Connecting Biochemical Photosynthesis Models with Crop Models to Support Crop Improvement

PubMed Central

Wu, Alex; Song, Youhong; van Oosterom, Erik J.; Hammer, Graeme L.

2016-01-01

The next advance in field crop productivity will likely need to come from improving crop use efficiency of resources (e.g., light, water, and nitrogen), aspects of which are closely linked with overall crop photosynthetic efficiency. Progress in genetic manipulation of photosynthesis is confounded by uncertainties of consequences at crop level because of difficulties connecting across scales. Crop growth and development simulation models that integrate across biological levels of organization and use a gene-to-phenotype modeling approach may present a way forward. There has been a long history of development of crop models capable of simulating dynamics of crop physiological attributes. Many crop models incorporate canopy photosynthesis (source) as a key driver for crop growth, while others derive crop growth from the balance between source- and sink-limitations. Modeling leaf photosynthesis has progressed from empirical modeling via light response curves to a more mechanistic basis, having clearer links to the underlying biochemical processes of photosynthesis. Cross-scale modeling that connects models at the biochemical and crop levels and utilizes developments in upscaling leaf-level models to canopy models has the potential to bridge the gap between photosynthetic manipulation at the biochemical level and its consequences on crop productivity. Here we review approaches to this emerging cross-scale modeling framework and reinforce the need for connections across levels of modeling. Further, we propose strategies for connecting biochemical models of photosynthesis into the cross-scale modeling framework to support crop improvement through photosynthetic manipulation. PMID:27790232

Connecting Biochemical Photosynthesis Models with Crop Models to Support Crop Improvement.

PubMed

Wu, Alex; Song, Youhong; van Oosterom, Erik J; Hammer, Graeme L

2016-01-01

The next advance in field crop productivity will likely need to come from improving crop use efficiency of resources (e.g., light, water, and nitrogen), aspects of which are closely linked with overall crop photosynthetic efficiency. Progress in genetic manipulation of photosynthesis is confounded by uncertainties of consequences at crop level because of difficulties connecting across scales. Crop growth and development simulation models that integrate across biological levels of organization and use a gene-to-phenotype modeling approach may present a way forward. There has been a long history of development of crop models capable of simulating dynamics of crop physiological attributes. Many crop models incorporate canopy photosynthesis (source) as a key driver for crop growth, while others derive crop growth from the balance between source- and sink-limitations. Modeling leaf photosynthesis has progressed from empirical modeling via light response curves to a more mechanistic basis, having clearer links to the underlying biochemical processes of photosynthesis. Cross-scale modeling that connects models at the biochemical and crop levels and utilizes developments in upscaling leaf-level models to canopy models has the potential to bridge the gap between photosynthetic manipulation at the biochemical level and its consequences on crop productivity. Here we review approaches to this emerging cross-scale modeling framework and reinforce the need for connections across levels of modeling. Further, we propose strategies for connecting biochemical models of photosynthesis into the cross-scale modeling framework to support crop improvement through photosynthetic manipulation.

Inferring multi-scale neural mechanisms with brain network modelling

PubMed Central

Schirner, Michael; McIntosh, Anthony Randal; Jirsa, Viktor; Deco, Gustavo

2018-01-01

The neurophysiological processes underlying non-invasive brain activity measurements are incompletely understood. Here, we developed a connectome-based brain network model that integrates individual structural and functional data with neural population dynamics to support multi-scale neurophysiological inference. Simulated populations were linked by structural connectivity and, as a novelty, driven by electroencephalography (EEG) source activity. Simulations not only predicted subjects' individual resting-state functional magnetic resonance imaging (fMRI) time series and spatial network topologies over 20 minutes of activity, but more importantly, they also revealed precise neurophysiological mechanisms that underlie and link six empirical observations from different scales and modalities: (1) resting-state fMRI oscillations, (2) functional connectivity networks, (3) excitation-inhibition balance, (4, 5) inverse relationships between α-rhythms, spike-firing and fMRI on short and long time scales, and (6) fMRI power-law scaling. These findings underscore the potential of this new modelling framework for general inference and integration of neurophysiological knowledge to complement empirical studies. PMID:29308767

An Interactive Simulation Program for Exploring Computational Models of Auto-Associative Memory.

PubMed

Fink, Christian G

2017-01-01

While neuroscience students typically learn about activity-dependent plasticity early in their education, they often struggle to conceptually connect modification at the synaptic scale with network-level neuronal dynamics, not to mention with their own everyday experience of recalling a memory. We have developed an interactive simulation program (based on the Hopfield model of auto-associative memory) that enables the user to visualize the connections generated by any pattern of neural activity, as well as to simulate the network dynamics resulting from such connectivity. An accompanying set of student exercises introduces the concepts of pattern completion, pattern separation, and sparse versus distributed neural representations. Results from a conceptual assessment administered before and after students worked through these exercises indicate that the simulation program is a useful pedagogical tool for illustrating fundamental concepts of computational models of memory.

WE-DE-202-00: Connecting Radiation Physics with Computational Biology

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

NONE

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

Pore-Scale Simulation and Sensitivity Analysis of Apparent Gas Permeability in Shale Matrix

PubMed Central

Zhang, Pengwei; Hu, Liming; Meegoda, Jay N.

2017-01-01

Extremely low permeability due to nano-scale pores is a distinctive feature of gas transport in a shale matrix. The permeability of shale depends on pore pressure, porosity, pore throat size and gas type. The pore network model is a practical way to explain the macro flow behavior of porous media from a microscopic point of view. In this research, gas flow in a shale matrix is simulated using a previously developed three-dimensional pore network model that includes typical bimodal pore size distribution, anisotropy and low connectivity of the pore structure in shale. The apparent gas permeability of shale matrix was calculated under different reservoir pressures corresponding to different gas exploitation stages. Results indicate that gas permeability is strongly related to reservoir gas pressure, and hence the apparent permeability is not a unique value during the shale gas exploitation, and simulations suggested that a constant permeability for continuum-scale simulation is not accurate. Hence, the reservoir pressures of different shale gas exploitations should be considered. In addition, a sensitivity analysis was also performed to determine the contributions to apparent permeability of a shale matrix from petro-physical properties of shale such as pore throat size and porosity. Finally, the impact of connectivity of nano-scale pores on shale gas flux was analyzed. These results would provide an insight into understanding nano/micro scale flows of shale gas in the shale matrix. PMID:28772465

Pore-Scale Simulation and Sensitivity Analysis of Apparent Gas Permeability in Shale Matrix.

PubMed

Zhang, Pengwei; Hu, Liming; Meegoda, Jay N

2017-01-25

Extremely low permeability due to nano-scale pores is a distinctive feature of gas transport in a shale matrix. The permeability of shale depends on pore pressure, porosity, pore throat size and gas type. The pore network model is a practical way to explain the macro flow behavior of porous media from a microscopic point of view. In this research, gas flow in a shale matrix is simulated using a previously developed three-dimensional pore network model that includes typical bimodal pore size distribution, anisotropy and low connectivity of the pore structure in shale. The apparent gas permeability of shale matrix was calculated under different reservoir pressures corresponding to different gas exploitation stages. Results indicate that gas permeability is strongly related to reservoir gas pressure, and hence the apparent permeability is not a unique value during the shale gas exploitation, and simulations suggested that a constant permeability for continuum-scale simulation is not accurate. Hence, the reservoir pressures of different shale gas exploitations should be considered. In addition, a sensitivity analysis was also performed to determine the contributions to apparent permeability of a shale matrix from petro-physical properties of shale such as pore throat size and porosity. Finally, the impact of connectivity of nano-scale pores on shale gas flux was analyzed. These results would provide an insight into understanding nano/micro scale flows of shale gas in the shale matrix.

Exploring connectivity with large-scale Granger causality on resting-state functional MRI.

PubMed

DSouza, Adora M; Abidin, Anas Z; Leistritz, Lutz; Wismüller, Axel

2017-08-01

Large-scale Granger causality (lsGC) is a recently developed, resting-state functional MRI (fMRI) connectivity analysis approach that estimates multivariate voxel-resolution connectivity. Unlike most commonly used multivariate approaches, which establish coarse-resolution connectivity by aggregating voxel time-series avoiding an underdetermined problem, lsGC estimates voxel-resolution, fine-grained connectivity by incorporating an embedded dimension reduction. We investigate application of lsGC on realistic fMRI simulations, modeling smoothing of neuronal activity by the hemodynamic response function and repetition time (TR), and empirical resting-state fMRI data. Subsequently, functional subnetworks are extracted from lsGC connectivity measures for both datasets and validated quantitatively. We also provide guidelines to select lsGC free parameters. Results indicate that lsGC reliably recovers underlying network structure with area under receiver operator characteristic curve (AUC) of 0.93 at TR=1.5s for a 10-min session of fMRI simulations. Furthermore, subnetworks of closely interacting modules are recovered from the aforementioned lsGC networks. Results on empirical resting-state fMRI data demonstrate recovery of visual and motor cortex in close agreement with spatial maps obtained from (i) visuo-motor fMRI stimulation task-sequence (Accuracy=0.76) and (ii) independent component analysis (ICA) of resting-state fMRI (Accuracy=0.86). Compared with conventional Granger causality approach (AUC=0.75), lsGC produces better network recovery on fMRI simulations. Furthermore, it cannot recover functional subnetworks from empirical fMRI data, since quantifying voxel-resolution connectivity is not possible as consequence of encountering an underdetermined problem. Functional network recovery from fMRI data suggests that lsGC gives useful insight into connectivity patterns from resting-state fMRI at a multivariate voxel-resolution. Copyright © 2017 Elsevier B.V. All rights reserved.

On nodes and modes in resting state fMRI

PubMed Central

Friston, Karl J.; Kahan, Joshua; Razi, Adeel; Stephan, Klaas Enno; Sporns, Olaf

2014-01-01

This paper examines intrinsic brain networks in light of recent developments in the characterisation of resting state fMRI timeseries — and simulations of neuronal fluctuations based upon the connectome. Its particular focus is on patterns or modes of distributed activity that underlie functional connectivity. We first demonstrate that the eigenmodes of functional connectivity – or covariance among regions or nodes – are the same as the eigenmodes of the underlying effective connectivity, provided we limit ourselves to symmetrical connections. This symmetry constraint is motivated by appealing to proximity graphs based upon multidimensional scaling. Crucially, the principal modes of functional connectivity correspond to the dynamically unstable modes of effective connectivity that decay slowly and show long term memory. Technically, these modes have small negative Lyapunov exponents that approach zero from below. Interestingly, the superposition of modes – whose exponents are sampled from a power law distribution – produces classical 1/f (scale free) spectra. We conjecture that the emergence of dynamical instability – that underlies intrinsic brain networks – is inevitable in any system that is separated from external states by a Markov blanket. This conjecture appeals to a free energy formulation of nonequilibrium steady-state dynamics. The common theme that emerges from these theoretical considerations is that endogenous fluctuations are dominated by a small number of dynamically unstable modes. We use this as the basis of a dynamic causal model (DCM) of resting state fluctuations — as measured in terms of their complex cross spectra. In this model, effective connectivity is parameterised in terms of eigenmodes and their Lyapunov exponents — that can also be interpreted as locations in a multidimensional scaling space. Model inversion provides not only estimates of edges or connectivity but also the topography and dimensionality of the underlying scaling space. Here, we focus on conceptual issues with simulated fMRI data and provide an illustrative application using an empirical multi-region timeseries. PMID:24862075

Linking a one-dimensional pesticide fate model to a three-dimensional groundwater model to simulate pollution risks of shallow and deep groundwater underlying fractured till.

PubMed

Stenemo, Fredrik; Jørgensen, Peter R; Jarvis, Nicholas

2005-09-01

The one-dimensional pesticide fate model MACRO was loose-linked to the three-dimensional discrete fracture/matrix diffusion model FRAC3DVS to describe transport of the pesticide mecoprop in a fractured moraine till and local sand aquifer (5-5.5 m depth) overlying a regional limestone aquifer (16 m depth) at Havdrup, Denmark. Alternative approaches to describe the upper boundary in the groundwater model were examined. Field-scale simulations were run to compare a uniform upper boundary condition with a spatially variable upper boundary derived from Monte-Carlo simulations with MACRO. Plot-scale simulations were run to investigate the influence of the temporal resolution of the upper boundary conditions for fluxes in the groundwater model and the effects of different assumptions concerning the macropore/fracture connectivity between the two models. The influence of within-field variability of leaching on simulated mecoprop concentrations in the local aquifer was relatively small. A fully transient simulation with FRAC3DVS gave 20 times larger leaching to the regional aquifer compared to the case with steady-state water flow, assuming full connectivity with respect to macropores/fractures across the boundary between the two models. For fully transient simulations 'disconnecting' the macropores/fractures at the interface between the two models reduced leaching by a factor 24. A fully connected, transient simulation with FRAC3DVS, with spatially uniform upper boundary fluxes derived from a MACRO simulation with 'effective' parameters is therefore recommended for assessing leaching risks to the regional aquifer, at this, and similar sites.

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.

An Integrated Modeling and Simulation Methodology for Intelligent Systems Design and Testing

DTIC Science & Technology

2002-08-01

simulation and actual execution. KEYWORDS: Model Continuity, Modeling, Simulation, Experimental Frame, Real Time Systems , Intelligent Systems...the methodology for a stand-alone real time system. Then it will scale up to distributed real time systems . For both systems, step-wise simulation...MODEL CONTINUITY Intelligent real time systems monitor, respond to, or control, an external environment. This environment is connected to the digital

Impact of bias correction and downscaling through quantile mapping on simulated climate change signal: a case study over Central Italy

NASA Astrophysics Data System (ADS)

Sangelantoni, Lorenzo; Russo, Aniello; Gennaretti, Fabio

2018-02-01

Quantile mapping (QM) represents a common post-processing technique used to connect climate simulations to impact studies at different spatial scales. Depending on the simulation-observation spatial scale mismatch, QM can be used for two different applications. The first application uses only the bias correction component, establishing transfer functions between observations and simulations at similar spatial scales. The second application includes a statistical downscaling component when point-scale observations are considered. However, knowledge of alterations to climate change signal (CCS) resulting from these two applications is limited. This study investigates QM impacts on the original temperature and precipitation CCSs when applied according to a bias correction only (BC-only) and a bias correction plus downscaling (BC + DS) application over reference stations in Central Italy. BC-only application is used to adjust regional climate model (RCM) simulations having the same resolution as the observation grid. QM BC + DS application adjusts the same simulations to point-wise observations. QM applications alter CCS mainly for temperature. BC-only application produces a CCS of the median 1 °C lower than the original ( 4.5 °C). BC + DS application produces CCS closer to the original, except over the summer 95th percentile, where substantial amplification of the original CCS resulted. The impacts of the two applications are connected to the ratio between the observed and the simulated standard deviation (STD) of the calibration period. For the precipitation, original CCS is essentially preserved in both applications. Yet, calibration period STD ratio cannot predict QM impact on the precipitation CCS when simulated STD and mean are similarly misrepresented.

Structural connectivity in schizophrenia and its impact on the dynamics of spontaneous functional networks

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

Cabral, Joana; Department of Psychiatry, University of Oxford, Oxford OX3 7JX; Fernandes, Henrique M.

The neuropathology of schizophrenia remains unclear. Some insight has come from modern neuroimaging techniques, which offer an unparalleled opportunity to explore in vivo the structure and function of the brain. Using functional magnetic resonance imaging, it has been found that the large-scale resting-state functional connectivity (rsFC) in schizophrenia — measured as the temporal correlations of the blood-oxygen-level-dependent (BOLD) signal — exhibit altered network topology, with lower small-world index. The origin of these rsFC alterations and link with the underlying structural connectivity remain unclear. In this work, we used a computational model of spontaneous large-scale brain activity to explore the rolemore » of the structural connectivity in the large-scale dynamics of the brain in health and schizophrenia. The structural connectomes from 15 adolescent patients with early-onset schizophrenia and 15 age- and gender-matched controls were built from diffusion tensor imaging data to detect the white matter tracts between 90 brain areas. Brain areas, simulated using a reduced dynamic mean-field model, receive excitatory input from other areas in proportion to the number of fibre tracts between them. The simulated mean field activity was transformed into BOLD signal, and the properties of the simulated functional networks were analyzed. Our results suggest that the functional alterations observed in schizophrenia are not directly linked to alterations in the structural topology. Instead, subtly randomized and less small-world functional networks appear when the brain operates with lower global coupling, which shifts the dynamics from the optimal healthy regime.« less

Structural connectivity in schizophrenia and its impact on the dynamics of spontaneous functional networks

NASA Astrophysics Data System (ADS)

Cabral, Joana; Fernandes, Henrique M.; Van Hartevelt, Tim J.; James, Anthony C.; Kringelbach, Morten L.; Deco, Gustavo

2013-12-01

The neuropathology of schizophrenia remains unclear. Some insight has come from modern neuroimaging techniques, which offer an unparalleled opportunity to explore in vivo the structure and function of the brain. Using functional magnetic resonance imaging, it has been found that the large-scale resting-state functional connectivity (rsFC) in schizophrenia — measured as the temporal correlations of the blood-oxygen-level-dependent (BOLD) signal — exhibit altered network topology, with lower small-world index. The origin of these rsFC alterations and link with the underlying structural connectivity remain unclear. In this work, we used a computational model of spontaneous large-scale brain activity to explore the role of the structural connectivity in the large-scale dynamics of the brain in health and schizophrenia. The structural connectomes from 15 adolescent patients with early-onset schizophrenia and 15 age- and gender-matched controls were built from diffusion tensor imaging data to detect the white matter tracts between 90 brain areas. Brain areas, simulated using a reduced dynamic mean-field model, receive excitatory input from other areas in proportion to the number of fibre tracts between them. The simulated mean field activity was transformed into BOLD signal, and the properties of the simulated functional networks were analyzed. Our results suggest that the functional alterations observed in schizophrenia are not directly linked to alterations in the structural topology. Instead, subtly randomized and less small-world functional networks appear when the brain operates with lower global coupling, which shifts the dynamics from the optimal healthy regime.

