planned to be launched in 2012). The main purpose of this mission is to investigate the dynamic behaviors of plasmas in the Earth's magnetosphere from the view-point of cross-scale coupling. Dynamical collisionless space plasma phenomena, be they large scale as a whole, are chracterized by coupling over various time and spatial scales. The best example would be the magnetic reconnection process, which is a large scale energy conversion process but has a small key region at the heart of its engine. Inside the key region, electron scale dynamics plays the key role in liberating the frozen-in constraint, by which reconnection is allowed to proceed. The SCOPE mission is composed of one large mother satellite and four small daughter satellites. The mother spacecraft will be equiped with the electron detector that has 10 msec time resolution so that scales down to the electron's will be resolved. Three of the four daughter satellites surround the mother satellite 3-dimensionally with the mutual distances between several km and several thousand km, which are varied during the mission. Plasma measurements on these spacecrafts will have 1 sec resolution and will provide information on meso-scale plasma structure. The fourth daughter satellite stays near the mother satellite with the distance less than 100km. By correlation between the two plasma wave instruments on the daughter and the mother spacecrafts, propagation of the waves and the information on the electron scale dynamics will be obtained. By this strategy, both meso- and micro-scale information on dynamics are obtained, that will enable us to investigate the physics of the space plasma from the cross-scale coupling point of view.

BlazeDEM3D-GPU A Large Scale DEM simulation code for GPUs

NASA Astrophysics Data System (ADS)

Govender, Nicolin; Wilke, Daniel; Pizette, Patrick; Khinast, Johannes

2017-06-01

Accurately predicting the dynamics of particulate materials is of importance to numerous scientific and industrial areas with applications ranging across particle scales from powder flow to ore crushing. Computational discrete element simulations is a viable option to aid in the understanding of particulate dynamics and design of devices such as mixers, silos and ball mills, as laboratory scale tests comes at a significant cost. However, the computational time required to simulate an industrial scale simulation which consists of tens of millions of particles can take months to complete on large CPU clusters, making the Discrete Element Method (DEM) unfeasible for industrial applications. Simulations are therefore typically restricted to tens of thousands of particles with highly detailed particle shapes or a few million of particles with often oversimplified particle shapes. However, a number of applications require accurate representation of the particle shape to capture the macroscopic behaviour of the particulate system. In this paper we give an overview of the recent extensions to the open source GPU based DEM code, BlazeDEM3D-GPU, that can simulate millions of polyhedra and tens of millions of spheres on a desktop computer with a single or multiple GPUs.

The relationship between structure and function in locally observed complex networks

NASA Astrophysics Data System (ADS)

Comin, Cesar H.; Viana, Matheus P.; Costa, Luciano da F.

2013-01-01

Recently, studies looking at the small scale interactions taking place in complex networks have started to unveil the wealth of interactions that occur between groups of nodes. Such findings make the claim for a new systematic methodology to quantify, at node level, how dynamics are influenced (or differentiated) by the structure of the underlying system. Here we define a new measure that, based on the dynamical characteristics obtained for a large set of initial conditions, compares the dynamical behavior of the nodes present in the system. Through this measure, we find that the geographic and Barabási-Albert models have a high capacity for generating networks that exhibit groups of nodes with distinct dynamics compared to the rest of the network. The application of our methodology is illustrated with respect to two real systems. In the first we use the neuronal network of the nematode Caenorhabditis elegans to show that the interneurons of the ventral cord of the nematode present a very large dynamical differentiation when compared to the rest of the network. The second application concerns the SIS epidemic model on an airport network, where we quantify how different the distribution of infection times of high and low degree nodes can be, when compared to the expected value for the network.

Dynamic reconfiguration of frontal brain networks during executive cognition in humans

PubMed Central

Braun, Urs; Schäfer, Axel; Walter, Henrik; Erk, Susanne; Romanczuk-Seiferth, Nina; Haddad, Leila; Schweiger, Janina I.; Grimm, Oliver; Heinz, Andreas; Tost, Heike; Meyer-Lindenberg, Andreas; Bassett, Danielle S.

2015-01-01

The brain is an inherently dynamic system, and executive cognition requires dynamically reconfiguring, highly evolving networks of brain regions that interact in complex and transient communication patterns. However, a precise characterization of these reconfiguration processes during cognitive function in humans remains elusive. Here, we use a series of techniques developed in the field of “dynamic network neuroscience” to investigate the dynamics of functional brain networks in 344 healthy subjects during a working-memory challenge (the “n-back” task). In contrast to a control condition, in which dynamic changes in cortical networks were spread evenly across systems, the effortful working-memory condition was characterized by a reconfiguration of frontoparietal and frontotemporal networks. This reconfiguration, which characterizes “network flexibility,” employs transient and heterogeneous connectivity between frontal systems, which we refer to as “integration.” Frontal integration predicted neuropsychological measures requiring working memory and executive cognition, suggesting that dynamic network reconfiguration between frontal systems supports those functions. Our results characterize dynamic reconfiguration of large-scale distributed neural circuits during executive cognition in humans and have implications for understanding impaired cognitive function in disorders affecting connectivity, such as schizophrenia or dementia. PMID:26324898

Shift of large-scale atmospheric systems over Europe during late MIS 3 and implications for Modern Human dispersal.

PubMed

Obreht, Igor; Hambach, Ulrich; Veres, Daniel; Zeeden, Christian; Bösken, Janina; Stevens, Thomas; Marković, Slobodan B; Klasen, Nicole; Brill, Dominik; Burow, Christoph; Lehmkuhl, Frank

2017-07-19

Understanding the past dynamics of large-scale atmospheric systems is crucial for our knowledge of the palaeoclimate conditions in Europe. Southeastern Europe currently lies at the border between Atlantic, Mediterranean, and continental climate zones. Past changes in the relative influence of associated atmospheric systems must have been recorded in the region's palaeoarchives. By comparing high-resolution grain-size, environmental magnetic and geochemical data from two loess-palaeosol sequences in the Lower Danube Basin with other Eurasian palaeorecords, we reconstructed past climatic patterns over Southeastern Europe and the related interaction of the prevailing large-scale circulation modes over Europe, especially during late Marine Isotope Stage 3 (40,000-27,000 years ago). We demonstrate that during this time interval, the intensification of the Siberian High had a crucial influence on European climate causing the more continental conditions over major parts of Europe, and a southwards shift of the Westerlies. Such a climatic and environmental change, combined with the Campanian Ignimbrite/Y-5 volcanic eruption, may have driven the Anatomically Modern Human dispersal towards Central and Western Europe, pointing to a corridor over the Eastern European Plain as an important pathway in their dispersal.

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).

Testing the paradigms of the glass transition in colloids

NASA Astrophysics Data System (ADS)

Zia, Roseanna; Wang, Jialun; Peng, Xiaoguang; Li, Qi; McKenna, Gregory

2017-11-01

Many molecular liquids freeze upon fast enough cooling. This so-called glass state is path dependent and out of equilibrium, as measured by the Kovacs signature experiments, i.e. intrinsic isotherms, asymmetry of approach and memory effect. The reasons for this path- and time-dependence are not fully understood, due to fast molecular relaxations. Colloids provide a natural way to model such behavior, owing to disparity in colloidal versus solvent time scales that can slow dynamics. To shed light on the ambiguity of glass transition, we study via large-scale dynamic simulation of hard-sphere colloidal glass after volume-fraction jumps, where particle size increases at fixed system volume followed by protocols of the McKenna-Kovacs signature experiments. During and following each jump, the positions, velocities, and particle-phase stress are tracked and utilized to characterize relaxation time scales. The impact of both quench depth and quench rate on arrested dynamics and ``state'' variables is explored. In addition, we expand our view to various structural signatures, and rearrangement mechanism is proposed. The results provide insight into not only the existence of an ``ideal'' glass transition, but also the role of structure in such a dense amorphous system.

NASA Marshall Space Flight Center Controls Systems Design and Analysis Branch

NASA Technical Reports Server (NTRS)

Gilligan, Eric

2014-01-01

Marshall Space Flight Center maintains a critical national capability in the analysis of launch vehicle flight dynamics and flight certification of GN&C algorithms. MSFC analysts are domain experts in the areas of flexible-body dynamics and control-structure interaction, thrust vector control, sloshing propellant dynamics, and advanced statistical methods. Marshall's modeling and simulation expertise has supported manned spaceflight for over 50 years. Marshall's unparalleled capability in launch vehicle guidance, navigation, and control technology stems from its rich heritage in developing, integrating, and testing launch vehicle GN&C systems dating to the early Mercury-Redstone and Saturn vehicles. The Marshall team is continuously developing novel methods for design, including advanced techniques for large-scale optimization and analysis.

Gravitational waves from non-Abelian gauge fields at a tachyonic transition

NASA Astrophysics Data System (ADS)

Tranberg, Anders; Tähtinen, Sara; Weir, David J.

2018-04-01

We compute the gravitational wave spectrum from a tachyonic preheating transition of a Standard Model-like SU(2)-Higgs system. Tachyonic preheating involves exponentially growing IR modes, at scales as large as the horizon. Such a transition at the electroweak scale could be detectable by LISA, if these non-perturbatively large modes translate into non-linear dynamics sourcing gravitational waves. Through large-scale numerical simulations, we find that the spectrum of gravitational waves does not exhibit such IR features. Instead, we find two peaks corresponding to the Higgs and gauge field mass, respectively. We find that the gravitational wave production is reduced when adding non-Abelian gauge fields to a scalar-only theory, but increases when adding Abelian gauge fields. In particular, gauge fields suppress the gravitational wave spectrum in the IR. A tachyonic transition in the early Universe will therefore not be detectable by LISA, even if it involves non-Abelian gauge fields.

Vibration-based structural health monitoring of the aircraft large component

NASA Astrophysics Data System (ADS)

Pavelko, V.; Kuznetsov, S.; Nevsky, A.; Marinbah, M.

2017-10-01

In the presented paper there are investigated the basic problems of the local system of SHM of large scale aircraft component. Vibration-based damage detection is accepted as a basic condition, and main attention focused to a low-cost solution that would be attractive for practice. The conditions of small damage detection in the full scale structural component at low-frequency excitation were defined in analytical study and modal FEA. In experimental study the dynamic test of the helicopter Mi-8 tail beam was performed at harmonic excitation with frequency close to first natural frequency of the beam. The index of correlation coefficient deviation (CCD) was used for extraction of the features due to embedded pseudo-damage. It is shown that the problem of vibration-based detection of a small damage in the large scale structure at low-frequency excitation can be solved successfully.