Small-scale multi-axial hybrid simulation of a shear-critical reinforced concrete frame

NASA Astrophysics Data System (ADS)

Sadeghian, Vahid; Kwon, Oh-Sung; Vecchio, Frank

2017-10-01

This study presents a numerical multi-scale simulation framework which is extended to accommodate hybrid simulation (numerical-experimental integration). The framework is enhanced with a standardized data exchange format and connected to a generalized controller interface program which facilitates communication with various types of laboratory equipment and testing configurations. A small-scale experimental program was conducted using a six degree-of-freedom hydraulic testing equipment to verify the proposed framework and provide additional data for small-scale testing of shearcritical reinforced concrete structures. The specimens were tested in a multi-axial hybrid simulation manner under a reversed cyclic loading condition simulating earthquake forces. The physical models were 1/3.23-scale representations of a beam and two columns. A mixed-type modelling technique was employed to analyze the remainder of the structures. The hybrid simulation results were compared against those obtained from a large-scale test and finite element analyses. The study found that if precautions are taken in preparing model materials and if the shear-related mechanisms are accurately considered in the numerical model, small-scale hybrid simulations can adequately simulate the behaviour of shear-critical structures. Although the findings of the study are promising, to draw general conclusions additional test data are required.

MODELING SCALE-DEPENDENT LANDSCAPE PATTERN, DISPERSAL, AND CONNECTIVITY FROM THE PERSPECTIVE OF THE ORGANISM

EPA Science Inventory

Effects of fine- to broad-scale patterns of landscape heterogeneity on dispersal success were examined for organisms varying in life history traits. To systematically control spatial pattern, a landscape model was created by merging physiographically-based maps of simulated land...

Better models are more effectively connected models

NASA Astrophysics Data System (ADS)

Nunes, João Pedro; Bielders, Charles; Darboux, Frederic; Fiener, Peter; Finger, David; Turnbull-Lloyd, Laura; Wainwright, John

2016-04-01

The concept of hydrologic and geomorphologic connectivity describes the processes and pathways which link sources (e.g. rainfall, snow and ice melt, springs, eroded areas and barren lands) to accumulation areas (e.g. foot slopes, streams, aquifers, reservoirs), and the spatial variations thereof. There are many examples of hydrological and sediment connectivity on a watershed scale; in consequence, a process-based understanding of connectivity is crucial to help managers understand their systems and adopt adequate measures for flood prevention, pollution mitigation and soil protection, among others. Modelling is often used as a tool to understand and predict fluxes within a catchment by complementing observations with model results. Catchment models should therefore be able to reproduce the linkages, and thus the connectivity of water and sediment fluxes within the systems under simulation. In modelling, a high level of spatial and temporal detail is desirable to ensure taking into account a maximum number of components, which then enables connectivity to emerge from the simulated structures and functions. However, computational constraints and, in many cases, lack of data prevent the representation of all relevant processes and spatial/temporal variability in most models. In most cases, therefore, the level of detail selected for modelling is too coarse to represent the system in a way in which connectivity can emerge; a problem which can be circumvented by representing fine-scale structures and processes within coarser scale models using a variety of approaches. This poster focuses on the results of ongoing discussions on modelling connectivity held during several workshops within COST Action Connecteur. It assesses the current state of the art of incorporating the concept of connectivity in hydrological and sediment models, as well as the attitudes of modellers towards this issue. The discussion will focus on the different approaches through which connectivity can be represented in models: either by allowing it to emerge from model behaviour or by parameterizing it inside model structures; and on the appropriate scale at which processes should be represented explicitly or implicitly. It will also explore how modellers themselves approach connectivity through the results of a community survey. Finally, it will present the outline of an international modelling exercise aimed at assessing how different modelling concepts can capture connectivity in real catchments.

Enabling Functional Neural Circuit Simulations with Distributed Computing of Neuromodulated Plasticity

PubMed Central

Potjans, Wiebke; Morrison, Abigail; Diesmann, Markus

2010-01-01

A major puzzle in the field of computational neuroscience is how to relate system-level learning in higher organisms to synaptic plasticity. Recently, plasticity rules depending not only on pre- and post-synaptic activity but also on a third, non-local neuromodulatory signal have emerged as key candidates to bridge the gap between the macroscopic and the microscopic level of learning. Crucial insights into this topic are expected to be gained from simulations of neural systems, as these allow the simultaneous study of the multiple spatial and temporal scales that are involved in the problem. In particular, synaptic plasticity can be studied during the whole learning process, i.e., on a time scale of minutes to hours and across multiple brain areas. Implementing neuromodulated plasticity in large-scale network simulations where the neuromodulatory signal is dynamically generated by the network itself is challenging, because the network structure is commonly defined purely by the connectivity graph without explicit reference to the embedding of the nodes in physical space. Furthermore, the simulation of networks with realistic connectivity entails the use of distributed computing. A neuromodulated synapse must therefore be informed in an efficient way about the neuromodulatory signal, which is typically generated by a population of neurons located on different machines than either the pre- or post-synaptic neuron. Here, we develop a general framework to solve the problem of implementing neuromodulated plasticity in a time-driven distributed simulation, without reference to a particular implementation language, neuromodulator, or neuromodulated plasticity mechanism. We implement our framework in the simulator NEST and demonstrate excellent scaling up to 1024 processors for simulations of a recurrent network incorporating neuromodulated spike-timing dependent plasticity. PMID:21151370

WE-DE-202-02: Are Track Structure Simulations Truly Needed for Radiobiology at the Cellular and Tissue Levels?

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

Stewart, R.

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

On the connectivity of the cosmic web: theory and implications for cosmology and galaxy formation

NASA Astrophysics Data System (ADS)

Codis, Sandrine; Pogosyan, Dmitri; Pichon, Christophe

2018-06-01

Cosmic connectivity and multiplicity, i.e. the number of filaments globally or locally connected to a given cluster is a natural probe of the growth of structure and in particular of the nature of dark energy. It is also a critical ingredient driving the assembly history of galaxies as it controls mass and angular momentum accretion. The connectivity of the cosmic web is investigated here via the persistent skeleton. This tool identifies topologically the ridges of the cosmic landscape which allows us to investigate how the nodes of the cosmic web are connected together. When applied to Gaussian random fields corresponding to the high redshift universe, it is found that on average the nodes are connected to exactly κ = 4 neighbours in two dimensions and ˜6.1 in three dimensions. Investigating spatial dimensions up to d = 6, typical departures from a cubic lattice κ = 2d are shown to scale like the power 7/4 of the dimension. These numbers strongly depend on the height of the peaks: the higher the peak the larger the connectivity. Predictions from first principles based on peak theory are shown to reproduce well the connectivity and multiplicity of Gaussian random fields and cosmological simulations. As an illustration, connectivity is quantified in galaxy lensing convergence maps and large dark haloes catalogues. As a function of redshift and scale the mean connectivity decreases in a cosmology-dependent way. As a function of halo mass it scales like 10/3 times the log of the mass. Implications on galactic scales are discussed.

Mapping sources, sinks, and connectivity using a simulation model of Northern Spotted Owls

EPA Science Inventory

This is a study of source-sink dynamics at a landscape scale. In conducting the study, we make use of a mature simulation model for the northern spotted owl (Strix occidentalis caurina) that was developed as part of the US Fish and Wildlife Service’s most recent recovery plannin...

Dimensionless, Scale Invariant, Edge Weight Metric for the Study of Complex Structural Networks

PubMed Central

Colon-Perez, Luis M.; Spindler, Caitlin; Goicochea, Shelby; Triplett, William; Parekh, Mansi; Montie, Eric; Carney, Paul R.; Price, Catherine; Mareci, Thomas H.

2015-01-01

High spatial and angular resolution diffusion weighted imaging (DWI) with network analysis provides a unique framework for the study of brain structure in vivo. DWI-derived brain connectivity patterns are best characterized with graph theory using an edge weight to quantify the strength of white matter connections between gray matter nodes. Here a dimensionless, scale-invariant edge weight is introduced to measure node connectivity. This edge weight metric provides reasonable and consistent values over any size scale (e.g. rodents to humans) used to quantify the strength of connection. Firstly, simulations were used to assess the effects of tractography seed point density and random errors in the estimated fiber orientations; with sufficient signal-to-noise ratio (SNR), edge weight estimates improve as the seed density increases. Secondly to evaluate the application of the edge weight in the human brain, ten repeated measures of DWI in the same healthy human subject were analyzed. Mean edge weight values within the cingulum and corpus callosum were consistent and showed low variability. Thirdly, using excised rat brains to study the effects of spatial resolution, the weight of edges connecting major structures in the temporal lobe were used to characterize connectivity in this local network. The results indicate that with adequate resolution and SNR, connections between network nodes are characterized well by this edge weight metric. Therefore this new dimensionless, scale-invariant edge weight metric provides a robust measure of network connectivity that can be applied in any size regime. PMID:26173147

Dimensionless, Scale Invariant, Edge Weight Metric for the Study of Complex Structural Networks.

PubMed

Colon-Perez, Luis M; Spindler, Caitlin; Goicochea, Shelby; Triplett, William; Parekh, Mansi; Montie, Eric; Carney, Paul R; Price, Catherine; Mareci, Thomas H

2015-01-01

High spatial and angular resolution diffusion weighted imaging (DWI) with network analysis provides a unique framework for the study of brain structure in vivo. DWI-derived brain connectivity patterns are best characterized with graph theory using an edge weight to quantify the strength of white matter connections between gray matter nodes. Here a dimensionless, scale-invariant edge weight is introduced to measure node connectivity. This edge weight metric provides reasonable and consistent values over any size scale (e.g. rodents to humans) used to quantify the strength of connection. Firstly, simulations were used to assess the effects of tractography seed point density and random errors in the estimated fiber orientations; with sufficient signal-to-noise ratio (SNR), edge weight estimates improve as the seed density increases. Secondly to evaluate the application of the edge weight in the human brain, ten repeated measures of DWI in the same healthy human subject were analyzed. Mean edge weight values within the cingulum and corpus callosum were consistent and showed low variability. Thirdly, using excised rat brains to study the effects of spatial resolution, the weight of edges connecting major structures in the temporal lobe were used to characterize connectivity in this local network. The results indicate that with adequate resolution and SNR, connections between network nodes are characterized well by this edge weight metric. Therefore this new dimensionless, scale-invariant edge weight metric provides a robust measure of network connectivity that can be applied in any size regime.

Perturbative approach to covariance matrix of the matter power spectrum

NASA Astrophysics Data System (ADS)

Mohammed, Irshad; Seljak, Uroš; Vlah, Zvonimir

2017-04-01

We evaluate the covariance matrix of the matter power spectrum using perturbation theory up to dominant terms at 1-loop order and compare it to numerical simulations. We decompose the covariance matrix into the disconnected (Gaussian) part, trispectrum from the modes outside the survey (supersample variance) and trispectrum from the modes inside the survey, and show how the different components contribute to the overall covariance matrix. We find the agreement with the simulations is at a 10 per cent level up to k ˜ 1 h Mpc-1. We show that all the connected components are dominated by the large-scale modes (k < 0.1 h Mpc-1), regardless of the value of the wave vectors k, k΄ of the covariance matrix, suggesting that one must be careful in applying the jackknife or bootstrap methods to the covariance matrix. We perform an eigenmode decomposition of the connected part of the covariance matrix, showing that at higher k, it is dominated by a single eigenmode. The full covariance matrix can be approximated as the disconnected part only, with the connected part being treated as an external nuisance parameter with a known scale dependence, and a known prior on its variance for a given survey volume. Finally, we provide a prescription for how to evaluate the covariance matrix from small box simulations without the need to simulate large volumes.

Extending atomistic scale chemistry to mesoscale model of condensed-phase deflagration

NASA Astrophysics Data System (ADS)

Joshi, Kaushik; Chaudhuri, Santanu

2017-01-01

Predictive simulations connecting chemistry that follow the shock or thermal initiation of energetic materials to subsequent deflagration or detonation events is currently outside the realm of possibilities. Molecular dynamics and first-principles based dynamics have made progress in understanding reactions in picosecond to nanosecond time scale. Results from thermal ignition of different phases of RDX show a complex reaction network and emergence of a deterministic behavior for critical temperature before ignition and hot spot growth rates. The kinetics observed is dependent on the hot spot temperature, system size and thermal conductivity. For cases where ignition is observed, the incubation period is dominated by intermolecular and intramolecular hydrogen transfer reactions. The gradual temperature and pressure increase in the incubation period is accompanied by accumulation of heavier polyradicals. The challenge of connecting such chemistry in mesoscale simulations remain in reducing the complexity of chemistry. The hot spot growth kinetics in RDX grains and interfaces is an important challenge for reactive simulations aiming to fill in the gaps in our knowledge in the nanoseconds to microseconds time scale. The results discussed indicate that the mesoscale chemistry may include large polyradical molecules in dense reactive mix reaching an instability point at certain temperatures and pressures.

A Biophysical Model for Hawaiian Coral Reefs: Coupling Local Ecology, Larval Transport and Climate Change

NASA Astrophysics Data System (ADS)

Kapur, M. R.

2016-02-01

Simulative models of reef ecosystems have been used to evaluate ecological responses to a myriad of disturbance events, including fishing pressure, coral bleaching, invasion by alien species, and nutrient loading. The Coral Reef Scenario Evaluation Tool (CORSET), has been developed and instantiated for both the Meso-American Reef (MAR) and South China Sea (SCS) regions. This model is novel in that it accounts for the many scales at which reef ecosystem processes take place; is comprised of a "bottom-up" structure wherein complex behaviors are not pre-programmed, but emergent and highly portable to new systems. Local-scale dynamics are coupled across regions through larval connectivity matrices, derived sophisticated particle transport simulations that include key elements of larval behavior. By this approach, we are able to directly evaluate some of the potential consequences of larval connectivity patterns across a range of spatial scales and under multiple climate scenarios. This work develops and applies the CORSET (Coral Reef Scenario Evaluation Tool) to the Main Hawaiian Islands under a suite of climate and ecological scenarios. We introduce an adaptation constant into reef-building coral dynamics to simulate observed resiliencies to bleaching events. This presentation will share results from the model's instantiation under two Resource Concentration Pathway climate scenarios, with emphasis upon larval connectivity dynamics, emergent coral tolerance to increasing thermal anomalies, and patterns of spatial fishing closures. Results suggest that under a business-as-usual scenario, thermal tolerance and herbivore removal will have synergistic effects on reef resilience.

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

McMahon, S.

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

Wind-driven variations in an overturning circulation

NASA Astrophysics Data System (ADS)

Bringedal, Carina; Eldevik, Tor; Spall, Michael

2017-04-01

The Atlantic overturning circulation and poleward heat transport is balanced by northern heat loss to the atmosphere and corresponding water mass transformation. The structure of this circulation and transformation is particularly manifested - and observed - at the Greenland-Scotland ridge. There is however a rich variability in the exchanges across the ridge on seasonal and yearly time scales. This variability has been almost perfectly captured in atmospherically forced ocean GCMs (e.g. Olsen et al 2008, Sandø et al 2012), suggesting that on shorter time scales the variability of the exchanges are connected to sea level pressure and corresponding wind stress forcing. Focusing on seasonal and yearly time scales, we accordingly propose that the connection between the exchanges of overturning waters across the Greenland-Scotland ridge and the sea level pressure must be direct and simple, and we use idealized simulations to support this hypothesis. The mechanisms underlying the connection are formulated through conceptual models. Although the models and simulations are simplified with respect to bathymetry and hydrography, they can reproduce the main features of the overturning circulation in the Nordic seas. In the observations, the variable exchanges can largely be related to sea level pressure variations and large scale wind patterns, and the idealized simulations and accompanying conceptual models show how these impacts can manifest via coastal downwelling and gyre circulation. S. M. Olsen, B. Hansen, D. Quadfasel and S. Østerhus, Observed and modelled stability of overflow across the Greenland-Scotland ridge, Nature 455, (2008) A. B. Sandø, J. E. Ø. Nilsen, T. Eldevik and M. Bentsen, Mechanisms for variable North Atlantic-Nordic seas exchanges, Journal of Geophysical Research 117, (2012)

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.

Neuron array with plastic synapses and programmable dendrites.

PubMed

Ramakrishnan, Shubha; Wunderlich, Richard; Hasler, Jennifer; George, Suma

2013-10-01

We describe a novel neuromorphic chip architecture that models neurons for efficient computation. Traditional architectures of neuron array chips consist of large scale systems that are interfaced with AER for implementing intra- or inter-chip connectivity. We present a chip that uses AER for inter-chip communication but uses fast, reconfigurable FPGA-style routing with local memory for intra-chip connectivity. We model neurons with biologically realistic channel models, synapses and dendrites. This chip is suitable for small-scale network simulations and can also be used for sequence detection, utilizing directional selectivity properties of dendrites, ultimately for use in word recognition.

Robust quantum optimizer with full connectivity.

PubMed

Nigg, Simon E; Lörch, Niels; Tiwari, Rakesh P

2017-04-01

Quantum phenomena have the potential to speed up the solution of hard optimization problems. For example, quantum annealing, based on the quantum tunneling effect, has recently been shown to scale exponentially better with system size than classical simulated annealing. However, current realizations of quantum annealers with superconducting qubits face two major challenges. First, the connectivity between the qubits is limited, excluding many optimization problems from a direct implementation. Second, decoherence degrades the success probability of the optimization. We address both of these shortcomings and propose an architecture in which the qubits are robustly encoded in continuous variable degrees of freedom. By leveraging the phenomenon of flux quantization, all-to-all connectivity with sufficient tunability to implement many relevant optimization problems is obtained without overhead. Furthermore, we demonstrate the robustness of this architecture by simulating the optimal solution of a small instance of the nondeterministic polynomial-time hard (NP-hard) and fully connected number partitioning problem in the presence of dissipation.

LES-based generation of high-frequency fluctuation in wind turbulence obtained by meteorological model

NASA Astrophysics Data System (ADS)

Tamura, Tetsuro; Kawaguchi, Masaharu; Kawai, Hidenori; Tao, Tao

2017-11-01

The connection between a meso-scale model and a micro-scale large eddy simulation (LES) is significant to simulate the micro-scale meteorological problem such as strong convective events due to the typhoon or the tornado using LES. In these problems the mean velocity profiles and the mean wind directions change with time according to the movement of the typhoons or tornadoes. Although, a fine grid micro-scale LES could not be connected to a coarse grid meso-scale WRF directly. In LES when the grid is suddenly refined at the interface of nested grids which is normal to the mean advection the resolved shear stresses decrease due to the interpolation errors and the delay of the generation of smaller scale turbulence that can be resolved on the finer mesh. For the estimation of wind gust disaster the peak wind acting on buildings and structures has to be correctly predicted. In the case of meteorological model the velocity fluctuations have a tendency of diffusive variation without the high frequency component due to the numerically filtering effects. In order to predict the peak value of wind velocity with good accuracy, this paper proposes a LES-based method for generating the higher frequency components of velocity and temperature fields obtained by meteorological model.

Understanding large-scale, long-term larval connectivity patterns: The case of the Northern Line Islands in the Central Pacific Ocean

PubMed Central

Mari, Lorenzo; Bonaventura, Luca; Storto, Andrea; Melià, Paco; Gatto, Marino; Masina, Simona

2017-01-01

Protecting key hotspots of marine biodiversity is essential to maintain ecosystem services at large spatial scales. Protected areas serve not only as sources of propagules colonizing other habitats, but also as receptors, thus acting as protected nurseries. To quantify the geographical extent and the temporal persistence of ecological benefits resulting from protection, we investigate larval connectivity within a remote archipelago, characterized by a strong spatial gradient of human impact from pristine to heavily exploited: the Northern Line Islands (NLIs), including part of the Pacific Remote Islands Marine National Monument (PRI-MNM). Larvae are described as passive Lagrangian particles transported by oceanic currents obtained from a oceanographic reanalysis. We compare different simulation schemes and compute connectivity measures (larval exchange probabilities and minimum/average larval dispersal distances from target islands). To explore the role of PRI-MNM in protecting marine organisms with pelagic larval stages, we drive millions of individual-based simulations for various Pelagic Larval Durations (PLDs), in all release seasons, and over a two-decades time horizon (1991–2010). We find that connectivity in the NLIs is spatially asymmetric and displays significant intra- and inter-annual variations. The islands belonging to PRI-MNM act more as sinks than sources of larvae, and connectivity is higher during the winter-spring period. In multi-annual analyses, yearly averaged southward connectivity significantly and negatively correlates with climatological anomalies (El Niño). This points out a possible system fragility and susceptibility to global warming. Quantitative assessments of large-scale, long-term marine connectivity patterns help understand region-specific, ecologically relevant interactions between islands. This is fundamental for devising scientifically-based protection strategies, which must be space- and time-varying to cope with the challenges posed by the concurrent pressures of human exploitation and global climate change. PMID:28809937

Understanding large-scale, long-term larval connectivity patterns: The case of the Northern Line Islands in the Central Pacific Ocean.

PubMed

Mari, Lorenzo; Bonaventura, Luca; Storto, Andrea; Melià, Paco; Gatto, Marino; Masina, Simona; Casagrandi, Renato

2017-01-01

Protecting key hotspots of marine biodiversity is essential to maintain ecosystem services at large spatial scales. Protected areas serve not only as sources of propagules colonizing other habitats, but also as receptors, thus acting as protected nurseries. To quantify the geographical extent and the temporal persistence of ecological benefits resulting from protection, we investigate larval connectivity within a remote archipelago, characterized by a strong spatial gradient of human impact from pristine to heavily exploited: the Northern Line Islands (NLIs), including part of the Pacific Remote Islands Marine National Monument (PRI-MNM). Larvae are described as passive Lagrangian particles transported by oceanic currents obtained from a oceanographic reanalysis. We compare different simulation schemes and compute connectivity measures (larval exchange probabilities and minimum/average larval dispersal distances from target islands). To explore the role of PRI-MNM in protecting marine organisms with pelagic larval stages, we drive millions of individual-based simulations for various Pelagic Larval Durations (PLDs), in all release seasons, and over a two-decades time horizon (1991-2010). We find that connectivity in the NLIs is spatially asymmetric and displays significant intra- and inter-annual variations. The islands belonging to PRI-MNM act more as sinks than sources of larvae, and connectivity is higher during the winter-spring period. In multi-annual analyses, yearly averaged southward connectivity significantly and negatively correlates with climatological anomalies (El Niño). This points out a possible system fragility and susceptibility to global warming. Quantitative assessments of large-scale, long-term marine connectivity patterns help understand region-specific, ecologically relevant interactions between islands. This is fundamental for devising scientifically-based protection strategies, which must be space- and time-varying to cope with the challenges posed by the concurrent pressures of human exploitation and global climate change.

DSC: software tool for simulation-based design of control strategies applied to wastewater treatment plants.

PubMed

Ruano, M V; Ribes, J; Seco, A; Ferrer, J

2011-01-01

This paper presents a computer tool called DSC (Simulation based Controllers Design) that enables an easy design of control systems and strategies applied to wastewater treatment plants. Although the control systems are developed and evaluated by simulation, this tool aims to facilitate the direct implementation of the designed control system to the PC of the full-scale WWTP (wastewater treatment plants). The designed control system can be programmed in a dedicated control application and can be connected to either the simulation software or the SCADA of the plant. To this end, the developed DSC incorporates an OPC server (OLE for process control) which facilitates an open-standard communication protocol for different industrial process applications. The potential capabilities of the DSC tool are illustrated through the example of a full-scale application. An aeration control system applied to a nutrient removing WWTP was designed, tuned and evaluated with the DSC tool before its implementation in the full scale plant. The control parameters obtained by simulation were suitable for the full scale plant with only few modifications to improve the control performance. With the DSC tool, the control systems performance can be easily evaluated by simulation. Once developed and tuned by simulation, the control systems can be directly applied to the full-scale WWTP.

The Robustness Analysis of Wireless Sensor Networks under Uncertain Interference

PubMed Central

Deng, Changjian

2013-01-01

Based on the complex network theory, robustness analysis of condition monitoring wireless sensor network under uncertain interference is present. In the evolution of the topology of sensor networks, the density weighted algebraic connectivity is taken into account, and the phenomenon of removing and repairing the link and node in the network is discussed. Numerical simulation is conducted to explore algebraic connectivity characteristics and network robustness performance. It is found that nodes density has the effect on algebraic connectivity distribution in the random graph model; high density nodes carry more connections, use more throughputs, and may be more unreliable. Moreover, the results show that, when network should be more error tolerant or robust by repairing nodes or adding new nodes, the network should be better clustered in median and high scale wireless sensor networks and be meshing topology in small scale networks. PMID:24363613

Integrating Multiple Approaches to Solving Solar Wind Turbulence Problems (Invited)

NASA Astrophysics Data System (ADS)

Karimabadi, H.; Roytershteyn, V.

2013-12-01

The ultimate understanding of the solar wind turbulence must explain the physical process and their connection at all scales ranging from the largest down to electron kinetic scales. This is a daunting task and as a result a more piecemeal approach to the problem has been followed. For example, the role of each wave has been explored in isolation and in simulations with scales limited to those of the underlying waves. In this talk, we present several issues with this approach and offer an alternative with an eye towards more realistic simulations of solar wind turbulence. The main simulation techniques used have been MHD, Hall MHD, hybrid, fully kinetic, and gyrokinetic. We examine the limitations of each approach and their viability for studies of solar wind turbulence. Finally, the effect of initial conditions on the resulting turbulence and their comparison with solar wind are demonstrated through several kinetic simulations.

Genome-Enabled Modeling of Biogeochemical Processes Predicts Metabolic Dependencies that Connect the Relative Fitness of Microbial Functional Guilds

NASA Astrophysics Data System (ADS)

Brodie, E.; King, E.; Molins, S.; Karaoz, U.; Steefel, C. I.; Banfield, J. F.; Beller, H. R.; Anantharaman, K.; Ligocki, T. J.; Trebotich, D.

2015-12-01

Pore-scale processes mediated by microorganisms underlie a range of critical ecosystem services, regulating carbon stability, nutrient flux, and the purification of water. Advances in cultivation-independent approaches now provide us with the ability to reconstruct thousands of genomes from microbial populations from which functional roles may be assigned. With this capability to reveal microbial metabolic potential, the next step is to put these microbes back where they belong to interact with their natural environment, i.e. the pore scale. At this scale, microorganisms communicate, cooperate and compete across their fitness landscapes with communities emerging that feedback on the physical and chemical properties of their environment, ultimately altering the fitness landscape and selecting for new microbial communities with new properties and so on. We have developed a trait-based model of microbial activity that simulates coupled functional guilds that are parameterized with unique combinations of traits that govern fitness under dynamic conditions. Using a reactive transport framework, we simulate the thermodynamics of coupled electron donor-acceptor reactions to predict energy available for cellular maintenance, respiration, biomass development, and enzyme production. From metagenomics, we directly estimate some trait values related to growth and identify the linkage of key traits associated with respiration and fermentation, macromolecule depolymerizing enzymes, and other key functions such as nitrogen fixation. Our simulations were carried out to explore abiotic controls on community emergence such as seasonally fluctuating water table regimes across floodplain organic matter hotspots. Simulations and metagenomic/metatranscriptomic observations highlighted the many dependencies connecting the relative fitness of functional guilds and the importance of chemolithoautotrophic lifestyles. Using an X-Ray microCT-derived soil microaggregate physical model combined with genome-enabled reactive flow and transport we simulated the importance of pore network properties including connectivity in regulating metabolic interdependencies between microbial functional guilds.

Multiscale solute transport upscaling for a three-dimensional hierarchical porous medium

NASA Astrophysics Data System (ADS)

Zhang, Mingkan; Zhang, Ye

2015-03-01

A laboratory-generated hierarchical, fully heterogeneous aquifer model (FHM) provides a reference for developing and testing an upscaling approach that integrates large-scale connectivity mapping with flow and transport modeling. Based on the FHM, three hydrostratigraphic models (HSMs) that capture lithological (static) connectivity at different resolutions are created, each corresponding to a sedimentary hierarchy. Under increasing system lnK variances (0.1, 1.0, 4.5), flow upscaling is first conducted to calculate equivalent hydraulic conductivity for individual connectivity (or unit) of the HSMs. Given the computed flow fields, an instantaneous, conservative tracer test is simulated by all models. For the HSMs, two upscaling formulations are tested based on the advection-dispersion equation (ADE), implementing space versus time-dependent macrodispersivity. Comparing flow and transport predictions of the HSMs against those of the reference model, HSMs capturing connectivity at increasing resolutions are more accurate, although upscaling errors increase with system variance. Results suggest: (1) by explicitly modeling connectivity, an enhanced degree of freedom in representing dispersion can improve the ADE-based upscaled models by capturing non-Fickian transport of the FHM; (2) when connectivity is sufficiently resolved, the type of data conditioning used to model transport becomes less critical. Data conditioning, however, is influenced by the prediction goal; (3) when aquifer is weakly-to-moderately heterogeneous, the upscaled models adequately capture the transport simulation of the FHM, despite the existence of hierarchical heterogeneity at smaller scales. When aquifer is strongly heterogeneous, the upscaled models become less accurate because lithological connectivity cannot adequately capture preferential flows; (4) three-dimensional transport connectivities of the hierarchical aquifer differ quantitatively from those analyzed for two-dimensional systems. This article was corrected on 7 MAY 2015. See the end of the full text for details.

Scale-dependent diffusion anisotropy in nanoporous silicon

PubMed Central

Kondrashova, Daria; Lauerer, Alexander; Mehlhorn, Dirk; Jobic, Hervé; Feldhoff, Armin; Thommes, Matthias; Chakraborty, Dipanjan; Gommes, Cedric; Zecevic, Jovana; de Jongh, Petra; Bunde, Armin; Kärger, Jörg; Valiullin, Rustem

2017-01-01

Nanoporous silicon produced by electrochemical etching of highly B-doped p-type silicon wafers can be prepared with tubular pores imbedded in a silicon matrix. Such materials have found many technological applications and provide a useful model system for studying phase transitions under confinement. This paper reports a joint experimental and simulation study of diffusion in such materials, covering displacements from molecular dimensions up to tens of micrometers with carefully selected probe molecules. In addition to mass transfer through the channels, diffusion (at much smaller rates) is also found to occur in directions perpendicular to the channels, thus providing clear evidence of connectivity. With increasing displacements, propagation in both axial and transversal directions is progressively retarded, suggesting a scale-dependent, hierarchical distribution of transport resistances (“constrictions” in the channels) and of shortcuts (connecting “bridges”) between adjacent channels. The experimental evidence from these studies is confirmed by molecular dynamics (MD) simulation in the range of atomistic displacements and rationalized with a simple model of statistically distributed “constrictions” and “bridges” for displacements in the micrometer range via dynamic Monte Carlo (DMC) simulation. Both ranges are demonstrated to be mutually transferrable by DMC simulations based on the pore space topology determined by electron tomography. PMID:28106047

New Computer Simulations of Macular Neural Functioning

NASA Technical Reports Server (NTRS)

Ross, Muriel D.; Doshay, D.; Linton, S.; Parnas, B.; Montgomery, K.; Chimento, T.

1994-01-01

We use high performance graphics workstations and supercomputers to study the functional significance of the three-dimensional (3-D) organization of gravity sensors. These sensors have a prototypic architecture foreshadowing more complex systems. Scaled-down simulations run on a Silicon Graphics workstation and scaled-up, 3-D versions run on a Cray Y-MP supercomputer. A semi-automated method of reconstruction of neural tissue from serial sections studied in a transmission electron microscope has been developed to eliminate tedious conventional photography. The reconstructions use a mesh as a step in generating a neural surface for visualization. Two meshes are required to model calyx surfaces. The meshes are connected and the resulting prisms represent the cytoplasm and the bounding membranes. A finite volume analysis method is employed to simulate voltage changes along the calyx in response to synapse activation on the calyx or on calyceal processes. The finite volume method insures that charge is conserved at the calyx-process junction. These and other models indicate that efferent processes act as voltage followers, and that the morphology of some afferent processes affects their functioning. In a final application, morphological information is symbolically represented in three dimensions in a computer. The possible functioning of the connectivities is tested using mathematical interpretations of physiological parameters taken from the literature. Symbolic, 3-D simulations are in progress to probe the functional significance of the connectivities. This research is expected to advance computer-based studies of macular functioning and of synaptic plasticity.

Perturbative approach to covariance matrix of the matter power spectrum

DOE PAGES

Mohammed, Irshad; Seljak, Uros; Vlah, Zvonimir

2016-12-14

Here, we evaluate the covariance matrix of the matter power spectrum using perturbation theory up to dominant terms at 1-loop order and compare it to numerical simulations. We decompose the covariance matrix into the disconnected (Gaussian) part, trispectrum from the modes outside the survey (beat coupling or super-sample variance), and trispectrum from the modes inside the survey, and show how the different components contribute to the overall covariance matrix. We find the agreement with the simulations is at a 10\\% level up tomore » $$k \\sim 1 h {\\rm Mpc^{-1}}$$. We also show that all the connected components are dominated by the large-scale modes ($$k<0.1 h {\\rm Mpc^{-1}}$$), regardless of the value of the wavevectors $$k,\\, k'$$ of the covariance matrix, suggesting that one must be careful in applying the jackknife or bootstrap methods to the covariance matrix. We perform an eigenmode decomposition of the connected part of the covariance matrix, showing that at higher $k$ it is dominated by a single eigenmode. Furthermore, the full covariance matrix can be approximated as the disconnected part only, with the connected part being treated as an external nuisance parameter with a known scale dependence, and a known prior on its variance for a given survey volume. Finally, we provide a prescription for how to evaluate the covariance matrix from small box simulations without the need to simulate large volumes.« less

Connectivity percolation in suspensions of attractive square-well spherocylinders.

PubMed

Dixit, Mohit; Meyer, Hugues; Schilling, Tanja

2016-01-01

We have studied the connectivity percolation transition in suspensions of attractive square-well spherocylinders by means of Monte Carlo simulation and connectedness percolation theory. In the 1980s the percolation threshold of slender fibers has been predicted to scale as the fibers' inverse aspect ratio [Phys. Rev. B 30, 3933 (1984)PRBMDO1098-012110.1103/PhysRevB.30.3933]. The main finding of our study is that the attractive spherocylinder system reaches this inverse scaling regime at much lower aspect ratios than found in suspensions of hard spherocylinders. We explain this difference by showing that third virial corrections of the pair connectedness functions, which are responsible for the deviation from the scaling regime, are less important for attractive potentials than for hard particles.

Field-Scale Modeling of Local Capillary Trapping During CO2 Injection into a Saline Aquifer

NASA Astrophysics Data System (ADS)

Ren, B.; Lake, L. W.; Bryant, S. L.

2015-12-01

Local capillary trapping is the small-scale (10-2 to 10+1 m) CO2 trapping that is caused by the capillary pressure heterogeneity. The benefit of LCT, applied specially to CO2 sequestration, is that saturation of stored CO2 is larger than the residual gas, yet these CO2 are not susceptible to leakage through failed seals. Thus quantifying the extent of local capillary trapping is valuable in design and risk assessment of geologic storage projects. Modeling local capillary trapping is computationally expensive and may even be intractable using a conventional reservoir simulator. In this paper, we propose a novel method to model local capillary trapping by combining geologic criteria and connectivity analysis. The connectivity analysis originally developed for characterizing well-to-reservoir connectivity is adapted to this problem by means of a newly defined edge weight property between neighboring grid blocks, which accounts for the multiphase flow properties, injection rate, and gravity effect. Then the connectivity is estimated from shortest path algorithm to predict the CO2 migration behavior and plume shape during injection. A geologic criteria algorithm is developed to estimate the potential local capillary traps based only on the entry capillary pressure field. The latter is correlated to a geostatistical realization of permeability field. The extended connectivity analysis shows a good match of CO2 plume computed by the full-physics simulation. We then incorporate it into the geologic algorithm to quantify the amount of LCT structures identified within the entry capillary pressure field that can be filled during CO2 injection. Several simulations are conducted in the reservoirs with different level of heterogeneity (measured by the Dykstra-Parsons coefficient) under various injection scenarios. We find that there exists a threshold Dykstra-Parsons coefficient, below which low injection rate gives rise to more LCT; whereas higher injection rate increases LCT in heterogeneous reservoirs. Both the geologic algorithm and connectivity analysis are very fast; therefore, the integrated methodology can be used as a quick tool to estimate local capillary trapping. It can also be used as a potential complement to the full-physics simulation to evaluate safe storage capacity.

The Illustris simulation: supermassive black hole-galaxy connection beyond the bulge

NASA Astrophysics Data System (ADS)

Mutlu-Pakdil, Burçin; Seigar, Marc S.; Hewitt, Ian B.; Treuthardt, Patrick; Berrier, Joel C.; Koval, Lauren E.