Active Brownian rods

NASA Astrophysics Data System (ADS)

Peruani, Fernando

2016-11-01

Bacteria, chemically-driven rods, and motility assays are examples of active (i.e. self-propelled) Brownian rods (ABR). The physics of ABR, despite their ubiquity in experimental systems, remains still poorly understood. Here, we review the large-scale properties of collections of ABR moving in a dissipative medium. We address the problem by presenting three different models, of decreasing complexity, which we refer to as model I, II, and III, respectively. Comparing model I, II, and III, we disentangle the role of activity and interactions. In particular, we learn that in two dimensions by ignoring steric or volume exclusion effects, large-scale nematic order seems to be possible, while steric interactions prevent the formation of orientational order at large scales. The macroscopic behavior of ABR results from the interplay between active stresses and local alignment. ABR exhibit, depending on where we locate ourselves in parameter space, a zoology of macroscopic patterns that ranges from polar and nematic bands to dynamic aggregates.

Broken Symmetries and Magnetic Dynamos

NASA Technical Reports Server (NTRS)

Shebalin, John V.

2007-01-01

Phase space symmetries inherent in the statistical theory of ideal magnetohydrodynamic (MHD) turbulence are known to be broken dynamically to produce large-scale coherent magnetic structure. Here, results of a numerical study of decaying MHD turbulence are presented that show large-scale coherent structure also arises and persists in the presence of dissipation. Dynamically broken symmetries in MHD turbulence may thus play a fundamental role in the dynamo process.

Partially Filled Aperture Interferometric Telescopes: Achieving Large Aperture and Coronagraphic Performance

NASA Astrophysics Data System (ADS)

Moretto, G.; Kuhn, J.; Langlois, M.; Berdugyna, S.; Tallon, M.

2017-09-01

Telescopes larger than currently planned 30-m class instruments must break the mass-aperture scaling relationship of the Keck-generation of multi-segmented telescopes. Partially filled aperture, but highly redundant baseline interferometric instruments may achieve both large aperture and high dynamic range. The PLANETS FOUNDATION group has explored hybrid telescope-interferometer concepts for narrow-field optical systems that exhibit coronagraphic performance over narrow fields-of-view. This paper describes how the Colossus and Exo-Life Finder telescope designs achieve 10x lower moving masses than current Extremely Large Telescopes.

Molecular Dynamics implementation of BN2D or 'Mercedes Benz' water model

NASA Astrophysics Data System (ADS)

Scukins, Arturs; Bardik, Vitaliy; Pavlov, Evgen; Nerukh, Dmitry

2015-05-01

Two-dimensional 'Mercedes Benz' (MB) or BN2D water model (Naim, 1971) is implemented in Molecular Dynamics. It is known that the MB model can capture abnormal properties of real water (high heat capacity, minima of pressure and isothermal compressibility, negative thermal expansion coefficient) (Silverstein et al., 1998). In this work formulas for calculating the thermodynamic, structural and dynamic properties in microcanonical (NVE) and isothermal-isobaric (NPT) ensembles for the model from Molecular Dynamics simulation are derived and verified against known Monte Carlo results. The convergence of the thermodynamic properties and the system's numerical stability are investigated. The results qualitatively reproduce the peculiarities of real water making the model a visually convenient tool that also requires less computational resources, thus allowing simulations of large (hydrodynamic scale) molecular systems. We provide the open source code written in C/C++ for the BN2D water model implementation using Molecular Dynamics.

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.

Habitat structure mediates biodiversity effects on ecosystem properties

PubMed Central

Godbold, J. A.; Bulling, M. T.; Solan, M.

2011-01-01

Much of what we know about the role of biodiversity in mediating ecosystem processes and function stems from manipulative experiments, which have largely been performed in isolated, homogeneous environments that do not incorporate habitat structure or allow natural community dynamics to develop. Here, we use a range of habitat configurations in a model marine benthic system to investigate the effects of species composition, resource heterogeneity and patch connectivity on ecosystem properties at both the patch (bioturbation intensity) and multi-patch (nutrient concentration) scale. We show that allowing fauna to move and preferentially select patches alters local species composition and density distributions, which has negative effects on ecosystem processes (bioturbation intensity) at the patch scale, but overall positive effects on ecosystem functioning (nutrient concentration) at the multi-patch scale. Our findings provide important evidence that community dynamics alter in response to localized resource heterogeneity and that these small-scale variations in habitat structure influence species contributions to ecosystem properties at larger scales. We conclude that habitat complexity forms an important buffer against disturbance and that contemporary estimates of the level of biodiversity required for maintaining future multi-functional systems may need to be revised. PMID:21227969

Habitat structure mediates biodiversity effects on ecosystem properties.

PubMed

Godbold, J A; Bulling, M T; Solan, M

2011-08-22

Much of what we know about the role of biodiversity in mediating ecosystem processes and function stems from manipulative experiments, which have largely been performed in isolated, homogeneous environments that do not incorporate habitat structure or allow natural community dynamics to develop. Here, we use a range of habitat configurations in a model marine benthic system to investigate the effects of species composition, resource heterogeneity and patch connectivity on ecosystem properties at both the patch (bioturbation intensity) and multi-patch (nutrient concentration) scale. We show that allowing fauna to move and preferentially select patches alters local species composition and density distributions, which has negative effects on ecosystem processes (bioturbation intensity) at the patch scale, but overall positive effects on ecosystem functioning (nutrient concentration) at the multi-patch scale. Our findings provide important evidence that community dynamics alter in response to localized resource heterogeneity and that these small-scale variations in habitat structure influence species contributions to ecosystem properties at larger scales. We conclude that habitat complexity forms an important buffer against disturbance and that contemporary estimates of the level of biodiversity required for maintaining future multi-functional systems may need to be revised.

The large-scale ionospheric transient current system response to upstream solar wind IMF Bz north-south and south-north turnings as seen by the WIND satellite and the full SuperMAG network of ground based magnetometers

NASA Astrophysics Data System (ADS)

Dods, Joe; Chapman, Sandra; Gjerloev, Jesper

2017-04-01

We characterise the response of the quiet-time (no substorms or storms) large scale ionospheric convection system to north-south and south-north IMF turnings by using a dynamical network of ground-based magnetometers. Canonical correlation between all pairs of SuperMAG magnetometer stations in the northern hemisphere (MLat 50-82°) is used to establish the extent of near-simultaneous magnetic response between regions of MLT-MLat. Parameters and maps that describe spatial-temporal correlation are used to characterise the system and its response to the turnings aggregated over several hundred events. We find that regions that experience large increases in correlation post-turning coincide with typical locations of a two cell convection system and are influenced by the IMF By. The time between the turnings reaching the magnetopause and a network response is found to be ˜8-10 minutes and correlation in the dayside occurs 2-8 mins before that in the nightside.

SUSTAINED TURBULENCE IN DIFFERENTIALLY ROTATING MAGNETIZED FLUIDS AT A LOW MAGNETIC PRANDTL NUMBER

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

Nauman, Farrukh; Pessah, Martin E., E-mail: nauman@nbi.ku.dk

2016-12-20

We show for the first time that sustained turbulence is possible at a low magnetic Prandtl number in local simulations of Keplerian flows with no mean magnetic flux. Our results indicate that increasing the vertical domain size is equivalent to increasing the dynamical range between the energy injection scale and the dissipative scale. This has important implications for a large variety of differentially rotating systems with low magnetic Prandtl number such as protostellar disks and laboratory experiments.

Aspects of turbulent-shear-layer dynamics and mixing

NASA Astrophysics Data System (ADS)

Slessor, Michael David

Experiments have been conducted in the GALCIT Supersonic Shear Layer Facility to investigate some aspects of high-Reynolds-number, turbulent, shear-layer flows in both incompressible- and compressible-flow regimes. Experiments designed to address several issues were performed; effects of inflow boundary conditions, freestream conditions (supersonic/subsonic flow), and compressibility, on both large-scale dynamics and small-scale mixing, are described. Chemically-reacting and non-reacting flows were investigated, the former relying on the (Hsb2 + NO)/Fsb2 chemical system, in the fast-kinetic regime, to infer the structure and amount of molecular-scale mixing through use of "flip" experiments. A variety of experimental techniques, including a color-schlieren visualization system developed as part of this work, were used to study the flows. Both inflow conditions and compressibility are found to have significant effects on the flow. In particular, inflow conditions are "remembered" for long distances downstream, a sensitivity similar to that observed in low-dimensionality, non-linear (chaotic) systems. The global flowfields (freestreams coupled by the shear layer) of transonic flows exhibit a sensitivity to imposed boundary conditions, a.e., local area ratios. A previously-proposed mode-selection rule for turbulent-structure convection speeds, based on the presence of a lab-frame subsonic freestream, was experimentally demonstrated to be incorrect. Compressibility, when decoupled from ail other parameters, e.g., Reynolds number, velocity and density ratios, etc., reduces large-scale entrainment and turbulent growth, but slightly enhances small-scale mixing, with an associated change in the structure of the molecularly-mixed fluid. This reduction in shear-layer growth rate is examined and a new parameter that interprets compressibility as an energy-exchange mechanism is proposed. The parameter reconciles and collapses experimentally-observed growth rates.

On the accuracy of modelling the dynamics of large space structures

NASA Technical Reports Server (NTRS)

Diarra, C. M.; Bainum, P. M.

1985-01-01

Proposed space missions will require large scale, light weight, space based structural systems. Large space structure technology (LSST) systems will have to accommodate (among others): ocean data systems; electronic mail systems; large multibeam antenna systems; and, space based solar power systems. The structures are to be delivered into orbit by the space shuttle. Because of their inherent size, modelling techniques and scaling algorithms must be developed so that system performance can be predicted accurately prior to launch and assembly. When the size and weight-to-area ratio of proposed LSST systems dictate that the entire system be considered flexible, there are two basic modeling methods which can be used. The first is a continuum approach, a mathematical formulation for predicting the motion of a general orbiting flexible body, in which elastic deformations are considered small compared with characteristic body dimensions. This approach is based on an a priori knowledge of the frequencies and shape functions of all modes included within the system model. Alternatively, finite element techniques can be used to model the entire structure as a system of lumped masses connected by a series of (restoring) springs and possibly dampers. In addition, a computational algorithm was developed to evaluate the coefficients of the various coupling terms in the equations of motion as applied to the finite element model of the Hoop/Column.

The role of fanatics in consensus formation

NASA Astrophysics Data System (ADS)

Gündüç, Semra

2015-08-01

A model of opinion dynamics with two types of agents as social actors are presented, using the Ising thermodynamic model as the dynamics template. The agents are considered as opportunists which live at sites and interact with the neighbors, or fanatics/missionaries which move from site to site randomly in persuasion of converting agents of opposite opinion with the help of opportunists. Here, the moving agents act as an external influence on the opportunists to convert them to the opposite opinion. It is shown by numerical simulations that such dynamics of opinion formation may explain some details of consensus formation even when one of the opinions are held by a minority. Regardless the distribution of the opinion, different size societies exhibit different opinion formation behavior and time scales. In order to understand general behavior, the scaling relations obtained by comparing opinion formation processes observed in societies with varying population and number of randomly moving agents are studied. For the proposed model two types of scaling relations are observed. In fixed size societies, increasing the number of randomly moving agents give a scaling relation for the time scale of the opinion formation process. The second type of scaling relation is due to the size dependent information propagation in finite but large systems, namely finite-size scaling.