2018-02-01

We study the spiral arm morphology of a sample of the local spiral galaxies in the Illustris simulation and explore the supermassive black hole-galaxy connection beyond the bulge (e.g. spiral arm pitch angle, total stellar mass, dark matter mass, and total halo mass), finding good agreement with other theoretical studies and observational constraints. It is important to study the properties of supermassive black holes and their host galaxies through both observations and simulations and compare their results in order to understand their physics and formative histories. We find that Illustris prediction for supermassive black hole mass relative to pitch angle is in rather good agreement with observations and that barred and non-barred galaxies follow similar scaling relations. Our work shows that Illustris presents very tight correlations between supermassive black hole mass and large-scale properties of the host galaxy, not only for early-type galaxies but also for low-mass, blue and star-forming galaxies. These tight relations beyond the bulge suggest that halo properties determine those of a disc galaxy and its supermassive black hole.

Visual Data-Analytics of Large-Scale Parallel Discrete-Event Simulations

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

Ross, Caitlin; Carothers, Christopher D.; Mubarak, Misbah

Parallel discrete-event simulation (PDES) is an important tool in the codesign of extreme-scale systems because PDES provides a cost-effective way to evaluate designs of highperformance computing systems. Optimistic synchronization algorithms for PDES, such as Time Warp, allow events to be processed without global synchronization among the processing elements. A rollback mechanism is provided when events are processed out of timestamp order. Although optimistic synchronization protocols enable the scalability of large-scale PDES, the performance of the simulations must be tuned to reduce the number of rollbacks and provide an improved simulation runtime. To enable efficient large-scale optimistic simulations, one has tomore » gain insight into the factors that affect the rollback behavior and simulation performance. We developed a tool for ROSS model developers that gives them detailed metrics on the performance of their large-scale optimistic simulations at varying levels of simulation granularity. Model developers can use this information for parameter tuning of optimistic simulations in order to achieve better runtime and fewer rollbacks. In this work, we instrument the ROSS optimistic PDES framework to gather detailed statistics about the simulation engine. We have also developed an interactive visualization interface that uses the data collected by the ROSS instrumentation to understand the underlying behavior of the simulation engine. The interface connects real time to virtual time in the simulation and provides the ability to view simulation data at different granularities. We demonstrate the usefulness of our framework by performing a visual analysis of the dragonfly network topology model provided by the CODES simulation framework built on top of ROSS. The instrumentation needs to minimize overhead in order to accurately collect data about the simulation performance. To ensure that the instrumentation does not introduce unnecessary overhead, we perform a scaling study that compares instrumented ROSS simulations with their noninstrumented counterparts in order to determine the amount of perturbation when running at different simulation scales.« less

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.

An individual-based modelling approach to estimate landscape connectivity for bighorn sheep (Ovis canadensis).

PubMed

Allen, Corrie H; Parrott, Lael; Kyle, Catherine

2016-01-01

Background. Preserving connectivity, or the ability of a landscape to support species movement, is among the most commonly recommended strategies to reduce the negative effects of climate change and human land use development on species. Connectivity analyses have traditionally used a corridor-based approach and rely heavily on least cost path modeling and circuit theory to delineate corridors. Individual-based models are gaining popularity as a potentially more ecologically realistic method of estimating landscape connectivity. However, this remains a relatively unexplored approach. We sought to explore the utility of a simple, individual-based model as a land-use management support tool in identifying and implementing landscape connectivity. Methods. We created an individual-based model of bighorn sheep (Ovis canadensis) that simulates a bighorn sheep traversing a landscape by following simple movement rules. The model was calibrated for bighorn sheep in the Okanagan Valley, British Columbia, Canada, a region containing isolated herds that are vital to conservation of the species in its northern range. Simulations were run to determine baseline connectivity between subpopulations in the study area. We then applied the model to explore two land management scenarios on simulated connectivity: restoring natural fire regimes and identifying appropriate sites for interventions that would increase road permeability for bighorn sheep. Results. This model suggests there are no continuous areas of good habitat between current subpopulations of sheep in the study area; however, a series of stepping-stones or circuitous routes could facilitate movement between subpopulations and into currently unoccupied, yet suitable, bighorn habitat. Restoring natural fire regimes or mimicking fire with prescribed burns and tree removal could considerably increase bighorn connectivity in this area. Moreover, several key road crossing sites that could benefit from wildlife overpasses were identified. Discussion. By linking individual-scale movement rules to landscape-scale outcomes, our individual-based model of bighorn sheep allows for the exploration of how on-the-ground management or conservation scenarios may increase functional connectivity for the species in the study area. More generally, this study highlights the usefulness of individual-based models to identify how a species makes broad use of a landscape for movement. Application of this approach can provide effective quantitative support for decision makers seeking to incorporate wildlife conservation and connectivity into land use planning.

An individual-based modelling approach to estimate landscape connectivity for bighorn sheep (Ovis canadensis)

PubMed Central

Allen, Corrie H.; Kyle, Catherine

2016-01-01

Background. Preserving connectivity, or the ability of a landscape to support species movement, is among the most commonly recommended strategies to reduce the negative effects of climate change and human land use development on species. Connectivity analyses have traditionally used a corridor-based approach and rely heavily on least cost path modeling and circuit theory to delineate corridors. Individual-based models are gaining popularity as a potentially more ecologically realistic method of estimating landscape connectivity. However, this remains a relatively unexplored approach. We sought to explore the utility of a simple, individual-based model as a land-use management support tool in identifying and implementing landscape connectivity. Methods. We created an individual-based model of bighorn sheep (Ovis canadensis) that simulates a bighorn sheep traversing a landscape by following simple movement rules. The model was calibrated for bighorn sheep in the Okanagan Valley, British Columbia, Canada, a region containing isolated herds that are vital to conservation of the species in its northern range. Simulations were run to determine baseline connectivity between subpopulations in the study area. We then applied the model to explore two land management scenarios on simulated connectivity: restoring natural fire regimes and identifying appropriate sites for interventions that would increase road permeability for bighorn sheep. Results. This model suggests there are no continuous areas of good habitat between current subpopulations of sheep in the study area; however, a series of stepping-stones or circuitous routes could facilitate movement between subpopulations and into currently unoccupied, yet suitable, bighorn habitat. Restoring natural fire regimes or mimicking fire with prescribed burns and tree removal could considerably increase bighorn connectivity in this area. Moreover, several key road crossing sites that could benefit from wildlife overpasses were identified. Discussion. By linking individual-scale movement rules to landscape-scale outcomes, our individual-based model of bighorn sheep allows for the exploration of how on-the-ground management or conservation scenarios may increase functional connectivity for the species in the study area. More generally, this study highlights the usefulness of individual-based models to identify how a species makes broad use of a landscape for movement. Application of this approach can provide effective quantitative support for decision makers seeking to incorporate wildlife conservation and connectivity into land use planning. PMID:27168997

On identifying relationships between the flood scaling exponent and basin attributes.

PubMed

Medhi, Hemanta; Tripathi, Shivam

2015-07-01

Floods are known to exhibit self-similarity and follow scaling laws that form the basis of regional flood frequency analysis. However, the relationship between basin attributes and the scaling behavior of floods is still not fully understood. Identifying these relationships is essential for drawing connections between hydrological processes in a basin and the flood response of the basin. The existing studies mostly rely on simulation models to draw these connections. This paper proposes a new methodology that draws connections between basin attributes and the flood scaling exponents by using observed data. In the proposed methodology, region-of-influence approach is used to delineate homogeneous regions for each gaging station. Ordinary least squares regression is then applied to estimate flood scaling exponents for each homogeneous region, and finally stepwise regression is used to identify basin attributes that affect flood scaling exponents. The effectiveness of the proposed methodology is tested by applying it to data from river basins in the United States. The results suggest that flood scaling exponent is small for regions having (i) large abstractions from precipitation in the form of large soil moisture storages and high evapotranspiration losses, and (ii) large fractions of overland flow compared to base flow, i.e., regions having fast-responding basins. Analysis of simple scaling and multiscaling of floods showed evidence of simple scaling for regions in which the snowfall dominates the total precipitation.

Supercomputers ready for use as discovery machines for neuroscience.

PubMed

Helias, Moritz; Kunkel, Susanne; Masumoto, Gen; Igarashi, Jun; Eppler, Jochen Martin; Ishii, Shin; Fukai, Tomoki; Morrison, Abigail; Diesmann, Markus

2012-01-01

NEST is a widely used tool to simulate biological spiking neural networks. Here we explain the improvements, guided by a mathematical model of memory consumption, that enable us to exploit for the first time the computational power of the K supercomputer for neuroscience. Multi-threaded components for wiring and simulation combine 8 cores per MPI process to achieve excellent scaling. K is capable of simulating networks corresponding to a brain area with 10(8) neurons and 10(12) synapses in the worst case scenario of random connectivity; for larger networks of the brain its hierarchical organization can be exploited to constrain the number of communicating computer nodes. We discuss the limits of the software technology, comparing maximum filling scaling plots for K and the JUGENE BG/P system. The usability of these machines for network simulations has become comparable to running simulations on a single PC. Turn-around times in the range of minutes even for the largest systems enable a quasi interactive working style and render simulations on this scale a practical tool for computational neuroscience.

Supercomputers Ready for Use as Discovery Machines for Neuroscience

PubMed Central

Helias, Moritz; Kunkel, Susanne; Masumoto, Gen; Igarashi, Jun; Eppler, Jochen Martin; Ishii, Shin; Fukai, Tomoki; Morrison, Abigail; Diesmann, Markus

2012-01-01

NEST is a widely used tool to simulate biological spiking neural networks. Here we explain the improvements, guided by a mathematical model of memory consumption, that enable us to exploit for the first time the computational power of the K supercomputer for neuroscience. Multi-threaded components for wiring and simulation combine 8 cores per MPI process to achieve excellent scaling. K is capable of simulating networks corresponding to a brain area with 108 neurons and 1012 synapses in the worst case scenario of random connectivity; for larger networks of the brain its hierarchical organization can be exploited to constrain the number of communicating computer nodes. We discuss the limits of the software technology, comparing maximum filling scaling plots for K and the JUGENE BG/P system. The usability of these machines for network simulations has become comparable to running simulations on a single PC. Turn-around times in the range of minutes even for the largest systems enable a quasi interactive working style and render simulations on this scale a practical tool for computational neuroscience. PMID:23129998

Evaluating the Global Precipitation Measurement mission with NOAA/NSSL Multi-Radar Multisensor: current status and future directions.

NASA Astrophysics Data System (ADS)

Kirstetter, P. E.; Petersen, W. A.; Gourley, J. J.; Kummerow, C. D.; Huffman, G. J.; Turk, J.; Tanelli, S.; Maggioni, V.; Anagnostou, E. N.; Hong, Y.; Schwaller, M.

2016-12-01

Natural gas production via hydraulic fracturing of shale has proliferated on a global scale, yet recovery factors remain low because production strategies are not based on the physics of flow in shale reservoirs. In particular, the physical mechanisms and time scales of depletion from the matrix into the simulated fracture network are not well understood, limiting the potential to optimize operations and reduce environmental impacts. Studying matrix flow is challenging because shale is heterogeneous and has porosity from the μm- to nm-scale. Characterizing nm-scale flow paths requires electron microscopy but the limited field of view does not capture the connectivity and heterogeneity observed at the mm-scale. Therefore, pore-scale models must link to larger volumes to simulate flow on the reservoir-scale. Upscaled models must honor the physics of flow, but at present there is a gap between cm-scale experiments and μm-scale simulations based on ex situ image data. To address this gap, we developed a synchrotron X-ray microscope with an in situ cell to simultaneously visualize and measure flow. We perform coupled flow and microtomography experiments on mm-scale samples from the Barnett, Eagle Ford and Marcellus reservoirs. We measure permeability at various pressures via the pulse-decay method to quantify effective stress dependence and the relative contributions of advective and diffusive mechanisms. Images at each pressure step document how microfractures, interparticle pores, and organic matter change with effective stress. Linking changes in the pore network to flow measurements motivates a physical model for depletion. To directly visualize flow, we measure imbibition rates using inert, high atomic number gases and image periodically with monochromatic beam. By imaging above/below X-ray adsorption edges, we magnify the signal of gas saturation in μm-scale porosity and nm-scale, sub-voxel features. Comparing vacuumed and saturated states yields image-based measurements of the distribution and time scales of imbibition. We also characterize nm-scale structure via focused ion beam tomography to quantify sub-voxel porosity and connectivity. The multi-scale image and flow data is used to develop a framework to upscale and benchmark pore-scale models.

Visualizing and measuring flow in shale matrix using in situ synchrotron X-ray microtomography

NASA Astrophysics Data System (ADS)

Kohli, A. H.; Kiss, A. M.; Kovscek, A. R.; Bargar, J.

2017-12-01

Natural gas production via hydraulic fracturing of shale has proliferated on a global scale, yet recovery factors remain low because production strategies are not based on the physics of flow in shale reservoirs. In particular, the physical mechanisms and time scales of depletion from the matrix into the simulated fracture network are not well understood, limiting the potential to optimize operations and reduce environmental impacts. Studying matrix flow is challenging because shale is heterogeneous and has porosity from the μm- to nm-scale. Characterizing nm-scale flow paths requires electron microscopy but the limited field of view does not capture the connectivity and heterogeneity observed at the mm-scale. Therefore, pore-scale models must link to larger volumes to simulate flow on the reservoir-scale. Upscaled models must honor the physics of flow, but at present there is a gap between cm-scale experiments and μm-scale simulations based on ex situ image data. To address this gap, we developed a synchrotron X-ray microscope with an in situ cell to simultaneously visualize and measure flow. We perform coupled flow and microtomography experiments on mm-scale samples from the Barnett, Eagle Ford and Marcellus reservoirs. We measure permeability at various pressures via the pulse-decay method to quantify effective stress dependence and the relative contributions of advective and diffusive mechanisms. Images at each pressure step document how microfractures, interparticle pores, and organic matter change with effective stress. Linking changes in the pore network to flow measurements motivates a physical model for depletion. To directly visualize flow, we measure imbibition rates using inert, high atomic number gases and image periodically with monochromatic beam. By imaging above/below X-ray adsorption edges, we magnify the signal of gas saturation in μm-scale porosity and nm-scale, sub-voxel features. Comparing vacuumed and saturated states yields image-based measurements of the distribution and time scales of imbibition. We also characterize nm-scale structure via focused ion beam tomography to quantify sub-voxel porosity and connectivity. The multi-scale image and flow data is used to develop a framework to upscale and benchmark pore-scale models.

Robust quantum optimizer with full connectivity

PubMed Central

Nigg, Simon E.; Lörch, Niels; Tiwari, Rakesh P.

2017-01-01

Quantum phenomena have the potential to speed up the solution of hard optimization problems. For example, quantum annealing, based on the quantum tunneling effect, has recently been shown to scale exponentially better with system size than classical simulated annealing. However, current realizations of quantum annealers with superconducting qubits face two major challenges. First, the connectivity between the qubits is limited, excluding many optimization problems from a direct implementation. Second, decoherence degrades the success probability of the optimization. We address both of these shortcomings and propose an architecture in which the qubits are robustly encoded in continuous variable degrees of freedom. By leveraging the phenomenon of flux quantization, all-to-all connectivity with sufficient tunability to implement many relevant optimization problems is obtained without overhead. Furthermore, we demonstrate the robustness of this architecture by simulating the optimal solution of a small instance of the nondeterministic polynomial-time hard (NP-hard) and fully connected number partitioning problem in the presence of dissipation. PMID:28435880

Processor farming in two-level analysis of historical bridge

NASA Astrophysics Data System (ADS)

Krejčí, T.; Kruis, J.; Koudelka, T.; Šejnoha, M.

2017-11-01

This contribution presents a processor farming method in connection with a multi-scale analysis. In this method, each macro-scopic integration point or each finite element is connected with a certain meso-scopic problem represented by an appropriate representative volume element (RVE). The solution of a meso-scale problem provides then effective parameters needed on the macro-scale. Such an analysis is suitable for parallel computing because the meso-scale problems can be distributed among many processors. The application of the processor farming method to a real world masonry structure is illustrated by an analysis of Charles bridge in Prague. The three-dimensional numerical model simulates the coupled heat and moisture transfer of one half of arch No. 3. and it is a part of a complex hygro-thermo-mechanical analysis which has been developed to determine the influence of climatic loading on the current state of the bridge.

On the Fidelity of Semi-distributed Hydrologic Model Simulations for Large Scale Catchment Applications

NASA Astrophysics Data System (ADS)

Ajami, H.; Sharma, A.; Lakshmi, V.

2017-12-01

Application of semi-distributed hydrologic modeling frameworks is a viable alternative to fully distributed hyper-resolution hydrologic models due to computational efficiency and resolving fine-scale spatial structure of hydrologic fluxes and states. However, fidelity of semi-distributed model simulations is impacted by (1) formulation of hydrologic response units (HRUs), and (2) aggregation of catchment properties for formulating simulation elements. Here, we evaluate the performance of a recently developed Soil Moisture and Runoff simulation Toolkit (SMART) for large catchment scale simulations. In SMART, topologically connected HRUs are delineated using thresholds obtained from topographic and geomorphic analysis of a catchment, and simulation elements are equivalent cross sections (ECS) representative of a hillslope in first order sub-basins. Earlier investigations have shown that formulation of ECSs at the scale of a first order sub-basin reduces computational time significantly without compromising simulation accuracy. However, the implementation of this approach has not been fully explored for catchment scale simulations. To assess SMART performance, we set-up the model over the Little Washita watershed in Oklahoma. Model evaluations using in-situ soil moisture observations show satisfactory model performance. In addition, we evaluated the performance of a number of soil moisture disaggregation schemes recently developed to provide spatially explicit soil moisture outputs at fine scale resolution. Our results illustrate that the statistical disaggregation scheme performs significantly better than the methods based on topographic data. Future work is focused on assessing the performance of SMART using remotely sensed soil moisture observations using spatially based model evaluation metrics.

Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories

PubMed Central

Donovan, Rory M.; Tapia, Jose-Juan; Sullivan, Devin P.; Faeder, James R.; Murphy, Robert F.; Dittrich, Markus; Zuckerman, Daniel M.