Coupling between populations of copepod taxa within an estuarine ecosystem and the adjacent offshore regions

NASA Astrophysics Data System (ADS)

McGinty, N.; Johnson, M. P.; Power, A. M.

2012-07-01

Population dynamics in open systems are complicated by the interactions of local demography and local environmental forcing with processes occurring at larger scales. A local system such as an estuary or bay may contain a zooplankton population that effectively becomes independent of regional dynamics or the local dynamics may be closely coupled to a broader scale pattern. As an alternative, the details of migration and advection may mean that dynamics in a local system are coupled to other specific areas rather than tracking the overall dynamics at a larger scale. We used a reconstructed time series (1973-1987) for copepod taxa to examine the extent to which zooplankton dynamics in Galway Bay reflect processes in broader areas of the NE Atlantic. Continuous Plankton Recorder (CPR) counts were used to establish time series for nine offshore ecoregions, with the regions themselves defined using underlying patterns of chlorophyll variability. The open nature of Galway Bay was reflected in strong associations between bay zooplankton counts and offshore CPR data in a majority of cases (7/10). For each zooplankton taxon, there were large differences among regions in the degree of association with Galway Bay time series. Akaike weights indicated that one ecoregion tended to be the dominant link for each taxon. This indicates that the zooplankton of the Bay reflect more than the local modification of a regional signal and that different zooplankton in the bay may have separate source regions. The data from Galway Bay also fall within a 'sampling shadow' of the CPR. Later years of the time series showed evidence for changes in phenology, with spring zooplankton peaks generally occurring earlier in the year for smaller species.

A transient FETI methodology for large-scale parallel implicit computations in structural mechanics

NASA Technical Reports Server (NTRS)

Farhat, Charbel; Crivelli, Luis; Roux, Francois-Xavier

1992-01-01

Explicit codes are often used to simulate the nonlinear dynamics of large-scale structural systems, even for low frequency response, because the storage and CPU requirements entailed by the repeated factorizations traditionally found in implicit codes rapidly overwhelm the available computing resources. With the advent of parallel processing, this trend is accelerating because explicit schemes are also easier to parallelize than implicit ones. However, the time step restriction imposed by the Courant stability condition on all explicit schemes cannot yet -- and perhaps will never -- be offset by the speed of parallel hardware. Therefore, it is essential to develop efficient and robust alternatives to direct methods that are also amenable to massively parallel processing because implicit codes using unconditionally stable time-integration algorithms are computationally more efficient when simulating low-frequency dynamics. Here we present a domain decomposition method for implicit schemes that requires significantly less storage than factorization algorithms, that is several times faster than other popular direct and iterative methods, that can be easily implemented on both shared and local memory parallel processors, and that is both computationally and communication-wise efficient. The proposed transient domain decomposition method is an extension of the method of Finite Element Tearing and Interconnecting (FETI) developed by Farhat and Roux for the solution of static problems. Serial and parallel performance results on the CRAY Y-MP/8 and the iPSC-860/128 systems are reported and analyzed for realistic structural dynamics problems. These results establish the superiority of the FETI method over both the serial/parallel conjugate gradient algorithm with diagonal scaling and the serial/parallel direct method, and contrast the computational power of the iPSC-860/128 parallel processor with that of the CRAY Y-MP/8 system.

Social-ecological resilience and geomorphic systems

NASA Astrophysics Data System (ADS)

Chaffin, Brian C.; Scown, Murray

2018-03-01

Governance of coupled social-ecological systems (SESs) and the underlying geomorphic processes that structure and alter Earth's surface is a key challenge for global sustainability amid the increasing uncertainty and change that defines the Anthropocene. Social-ecological resilience as a concept of scientific inquiry has contributed to new understandings of the dynamics of change in SESs, increasing our ability to contextualize and implement governance in these systems. Often, however, the importance of geomorphic change and geomorphological knowledge is somewhat missing from processes employed to inform SES governance. In this contribution, we argue that geomorphology and social-ecological resilience research should be integrated to improve governance toward sustainability. We first provide definitions of engineering, ecological, community, and social-ecological resilience and then explore the use of these concepts within and alongside geomorphology in the literature. While ecological studies often consider geomorphology as an important factor influencing the resilience of ecosystems and geomorphological studies often consider the engineering resilience of geomorphic systems of interest, very few studies define and employ a social-ecological resilience framing and explicitly link the concept to geomorphic systems. We present five key concepts-scale, feedbacks, state or regime, thresholds and regime shifts, and humans as part of the system-which we believe can help explicitly link important aspects of social-ecological resilience inquiry and geomorphological inquiry in order to strengthen the impact of both lines of research. Finally, we discuss how these five concepts might be used to integrate social-ecological resilience and geomorphology to better understand change in, and inform governance of, SESs. To compound these dynamics of resilience, complex systems are nested and cross-scale interactions from smaller and larger scales relative to the system of interest can play formative roles during periods of collapse and reorganization. Large- and small-scale disturbances as well as large-scale system memory/capacity and small-scale innovation can have significant impacts on the trajectory of a reorganizing system (Gunderson and Holling, 2002; Chaffin and Gunderson, 2016). Attempts to measure the property of ecological resilience across complex systems amounts to attempts to measure the persistence of system-controlling variables, including processes, parameters, and important feedbacks, when the system is exposed to varying degrees of disturbance (Folke, 2016).

Hopf bifurcation of an (n + 1) -neuron bidirectional associative memory neural network model with delays.

PubMed

Xiao, Min; Zheng, Wei Xing; Cao, Jinde

2013-01-01

Recent studies on Hopf bifurcations of neural networks with delays are confined to simplified neural network models consisting of only two, three, four, five, or six neurons. It is well known that neural networks are complex and large-scale nonlinear dynamical systems, so the dynamics of the delayed neural networks are very rich and complicated. Although discussing the dynamics of networks with a few neurons may help us to understand large-scale networks, there are inevitably some complicated problems that may be overlooked if simplified networks are carried over to large-scale networks. In this paper, a general delayed bidirectional associative memory neural network model with n + 1 neurons is considered. By analyzing the associated characteristic equation, the local stability of the trivial steady state is examined, and then the existence of the Hopf bifurcation at the trivial steady state is established. By applying the normal form theory and the center manifold reduction, explicit formulae are derived to determine the direction and stability of the bifurcating periodic solution. Furthermore, the paper highlights situations where the Hopf bifurcations are particularly critical, in the sense that the amplitude and the period of oscillations are very sensitive to errors due to tolerances in the implementation of neuron interconnections. It is shown that the sensitivity is crucially dependent on the delay and also significantly influenced by the feature of the number of neurons. Numerical simulations are carried out to illustrate the main results.

Scale-dependent habitat use by a large free-ranging predator, the Mediterranean fin whale

NASA Astrophysics Data System (ADS)

Cotté, Cédric; Guinet, Christophe; Taupier-Letage, Isabelle; Mate, Bruce; Petiau, Estelle

2009-05-01

Since the heterogeneity of oceanographic conditions drives abundance, distribution, and availability of prey, it is essential to understand how foraging predators interact with their dynamic environment at various spatial and temporal scales. We examined the spatio-temporal relationships between oceanographic features and abundance of fin whales ( Balaenoptera physalus), the largest free-ranging predator in the Western Mediterranean Sea (WM), through two independent approaches. First, spatial modeling was used to estimate whale density, using waiting distance (the distance between detections) for fin whales along ferry routes across the WM, in relation to remotely sensed oceanographic parameters. At a large scale (basin and year), fin whales exhibited fidelity to the northern WM with a summer-aggregated and winter-dispersed pattern. At mesoscale (20-100 km), whales were found in colder, saltier (from an on-board system) and dynamic areas defined by steep altimetric and temperature gradients. Second, using an independent fin whale satellite tracking dataset, we showed that tracked whales were effectively preferentially located in favorable habitats, i.e. in areas of high predicted densities as identified by our previous model using oceanographic data contemporaneous to the tracking period. We suggest that the large-scale fidelity corresponds to temporally and spatially predictable habitat of whale favorite prey, the northern krill ( Meganyctiphanes norvegica), while mesoscale relationships are likely to identify areas of high prey concentration and availability.

Climate and wildfires in the North American boreal forest.

PubMed

Macias Fauria, Marc; Johnson, E A

2008-07-12

The area burned in the North American boreal forest is controlled by the frequency of mid-tropospheric blocking highs that cause rapid fuel drying. Climate controls the area burned through changing the dynamics of large-scale teleconnection patterns (Pacific Decadal Oscillation/El Niño Southern Oscillation and Arctic Oscillation, PDO/ENSO and AO) that control the frequency of blocking highs over the continent at different time scales. Changes in these teleconnections may be caused by the current global warming. Thus, an increase in temperature alone need not be associated with an increase in area burned in the North American boreal forest. Since the end of the Little Ice Age, the climate has been unusually moist and variable: large fire years have occurred in unusual years, fire frequency has decreased and fire-climate relationships have occurred at interannual to decadal time scales. Prolonged and severe droughts were common in the past and were partly associated with changes in the PDO/ENSO system. Under these conditions, large fire years become common, fire frequency increases and fire-climate relationships occur at decadal to centennial time scales. A suggested return to the drier climate regimes of the past would imply major changes in the temporal dynamics of fire-climate relationships and in area burned, a reduction in the mean age of the forest, and changes in species composition of the North American boreal forest.

Novel fine-scale aerial mapping approach quantifies grassland weed cover dynamics and response to management.

PubMed

Malmstrom, Carolyn M; Butterfield, H Scott; Planck, Laura; Long, Christopher W; Eviner, Valerie T

2017-01-01

Invasive weeds threaten the biodiversity and forage productivity of grasslands worldwide. However, management of these weeds is constrained by the practical difficulty of detecting small-scale infestations across large landscapes and by limits in understanding of landscape-scale invasion dynamics, including mechanisms that enable patches to expand, contract, or remain stable. While high-end hyperspectral remote sensing systems can effectively map vegetation cover, these systems are currently too costly and limited in availability for most land managers. We demonstrate application of a more accessible and cost-effective remote sensing approach, based on simple aerial imagery, for quantifying weed cover dynamics over time. In California annual grasslands, the target communities of interest include invasive weedy grasses (Aegilops triuncialis and Elymus caput-medusae) and desirable forage grass species (primarily Avena spp. and Bromus spp.). Detecting invasion of annual grasses into an annual-dominated community is particularly challenging, but we were able to consistently characterize these two communities based on their phenological differences in peak growth and senescence using maximum likelihood supervised classification of imagery acquired twice per year (in mid- and end-of season). This approach permitted us to map weed-dominated cover at a 1-m scale (correctly detecting 93% of weed patches across the landscape) and to evaluate weed cover change over time. We found that weed cover was more pervasive and persistent in management units that had no significant grazing for several years than in those that were grazed, whereas forage cover was more abundant and stable in the grazed units. This application demonstrates the power of this method for assessing fine-scale vegetation transitions across heterogeneous landscapes. It thus provides means for small-scale early detection of invasive species and for testing fundamental questions about landscape dynamics.

Novel fine-scale aerial mapping approach quantifies grassland weed cover dynamics and response to management

PubMed Central

Butterfield, H. Scott; Planck, Laura; Long, Christopher W.; Eviner, Valerie T.

2017-01-01

Invasive weeds threaten the biodiversity and forage productivity of grasslands worldwide. However, management of these weeds is constrained by the practical difficulty of detecting small-scale infestations across large landscapes and by limits in understanding of landscape-scale invasion dynamics, including mechanisms that enable patches to expand, contract, or remain stable. While high-end hyperspectral remote sensing systems can effectively map vegetation cover, these systems are currently too costly and limited in availability for most land managers. We demonstrate application of a more accessible and cost-effective remote sensing approach, based on simple aerial imagery, for quantifying weed cover dynamics over time. In California annual grasslands, the target communities of interest include invasive weedy grasses (Aegilops triuncialis and Elymus caput-medusae) and desirable forage grass species (primarily Avena spp. and Bromus spp.). Detecting invasion of annual grasses into an annual-dominated community is particularly challenging, but we were able to consistently characterize these two communities based on their phenological differences in peak growth and senescence using maximum likelihood supervised classification of imagery acquired twice per year (in mid- and end-of season). This approach permitted us to map weed-dominated cover at a 1-m scale (correctly detecting 93% of weed patches across the landscape) and to evaluate weed cover change over time. We found that weed cover was more pervasive and persistent in management units that had no significant grazing for several years than in those that were grazed, whereas forage cover was more abundant and stable in the grazed units. This application demonstrates the power of this method for assessing fine-scale vegetation transitions across heterogeneous landscapes. It thus provides means for small-scale early detection of invasive species and for testing fundamental questions about landscape dynamics. PMID:29016604

An empirical, integrated forest biomass monitoring system

NASA Astrophysics Data System (ADS)

Kennedy, Robert E.; Ohmann, Janet; Gregory, Matt; Roberts, Heather; Yang, Zhiqiang; Bell, David M.; Kane, Van; Hughes, M. Joseph; Cohen, Warren B.; Powell, Scott; Neeti, Neeti; Larrue, Tara; Hooper, Sam; Kane, Jonathan; Miller, David L.; Perkins, James; Braaten, Justin; Seidl, Rupert

2018-02-01

The fate of live forest biomass is largely controlled by growth and disturbance processes, both natural and anthropogenic. Thus, biomass monitoring strategies must characterize both the biomass of the forests at a given point in time and the dynamic processes that change it. Here, we describe and test an empirical monitoring system designed to meet those needs. Our system uses a mix of field data, statistical modeling, remotely-sensed time-series imagery, and small-footprint lidar data to build and evaluate maps of forest biomass. It ascribes biomass change to specific change agents, and attempts to capture the impact of uncertainty in methodology. We find that: • A common image framework for biomass estimation and for change detection allows for consistent comparison of both state and change processes controlling biomass dynamics. • Regional estimates of total biomass agree well with those from plot data alone. • The system tracks biomass densities up to 450-500 Mg ha-1 with little bias, but begins underestimating true biomass as densities increase further. • Scale considerations are important. Estimates at the 30 m grain size are noisy, but agreement at broad scales is good. Further investigation to determine the appropriate scales is underway. • Uncertainty from methodological choices is evident, but much smaller than uncertainty based on choice of allometric equation used to estimate biomass from tree data. • In this forest-dominated study area, growth and loss processes largely balance in most years, with loss processes dominated by human removal through harvest. In years with substantial fire activity, however, overall biomass loss greatly outpaces growth. Taken together, our methods represent a unique combination of elements foundational to an operational landscape-scale forest biomass monitoring program.

Large scale rigidity-based flexibility analysis of biomolecules

PubMed Central

Streinu, Ileana

2016-01-01

KINematics And RIgidity (KINARI) is an on-going project for in silico flexibility analysis of proteins. The new version of the software, Kinari-2, extends the functionality of our free web server KinariWeb, incorporates advanced web technologies, emphasizes the reproducibility of its experiments, and makes substantially improved tools available to the user. It is designed specifically for large scale experiments, in particular, for (a) very large molecules, including bioassemblies with high degree of symmetry such as viruses and crystals, (b) large collections of related biomolecules, such as those obtained through simulated dilutions, mutations, or conformational changes from various types of dynamics simulations, and (c) is intended to work as seemlessly as possible on the large, idiosyncratic, publicly available repository of biomolecules, the Protein Data Bank. We describe the system design, along with the main data processing, computational, mathematical, and validation challenges underlying this phase of the KINARI project. PMID:26958583

Integrating neuroinformatics tools in TheVirtualBrain.

PubMed

Woodman, M Marmaduke; Pezard, Laurent; Domide, Lia; Knock, Stuart A; Sanz-Leon, Paula; Mersmann, Jochen; McIntosh, Anthony R; Jirsa, Viktor

2014-01-01

TheVirtualBrain (TVB) is a neuroinformatics Python package representing the convergence of clinical, systems, and theoretical neuroscience in the analysis, visualization and modeling of neural and neuroimaging dynamics. TVB is composed of a flexible simulator for neural dynamics measured across scales from local populations to large-scale dynamics measured by electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), and core analytic and visualization functions, all accessible through a web browser user interface. A datatype system modeling neuroscientific data ties together these pieces with persistent data storage, based on a combination of SQL and HDF5. These datatypes combine with adapters allowing TVB to integrate other algorithms or computational systems. TVB provides infrastructure for multiple projects and multiple users, possibly participating under multiple roles. For example, a clinician might import patient data to identify several potential lesion points in the patient's connectome. A modeler, working on the same project, tests these points for viability through whole brain simulation, based on the patient's connectome, and subsequent analysis of dynamical features. TVB also drives research forward: the simulator itself represents the culmination of several simulation frameworks in the modeling literature. The availability of the numerical methods, set of neural mass models and forward solutions allows for the construction of a wide range of brain-scale simulation scenarios. This paper briefly outlines the history and motivation for TVB, describing the framework and simulator, giving usage examples in the web UI and Python scripting.

Integrating neuroinformatics tools in TheVirtualBrain

PubMed Central

Woodman, M. Marmaduke; Pezard, Laurent; Domide, Lia; Knock, Stuart A.; Sanz-Leon, Paula; Mersmann, Jochen; McIntosh, Anthony R.; Jirsa, Viktor

2014-01-01

TheVirtualBrain (TVB) is a neuroinformatics Python package representing the convergence of clinical, systems, and theoretical neuroscience in the analysis, visualization and modeling of neural and neuroimaging dynamics. TVB is composed of a flexible simulator for neural dynamics measured across scales from local populations to large-scale dynamics measured by electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), and core analytic and visualization functions, all accessible through a web browser user interface. A datatype system modeling neuroscientific data ties together these pieces with persistent data storage, based on a combination of SQL and HDF5. These datatypes combine with adapters allowing TVB to integrate other algorithms or computational systems. TVB provides infrastructure for multiple projects and multiple users, possibly participating under multiple roles. For example, a clinician might import patient data to identify several potential lesion points in the patient's connectome. A modeler, working on the same project, tests these points for viability through whole brain simulation, based on the patient's connectome, and subsequent analysis of dynamical features. TVB also drives research forward: the simulator itself represents the culmination of several simulation frameworks in the modeling literature. The availability of the numerical methods, set of neural mass models and forward solutions allows for the construction of a wide range of brain-scale simulation scenarios. This paper briefly outlines the history and motivation for TVB, describing the framework and simulator, giving usage examples in the web UI and Python scripting. PMID:24795617

Neocortical dynamics at multiple scales: EEG standing waves, statistical mechanics, and physical analogs.

PubMed

Ingber, Lester; Nunez, Paul L

2011-02-01

The dynamic behavior of scalp potentials (EEG) is apparently due to some combination of global and local processes with important top-down and bottom-up interactions across spatial scales. In treating global mechanisms, we stress the importance of myelinated axon propagation delays and periodic boundary conditions in the cortical-white matter system, which is topologically close to a spherical shell. By contrast, the proposed local mechanisms are multiscale interactions between cortical columns via short-ranged non-myelinated fibers. A mechanical model consisting of a stretched string with attached nonlinear springs demonstrates the general idea. The string produces standing waves analogous to large-scale coherent EEG observed in some brain states. The attached springs are analogous to the smaller (mesoscopic) scale columnar dynamics. Generally, we expect string displacement and EEG at all scales to result from both global and local phenomena. A statistical mechanics of neocortical interactions (SMNI) calculates oscillatory behavior consistent with typical EEG, within columns, between neighboring columns via short-ranged non-myelinated fibers, across cortical regions via myelinated fibers, and also derives a string equation consistent with the global EEG model. Copyright © 2010 Elsevier Inc. All rights reserved.

Development of multitissue microfluidic dynamic array for assessing changes in gene expression associated with channel catfish appetite, growth, metabolism, and intestinal health

USDA-ARS?s Scientific Manuscript database

Large-scale, gene expression methods allow for high throughput analysis of physiological pathways at a fraction of the cost of individual gene expression analysis. Systems, such as the Fluidigm quantitative PCR array described here, can provide powerful assessments of the effects of diet, environme...

Heterogeneous Gossip

NASA Astrophysics Data System (ADS)

Frey, Davide; Guerraoui, Rachid; Kermarrec, Anne-Marie; Koldehofe, Boris; Mogensen, Martin; Monod, Maxime; Quéma, Vivien

Gossip-based information dissemination protocols are considered easy to deploy, scalable and resilient to network dynamics. Load-balancing is inherent in these protocols as the dissemination work is evenly spread among all nodes. Yet, large-scale distributed systems are usually heterogeneous with respect to network capabilities such as bandwidth. In practice, a blind load-balancing strategy might significantly hamper the performance of the gossip dissemination.

Enhancements for a Dynamic Data Warehousing and Mining System for Large-scale HSCB Data

DTIC Science & Technology

2016-06-20

YouTube Data Collection ................................................................................. 2 1.1.1 Scraawl YouTube Data Collection API...Development ............................... 2 1.1.2 Scraawl UI Development for YouTube Searches ....................................... 3 2 Current...following tasks.  Developed automated YouTube data collection capabilities. We have developed automated YouTube video metadata collection capabilities and

Avalanche Statistics Identify Intrinsic Stellar Processes near Criticality in KIC 8462852

NASA Astrophysics Data System (ADS)

Sheikh, Mohammed A.; Weaver, Richard L.; Dahmen, Karin A.

2016-12-01

The star KIC8462852 (Tabby's star) has shown anomalous drops in light flux. We perform a statistical analysis of the more numerous smaller dimming events by using methods found useful for avalanches in ferromagnetism and plastic flow. Scaling exponents for avalanche statistics and temporal profiles of the flux during the dimming events are close to mean field predictions. Scaling collapses suggest that this star may be near a nonequilibrium critical point. The large events are interpreted as avalanches marked by modified dynamics, limited by the system size, and not within the scaling regime.