2016-01-01

The long-term goal of connecting scales in biological simulation can be facilitated by scale-agnostic methods. We demonstrate that the weighted ensemble (WE) strategy, initially developed for molecular simulations, applies effectively to spatially resolved cell-scale simulations. The WE approach runs an ensemble of parallel trajectories with assigned weights and uses a statistical resampling strategy of replicating and pruning trajectories to focus computational effort on difficult-to-sample regions. The method can also generate unbiased estimates of non-equilibrium and equilibrium observables, sometimes with significantly less aggregate computing time than would be possible using standard parallelization. Here, we use WE to orchestrate particle-based kinetic Monte Carlo simulations, which include spatial geometry (e.g., of organelles, plasma membrane) and biochemical interactions among mobile molecular species. We study a series of models exhibiting spatial, temporal and biochemical complexity and show that although WE has important limitations, it can achieve performance significantly exceeding standard parallel simulation—by orders of magnitude for some observables. PMID:26845334

Supporting observation campaigns with high resolution modeling

NASA Astrophysics Data System (ADS)

Klocke, Daniel; Brueck, Matthias; Voigt, Aiko

2017-04-01

High resolution simulation in support of measurement campaigns offers a promising and emerging way to create large-scale context for small-scale observations of clouds and precipitation processes. As these simulation include the coupling of measured small-scale processes with the circulation, they also help to integrate the research communities from modeling and observations and allow for detailed model evaluations against dedicated observations. In connection with the measurement campaign NARVAL (August 2016 and December 2013) simulations with a grid-spacing of 2.5 km for the tropical Atlantic region (9000x3300 km), with local refinement to 1.2 km for the western part of the domain, were performed using the icosahedral non-hydrostatic (ICON) general circulation model. These simulations are again used to drive large eddy resolving simulations with the same model for selected days in the high definition clouds and precipitation for advancing climate prediction (HD(CP)2) project. The simulations are presented with the focus on selected results showing the benefit for the scientific communities doing atmospheric measurements and numerical modeling of climate and weather. Additionally, an outlook will be given on how similar simulations will support the NAWDEX measurement campaign in the North Atlantic and AC3 measurement campaign in the Arctic.

Towards mechanism-based simulation of impact damage using exascale computing

NASA Astrophysics Data System (ADS)

Shterenlikht, Anton; Margetts, Lee; McDonald, Samuel; Bourne, Neil K.

2017-01-01

Over the past 60 years, the finite element method has been very successful in modelling deformation in engineering structures. However the method requires the definition of constitutive models that represent the response of the material to applied loads. There are two issues. Firstly, the models are often difficult to define. Secondly, there is often no physical connection between the models and the mechanisms that accommodate deformation. In this paper, we present a potentially disruptive two-level strategy which couples the finite element method at the macroscale with cellular automata at the mesoscale. The cellular automata are used to simulate mechanisms, such as crack propagation. The stress-strain relationship emerges as a continuum mechanics scale interpretation of changes at the micro- and meso-scales. Iterative two-way updating between the cellular automata and finite elements drives the simulation forward as the material undergoes progressive damage at high strain rates. The strategy is particularly attractive on large-scale computing platforms as both methods scale well on tens of thousands of CPUs.

Identifying fracture‐zone geometry using simulated annealing and hydraulic‐connection data

USGS Publications Warehouse

Day-Lewis, Frederick D.; Hsieh, Paul A.; Gorelick, Steven M.

2000-01-01

A new approach is presented to condition geostatistical simulation of high‐permeability zones in fractured rock to hydraulic‐connection data. A simulated‐annealing algorithm generates three‐dimensional (3‐D) realizations conditioned to borehole data, inferred hydraulic connections between packer‐isolated borehole intervals, and an indicator (fracture zone or background‐K bedrock) variogram model of spatial variability. We apply the method to data from the U.S. Geological Survey Mirror Lake Site in New Hampshire, where connected high‐permeability fracture zones exert a strong control on fluid flow at the hundred‐meter scale. Single‐well hydraulic‐packer tests indicate where permeable fracture zones intersect boreholes, and multiple‐well pumping tests indicate the degree of hydraulic connection between boreholes. Borehole intervals connected by a fracture zone exhibit similar hydraulic responses, whereas intervals not connected by a fracture zone exhibit different responses. Our approach yields valuable insights into the 3‐D geometry of fracture zones at Mirror Lake. Statistical analysis of the realizations yields maps of the probabilities of intersecting specific fracture zones with additional wells. Inverse flow modeling based on the assumption of equivalent porous media is used to estimate hydraulic conductivity and specific storage and to identify those fracture‐zone geometries that are consistent with hydraulic test data.

Large-Scale Modeling of Epileptic Seizures: Scaling Properties of Two Parallel Neuronal Network Simulation Algorithms

DOE PAGES

Pesce, Lorenzo L.; Lee, Hyong C.; Hereld, Mark; ...

2013-01-01

Our limited understanding of the relationship between the behavior of individual neurons and large neuronal networks is an important limitation in current epilepsy research and may be one of the main causes of our inadequate ability to treat it. Addressing this problem directly via experiments is impossibly complex; thus, we have been developing and studying medium-large-scale simulations of detailed neuronal networks to guide us. Flexibility in the connection schemas and a complete description of the cortical tissue seem necessary for this purpose. In this paper we examine some of the basic issues encountered in these multiscale simulations. We have determinedmore » the detailed behavior of two such simulators on parallel computer systems. The observed memory and computation-time scaling behavior for a distributed memory implementation were very good over the range studied, both in terms of network sizes (2,000 to 400,000 neurons) and processor pool sizes (1 to 256 processors). Our simulations required between a few megabytes and about 150 gigabytes of RAM and lasted between a few minutes and about a week, well within the capability of most multinode clusters. Therefore, simulations of epileptic seizures on networks with millions of cells should be feasible on current supercomputers.« less

Tests of peak flow scaling in simulated self-similar river networks

USGS Publications Warehouse

Menabde, M.; Veitzer, S.; Gupta, V.; Sivapalan, M.

2001-01-01

The effect of linear flow routing incorporating attenuation and network topology on peak flow scaling exponent is investigated for an instantaneously applied uniform runoff on simulated deterministic and random self-similar channel networks. The flow routing is modelled by a linear mass conservation equation for a discrete set of channel links connected in parallel and series, and having the same topology as the channel network. A quasi-analytical solution for the unit hydrograph is obtained in terms of recursion relations. The analysis of this solution shows that the peak flow has an asymptotically scaling dependence on the drainage area for deterministic Mandelbrot-Vicsek (MV) and Peano networks, as well as for a subclass of random self-similar channel networks. However, the scaling exponent is shown to be different from that predicted by the scaling properties of the maxima of the width functions. ?? 2001 Elsevier Science Ltd. All rights reserved.

Simulating stream response to floodplain connectivity, reforestation and wetland restoration from reach to catchment scales

NASA Astrophysics Data System (ADS)

Singh, N.; Bomblies, A.; Wemple, B. C.; Ricketts, T.

2017-12-01

Natural infrastructure (e.g., floodplains, forests) can offer multiple ecosystem services (ES), including flood resilience and water quality improvement. In order to maintain these ES, state, federal and non-profit organizations may consider various interventions, such as increased floodplain connectivity, reforestation, and wetland restoration to minimize flood peaks and erosion during events. However, the effect of these interventions on hydro-geomorphic responses of streams from reach to catchment scales (>100 km2) are rarely quantified. We used stream geomorphic assessment datasets with a hydraulic model to investigate the influence of above mentioned interventions on stream power (SP), water depth (WD) and channel velocity (VEL) during floods of 2yr and 100yr return periods for three catchments in the Lake Champlain basin, Vermont. To simulate the effect of forests and wetlands, we changed the Manning's coefficient in the model, and to simulate the increased connectivity of the floodplain, we edited the LIDAR data to lower bank elevations. We find that the wetland scenario resulted in the greatest decline in WD and SP, whereas forested scenario exhibited maximum reduction in VEL. The connectivity scenario showed a decline in almost all stream responses, but the magnitude of change was relatively smaller. On average, 35% (2yr) and 50% (100yr) of altered reaches demonstrated improvement over baseline, and 39% (2yr) and 31% (100yr) of altered reaches showed degradation over baseline, across all interventions. We also noted changes in stream response along unaltered reaches (>30%), where we did not make interventions. Overall, these results point to the complexity related to stream interventions and suggest careful evaluation of spatially explicit tradeoffs of these interventions on river-floodplain ecosystem. The proposed approach of simulating and understanding stream's response to interventions, prior to the implementation of restoration activities, may lead to more effective and efficient management of rivers.

Mesoscale Effective Property Simulations Incorporating Conductive Binder

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

Trembacki, Bradley L.; Noble, David R.; Brunini, Victor E.

Lithium-ion battery electrodes are composed of active material particles, binder, and conductive additives that form an electrolyte-filled porous particle composite. The mesoscale (particle-scale) interplay of electrochemistry, mechanical deformation, and transport through this tortuous multi-component network dictates the performance of a battery at the cell-level. Effective electrode properties connect mesoscale phenomena with computationally feasible battery-scale simulations. We utilize published tomography data to reconstruct a large subsection (1000+ particles) of an NMC333 cathode into a computational mesh and extract electrode-scale effective properties from finite element continuum-scale simulations. We present a novel method to preferentially place a composite binder phase throughout the mesostructure,more » a necessary approach due difficulty distinguishing between non-active phases in tomographic data. We compare stress generation and effective thermal, electrical, and ionic conductivities across several binder placement approaches. Isotropic lithiation-dependent mechanical swelling of the NMC particles and the consideration of strain-dependent composite binder conductivity significantly impact the resulting effective property trends and stresses generated. Lastly, our results suggest that composite binder location significantly affects mesoscale behavior, indicating that a binder coating on active particles is not sufficient and that more accurate approaches should be used when calculating effective properties that will inform battery-scale models in this inherently multi-scale battery simulation challenge.« less

Mesoscale Effective Property Simulations Incorporating Conductive Binder

DOE PAGES

Trembacki, Bradley L.; Noble, David R.; Brunini, Victor E.; ...

2017-07-26

Lithium-ion battery electrodes are composed of active material particles, binder, and conductive additives that form an electrolyte-filled porous particle composite. The mesoscale (particle-scale) interplay of electrochemistry, mechanical deformation, and transport through this tortuous multi-component network dictates the performance of a battery at the cell-level. Effective electrode properties connect mesoscale phenomena with computationally feasible battery-scale simulations. We utilize published tomography data to reconstruct a large subsection (1000+ particles) of an NMC333 cathode into a computational mesh and extract electrode-scale effective properties from finite element continuum-scale simulations. We present a novel method to preferentially place a composite binder phase throughout the mesostructure,more » a necessary approach due difficulty distinguishing between non-active phases in tomographic data. We compare stress generation and effective thermal, electrical, and ionic conductivities across several binder placement approaches. Isotropic lithiation-dependent mechanical swelling of the NMC particles and the consideration of strain-dependent composite binder conductivity significantly impact the resulting effective property trends and stresses generated. Lastly, our results suggest that composite binder location significantly affects mesoscale behavior, indicating that a binder coating on active particles is not sufficient and that more accurate approaches should be used when calculating effective properties that will inform battery-scale models in this inherently multi-scale battery simulation challenge.« less

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.

Network structure shapes spontaneous functional connectivity dynamics.

PubMed

Shen, Kelly; Hutchison, R Matthew; Bezgin, Gleb; Everling, Stefan; McIntosh, Anthony R

2015-04-08

The structural organization of the brain constrains the range of interactions between different regions and shapes ongoing information processing. Therefore, it is expected that large-scale dynamic functional connectivity (FC) patterns, a surrogate measure of coordination between brain regions, will be closely tied to the fiber pathways that form the underlying structural network. Here, we empirically examined the influence of network structure on FC dynamics by comparing resting-state FC (rsFC) obtained using BOLD-fMRI in macaques (Macaca fascicularis) to structural connectivity derived from macaque axonal tract tracing studies. Consistent with predictions from simulation studies, the correspondence between rsFC and structural connectivity increased as the sample duration increased. Regions with reciprocal structural connections showed the most stable rsFC across time. The data suggest that the transient nature of FC is in part dependent on direct underlying structural connections, but also that dynamic coordination can occur via polysynaptic pathways. Temporal stability was found to be dependent on structural topology, with functional connections within the rich-club core exhibiting the greatest stability over time. We discuss these findings in light of highly variable functional hubs. The results further elucidate how large-scale dynamic functional coordination exists within a fixed structural architecture. Copyright © 2015 the authors 0270-6474/15/355579-10$15.00/0.

Sole larval supply to coastal nurseries: Interannual variability and connectivity at interregional and interpopulation scales

NASA Astrophysics Data System (ADS)

Savina, M.; Lunghi, M.; Archambault, B.; Baulier, L.; Huret, M.; Le Pape, O.

2016-05-01

Simulating fish larval drift helps assess the sensitivity of recruitment variability to early life history. An individual-based model (IBM) coupled to a hydrodynamic model was used to simulate common sole larval supply from spawning areas to coastal and estuarine nursery grounds at the meta-population scale (4 assessed stocks), from the southern North Sea to the Bay of Biscay (Western Europe) on a 26-yr time series, from 1982 to 2007. The IBM allowed each particle released to be transported by currents, to grow depending on temperature, to migrate vertically depending on development stage, to die along pelagic stages or to settle on a nursery, representing the life history from spawning to metamorphosis. The model outputs were analysed to explore interannual patterns in the amounts of settled sole larvae at the population scale; they suggested: (i) a low connectivity between populations at the larval stage, (ii) a moderate influence of interannual variation in the spawning biomass, (iii) dramatic consequences of life history on the abundance of settling larvae and (iv) the effects of climate variability on the interannual variability of the larvae settlement success.

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.

On the galaxy-halo connection in the EAGLE simulation

NASA Astrophysics Data System (ADS)

Desmond, Harry; Mao, Yao-Yuan; Wechsler, Risa H.; Crain, Robert A.; Schaye, Joop

2017-10-01

Empirical models of galaxy formation require assumptions about the correlations between galaxy and halo properties. These may be calibrated against observations or inferred from physical models such as hydrodynamical simulations. In this Letter, we use the EAGLE simulation to investigate the correlation of galaxy size with halo properties. We motivate this analysis by noting that the common assumption of angular momentum partition between baryons and dark matter in rotationally supported galaxies overpredicts both the spread in the stellar mass-size relation and the anticorrelation of size and velocity residuals, indicating a problem with the galaxy-halo connection it implies. We find the EAGLE galaxy population to perform significantly better on both statistics, and trace this success to the weakness of the correlations of galaxy size with halo mass, concentration and spin at fixed stellar mass. Using these correlations in empirical models will enable fine-grained aspects of galaxy scalings to be matched.

Using a million cell simulation of the cerebellum: network scaling and task generality.

PubMed

Li, Wen-Ke; Hausknecht, Matthew J; Stone, Peter; Mauk, Michael D

2013-11-01

Several factors combine to make it feasible to build computer simulations of the cerebellum and to test them in biologically realistic ways. These simulations can be used to help understand the computational contributions of various cerebellar components, including the relevance of the enormous number of neurons in the granule cell layer. In previous work we have used a simulation containing 12000 granule cells to develop new predictions and to account for various aspects of eyelid conditioning, a form of motor learning mediated by the cerebellum. Here we demonstrate the feasibility of scaling up this simulation to over one million granule cells using parallel graphics processing unit (GPU) technology. We observe that this increase in number of granule cells requires only twice the execution time of the smaller simulation on the GPU. We demonstrate that this simulation, like its smaller predecessor, can emulate certain basic features of conditioned eyelid responses, with a slight improvement in performance in one measure. We also use this simulation to examine the generality of the computation properties that we have derived from studying eyelid conditioning. We demonstrate that this scaled up simulation can learn a high level of performance in a classic machine learning task, the cart-pole balancing task. These results suggest that this parallel GPU technology can be used to build very large-scale simulations whose connectivity ratios match those of the real cerebellum and that these simulations can be used guide future studies on cerebellar mediated tasks and on machine learning problems. Copyright © 2012 Elsevier Ltd. All rights reserved.

The Relationship Between Galaxies and the Large-Scale Structure of the Universe

NASA Astrophysics Data System (ADS)

Coil, Alison L.

2018-06-01

I will describe our current understanding of the relationship between galaxies and the large-scale structure of the Universe, often called the galaxy-halo connection. Galaxies are thought to form and evolve in the centers of dark matter halos, which grow along with the galaxies they host. Large galaxy redshift surveys have revealed clear observational signatures of connections between galaxy properties and their clustering properties on large scales. For example, older, quiescent galaxies are known to cluster more strongly than younger, star-forming galaxies, which are more likely to be found in galactic voids and filaments rather than the centers of galaxy clusters. I will show how cosmological numerical simulations have aided our understanding of this galaxy-halo connection and what is known from a statistical point of view about how galaxies populate dark matter halos. This knowledge both helps us learn about galaxy evolution and is fundamental to our ability to use galaxy surveys to reveal cosmological information. I will talk briefly about some of the current open questions in the field, including galactic conformity and assembly bias.

Dynamics of tax evasion through an epidemic-like model

NASA Astrophysics Data System (ADS)

Brum, Rafael M.; Crokidakis, Nuno

In this work, we study a model of tax evasion. We considered a fixed population divided in three compartments, namely honest tax payers, tax evaders and a third class between the mentioned two, which we call susceptibles to become evaders. The transitions among those compartments are ruled by probabilities, similarly to a model of epidemic spreading. These probabilities model social interactions among the individuals, as well as the government’s fiscalization. We simulate the model on fully-connected graphs, as well as on scale-free and random complex networks. For the fully-connected and random graph cases, we observe that the emergence of tax evaders in the population is associated with an active-absorbing nonequilibrium phase transition, that is absent in scale-free networks.

Decentralized state estimation for a large-scale spatially interconnected system.

PubMed

Liu, Huabo; Yu, Haisheng

2018-03-01

A decentralized state estimator is derived for the spatially interconnected systems composed of many subsystems with arbitrary connection relations. An optimization problem on the basis of linear matrix inequality (LMI) is constructed for the computations of improved subsystem parameter matrices. Several computationally effective approaches are derived which efficiently utilize the block-diagonal characteristic of system parameter matrices and the sparseness of subsystem connection matrix. Moreover, this decentralized state estimator is proved to converge to a stable system and obtain a bounded covariance matrix of estimation errors under certain conditions. Numerical simulations show that the obtained decentralized state estimator is attractive in the synthesis of a large-scale networked system. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

You can run, you can hide: The epidemiology and statistical mechanics of zombies

NASA Astrophysics Data System (ADS)

Alemi, Alexander A.; Bierbaum, Matthew; Myers, Christopher R.; Sethna, James P.