Generic dynamical phase transition in one-dimensional bulk-driven lattice gases with exclusion

NASA Astrophysics Data System (ADS)

Lazarescu, Alexandre

2017-06-01

Dynamical phase transitions are crucial features of the fluctuations of statistical systems, corresponding to boundaries between qualitatively different mechanisms of maintaining unlikely values of dynamical observables over long periods of time. They manifest themselves in the form of non-analyticities in the large deviation function of those observables. In this paper, we look at bulk-driven exclusion processes with open boundaries. It is known that the standard asymmetric simple exclusion process exhibits a dynamical phase transition in the large deviations of the current of particles flowing through it. That phase transition has been described thanks to specific calculation methods relying on the model being exactly solvable, but more general methods have also been used to describe the extreme large deviations of that current, far from the phase transition. We extend those methods to a large class of models based on the ASEP, where we add arbitrary spatial inhomogeneities in the rates and short-range potentials between the particles. We show that, as for the regular ASEP, the large deviation function of the current scales differently with the size of the system if one considers very high or very low currents, pointing to the existence of a dynamical phase transition between those two regimes: high current large deviations are extensive in the system size, and the typical states associated to them are Coulomb gases, which are highly correlated; low current large deviations do not depend on the system size, and the typical states associated to them are anti-shocks, consistently with a hydrodynamic behaviour. Finally, we illustrate our results numerically on a simple example, and we interpret the transition in terms of the current pushing beyond its maximal hydrodynamic value, as well as relate it to the appearance of Tracy-Widom distributions in the relaxation statistics of such models. , which features invited work from the best early-career researchers working within the scope of J. Phys. A. This project is part of the Journal of Physics series’ 50th anniversary celebrations in 2017. Alexandre Lazarescu was selected by the Editorial Board of J. Phys. A as an Emerging Talent.

Bond graph modelling of multibody dynamics and its symbolic scheme

NASA Astrophysics Data System (ADS)

Kawase, Takehiko; Yoshimura, Hiroaki

A bond graph method of modeling multibody dynamics is demonstrated. Specifically, a symbolic generation scheme which fully utilizes the bond graph information is presented. It is also demonstrated that structural understanding and representation in bond graph theory is quite powerful for the modeling of such large scale systems, and that the nonenergic multiport of junction structure, which is a multiport expression of the system structure, plays an important role, as first suggested by Paynter. The principal part of the proposed symbolic scheme, that is, the elimination of excess variables, is done through tearing and interconnection in the sense of Kron using newly defined causal and causal coefficient arrays.

Spatio-temporal dynamics of a tree-killing beetle and its predator

Treesearch

Aaron S. Weed; Matthew P. Ayres; Andrew M. Liebhold; Ronald F. Billings

2016-01-01

Resolving linkages between local-scale processes and regional-scale patterns in abundance of interacting species is important for understanding long-term population stability across spatial scales. Landscape patterning in consumer population dynamics may be largely the result of interactions between consumers and their predators, or driven by spatial variation in basal...

Characterizing popularity dynamics of online videos

NASA Astrophysics Data System (ADS)

Ren, Zhuo-Ming; Shi, Yu-Qiang; Liao, Hao

2016-07-01

Online popularity has a major impact on videos, music, news and other contexts in online systems. Characterizing online popularity dynamics is nature to explain the observed properties in terms of the already acquired popularity of each individual. In this paper, we provide a quantitative, large scale, temporal analysis of the popularity dynamics in two online video-provided websites, namely MovieLens and Netflix. The two collected data sets contain over 100 million records and even span a decade. We characterize that the popularity dynamics of online videos evolve over time, and find that the dynamics of the online video popularity can be characterized by the burst behaviors, typically occurring in the early life span of a video, and later restricting to the classic preferential popularity increase mechanism.

Large-scale molecular dynamics simulation of DNA: implementation and validation of the AMBER98 force field in LAMMPS.

PubMed

Grindon, Christina; Harris, Sarah; Evans, Tom; Novik, Keir; Coveney, Peter; Laughton, Charles

2004-07-15

Molecular modelling played a central role in the discovery of the structure of DNA by Watson and Crick. Today, such modelling is done on computers: the more powerful these computers are, the more detailed and extensive can be the study of the dynamics of such biological macromolecules. To fully harness the power of modern massively parallel computers, however, we need to develop and deploy algorithms which can exploit the structure of such hardware. The Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) is a scalable molecular dynamics code including long-range Coulomb interactions, which has been specifically designed to function efficiently on parallel platforms. Here we describe the implementation of the AMBER98 force field in LAMMPS and its validation for molecular dynamics investigations of DNA structure and flexibility against the benchmark of results obtained with the long-established code AMBER6 (Assisted Model Building with Energy Refinement, version 6). Extended molecular dynamics simulations on the hydrated DNA dodecamer d(CTTTTGCAAAAG)(2), which has previously been the subject of extensive dynamical analysis using AMBER6, show that it is possible to obtain excellent agreement in terms of static, dynamic and thermodynamic parameters between AMBER6 and LAMMPS. In comparison with AMBER6, LAMMPS shows greatly improved scalability in massively parallel environments, opening up the possibility of efficient simulations of order-of-magnitude larger systems and/or for order-of-magnitude greater simulation times.

Scale Dependence of Dark Energy Antigravity

NASA Astrophysics Data System (ADS)

Perivolaropoulos, L.

2002-09-01

We investigate the effects of negative pressure induced by dark energy (cosmological constant or quintessence) on the dynamics at various astrophysical scales. Negative pressure induces a repulsive term (antigravity) in Newton's law which dominates on large scales. Assuming a value of the cosmological constant consistent with the recent SnIa data we determine the critical scale $r_c$ beyond which antigravity dominates the dynamics ($r_c \\sim 1Mpc $) and discuss some of the dynamical effects implied. We show that dynamically induced mass estimates on the scale of the Local Group and beyond are significantly modified due to negative pressure. We also briefly discuss possible dynamical tests (eg effects on local Hubble flow) that can be applied on relatively small scales (a few $Mpc$) to determine the density and equation of state of dark energy.

Mathematical Modeling and Dynamic Simulation of Metabolic Reaction Systems Using Metabolome Time Series Data.

PubMed

Sriyudthsak, Kansuporn; Shiraishi, Fumihide; Hirai, Masami Yokota

2016-01-01

The high-throughput acquisition of metabolome data is greatly anticipated for the complete understanding of cellular metabolism in living organisms. A variety of analytical technologies have been developed to acquire large-scale metabolic profiles under different biological or environmental conditions. Time series data are useful for predicting the most likely metabolic pathways because they provide important information regarding the accumulation of metabolites, which implies causal relationships in the metabolic reaction network. Considerable effort has been undertaken to utilize these data for constructing a mathematical model merging system properties and quantitatively characterizing a whole metabolic system in toto. However, there are technical difficulties between benchmarking the provision and utilization of data. Although, hundreds of metabolites can be measured, which provide information on the metabolic reaction system, simultaneous measurement of thousands of metabolites is still challenging. In addition, it is nontrivial to logically predict the dynamic behaviors of unmeasurable metabolite concentrations without sufficient information on the metabolic reaction network. Yet, consolidating the advantages of advancements in both metabolomics and mathematical modeling remain to be accomplished. This review outlines the conceptual basis of and recent advances in technologies in both the research fields. It also highlights the potential for constructing a large-scale mathematical model by estimating model parameters from time series metabolome data in order to comprehensively understand metabolism at the systems level.

A socio-hydrologic model of coupled water-agriculture dynamics with emphasis on farm size.

NASA Astrophysics Data System (ADS)

Brugger, D. R.; Maneta, M. P.

2015-12-01

Agricultural land cover dynamics in the U.S. are dominated by two trends: 1) total agricultural land is decreasing and 2) average farm size is increasing. These trends have important implications for the future of water resources because 1) growing more food on less land is due in large part to increased groundwater withdrawal and 2) larger farms can better afford both more efficient irrigation and more groundwater access. However, these large-scale trends are due to individual farm operators responding to many factors including climate, economics, and policy. It is therefore difficult to incorporate the trends into watershed-scale hydrologic models. Traditional scenario-based approaches are valuable for many applications, but there is typically no feedback between the hydrologic model and the agricultural dynamics and so limited insight is gained into the how agriculture co-evolves with water resources. We present a socio-hydrologic model that couples simplified hydrologic and agricultural economic dynamics, accounting for many factors that depend on farm size such as irrigation efficiency and returns to scale. We introduce an "economic memory" (EM) state variable that is driven by agricultural revenue and affects whether farms are sold when land market values exceed expected returns from agriculture. The model uses a Generalized Mixture Model of Gaussians to approximate the distribution of farm sizes in a study area, effectively lumping farms into "small," "medium," and "large" groups that have independent parameterizations. We apply the model in a semi-arid watershed in the upper Columbia River Basin, calibrating to data on streamflow, total agricultural land cover, and farm size distribution. The model is used to investigate the sensitivity of the coupled system to various hydrologic and economic scenarios such as increasing market value of land, reduced surface water availability, and increased irrigation efficiency in small farms.

Dopaminergic modulation of hemodynamic signal variability and the functional connectome during cognitive performance.

PubMed

Alavash, Mohsen; Lim, Sung-Joo; Thiel, Christiane; Sehm, Bernhard; Deserno, Lorenz; Obleser, Jonas

2018-05-15

Dopamine underlies important aspects of cognition, and has been suggested to boost cognitive performance. However, how dopamine modulates the large-scale cortical dynamics during cognitive performance has remained elusive. Using functional MRI during a working memory task in healthy young human listeners, we investigated the effect of levodopa (l-dopa) on two aspects of cortical dynamics, blood oxygen-level-dependent (BOLD) signal variability and the functional connectome of large-scale cortical networks. We here show that enhanced dopaminergic signaling modulates the two potentially interrelated aspects of large-scale cortical dynamics during cognitive performance, and the degree of these modulations is able to explain inter-individual differences in l-dopa-induced behavioral benefits. Relative to placebo, l-dopa increased BOLD signal variability in task-relevant temporal, inferior frontal, parietal and cingulate regions. On the connectome level, however, l-dopa diminished functional integration across temporal and cingulo-opercular regions. This hypo-integration was expressed as a reduction in network efficiency and modularity in more than two thirds of the participants and to different degrees. Hypo-integration co-occurred with relative hyper-connectivity in paracentral lobule and precuneus, as well as posterior putamen. Both, l-dopa-induced BOLD signal variability modulation and functional connectome modulations proved predictive of an individual's l-dopa-induced benefits in behavioral performance, namely response speed and perceptual sensitivity. Lastly, l-dopa-induced modulations of BOLD signal variability were correlated with l-dopa-induced modulation of nodal connectivity and network efficiency. Our findings underline the role of dopamine in maintaining the dynamic range of, and communication between, cortical systems, and their explanatory power for inter-individual differences in benefits from dopamine during cognitive performance. Copyright © 2018 Elsevier Inc. All rights reserved.