2015-11-01

We use a popular fictional disease, zombies, in order to introduce techniques used in modern epidemiology modeling, and ideas and techniques used in the numerical study of critical phenomena. We consider variants of zombie models, from fully connected continuous time dynamics to a full scale exact stochastic dynamic simulation of a zombie outbreak on the continental United States. Along the way, we offer a closed form analytical expression for the fully connected differential equation, and demonstrate that the single person per site two dimensional square lattice version of zombies lies in the percolation universality class. We end with a quantitative study of the full scale US outbreak, including the average susceptibility of different geographical regions.

Integrity of Bolted Angle Connections Subjected to Simulated Column Removal

PubMed Central

Weigand, Jonathan M.; Berman, Jeffrey W.

2016-01-01

Large-scale tests of steel gravity framing systems (SGFSs) have shown that the connections are critical to the system integrity, when a column suffers damage that compromises its ability to carry gravity loads. When supporting columns were removed, the SGFSs redistributed gravity loads through the development of an alternate load path in a sustained tensile configuration resulting from large vertical deflections. The ability of the system to sustain such an alternate load path depends on the capacity of the gravity connections to remain intact after undergoing large rotation and axial extension demands, for which they were not designed. This study experimentally evaluates the performance of steel bolted angle connections subjected to loading consistent with an interior column removal. The characteristic connection behaviors are described and the performance of multiple connection configurations are compared in terms of their peak resistances and deformation capacities. PMID:27110059

Memory replay in balanced recurrent networks

PubMed Central

Chenkov, Nikolay; Sprekeler, Henning; Kempter, Richard

2017-01-01

Complex patterns of neural activity appear during up-states in the neocortex and sharp waves in the hippocampus, including sequences that resemble those during prior behavioral experience. The mechanisms underlying this replay are not well understood. How can small synaptic footprints engraved by experience control large-scale network activity during memory retrieval and consolidation? We hypothesize that sparse and weak synaptic connectivity between Hebbian assemblies are boosted by pre-existing recurrent connectivity within them. To investigate this idea, we connect sequences of assemblies in randomly connected spiking neuronal networks with a balance of excitation and inhibition. Simulations and analytical calculations show that recurrent connections within assemblies allow for a fast amplification of signals that indeed reduces the required number of inter-assembly connections. Replay can be evoked by small sensory-like cues or emerge spontaneously by activity fluctuations. Global—potentially neuromodulatory—alterations of neuronal excitability can switch between network states that favor retrieval and consolidation. PMID:28135266

Enhancement of Spike Synchrony in Hindmarsh-Rose Neural Networks by Randomly Rewiring Connections

NASA Astrophysics Data System (ADS)

Yang, Renhuan; Song, Aiguo; Yuan, Wujie

Spike synchrony of the neural system is thought to have very dichotomous roles. On the one hand, it is ubiquitously present in the healthy brain and is thought to underlie feature binding during information processing. On the other hand, large scale synchronization is an underlying mechanism of epileptic seizures. In this paper, we investigate the spike synchrony of Hindmarsh-Rose (HR) neural networks. Our focus is the influence of the network connections on the spike synchrony of the neural networks. The simulations show that desynchronization in the nearest-neighbor coupled network evolves into accurate synchronization with connection-rewiring probability p increasing. We uncover a phenomenon of enhancement of spike synchrony by randomly rewiring connections. With connection strength c and average connection number m increasing spike synchrony is enhanced but it is not the whole story. Furthermore, the possible mechanism behind such synchronization is also addressed.

Coarse-grained stochastic processes and kinetic Monte Carlo simulators for the diffusion of interacting particles

NASA Astrophysics Data System (ADS)

Katsoulakis, Markos A.; Vlachos, Dionisios G.

2003-11-01

We derive a hierarchy of successively coarse-grained stochastic processes and associated coarse-grained Monte Carlo (CGMC) algorithms directly from the microscopic processes as approximations in larger length scales for the case of diffusion of interacting particles on a lattice. This hierarchy of models spans length scales between microscopic and mesoscopic, satisfies a detailed balance, and gives self-consistent fluctuation mechanisms whose noise is asymptotically identical to the microscopic MC. Rigorous, detailed asymptotics justify and clarify these connections. Gradient continuous time microscopic MC and CGMC simulations are compared under far from equilibrium conditions to illustrate the validity of our theory and delineate the errors obtained by rigorous asymptotics. Information theory estimates are employed for the first time to provide rigorous error estimates between the solutions of microscopic MC and CGMC, describing the loss of information during the coarse-graining process. Simulations under periodic boundary conditions are used to verify the information theory error estimates. It is shown that coarse-graining in space leads also to coarse-graining in time by q2, where q is the level of coarse-graining, and overcomes in part the hydrodynamic slowdown. Operation counting and CGMC simulations demonstrate significant CPU savings in continuous time MC simulations that vary from q3 for short potentials to q4 for long potentials. Finally, connections of the new coarse-grained stochastic processes to stochastic mesoscopic and Cahn-Hilliard-Cook models are made.

Extraction of MOS VLSI (Very-Large-Scale-Integrated) Circuit Models Including Critical Interconnect Parasitics.

DTIC Science & Technology

1987-09-01

can be reduced substantially, compared to using numerical methods to model inter - " connect parasitics. Although some accuracy might be lost with...conductor widths and spacings listed in Table 2 1 , have been employed for simulation. In the first set of the simulations, planar dielectric inter ...model, there are no restrictions on the iumber ol diele-iric and conductors. andl the shape of the conductors and the dielectric inter - a.e,, In the

Atomic-scale reversibility in sheared glasses

NASA Astrophysics Data System (ADS)

Fan, Meng; Wang, Minglei; Liu, Yanhui; Schroers, Jan; Shattuck, Mark; O'Hern, Corey

Systems become irreversible on a macroscopic scale when they are sheared beyond the yield strain and begin flowing. Using computer simulations of oscillatory shear, we investigate atomic scale reversibility. We employ molecular dynamics simulations to cool binary Lennard-Jones liquids to zero temperature over a wide range of cooling rates. We then apply oscillatory quasistatic shear at constant pressure to the zero-temperature glasses and identify neighbor-switching atomic rearrangement events. We determine the critical strain γ*, beyond which atoms in the system do not return to their original positions upon reversing the strain. We show that for more slowly cooled glasses, the average potential energy is lower and the typical size of atomic rearrangements is smaller, which correlates with larger γ*. Finally, we connect atomic- and macro-scale reversibility by determining the number of and correlations between the atomic rearrangements that occur as the system reaches the yield strain.

Web-based Visual Analytics for Extreme Scale Climate Science

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

Steed, Chad A; Evans, Katherine J; Harney, John F

In this paper, we introduce a Web-based visual analytics framework for democratizing advanced visualization and analysis capabilities pertinent to large-scale earth system simulations. We address significant limitations of present climate data analysis tools such as tightly coupled dependencies, ineffi- cient data movements, complex user interfaces, and static visualizations. Our Web-based visual analytics framework removes critical barriers to the widespread accessibility and adoption of advanced scientific techniques. Using distributed connections to back-end diagnostics, we minimize data movements and leverage HPC platforms. We also mitigate system dependency issues by employing a RESTful interface. Our framework embraces the visual analytics paradigm via newmore » visual navigation techniques for hierarchical parameter spaces, multi-scale representations, and interactive spatio-temporal data mining methods that retain details. Although generalizable to other science domains, the current work focuses on improving exploratory analysis of large-scale Community Land Model (CLM) and Community Atmosphere Model (CAM) simulations.« less

The large-scale environment from cosmological simulations - I. The baryonic cosmic web

NASA Astrophysics Data System (ADS)

Cui, Weiguang; Knebe, Alexander; Yepes, Gustavo; Yang, Xiaohu; Borgani, Stefano; Kang, Xi; Power, Chris; Staveley-Smith, Lister

2018-01-01

Using a series of cosmological simulations that includes one dark-matter-only (DM-only) run, one gas cooling-star formation-supernova feedback (CSF) run and one that additionally includes feedback from active galactic nuclei (AGNs), we classify the large-scale structures with both a velocity-shear-tensor code (VWEB) and a tidal-tensor code (PWEB). We find that the baryonic processes have almost no impact on large-scale structures - at least not when classified using aforementioned techniques. More importantly, our results confirm that the gas component alone can be used to infer the filamentary structure of the universe practically un-biased, which could be applied to cosmology constraints. In addition, the gas filaments are classified with its velocity (VWEB) and density (PWEB) fields, which can theoretically connect to the radio observations, such as H I surveys. This will help us to bias-freely link the radio observations with dark matter distributions at large scale.

A compositional reservoir simulator on distributed memory parallel computers

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

Rame, M.; Delshad, M.

1995-12-31

This paper presents the application of distributed memory parallel computes to field scale reservoir simulations using a parallel version of UTCHEM, The University of Texas Chemical Flooding Simulator. The model is a general purpose highly vectorized chemical compositional simulator that can simulate a wide range of displacement processes at both field and laboratory scales. The original simulator was modified to run on both distributed memory parallel machines (Intel iPSC/960 and Delta, Connection Machine 5, Kendall Square 1 and 2, and CRAY T3D) and a cluster of workstations. A domain decomposition approach has been taken towards parallelization of the code. Amore » portion of the discrete reservoir model is assigned to each processor by a set-up routine that attempts a data layout as even as possible from the load-balance standpoint. Each of these subdomains is extended so that data can be shared between adjacent processors for stencil computation. The added routines that make parallel execution possible are written in a modular fashion that makes the porting to new parallel platforms straight forward. Results of the distributed memory computing performance of Parallel simulator are presented for field scale applications such as tracer flood and polymer flood. A comparison of the wall-clock times for same problems on a vector supercomputer is also presented.« less

Efficient generation of connectivity in neuronal networks from simulator-independent descriptions

PubMed Central

Djurfeldt, Mikael; Davison, Andrew P.; Eppler, Jochen M.

2014-01-01

Simulator-independent descriptions of connectivity in neuronal networks promise greater ease of model sharing, improved reproducibility of simulation results, and reduced programming effort for computational neuroscientists. However, until now, enabling the use of such descriptions in a given simulator in a computationally efficient way has entailed considerable work for simulator developers, which must be repeated for each new connectivity-generating library that is developed. We have developed a generic connection generator interface that provides a standard way to connect a connectivity-generating library to a simulator, such that one library can easily be replaced by another, according to the modeler's needs. We have used the connection generator interface to connect C++ and Python implementations of the previously described connection-set algebra to the NEST simulator. We also demonstrate how the simulator-independent modeling framework PyNN can transparently take advantage of this, passing a connection description through to the simulator layer for rapid processing in C++ where a simulator supports the connection generator interface and falling-back to slower iteration in Python otherwise. A set of benchmarks demonstrates the good performance of the interface. PMID:24795620

A graph-theory framework for evaluating landscape connectivity and conservation planning.

PubMed

Minor, Emily S; Urban, Dean L

2008-04-01

Connectivity of habitat patches is thought to be important for movement of genes, individuals, populations, and species over multiple temporal and spatial scales. We used graph theory to characterize multiple aspects of landscape connectivity in a habitat network in the North Carolina Piedmont (U.S.A). We compared this landscape with simulated networks with known topology, resistance to disturbance, and rate of movement. We introduced graph measures such as compartmentalization and clustering, which can be used to identify locations on the landscape that may be especially resilient to human development or areas that may be most suitable for conservation. Our analyses indicated that for songbirds the Piedmont habitat network was well connected. Furthermore, the habitat network had commonalities with planar networks, which exhibit slow movement, and scale-free networks, which are resistant to random disturbances. These results suggest that connectivity in the habitat network was high enough to prevent the negative consequences of isolation but not so high as to allow rapid spread of disease. Our graph-theory framework provided insight into regional and emergent global network properties in an intuitive and visual way and allowed us to make inferences about rates and paths of species movements and vulnerability to disturbance. This approach can be applied easily to assessing habitat connectivity in any fragmented or patchy landscape.

Increased Hydrologic Connectivity: Consequences of Reduced Water Storage Capacity in the Delmarva Peninsula (U.S.)

NASA Astrophysics Data System (ADS)

Mclaughlin, D. L.; Jones, C. N.; Evenson, G. R.; Golden, H. E.; Lane, C.; Alexander, L. C.; Lang, M.

2017-12-01

Combined geospatial and modeling approaches are required to fully enumerate wetland hydrologic connectivity and downstream effects. Here, we utilized both geospatial analysis and hydrologic modeling to explore drivers and consequences of modified surface water connectivity in the Delmarva Peninsula, with particular focus on increased connectivity via pervasive wetland ditching. Our geospatial analysis quantified both historical and contemporary wetland storage capacity across the region, and suggests that over 70% of historical storage capacity has been lost due to this ditching. Building upon this analysis, we applied a catchment-scale model to simulate implications of reduced storage capacity on catchment-scale hydrology. In short, increased connectivity (and concomitantly reduced wetland water storage capacity) decreases catchment inundation extent and spatial heterogeneity, shortens cumulative residence times, and increases downstream flow variation with evident effects on peak and baseflow dynamics. As such, alterations in connectivity have implications for hydrologically mediated functions in catchments (e.g., nutrient removal) and downstream systems (e.g., maintenance of flow for aquatic habitat). Our work elucidates such consequences in Delmarva Peninsula while also providing new tools for broad application to target wetland restoration and conservation. Views expressed are those of the authors and do not necessarily reflect policies of the US EPA or US FWS.

Temperature measurement in PV facilities on a per-panel scale.

PubMed

Martínez, Miguel A; Andújar, José M; Enrique, Juan M

2014-07-24

This paper presents the design, construction and testing of an instrumentation system for temperature measurement in PV facilities on a per-panel scale (i.e., one or more temperature measurements per panel). Its main characteristics are: precision, ease of connection, immunity to noise, remote operation, easy scaling; and all of this at a very low cost. The paper discusses the advantages of temperature measurements in PV facilities on a per-panel scale. The paper presents the whole development to implementation of a real system that is being tested in an actual facility. This has enabled the authors to provide the readers with practical guidelines, which would be very difficult to achieve if the developments were implemented by just simulation or in a theoretical way. The instrumentation system is fully developed, from the temperature sensing to its presentation in a virtual instrument. The developed instrumentation system is able to work both locally and remotely connected to both wired and wireless network.

Temperature Measurement in PV Facilities on a Per-Panel Scale

PubMed Central

Martínez, Miguel A.; Andújar, José M.; Enrique, Juan M.

2014-01-01

This paper presents the design, construction and testing of an instrumentation system for temperature measurement in PV facilities on a per-panel scale (i.e., one or more temperature measurements per panel). Its main characteristics are: precision, ease of connection, immunity to noise, remote operation, easy scaling; and all of this at a very low cost. The paper discusses the advantages of temperature measurements in PV facilities on a per-panel scale. The paper presents the whole development to implementation of a real system that is being tested in an actual facility. This has enabled the authors to provide the readers with practical guidelines, which would be very difficult to achieve if the developments were implemented by just simulation or in a theoretical way. The instrumentation system is fully developed, from the temperature sensing to its presentation in a virtual instrument. The developed instrumentation system is able to work both locally and remotely connected to both wired and wireless network. PMID:25061834

Using synchronization in multi-model ensembles to improve prediction

NASA Astrophysics Data System (ADS)

Hiemstra, P.; Selten, F.

2012-04-01

In recent decades, many climate models have been developed to understand and predict the behavior of the Earth's climate system. Although these models are all based on the same basic physical principles, they still show different behavior. This is for example caused by the choice of how to parametrize sub-grid scale processes. One method to combine these imperfect models, is to run a multi-model ensemble. The models are given identical initial conditions and are integrated forward in time. A multi-model estimate can for example be a weighted mean of the ensemble members. We propose to go a step further, and try to obtain synchronization between the imperfect models by connecting the multi-model ensemble, and exchanging information. The combined multi-model ensemble is also known as a supermodel. The supermodel has learned from observations how to optimally exchange information between the ensemble members. In this study we focused on the density and formulation of the onnections within the supermodel. The main question was whether we could obtain syn-chronization between two climate models when connecting only a subset of their state spaces. Limiting the connected subspace has two advantages: 1) it limits the transfer of data (bytes) between the ensemble, which can be a limiting factor in large scale climate models, and 2) learning the optimal connection strategy from observations is easier. To answer the research question, we connected two identical quasi-geostrohic (QG) atmospheric models to each other, where the model have different initial conditions. The QG model is a qualitatively realistic simulation of the winter flow on the Northern hemisphere, has three layers and uses a spectral imple-mentation. We connected the models in the original spherical harmonical state space, and in linear combinations of these spherical harmonics, i.e. Empirical Orthogonal Functions (EOFs). We show that when connecting through spherical harmonics, we only need to connect 28% of the state variables to obtain synchronization. In addition, when connecting through EOFs, we can reduce this percentage even more to 12%. This reduction is caused by the more efficient description of the model state variables when using EOFs. The connected state variables center around the medium scale structures in the model. Small and large scale structures need not be connected in order to obtain synchronization. This could be related to the baroclinic instabilities in the QG model which are located in the medium scale structures of the model. The baroclinic instabilities are the main source of divergence between the two connected models.

Proceedings of the 14th International Conference on the Numerical Simulation of Plasmas

NASA Astrophysics Data System (ADS)

Partial Contents are as follows: Numerical Simulations of the Vlasov-Maxwell Equations by Coupled Particle-Finite Element Methods on Unstructured Meshes; Electromagnetic PIC Simulations Using Finite Elements on Unstructured Grids; Modelling Travelling Wave Output Structures with the Particle-in-Cell Code CONDOR; SST--A Single-Slice Particle Simulation Code; Graphical Display and Animation of Data Produced by Electromagnetic, Particle-in-Cell Codes; A Post-Processor for the PEST Code; Gray Scale Rendering of Beam Profile Data; A 2D Electromagnetic PIC Code for Distributed Memory Parallel Computers; 3-D Electromagnetic PIC Simulation on the NRL Connection Machine; Plasma PIC Simulations on MIMD Computers; Vlasov-Maxwell Algorithm for Electromagnetic Plasma Simulation on Distributed Architectures; MHD Boundary Layer Calculation Using the Vortex Method; and Eulerian Codes for Plasma Simulations.