Entanglement replication in driven dissipative many-body systems.

PubMed

Zippilli, S; Paternostro, M; Adesso, G; Illuminati, F

2013-01-25

We study the dissipative dynamics of two independent arrays of many-body systems, locally driven by a common entangled field. We show that in the steady state the entanglement of the driving field is reproduced in an arbitrarily large series of inter-array entangled pairs over all distances. Local nonclassical driving thus realizes a scale-free entanglement replication and long-distance entanglement distribution mechanism that has immediate bearing on the implementation of quantum communication networks.

Performance measurements of a pilot superconducting solenoid model core for a wind tunnel magnetic suspension and balance system

NASA Technical Reports Server (NTRS)

Goodyer, M. J.; Britcher, C. P.

1983-01-01

The results of experimental demonstrations of a superconducting solenoid model core in the Southampton University Magnetic Suspension and Balance System are detailed. Technology and techniques relevant to large-scale wind tunnel MSBSs comprise the long term goals. The magnetic moment of solenoids, difficulties peculiar to superconducting solenoid cores, lift force and pitching moment, dynamic lift calibration, and helium boil-off measurements are discussed.

Concurrent heterogeneous neural model simulation on real-time neuromimetic hardware.

PubMed

Rast, Alexander; Galluppi, Francesco; Davies, Sergio; Plana, Luis; Patterson, Cameron; Sharp, Thomas; Lester, David; Furber, Steve

2011-11-01

Dedicated hardware is becoming increasingly essential to simulate emerging very-large-scale neural models. Equally, however, it needs to be able to support multiple models of the neural dynamics, possibly operating simultaneously within the same system. This may be necessary either to simulate large models with heterogeneous neural types, or to simplify simulation and analysis of detailed, complex models in a large simulation by isolating the new model to a small subpopulation of a larger overall network. The SpiNNaker neuromimetic chip is a dedicated neural processor able to support such heterogeneous simulations. Implementing these models on-chip uses an integrated library-based tool chain incorporating the emerging PyNN interface that allows a modeller to input a high-level description and use an automated process to generate an on-chip simulation. Simulations using both LIF and Izhikevich models demonstrate the ability of the SpiNNaker system to generate and simulate heterogeneous networks on-chip, while illustrating, through the network-scale effects of wavefront synchronisation and burst gating, methods that can provide effective behavioural abstractions for large-scale hardware modelling. SpiNNaker's asynchronous virtual architecture permits greater scope for model exploration, with scalable levels of functional and temporal abstraction, than conventional (or neuromorphic) computing platforms. The complete system illustrates a potential path to understanding the neural model of computation, by building (and breaking) neural models at various scales, connecting the blocks, then comparing them against the biology: computational cognitive neuroscience. Copyright © 2011 Elsevier Ltd. All rights reserved.

Development of the Large-Scale Forcing Data to Support MC3E Cloud Modeling Studies

NASA Astrophysics Data System (ADS)

Xie, S.; Zhang, Y.

2011-12-01

The large-scale forcing fields (e.g., vertical velocity and advective tendencies) are required to run single-column and cloud-resolving models (SCMs/CRMs), which are the two key modeling frameworks widely used to link field data to climate model developments. In this study, we use an advanced objective analysis approach to derive the required forcing data from the soundings collected by the Midlatitude Continental Convective Cloud Experiment (MC3E) in support of its cloud modeling studies. MC3E is the latest major field campaign conducted during the period 22 April 2011 to 06 June 2011 in south-central Oklahoma through a joint effort between the DOE ARM program and the NASA Global Precipitation Measurement Program. One of its primary goals is to provide a comprehensive dataset that can be used to describe the large-scale environment of convective cloud systems and evaluate model cumulus parameterizations. The objective analysis used in this study is the constrained variational analysis method. A unique feature of this approach is the use of domain-averaged surface and top-of-the atmosphere (TOA) observations (e.g., precipitation and radiative and turbulent fluxes) as constraints to adjust atmospheric state variables from soundings by the smallest possible amount to conserve column-integrated mass, moisture, and static energy so that the final analysis data is dynamically and thermodynamically consistent. To address potential uncertainties in the surface observations, an ensemble forcing dataset will be developed. Multi-scale forcing will be also created for simulating various scale convective systems. At the meeting, we will provide more details about the forcing development and present some preliminary analysis of the characteristics of the large-scale forcing structures for several selected convective systems observed during MC3E.

Dynamics analysis of the fast-slow hydro-turbine governing system with different time-scale coupling

NASA Astrophysics Data System (ADS)

Zhang, Hao; Chen, Diyi; Wu, Changzhi; Wang, Xiangyu

2018-01-01

Multi-time scales modeling of hydro-turbine governing system is crucial in precise modeling of hydropower plant and provides support for the stability analysis of the system. Considering the inertia and response time of the hydraulic servo system, the hydro-turbine governing system is transformed into the fast-slow hydro-turbine governing system. The effects of the time-scale on the dynamical behavior of the system are analyzed and the fast-slow dynamical behaviors of the system are investigated with different time-scale. Furthermore, the theoretical analysis of the stable regions is presented. The influences of the time-scale on the stable region are analyzed by simulation. The simulation results prove the correctness of the theoretical analysis. More importantly, the methods and results of this paper provide a perspective to multi-time scales modeling of hydro-turbine governing system and contribute to the optimization analysis and control of the system.

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

Statistical Characterization of School Bus Drive Cycles Collected via Onboard Logging Systems

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

Duran, A.; Walkowicz, K.

In an effort to characterize the dynamics typical of school bus operation, National Renewable Energy Laboratory (NREL) researchers set out to gather in-use duty cycle data from school bus fleets operating across the country. Employing a combination of Isaac Instruments GPS/CAN data loggers in conjunction with existing onboard telemetric systems resulted in the capture of operating information for more than 200 individual vehicles in three geographically unique domestic locations. In total, over 1,500 individual operational route shifts from Washington, New York, and Colorado were collected. Upon completing the collection of in-use field data using either NREL-installed data acquisition devices ormore » existing onboard telemetry systems, large-scale duty-cycle statistical analyses were performed to examine underlying vehicle dynamics trends within the data and to explore vehicle operation variations between fleet locations. Based on the results of these analyses, high, low, and average vehicle dynamics requirements were determined, resulting in the selection of representative standard chassis dynamometer test cycles for each condition. In this paper, the methodology and accompanying results of the large-scale duty-cycle statistical analysis are presented, including graphical and tabular representations of a number of relationships between key duty-cycle metrics observed within the larger data set. In addition to presenting the results of this analysis, conclusions are drawn and presented regarding potential applications of advanced vehicle technology as it relates specifically to school buses.« less

Modeling Multi-Agent Self-Organization through the Lens of Higher Order Attractor Dynamics.

PubMed

Butner, Jonathan E; Wiltshire, Travis J; Munion, A K

2017-01-01

Social interaction occurs across many time scales and varying numbers of agents; from one-on-one to large-scale coordination in organizations, crowds, cities, and colonies. These contexts, are characterized by emergent self-organization that implies higher order coordinated patterns occurring over time that are not due to the actions of any particular agents, but rather due to the collective ordering that occurs from the interactions of the agents. Extant research to understand these social coordination dynamics (SCD) has primarily examined dyadic contexts performing rhythmic tasks. To advance this area of study, we elaborate on attractor dynamics, our ability to depict them visually, and quantitatively model them. Primarily, we combine difference/differential equation modeling with mixture modeling as a way to infer the underlying topological features of the data, which can be described in terms of attractor dynamic patterns. The advantage of this approach is that we are able to quantify the self-organized dynamics that agents exhibit, link these dynamics back to activity from individual agents, and relate it to other variables central to understanding the coordinative functionality of a system's behavior. We present four examples that differ in the number of variables used to depict the attractor dynamics (1, 2, and 6) and range from simulated to non-simulated data sources. We demonstrate that this is a flexible method that advances scientific study of SCD in a variety of multi-agent systems.

Toward a social-ecological theory of forest macrosystems for improved ecosystem management

USGS Publications Warehouse

Kleindl, William J.; Stoy, Paul C.; Binford, Michael W.; Desai, Ankur R.; Dietze, Michael C.; Schultz, Courtney A.; Starr, Gregory; Staudhammer, Christina; Wood, David J. A.

2018-01-01

The implications of cumulative land-use decisions and shifting climate on forests, require us to integrate our understanding of ecosystems, markets, policy, and resource management into a social-ecological system. Humans play a central role in macrosystem dynamics, which complicates ecological theories that do not explicitly include human interactions. These dynamics also impact ecological services and related markets, which challenges economic theory. Here, we use two forest macroscale management initiatives to develop a theoretical understanding of how management interacts with ecological functions and services at these scales and how the multiple large-scale management goals work either in consort or conflict with other forest functions and services. We suggest that calling upon theories developed for organismal ecology, ecosystem ecology, and ecological economics adds to our understanding of social-ecological macrosystems. To initiate progress, we propose future research questions to add rigor to macrosystem-scale studies: (1) What are the ecosystem functions that operate at macroscales, their necessary structural components, and how do we observe them? (2) How do systems at one scale respond if altered at another scale? (3) How do we both effectively measure these components and interactions, and communicate that information in a meaningful manner for policy and management across different scales?

Co-evolutionary dynamics of the human-environment system in the Heihe River basin in the past 2000years.

PubMed

Lu, Zhixiang; Wei, Yongping; Feng, Qi; Xie, Jiali; Xiao, Honglang; Cheng, Guodong

2018-09-01

There is limited quantitative understanding of interactions between human and environmental systems over the millennial scale. We aim to reveal the co-evolutionary dynamics of the human-environment system in a river basin by simulating the water use and net primary production (NPP) allocation for human and environmental systems over the last 2000years in Heihe River basin (HRB) in northwest China. We partition the catchment total evapotranspiration (ET) into ET for human and environmental systems with a social-hydrological framework and estimate the NPP for human and environmental systems using the Box-Lieth model, then classify the co-evolutionary processes of the human-environment system into distinct phases using the rate of changes of NPP over time, and discover the trade-offs or synergies relationships between them based on the elasticity of change of the NPP for humans to the change of NPP for environment. The co-evolutionary dynamics of human-environment system in the HRB can be divided into four periods, including: Phase I (Han Dynasty-Yuan Dynasty): predevelopment characterized by nearly no trade-offs between human and environment; Phase II (Yuan Dynasty-RC): slow agricultural development: characterized by a small human win due to small trade-offs between human and environment; Phase III (RC-2000): rapid agricultural development: characterized by a large human win due to large trade-offs between human and environment, and Phase IV (2000-2010): a rebalance characterized by large human wins with a small-environment win due to synergies, although these occurred very occasionally. This study provides a quantitative approach to describe the co-evolution of the human-environment system from the perspective of trade-offs and synergies in the millennial scale for the first time. The relationships between humans and environment changed from trade-off to synergy with the implementation of the water reallocation scheme in 2000. These findings improve the understanding of how humans influence environmental systems and responses to environmental stresses. Copyright © 2018 Elsevier B.V. All rights reserved.

Dark energy in the three-body problem: Wide triple galaxies

NASA Astrophysics Data System (ADS)

Emel'yanov, N. V.; Kovalev, M. Yu.; Chernin, A. D.

2016-04-01

The structure and evolution of triple galaxy systems in the presence of the cosmic dark-energy background is studied in the framework of the three-body problem. The dynamics of wide triple systems are determinedmainly by the competition between the mutual gravitational forces between the three bodies and the anti-gravity created by the dark-energy background. This problem can be solved via numerical integration of the equations of motion with initial conditions that admit various types of evolutionary behavior of the system. Such dynamical models show that the anti-gravity created by dark energy makes a triple system less tightly bound, thereby facilitating its decay, with a subsequent transition to motion of the bodies away from each other in an accelerating regime with a linear Hubble-law dependence of the velocity on distance. The coefficient of proportionality between the velocity and distance in this asymptotic relation corresponds to the universal value H Λ = 61 km s-1 Mpc-1, which depends only on the dark-energy density. The similarity of this relation to the large-scale recession of galaxies indicates that double and triple galaxies represent elementary dynamical cells realizing the overall behavior of a system dominated by dark energy on their own scale, independent of their masses and dimensions.

A Novel Interdisciplinary Approach to Socio-Technical Complexity

NASA Astrophysics Data System (ADS)

Bassetti, Chiara

The chapter presents a novel interdisciplinary approach that integrates micro-sociological analysis into computer-vision and pattern-recognition modeling and algorithms, the purpose being to tackle socio-technical complexity at a systemic yet micro-grounded level. The approach is empirically-grounded and both theoretically- and analytically-driven, yet systemic and multidimensional, semi-supervised and computable, and oriented towards large scale applications. The chapter describes the proposed approach especially as for its sociological foundations, and as applied to the analysis of a particular setting --i.e. sport-spectator crowds. Crowds, better defined as large gatherings, are almost ever-present in our societies, and capturing their dynamics is crucial. From social sciences to public safety management and emergency response, modeling and predicting large gatherings' presence and dynamics, thus possibly preventing critical situations and being able to properly react to them, is fundamental. This is where semi/automated technologies can make the difference. The work presented in this chapter is intended as a scientific step towards such an objective.

Future changes in large-scale transport and stratosphere-troposphere exchange

NASA Astrophysics Data System (ADS)

Abalos, M.; Randel, W. J.; Kinnison, D. E.; Garcia, R. R.

2017-12-01

Future changes in large-scale transport are investigated in long-term (1955-2099) simulations of the Community Earth System Model - Whole Atmosphere Community Climate Model (CESM-WACCM) under an RCP6.0 climate change scenario. We examine artificial passive tracers in order to isolate transport changes from future changes in emissions and chemical processes. The model suggests enhanced stratosphere-troposphere exchange in both directions (STE), with decreasing tropospheric and increasing stratospheric tracer concentrations in the troposphere. Changes in the different transport processes are evaluated using the Transformed Eulerian Mean continuity equation, including parameterized convective transport. Dynamical changes associated with the rise of the tropopause height are shown to play a crucial role on future transport trends.

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

Accurate hybrid stochastic simulation of a system of coupled chemical or biochemical reactions.

PubMed

Salis, Howard; Kaznessis, Yiannis

2005-02-01

The dynamical solution of a well-mixed, nonlinear stochastic chemical kinetic system, described by the Master equation, may be exactly computed using the stochastic simulation algorithm. However, because the computational cost scales with the number of reaction occurrences, systems with one or more "fast" reactions become costly to simulate. This paper describes a hybrid stochastic method that partitions the system into subsets of fast and slow reactions, approximates the fast reactions as a continuous Markov process, using a chemical Langevin equation, and accurately describes the slow dynamics using the integral form of the "Next Reaction" variant of the stochastic simulation algorithm. The key innovation of this method is its mechanism of efficiently monitoring the occurrences of slow, discrete events while simultaneously simulating the dynamics of a continuous, stochastic or deterministic process. In addition, by introducing an approximation in which multiple slow reactions may occur within a time step of the numerical integration of the chemical Langevin equation, the hybrid stochastic method performs much faster with only a marginal decrease in accuracy. Multiple examples, including a biological pulse generator and a large-scale system benchmark, are simulated using the exact and proposed hybrid methods as well as, for comparison, a previous hybrid stochastic method. Probability distributions of the solutions are compared and the weak errors of the first two moments are computed. In general, these hybrid methods may be applied to the simulation of the dynamics of a system described by stochastic differential, ordinary differential, and Master equations.

Aftershocks following crash of currency exchange rate: The case of RUB/USD in 2014

NASA Astrophysics Data System (ADS)

Usmanova, Vasilya; Lysogorskiy, Yury V.; Abe, Sumiyoshi

2018-02-01

The dynamical behavior of the currency exchange rate after its large-scale catastrophe is discussed through a case study of the rate of Russian rubles to US dollars after its crash in 2014. It is shown that, similarly to the case of the stock market crash, the relaxation is characterized by a power law, which is in analogy with the Omori-Utsu law for earthquake aftershocks. The waiting-time distribution is found to also obey a power law. Furthermore, the event-event correlation is discussed, and the aging phenomenon and scaling property are observed. Comments are made on (non-)Markovianity of the aftershock process and on a possible relevance of glassy dynamics to the market system after the crash.

Job Management and Task Bundling

NASA Astrophysics Data System (ADS)

Berkowitz, Evan; Jansen, Gustav R.; McElvain, Kenneth; Walker-Loud, André

2018-03-01

High Performance Computing is often performed on scarce and shared computing resources. To ensure computers are used to their full capacity, administrators often incentivize large workloads that are not possible on smaller systems. Measurements in Lattice QCD frequently do not scale to machine-size workloads. By bundling tasks together we can create large jobs suitable for gigantic partitions. We discuss METAQ and mpi_jm, software developed to dynamically group computational tasks together, that can intelligently backfill to consume idle time without substantial changes to users' current workflows or executables.

Collective evolution of submicron hillocks during the early stages of anisotropic alkaline wet chemical etching of Si(1 0 0) surfaces

NASA Astrophysics Data System (ADS)

Sana, P.; Vázquez, Luis; Cuerno, Rodolfo; Sarkar, Subhendu

2017-11-01

We address experimentally the large-scale dynamics of Si(1 0 0) surfaces during the initial stages of anisotropic wet (KOH) chemical etching, which are characterized through atomic force microscopy. These systems are known to lead to the formation of characteristic pyramids, or hillocks, of typical sizes in the nanometric/micrometer scales, thus with the potential for a large number of applications that can benefit from the nanotexturing of Si surfaces. The present pattern formation process is very strongly disordered in space. We assess the space correlations in such a type of rough surface and elucidate the existence of a complex and rich morphological evolution, featuring at least three different regimes in just 10 min of etching. Such a complex time behavior cannot be consistently explained within a single formalism for dynamic scaling. The pyramidal structure reveals itself as the basic morphological motif of the surface throughout the dynamics. A detailed analysis of the surface slope distribution with etching time reveals that the texturing process induced by the KOH etching is rather gradual and progressive, which accounts for the dynamic complexity. The various stages of the morphological evolution can be accurately reproduced by computer-generated surfaces composed by uncorrelated pyramidal structures. To reach such an agreement, the key parameters are the average pyramid size, which increases with etching time, its distribution and the surface coverage by the pyramidal structures.

On the characteristics of aerosol indirect effect based on dynamic regimes in global climate models

DOE PAGES

Zhang, Shipeng; Wang, Minghuai; Ghan, Steven J.; ...

2016-03-04

Aerosol–cloud interactions continue to constitute a major source of uncertainty for the estimate of climate radiative forcing. The variation of aerosol indirect effects (AIE) in climate models is investigated across different dynamical regimes, determined by monthly mean 500 hPa vertical pressure velocity ( ω 500), lower-tropospheric stability (LTS) and large-scale surface precipitation rate derived from several global climate models (GCMs), with a focus on liquid water path (LWP) response to cloud condensation nuclei (CCN) concentrations. The LWP sensitivity to aerosol perturbation within dynamic regimes is found to exhibit a large spread among these GCMs. It is in regimes of strongmore » large-scale ascent ( ω 500  <  −25 hPa day −1) and low clouds (stratocumulus and trade wind cumulus) where the models differ most. Shortwave aerosol indirect forcing is also found to differ significantly among different regimes. Shortwave aerosol indirect forcing in ascending regimes is close to that in subsidence regimes, which indicates that regimes with strong large-scale ascent are as important as stratocumulus regimes in studying AIE. It is further shown that shortwave aerosol indirect forcing over regions with high monthly large-scale surface precipitation rate (> 0.1 mm day −1) contributes the most to the total aerosol indirect forcing (from 64 to nearly 100 %). Results show that the uncertainty in AIE is even larger within specific dynamical regimes compared to the uncertainty in its global mean values, pointing to the need to reduce the uncertainty in AIE in different dynamical regimes.« less

Timescales of Massive Human Entrainment

PubMed Central

Fusaroli, Riccardo; Perlman, Marcus; Mislove, Alan; Paxton, Alexandra; Matlock, Teenie; Dale, Rick

2015-01-01

The past two decades have seen an upsurge of interest in the collective behaviors of complex systems composed of many agents entrained to each other and to external events. In this paper, we extend the concept of entrainment to the dynamics of human collective attention. We conducted a detailed investigation of the unfolding of human entrainment—as expressed by the content and patterns of hundreds of thousands of messages on Twitter—during the 2012 US presidential debates. By time-locking these data sources, we quantify the impact of the unfolding debate on human attention at three time scales. We show that collective social behavior covaries second-by-second to the interactional dynamics of the debates: A candidate speaking induces rapid increases in mentions of his name on social media and decreases in mentions of the other candidate. Moreover, interruptions by an interlocutor increase the attention received. We also highlight a distinct time scale for the impact of salient content during the debates: Across well-known remarks in each debate, mentions in social media start within 5–10 seconds after it occurs; peak at approximately one minute; and slowly decay in a consistent fashion across well-known events during the debates. Finally, we show that public attention after an initial burst slowly decays through the course of the debates. Thus we demonstrate that large-scale human entrainment may hold across a number of distinct scales, in an exquisitely time-locked fashion. The methods and results pave the way for careful study of the dynamics and mechanisms of large-scale human entrainment. PMID:25880357

Reproducing the scaling laws for Slow and Fast ruptures

NASA Astrophysics Data System (ADS)

Romanet, Pierre; Bhat, Harsha; Madariaga, Raúl

2017-04-01

Modelling long term behaviour of large, natural fault systems, that are geometrically complex, is a challenging problem. This is why most of the research so far has concentrated on modelling the long term response of single planar fault system. To overcome this limitation, we appeal to a novel algorithm called the Fast Multipole Method which was developed in the context of modelling gravitational N-body problems. This method allows us to decrease the computational complexity of the calculation from O(N2) to O(N log N), N being the number of discretised elements on the fault. We then adapted this method to model the long term quasi-dynamic response of two faults, with step-over like geometry, that are governed by rate and state friction laws. We assume the faults have spatially uniform rate weakening friction. The results show that when stress interaction between faults is accounted, a complex spectrum of slip (including slow-slip events, dynamic ruptures and partial ruptures) emerges naturally. The simulated slow-slip and dynamic events follow the scaling law inferred by Ide et al. 2007 i. e. M ∝ T for slow-slip events and M ∝ T2 (in 2D) for dynamic events.