The effects of neuron morphology on graph theoretic measures of network connectivity: the analysis of a two-level statistical model.

PubMed

Aćimović, Jugoslava; Mäki-Marttunen, Tuomo; Linne, Marja-Leena

2015-01-01

We developed a two-level statistical model that addresses the question of how properties of neurite morphology shape the large-scale network connectivity. We adopted a low-dimensional statistical description of neurites. From the neurite model description we derived the expected number of synapses, node degree, and the effective radius, the maximal distance between two neurons expected to form at least one synapse. We related these quantities to the network connectivity described using standard measures from graph theory, such as motif counts, clustering coefficient, minimal path length, and small-world coefficient. These measures are used in a neuroscience context to study phenomena from synaptic connectivity in the small neuronal networks to large scale functional connectivity in the cortex. For these measures we provide analytical solutions that clearly relate different model properties. Neurites that sparsely cover space lead to a small effective radius. If the effective radius is small compared to the overall neuron size the obtained networks share similarities with the uniform random networks as each neuron connects to a small number of distant neurons. Large neurites with densely packed branches lead to a large effective radius. If this effective radius is large compared to the neuron size, the obtained networks have many local connections. In between these extremes, the networks maximize the variability of connection repertoires. The presented approach connects the properties of neuron morphology with large scale network properties without requiring heavy simulations with many model parameters. The two-steps procedure provides an easier interpretation of the role of each modeled parameter. The model is flexible and each of its components can be further expanded. We identified a range of model parameters that maximizes variability in network connectivity, the property that might affect network capacity to exhibit different dynamical regimes.

Advanced data management for optimising the operation of a full-scale WWTP.

PubMed

Beltrán, Sergio; Maiza, Mikel; de la Sota, Alejandro; Villanueva, José María; Ayesa, Eduardo

2012-01-01

The lack of appropriate data management tools is presently a limiting factor for a broader implementation and a more efficient use of sensors and analysers, monitoring systems and process controllers in wastewater treatment plants (WWTPs). This paper presents a technical solution for advanced data management of a full-scale WWTP. The solution is based on an efficient and intelligent use of the plant data by a standard centralisation of the heterogeneous data acquired from different sources, effective data processing to extract adequate information, and a straightforward connection to other emerging tools focused on the operational optimisation of the plant such as advanced monitoring and control or dynamic simulators. A pilot study of the advanced data manager tool was designed and implemented in the Galindo-Bilbao WWTP. The results of the pilot study showed its potential for agile and intelligent plant data management by generating new enriched information combining data from different plant sources, facilitating the connection of operational support systems, and developing automatic plots and trends of simulated results and actual data for plant performance and diagnosis.

Mapping Dark Matter in Simulated Galaxy Clusters

NASA Astrophysics Data System (ADS)

Bowyer, Rachel

2018-01-01

Galaxy clusters are the most massive bound objects in the Universe with most of their mass being dark matter. Cosmological simulations of structure formation show that clusters are embedded in a cosmic web of dark matter filaments and large scale structure. It is thought that these filaments are found preferentially close to the long axes of clusters. We extract galaxy clusters from the simulations "cosmo-OWLS" in order to study their properties directly and also to infer their properties from weak gravitational lensing signatures. We investigate various stacking procedures to enhance the signal of the filaments and large scale structure surrounding the clusters to better understand how the filaments of the cosmic web connect with galaxy clusters. This project was supported in part by the NSF REU grant AST-1358980 and by the Nantucket Maria Mitchell Association.

Scaling analysis and instantons for thermally assisted tunneling and quantum Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Jiang, Zhang; Smelyanskiy, Vadim N.; Isakov, Sergei V.; Boixo, Sergio; Mazzola, Guglielmo; Troyer, Matthias; Neven, Hartmut

2017-01-01

We develop an instantonic calculus to derive an analytical expression for the thermally assisted tunneling decay rate of a metastable state in a fully connected quantum spin model. The tunneling decay problem can be mapped onto the Kramers escape problem of a classical random dynamical field. This dynamical field is simulated efficiently by path-integral quantum Monte Carlo (QMC). We show analytically that the exponential scaling with the number of spins of the thermally assisted quantum tunneling rate and the escape rate of the QMC process are identical. We relate this effect to the existence of a dominant instantonic tunneling path. The instanton trajectory is described by nonlinear dynamical mean-field theory equations for a single-site magnetization vector, which we solve exactly. Finally, we derive scaling relations for the "spiky" barrier shape when the spin tunneling and QMC rates scale polynomially with the number of spins N while a purely classical over-the-barrier activation rate scales exponentially with N .

Higher-Order Neural Networks Applied to 2D and 3D Object Recognition

NASA Technical Reports Server (NTRS)

Spirkovska, Lilly; Reid, Max B.

1994-01-01

A Higher-Order Neural Network (HONN) can be designed to be invariant to geometric transformations such as scale, translation, and in-plane rotation. Invariances are built directly into the architecture of a HONN and do not need to be learned. Thus, for 2D object recognition, the network needs to be trained on just one view of each object class, not numerous scaled, translated, and rotated views. Because the 2D object recognition task is a component of the 3D object recognition task, built-in 2D invariance also decreases the size of the training set required for 3D object recognition. We present results for 2D object recognition both in simulation and within a robotic vision experiment and for 3D object recognition in simulation. We also compare our method to other approaches and show that HONNs have distinct advantages for position, scale, and rotation-invariant object recognition. The major drawback of HONNs is that the size of the input field is limited due to the memory required for the large number of interconnections in a fully connected network. We present partial connectivity strategies and a coarse-coding technique for overcoming this limitation and increasing the input field to that required by practical object recognition problems.

Simulation of carbon allocation and organ growth variability in apple tree by connecting architectural and source–sink models

PubMed Central

Pallas, Benoît; Da Silva, David; Valsesia, Pierre; Yang, Weiwei; Guillaume, Olivier; Lauri, Pierre-Eric; Vercambre, Gilles; Génard, Michel; Costes, Evelyne

2016-01-01

Background and aims Plant growth depends on carbon availability and allocation among organs. QualiTree has been designed to simulate carbon allocation and partitioning in the peach tree (Prunus persica), whereas MappleT is dedicated to the simulation of apple tree (Malus × domestica) architecture. The objective of this study was to couple both models and adapt QualiTree to apple trees to simulate organ growth traits and their within-tree variability. Methods MappleT was used to generate architectures corresponding to the ‘Fuji’ cultivar, accounting for the variability within and among individuals. These architectures were input into QualiTree to simulate shoot and fruit growth during a growth cycle. We modified QualiTree to account for the observed shoot polymorphism in apple trees, i.e. different classes (long, medium and short) that were characterized by different growth function parameters. Model outputs were compared with observed 3D tree geometries, considering shoot and final fruit size and growth dynamics. Key Results The modelling approach connecting MappleT and QualiTree was appropriate to the simulation of growth and architectural characteristics at the tree scale (plant leaf area, shoot number and types, fruit weight at harvest). At the shoot scale, mean fruit weight and its variability within trees was accurately simulated, whereas the model tended to overestimate individual shoot leaf area and underestimate its variability for each shoot type. Varying the parameter related to the intensity of carbon exchange between shoots revealed that behaviour intermediate between shoot autonomy and a common assimilate pool was required to properly simulate within-tree fruit growth variability. Moreover, the model correctly dealt with the crop load effect on organ growth. Conclusions This study provides understanding of the integration of shoot ontogenetic properties, carbon supply and transport between entities for simulating organ growth in trees. Further improvements regarding the integration of retroaction loops between carbon allocation and the resulting plant architecture are expected to allow multi-year simulations. PMID:27279576

No Reef Is an Island: Integrating Coral Reef Connectivity Data into the Design of Regional-Scale Marine Protected Area Networks.

PubMed

Schill, Steven R; Raber, George T; Roberts, Jason J; Treml, Eric A; Brenner, Jorge; Halpin, Patrick N

2015-01-01

We integrated coral reef connectivity data for the Caribbean and Gulf of Mexico into a conservation decision-making framework for designing a regional scale marine protected area (MPA) network that provides insight into ecological and political contexts. We used an ocean circulation model and regional coral reef data to simulate eight spawning events from 2008-2011, applying a maximum 30-day pelagic larval duration and 20% mortality rate. Coral larval dispersal patterns were analyzed between coral reefs across jurisdictional marine zones to identify spatial relationships between larval sources and destinations within countries and territories across the region. We applied our results in Marxan, a conservation planning software tool, to identify a regional coral reef MPA network design that meets conservation goals, minimizes underlying threats, and maintains coral reef connectivity. Our results suggest that approximately 77% of coral reefs identified as having a high regional connectivity value are not included in the existing MPA network. This research is unique because we quantify and report coral larval connectivity data by marine ecoregions and Exclusive Economic Zones (EZZ) and use this information to identify gaps in the current Caribbean-wide MPA network by integrating asymmetric connectivity information in Marxan to design a regional MPA network that includes important reef network connections. The identification of important reef connectivity metrics guides the selection of priority conservation areas and supports resilience at the whole system level into the future.

No Reef Is an Island: Integrating Coral Reef Connectivity Data into the Design of Regional-Scale Marine Protected Area Networks

PubMed Central

Schill, Steven R.; Raber, George T.; Roberts, Jason J.; Treml, Eric A.; Brenner, Jorge; Halpin, Patrick N.

2015-01-01

We integrated coral reef connectivity data for the Caribbean and Gulf of Mexico into a conservation decision-making framework for designing a regional scale marine protected area (MPA) network that provides insight into ecological and political contexts. We used an ocean circulation model and regional coral reef data to simulate eight spawning events from 2008–2011, applying a maximum 30-day pelagic larval duration and 20% mortality rate. Coral larval dispersal patterns were analyzed between coral reefs across jurisdictional marine zones to identify spatial relationships between larval sources and destinations within countries and territories across the region. We applied our results in Marxan, a conservation planning software tool, to identify a regional coral reef MPA network design that meets conservation goals, minimizes underlying threats, and maintains coral reef connectivity. Our results suggest that approximately 77% of coral reefs identified as having a high regional connectivity value are not included in the existing MPA network. This research is unique because we quantify and report coral larval connectivity data by marine ecoregions and Exclusive Economic Zones (EZZ) and use this information to identify gaps in the current Caribbean-wide MPA network by integrating asymmetric connectivity information in Marxan to design a regional MPA network that includes important reef network connections. The identification of important reef connectivity metrics guides the selection of priority conservation areas and supports resilience at the whole system level into the future. PMID:26641083

Network diffusion accurately models the relationship between structural and functional brain connectivity networks

PubMed Central

Abdelnour, Farras; Voss, Henning U.; Raj, Ashish

2014-01-01

The relationship between anatomic connectivity of large-scale brain networks and their functional connectivity is of immense importance and an area of active research. Previous attempts have required complex simulations which model the dynamics of each cortical region, and explore the coupling between regions as derived by anatomic connections. While much insight is gained from these non-linear simulations, they can be computationally taxing tools for predicting functional from anatomic connectivities. Little attention has been paid to linear models. Here we show that a properly designed linear model appears to be superior to previous non-linear approaches in capturing the brain’s long-range second order correlation structure that governs the relationship between anatomic and functional connectivities. We derive a linear network of brain dynamics based on graph diffusion, whereby the diffusing quantity undergoes a random walk on a graph. We test our model using subjects who underwent diffusion MRI and resting state fMRI. The network diffusion model applied to the structural networks largely predicts the correlation structures derived from their fMRI data, to a greater extent than other approaches. The utility of the proposed approach is that it can routinely be used to infer functional correlation from anatomic connectivity. And since it is linear, anatomic connectivity can also be inferred from functional data. The success of our model confirms the linearity of ensemble average signals in the brain, and implies that their long-range correlation structure may percolate within the brain via purely mechanistic processes enacted on its structural connectivity pathways. PMID:24384152

Slicing, sampling, and distance-dependent effects affect network measures in simulated cortical circuit structures.

PubMed

Miner, Daniel C; Triesch, Jochen

2014-01-01

The neuroanatomical connectivity of cortical circuits is believed to follow certain rules, the exact origins of which are still poorly understood. In particular, numerous nonrandom features, such as common neighbor clustering, overrepresentation of reciprocal connectivity, and overrepresentation of certain triadic graph motifs have been experimentally observed in cortical slice data. Some of these data, particularly regarding bidirectional connectivity are seemingly contradictory, and the reasons for this are unclear. Here we present a simple static geometric network model with distance-dependent connectivity on a realistic scale that naturally gives rise to certain elements of these observed behaviors, and may provide plausible explanations for some of the conflicting findings. Specifically, investigation of the model shows that experimentally measured nonrandom effects, especially bidirectional connectivity, may depend sensitively on experimental parameters such as slice thickness and sampling area, suggesting potential explanations for the seemingly conflicting experimental results.

Slicing, sampling, and distance-dependent effects affect network measures in simulated cortical circuit structures

PubMed Central

Miner, Daniel C.; Triesch, Jochen

2014-01-01

The neuroanatomical connectivity of cortical circuits is believed to follow certain rules, the exact origins of which are still poorly understood. In particular, numerous nonrandom features, such as common neighbor clustering, overrepresentation of reciprocal connectivity, and overrepresentation of certain triadic graph motifs have been experimentally observed in cortical slice data. Some of these data, particularly regarding bidirectional connectivity are seemingly contradictory, and the reasons for this are unclear. Here we present a simple static geometric network model with distance-dependent connectivity on a realistic scale that naturally gives rise to certain elements of these observed behaviors, and may provide plausible explanations for some of the conflicting findings. Specifically, investigation of the model shows that experimentally measured nonrandom effects, especially bidirectional connectivity, may depend sensitively on experimental parameters such as slice thickness and sampling area, suggesting potential explanations for the seemingly conflicting experimental results. PMID:25414647

Simulating the wealth distribution with a Richest-Following strategy on scale-free network

NASA Astrophysics Data System (ADS)

Hu, Mao-Bin; Jiang, Rui; Wu, Qing-Song; Wu, Yong-Hong

2007-07-01

In this paper, we investigate the wealth distribution with agents playing evolutionary games on a scale-free social network adopting the Richest-Following strategy. Pareto's power-law distribution (1897) of wealth is demonstrated with power factor in agreement with that of US or Japan. Moreover, the agent's personal wealth is proportional to its number of contacts (connectivity), and this leads to the phenomenon that the rich gets richer and the poor gets relatively poorer, which agrees with the Matthew Effect.

Sensitivity simulations of superparameterised convection in a general circulation model

NASA Astrophysics Data System (ADS)

Rybka, Harald; Tost, Holger

2015-04-01

Cloud Resolving Models (CRMs) covering a horizontal grid spacing from a few hundred meters up to a few kilometers have been used to explicitly resolve small-scale and mesoscale processes. Special attention has been paid to realistically represent cloud dynamics and cloud microphysics involving cloud droplets, ice crystals, graupel and aerosols. The entire variety of physical processes on the small-scale interacts with the larger-scale circulation and has to be parameterised on the coarse grid of a general circulation model (GCM). Since more than a decade an approach to connect these two types of models which act on different scales has been developed to resolve cloud processes and their interactions with the large-scale flow. The concept is to use an ensemble of CRM grid cells in a 2D or 3D configuration in each grid cell of the GCM to explicitly represent small-scale processes avoiding the use of convection and large-scale cloud parameterisations which are a major source for uncertainties regarding clouds. The idea is commonly known as superparameterisation or cloud-resolving convection parameterisation. This study presents different simulations of an adapted Earth System Model (ESM) connected to a CRM which acts as a superparameterisation. Simulations have been performed with the ECHAM/MESSy atmospheric chemistry (EMAC) model comparing conventional GCM runs (including convection and large-scale cloud parameterisations) with the improved superparameterised EMAC (SP-EMAC) modeling one year with prescribed sea surface temperatures and sea ice content. The sensitivity of atmospheric temperature, precipiation patterns, cloud amount and types is observed changing the embedded CRM represenation (orientation, width, no. of CRM cells, 2D vs. 3D). Additionally, we also evaluate the radiation balance with the new model configuration, and systematically analyse the impact of tunable parameters on the radiation budget and hydrological cycle. Furthermore, the subgrid variability (individual CRM cell output) is analysed in order to illustrate the importance of a highly varying atmospheric structure inside a single GCM grid box. Finally, the convective transport of Radon is observed comparing different transport procedures and their influence on the vertical tracer distribution.

Dispersion Analysis Using Particle Tracking Simulations Through Heterogeneity Based on Outcrop Lidar Imagery

NASA Astrophysics Data System (ADS)

Klise, K. A.; Weissmann, G. S.; McKenna, S. A.; Tidwell, V. C.; Frechette, J. D.; Wawrzyniec, T. F.

2007-12-01

Solute plumes are believed to disperse in a non-Fickian manner due to small-scale heterogeneity and variable velocities that create preferential pathways. In order to accurately predict dispersion in naturally complex geologic media, the connection between heterogeneity and dispersion must be better understood. Since aquifer properties can not be measured at every location, it is common to simulate small-scale heterogeneity with random field generators based on a two-point covariance (e.g., through use of sequential simulation algorithms). While these random fields can produce preferential flow pathways, it is unknown how well the results simulate solute dispersion through natural heterogeneous media. To evaluate the influence that complex heterogeneity has on dispersion, we utilize high-resolution terrestrial lidar to identify and model lithofacies from outcrop for application in particle tracking solute transport simulations using RWHet. The lidar scan data are used to produce a lab (meter) scale two-dimensional model that captures 2-8 mm scale natural heterogeneity. Numerical simulations utilize various methods to populate the outcrop structure captured by the lidar-based image with reasonable hydraulic conductivity values. The particle tracking simulations result in residence time distributions used to evaluate the nature of dispersion through complex media. Particle tracking simulations through conductivity fields produced from the lidar images are then compared to particle tracking simulations through hydraulic conductivity fields produced from sequential simulation algorithms. Based on this comparison, the study aims to quantify the difference in dispersion when using realistic and simplified representations of aquifer heterogeneity. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Delineating wetland catchments and modeling hydrologic connectivity using lidar data and aerial imagery

NASA Astrophysics Data System (ADS)

Wu, Qiusheng; Lane, Charles R.