Potential-based dynamical reweighting for Markov state models of protein dynamics.

PubMed

Weber, Jeffrey K; Pande, Vijay S

2015-06-09

As simulators attempt to replicate the dynamics of large cellular components in silico, problems related to sampling slow, glassy degrees of freedom in molecular systems will be amplified manyfold. It is tempting to augment simulation techniques with external biases to overcome such barriers with ease; biased simulations, however, offer little utility unless equilibrium properties of interest (both kinetic and thermodynamic) can be recovered from the data generated. In this Article, we present a general scheme that harnesses the power of Markov state models (MSMs) to extract equilibrium kinetic properties from molecular dynamics trajectories collected on biased potential energy surfaces. We first validate our reweighting protocol on a simple two-well potential, and we proceed to test our method on potential-biased simulations of the Trp-cage miniprotein. In both cases, we find that equilibrium populations, time scales, and dynamical processes are reliably reproduced as compared to gold standard, unbiased data sets. We go on to discuss the limitations of our dynamical reweighting approach, and we suggest auspicious target systems for further application.

Robustness of Oscillatory Behavior in Correlated Networks

PubMed Central

Sasai, Takeyuki; Morino, Kai; Tanaka, Gouhei; Almendral, Juan A.; Aihara, Kazuyuki

2015-01-01

Understanding network robustness against failures of network units is useful for preventing large-scale breakdowns and damages in real-world networked systems. The tolerance of networked systems whose functions are maintained by collective dynamical behavior of the network units has recently been analyzed in the framework called dynamical robustness of complex networks. The effect of network structure on the dynamical robustness has been examined with various types of network topology, but the role of network assortativity, or degree–degree correlations, is still unclear. Here we study the dynamical robustness of correlated (assortative and disassortative) networks consisting of diffusively coupled oscillators. Numerical analyses for the correlated networks with Poisson and power-law degree distributions show that network assortativity enhances the dynamical robustness of the oscillator networks but the impact of network disassortativity depends on the detailed network connectivity. Furthermore, we theoretically analyze the dynamical robustness of correlated bimodal networks with two-peak degree distributions and show the positive impact of the network assortativity. PMID:25894574

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.

Capturing change: the duality of time-lapse imagery to acquire data and depict ecological dynamics

USGS Publications Warehouse

Brinley Buckley, Emma M.; Allen, Craig R.; Forsberg, Michael; Farrell, Michael; Caven, Andrew J.

2017-01-01

We investigate the scientific and communicative value of time-lapse imagery by exploring applications for data collection and visualization. Time-lapse imagery has a myriad of possible applications to study and depict ecosystems and can operate at unique temporal and spatial scales to bridge the gap between large-scale satellite imagery projects and observational field research. Time-lapse data sequences, linking time-lapse imagery with data visualization, have the ability to make data come alive for a wider audience by connecting abstract numbers to images that root data in time and place. Utilizing imagery from the Platte Basin Timelapse Project, water inundation and vegetation phenology metrics are quantified via image analysis and then paired with passive monitoring data, including streamflow and water chemistry. Dynamic and interactive time-lapse data sequences elucidate the visible and invisible ecological dynamics of a significantly altered yet internationally important river system in central Nebraska.

Towards large scale modelling of wetland water dynamics in northern basins.

NASA Astrophysics Data System (ADS)

Pedinotti, V.; Sapriza, G.; Stone, L.; Davison, B.; Pietroniro, A.; Quinton, W. L.; Spence, C.; Wheater, H. S.

2015-12-01

Understanding the hydrological behaviour of low topography, wetland-dominated sub-arctic areas is one major issue needed for the improvement of large scale hydrological models. These wet organic soils cover a large extent of Northern America and have a considerable impact on the rainfall-runoff response of a catchment. Moreover their strong interactions with the lower atmosphere and the carbon cycle make of these areas a noteworthy component of the regional climate system. In the framework of the Changing Cold Regions Network (CCRN), this study aims at providing a model for wetland water dynamics that can be used for large scale applications in cold regions. The modelling system has two main components : a) the simulation of surface runoff using the Modélisation Environmentale Communautaire - Surface and Hydrology (MESH) land surface model driven with several gridded atmospheric datasets and b) the routing of surface runoff using the WATROUTE channel scheme. As a preliminary study, we focus on two small representative study basins in Northern Canada : Scotty Creek in the lower Liard River valley of the Northwest Territories and Baker Creek, located a few kilometers north of Yellowknife. Both areas present characteristic landscapes dominated by a series of peat plateaus, channel fens, small lakes and bogs. Moreover, they constitute important fieldwork sites with detailed data to support our modelling study. The challenge of our new wetland model is to represent the hydrological functioning of the various landscape units encountered in those watersheds and their interactions using simple numerical formulations that can be later extended to larger basins such as the Mackenzie river basin. Using observed datasets, the performance of the model to simulate the temporal evolution of hydrological variables such as the water table depth, frost table depth and discharge is assessed.

Prototype Mcs Parameterization for Global Climate Models

NASA Astrophysics Data System (ADS)

Moncrieff, M. W.

2017-12-01

Excellent progress has been made with observational, numerical and theoretical studies of MCS processes but the parameterization of those processes remain in a dire state and are missing from GCMs. The perceived complexity of the distribution, type, and intensity of organized precipitation systems has arguably daunted attention and stifled the development of adequate parameterizations. TRMM observations imply links between convective organization and large-scale meteorological features in the tropics and subtropics that are inadequately treated by GCMs. This calls for improved physical-dynamical treatment of organized convection to enable the next-generation of GCMs to reliably address a slew of challenges. The multiscale coherent structure parameterization (MCSP) paradigm is based on the fluid-dynamical concept of coherent structures in turbulent environments. The effects of vertical shear on MCS dynamics implemented as 2nd baroclinic convective heating and convective momentum transport is based on Lagrangian conservation principles, nonlinear dynamical models, and self-similarity. The prototype MCS parameterization, a minimalist proof-of-concept, is applied in the NCAR Community Climate Model, Version 5.5 (CAM 5.5). The MCSP generates convectively coupled tropical waves and large-scale precipitation features notably in the Indo-Pacific warm-pool and Maritime Continent region, a center-of-action for weather and climate variability around the globe.

Regional modeling of groundwater flow and arsenic transport in the Bengal Basin: challenges of scale and complexity (Invited)

NASA Astrophysics Data System (ADS)

Michael, H. A.; Voss, C. I.

2009-12-01

Widespread arsenic poisoning is occurring in large areas of Bangladesh and West Bengal, India due to high arsenic levels in shallow groundwater, which is the primary source of irrigation and drinking water in the region. The high-arsenic groundwater exists in aquifers of the Bengal Basin, a huge sedimentary system approximately 500km x 500km wide and greater than 15km deep in places. Deeper groundwater (>150m) is nearly universally low in arsenic and a potential source of safe drinking water, but evaluation of its sustainability requires understanding of the entire, interconnected regional aquifer system. Numerical modeling of flow and arsenic transport in the basin introduces problems of scale: challenges in representing the system in enough detail to produce meaningful simulations and answer relevant questions while maintaining enough simplicity to understand controls on processes and operating within computational constraints. A regional groundwater flow and transport model of the Bengal Basin was constructed to assess the large-scale functioning of the deep groundwater flow system, the vulnerability of deep groundwater to pumping-induced migration from above, and the effect of chemical properties of sediments (sorption) on sustainability. The primary challenges include the very large spatial scale of the system, dynamic monsoonal hydrology (small temporal scale fluctuations), complex sedimentary architecture (small spatial scale heterogeneity), and a lack of reliable hydrologic and geologic data. The approach was simple. Detailed inputs were reduced to only those that affect the functioning of the deep flow system. Available data were used to estimate upscaled parameter values. Nested small-scale simulations were performed to determine the effects of the simplifications, which include treatment of the top boundary condition and transience, effects of small-scale heterogeneity, and effects of individual pumping wells. Simulation of arsenic transport at the large scale adds another element of complexity. Minimization of numerical oscillation and mass balance errors required experimentation with solvers and discretization. In the face of relatively few data in a very large-scale model, sensitivity analyses were essential. The scale of the system limits evaluation of localized behavior, but results clearly identified the primary controls on the system and effects of various pumping scenarios and sorptive properties. It was shown that limiting deep pumping to domestic supply may result in sustainable arsenic-safe water for 90% of the arsenic-affected region over a 1000 year timescale, and that sorption of arsenic onto deep, oxidized Pleistocene sediments may increase the breakthrough time in unsustainable zones by more than an order of magnitude. Thus, both hydraulic and chemical defenses indicate the potential for sustainable, managed use of deep, safe groundwater resources in the Bengal Basin.

Balance models for equatorial planetary-scale dynamics

NASA Astrophysics Data System (ADS)

Chan, Ian Hiu-Fung

This thesis aims at advancing our understanding of large-scale dynamics in the tropics, specifically the characterization of slow planetary-scale motions through a balance theory; current balance theories in the tropics are unsatisfactory as they filter out Kelvin waves, which are an important component of variability, along with fast inertia-gravity (IG) waves. (Abstract shortened by UMI.).

Experimenting with ecosystem interaction networks in search of threshold potentials in real-world marine ecosystems.

PubMed

Thrush, Simon F; Hewitt, Judi E; Parkes, Samantha; Lohrer, Andrew M; Pilditch, Conrad; Woodin, Sarah A; Wethey, David S; Chiantore, Mariachiara; Asnaghi, Valentina; De Juan, Silvia; Kraan, Casper; Rodil, Ivan; Savage, Candida; Van Colen, Carl

2014-06-01

Thresholds profoundly affect our understanding and management of ecosystem dynamics, but we have yet to develop practical techniques to assess the risk that thresholds will be crossed. Combining ecological knowledge of critical system interdependencies with a large-scale experiment, we tested for breaks in the ecosystem interaction network to identify threshold potential in real-world ecosystem dynamics. Our experiment with the bivalves Macomona liliana and Austrovenus stutchburyi on marine sandflats in New Zealand demonstrated that reductions in incident sunlight changed the interaction network between sediment biogeochemical fluxes, productivity, and macrofauna. By demonstrating loss of positive feedbacks and changes in the architecture of the network, we provide mechanistic evidence that stressors lead to break points in dynamics, which theory predicts predispose a system to a critical transition.

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