2017-07-01

In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In reality, however, many depressions in the DEM are actual wetland landscape features with seasonal to permanent inundation patterning characterized by nested hierarchical structures and dynamic filling-spilling-merging surface-water hydrological processes. Differentiating and appropriately processing such ecohydrologically meaningful features remains a major technical terrain-processing challenge, particularly as high-resolution spatial data are increasingly used to support modeling and geographic analysis needs. The objectives of this study were to delineate hierarchical wetland catchments and model their hydrologic connectivity using high-resolution lidar data and aerial imagery. The graph-theory-based contour tree method was used to delineate the hierarchical wetland catchments and characterize their geometric and topological properties. Potential hydrologic connectivity between wetlands and streams were simulated using the least-cost-path algorithm. The resulting flow network delineated potential flow paths connecting wetland depressions to each other or to the river network on scales finer than those available through the National Hydrography Dataset. The results demonstrated that our proposed framework is promising for improving overland flow simulation and hydrologic connectivity analysis.

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.

Spatial distribution of GRBs and large scale structure of the Universe

NASA Astrophysics Data System (ADS)

Bagoly, Zsolt; Rácz, István I.; Balázs, Lajos G.; Tóth, L. Viktor; Horváth, István

We studied the space distribution of the starburst galaxies from Millennium XXL database at z = 0.82. We examined the starburst distribution in the classical Millennium I (De Lucia et al. (2006)) using a semi-analytical model for the genesis of the galaxies. We simulated a starburst galaxies sample with Markov Chain Monte Carlo method. The connection between the large scale structures homogenous and starburst groups distribution (Kofman and Shandarin 1998), Suhhonenko et al. (2011), Liivamägi et al. (2012), Park et al. (2012), Horvath et al. (2014), Horvath et al. (2015)) on a defined scale were checked too.

Formation of large-scale structure from cosmic-string loops and cold dark matter

NASA Technical Reports Server (NTRS)

Melott, Adrian L.; Scherrer, Robert J.

1987-01-01

Some results from a numerical simulation of the formation of large-scale structure from cosmic-string loops are presented. It is found that even though G x mu is required to be lower than 2 x 10 to the -6th (where mu is the mass per unit length of the string) to give a low enough autocorrelation amplitude, there is excessive power on smaller scales, so that galaxies would be more dense than observed. The large-scale structure does not include a filamentary or connected appearance and shares with more conventional models based on Gaussian perturbations the lack of cluster-cluster correlation at the mean cluster separation scale as well as excessively small bulk velocities at these scales.

MODELING THE SUN’S SMALL-SCALE GLOBAL PHOTOSPHERIC MAGNETIC FIELD

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

Meyer, K. A.; Mackay, D. H., E-mail: k.meyer@abertay.ac.uk

We present a new model for the Sun’s global photospheric magnetic field during a deep minimum of activity, in which no active regions emerge. The emergence and subsequent evolution of small-scale magnetic features across the full solar surface is simulated, subject to the influence of a global supergranular flow pattern. Visually, the resulting simulated magnetograms reproduce the typical structure and scale observed in quiet Sun magnetograms. Quantitatively, the simulation quickly reaches a steady state, resulting in a mean field and flux distribution that are in good agreement with those determined from observations. A potential coronal magnetic field is extrapolated frommore » the simulated full Sun magnetograms to consider the implications of such a quiet photospheric magnetic field on the corona and inner heliosphere. The bulk of the coronal magnetic field closes very low down, in short connections between small-scale features in the simulated magnetic network. Just 0.1% of the photospheric magnetic flux is found to be open at 2.5 R {sub ⊙}, around 10–100 times less than that determined for typical Helioseismic and Magnetic Imager synoptic map observations. If such conditions were to exist on the Sun, this would lead to a significantly weaker interplanetary magnetic field than is currently observed, and hence a much higher cosmic ray flux at Earth.« less

On the Simulation-Based Reliability of Complex Emergency Logistics Networks in Post-Accident Rescues.

PubMed

Wang, Wei; Huang, Li; Liang, Xuedong

2018-01-06

This paper investigates the reliability of complex emergency logistics networks, as reliability is crucial to reducing environmental and public health losses in post-accident emergency rescues. Such networks' statistical characteristics are analyzed first. After the connected reliability and evaluation indices for complex emergency logistics networks are effectively defined, simulation analyses of network reliability are conducted under two different attack modes using a particular emergency logistics network as an example. The simulation analyses obtain the varying trends in emergency supply times and the ratio of effective nodes and validates the effects of network characteristics and different types of attacks on network reliability. The results demonstrate that this emergency logistics network is both a small-world and a scale-free network. When facing random attacks, the emergency logistics network steadily changes, whereas it is very fragile when facing selective attacks. Therefore, special attention should be paid to the protection of supply nodes and nodes with high connectivity. The simulation method provides a new tool for studying emergency logistics networks and a reference for similar studies.

On the Simulation-Based Reliability of Complex Emergency Logistics Networks in Post-Accident Rescues

PubMed Central

Wang, Wei; Huang, Li; Liang, Xuedong

2018-01-01

This paper investigates the reliability of complex emergency logistics networks, as reliability is crucial to reducing environmental and public health losses in post-accident emergency rescues. Such networks’ statistical characteristics are analyzed first. After the connected reliability and evaluation indices for complex emergency logistics networks are effectively defined, simulation analyses of network reliability are conducted under two different attack modes using a particular emergency logistics network as an example. The simulation analyses obtain the varying trends in emergency supply times and the ratio of effective nodes and validates the effects of network characteristics and different types of attacks on network reliability. The results demonstrate that this emergency logistics network is both a small-world and a scale-free network. When facing random attacks, the emergency logistics network steadily changes, whereas it is very fragile when facing selective attacks. Therefore, special attention should be paid to the protection of supply nodes and nodes with high connectivity. The simulation method provides a new tool for studying emergency logistics networks and a reference for similar studies. PMID:29316614

An approach to understanding hydrologic connectivity on the hillslope and the implications for nutrient transport

USGS Publications Warehouse

Stieglitz, M.; Shaman, J.; McNamara, J.; Engel, V.; Shanley, J.; Kling, G.W.

2003-01-01

Hydrologic processes control much of the export of organic matter and nutrients from the land surface. It is the variability of these hydrologic processes that produces variable patterns of nutrient transport in both space and time. In this paper, we explore how hydrologic "connectivity" potentially affects nutrient transport. Hydrologic connectivity is defined as the condition by which disparate regions on the hillslope are linked via subsurface water flow. We present simulations that suggest that for much of the year, water draining through a catchment is spatially isolated. Only rarely, during storm and snowmelt events when antecedent soil moisture is high, do our simulations suggest that mid-slope saturation (or near saturation) occurs and that a catchment connects from ridge to valley. Observations during snowmelt at a small headwater catchment in Idaho are consistent with these model simulations. During early season discharge episodes, in which the mid-slope soil column is not saturated, the electrical conductivity in the stream remains low, reflecting a restricted, local (lower slope) source of stream water and the continued isolation of upper and mid-slope soil water and nutrients from the stream system. Increased streamflow and higher stream water electrical conductivity, presumably reflecting the release of water from the upper reaches of the catchment, are simultaneously observed when the mid-slope becomes sufficiently wet. This study provides preliminary evidence that the seasonal timing of hydrologic connectivity may affect a range of ecological processes, including downslope nutrient transport, C/N cycling, and biological productivity along the toposequence. A better elucidation of hydrologic connectivity will be necessary for understanding local processes as well as material export from land to water at regional and global scales. Copyright 2003 by the American Geophysical Union.

A generative model of whole-brain effective connectivity.

PubMed

Frässle, Stefan; Lomakina, Ekaterina I; Kasper, Lars; Manjaly, Zina M; Leff, Alex; Pruessmann, Klaas P; Buhmann, Joachim M; Stephan, Klaas E

2018-05-25

The development of whole-brain models that can infer effective (directed) connection strengths from fMRI data represents a central challenge for computational neuroimaging. A recently introduced generative model of fMRI data, regression dynamic causal modeling (rDCM), moves towards this goal as it scales gracefully to very large networks. However, large-scale networks with thousands of connections are difficult to interpret; additionally, one typically lacks information (data points per free parameter) for precise estimation of all model parameters. This paper introduces sparsity constraints to the variational Bayesian framework of rDCM as a solution to these problems in the domain of task-based fMRI. This sparse rDCM approach enables highly efficient effective connectivity analyses in whole-brain networks and does not require a priori assumptions about the network's connectivity structure but prunes fully (all-to-all) connected networks as part of model inversion. Following the derivation of the variational Bayesian update equations for sparse rDCM, we use both simulated and empirical data to assess the face validity of the model. In particular, we show that it is feasible to infer effective connection strengths from fMRI data using a network with more than 100 regions and 10,000 connections. This demonstrates the feasibility of whole-brain inference on effective connectivity from fMRI data - in single subjects and with a run-time below 1 min when using parallelized code. We anticipate that sparse rDCM may find useful application in connectomics and clinical neuromodeling - for example, for phenotyping individual patients in terms of whole-brain network structure. Copyright © 2018. Published by Elsevier Inc.

Trans-oceanic Remote Power Hardware-in-the-Loop: Multi-site Hardware, Integrated Controller, and Electric Network Co-simulation

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

Lundstrom, Blake R.; Palmintier, Bryan S.; Rowe, Daniel

Electric system operators are increasingly concerned with the potential system-wide impacts of the large-scale integration of distributed energy resources (DERs) including voltage control, protection coordination, and equipment wear. This prompts a need for new simulation techniques that can simultaneously capture all the components of these large integrated smart grid systems. This paper describes a novel platform that combines three emerging research areas: power systems co-simulation, power hardware in the loop (PHIL) simulation, and lab-lab links. The platform is distributed, real-time capable, allows for easy internet-based connection from geographically-dispersed participants, and is software platform agnostic. We demonstrate its utility by studyingmore » real-time PHIL co-simulation of coordinated solar PV firming control of two inverters connected in multiple electric distribution network models, prototypical of U.S. and Australian systems. Here, the novel trans-pacific closed-loop system simulation was conducted in real-time using a power network simulator and physical PV/battery inverter at power at the National Renewable Energy Laboratory in Golden, CO, USA and a physical PV inverter at power at the Commonwealth Scientific and Industrial Research Organisation's Energy Centre in Newcastle, NSW, Australia. This capability enables smart grid researchers throughout the world to leverage their unique simulation capabilities for multi-site collaborations that can effectively simulate and validate emerging smart grid technology solutions.« less

Trans-oceanic Remote Power Hardware-in-the-Loop: Multi-site Hardware, Integrated Controller, and Electric Network Co-simulation

DOE PAGES

Lundstrom, Blake R.; Palmintier, Bryan S.; Rowe, Daniel; ...

2017-07-24

Electric system operators are increasingly concerned with the potential system-wide impacts of the large-scale integration of distributed energy resources (DERs) including voltage control, protection coordination, and equipment wear. This prompts a need for new simulation techniques that can simultaneously capture all the components of these large integrated smart grid systems. This paper describes a novel platform that combines three emerging research areas: power systems co-simulation, power hardware in the loop (PHIL) simulation, and lab-lab links. The platform is distributed, real-time capable, allows for easy internet-based connection from geographically-dispersed participants, and is software platform agnostic. We demonstrate its utility by studyingmore » real-time PHIL co-simulation of coordinated solar PV firming control of two inverters connected in multiple electric distribution network models, prototypical of U.S. and Australian systems. Here, the novel trans-pacific closed-loop system simulation was conducted in real-time using a power network simulator and physical PV/battery inverter at power at the National Renewable Energy Laboratory in Golden, CO, USA and a physical PV inverter at power at the Commonwealth Scientific and Industrial Research Organisation's Energy Centre in Newcastle, NSW, Australia. This capability enables smart grid researchers throughout the world to leverage their unique simulation capabilities for multi-site collaborations that can effectively simulate and validate emerging smart grid technology solutions.« less

On the galaxy–halo connection in the EAGLE simulation

DOE PAGES

Desmond, Harry; Mao, Yao -Yuan; Wechsler, Risa H.; ...

2017-06-13

Empirical models of galaxy formation require assumptions about the correlations between galaxy and halo properties. These may be calibrated against observations or inferred from physical models such as hydrodynamical simulations. In this Letter, we use the EAGLE simulation to investigate the correlation of galaxy size with halo properties. We motivate this analysis by noting that the common assumption of angular momentum partition between baryons and dark matter in rotationally supported galaxies overpredicts both the spread in the stellar mass–size relation and the anticorrelation of size and velocity residuals, indicating a problem with the galaxy–halo connection it implies. We find themore » EAGLE galaxy population to perform significantly better on both statistics, and trace this success to the weakness of the correlations of galaxy size with halo mass, concentration and spin at fixed stellar mass. Here by, using these correlations in empirical models will enable fine-grained aspects of galaxy scalings to be matched.« less

On the galaxy–halo connection in the EAGLE simulation

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

Desmond, Harry; Mao, Yao -Yuan; Wechsler, Risa H.

Empirical models of galaxy formation require assumptions about the correlations between galaxy and halo properties. These may be calibrated against observations or inferred from physical models such as hydrodynamical simulations. In this Letter, we use the EAGLE simulation to investigate the correlation of galaxy size with halo properties. We motivate this analysis by noting that the common assumption of angular momentum partition between baryons and dark matter in rotationally supported galaxies overpredicts both the spread in the stellar mass–size relation and the anticorrelation of size and velocity residuals, indicating a problem with the galaxy–halo connection it implies. We find themore » EAGLE galaxy population to perform significantly better on both statistics, and trace this success to the weakness of the correlations of galaxy size with halo mass, concentration and spin at fixed stellar mass. Here by, using these correlations in empirical models will enable fine-grained aspects of galaxy scalings to be matched.« less

Maximizing algebraic connectivity in air transportation networks

NASA Astrophysics Data System (ADS)

Wei, Peng

In air transportation networks the robustness of a network regarding node and link failures is a key factor for its design. An experiment based on the real air transportation network is performed to show that the algebraic connectivity is a good measure for network robustness. Three optimization problems of algebraic connectivity maximization are then formulated in order to find the most robust network design under different constraints. The algebraic connectivity maximization problem with flight routes addition or deletion is first formulated. Three methods to optimize and analyze the network algebraic connectivity are proposed. The Modified Greedy Perturbation Algorithm (MGP) provides a sub-optimal solution in a fast iterative manner. The Weighted Tabu Search (WTS) is designed to offer a near optimal solution with longer running time. The relaxed semi-definite programming (SDP) is used to set a performance upper bound and three rounding techniques are discussed to find the feasible solution. The simulation results present the trade-off among the three methods. The case study on two air transportation networks of Virgin America and Southwest Airlines show that the developed methods can be applied in real world large scale networks. The algebraic connectivity maximization problem is extended by adding the leg number constraint, which considers the traveler's tolerance for the total connecting stops. The Binary Semi-Definite Programming (BSDP) with cutting plane method provides the optimal solution. The tabu search and 2-opt search heuristics can find the optimal solution in small scale networks and the near optimal solution in large scale networks. The third algebraic connectivity maximization problem with operating cost constraint is formulated. When the total operating cost budget is given, the number of the edges to be added is not fixed. Each edge weight needs to be calculated instead of being pre-determined. It is illustrated that the edge addition and the weight assignment can not be studied separately for the problem with operating cost constraint. Therefore a relaxed SDP method with golden section search is developed to solve both at the same time. The cluster decomposition is utilized to solve large scale networks.

From crater functions to partial differential equations: a new approach to ion bombardment induced nonequilibrium pattern formation.

PubMed

Norris, Scott A; Brenner, Michael P; Aziz, Michael J

2009-06-03

We develop a methodology for deriving continuum partial differential equations for the evolution of large-scale surface morphology directly from molecular dynamics simulations of the craters formed from individual ion impacts. Our formalism relies on the separation between the length scale of ion impact and the characteristic scale of pattern formation, and expresses the surface evolution in terms of the moments of the crater function. We demonstrate that the formalism reproduces the classical Bradley-Harper results, as well as ballistic atomic drift, under the appropriate simplifying assumptions. Given an actual set of converged molecular dynamics moments and their derivatives with respect to the incidence angle, our approach can be applied directly to predict the presence and absence of surface morphological instabilities. This analysis represents the first work systematically connecting molecular dynamics simulations of ion bombardment to partial differential equations that govern topographic pattern-forming instabilities.

Sediment Connectivity and Transport Pathways in Tidal Inlets: a Conceptual Framework with Application to Ameland Inlet

NASA Astrophysics Data System (ADS)

Pearson, S.; van Prooijen, B. C.; Zheng Bing, W.; Bak, J.

2017-12-01

Predicting the response of tidal inlets and adjacent coastlines to sea level rise and anthropogenic interventions (e.g. sand nourishments) requires understanding of sediment transport pathways. These pathways are strongly dependent on hydrodynamic forcing, grain size, underlying morphology, and the timescale considered. To map and describe these pathways, we considered the concept of sediment connectivity, which quantifies the degree to which sediment transport pathways link sources to receptors. In this study we established a framework for understanding sediment transport pathways in coastal environments, using Ameland Inlet in the Dutch Wadden Sea as a basis. We used the Delft3D morphodynamic model to assess the fate of sediment as it moved between specific morphological units defined in the model domain. Simulation data was synthesized in a graphical network and then graph theory used to analyze connectivity at different space and time scales. At decadal time scales, fine and very fine sand (<250μm) have greater connectivity with receptor areas further away from their sources. Conversely, medium sand (>250μm) shows lower connectivity, even in more energetic areas. Greater sediment connectivity was found under the influence of wind and waves when compared to purely tidal forcing. Connectivity shows considerable spatial variation in cross shore and alongshore directions, depending on proximity to the inlet and dominant wave direction. Furthermore, connectivity generally increases at longer timescales. Asymmetries in connectivity (i.e. unidirectional transport) can be used to explain long-term erosional or depositional trends. As such, an understanding of sediment connectivity as a function of grain size could yield useful insights for resolving sediment transport pathways and the fate of a nourishment in coastal environments.

The Large-scale Structure of the Universe: Probes of Cosmology and Structure Formation

NASA Astrophysics Data System (ADS)

Noh, Yookyung

The usefulness of large-scale structure as a probe of cosmology and structure formation is increasing as large deep surveys in multi-wavelength bands are becoming possible. The observational analysis of large-scale structure guided by large volume numerical simulations are beginning to offer us complementary information and crosschecks of cosmological parameters estimated from the anisotropies in Cosmic Microwave Background (CMB) radiation. Understanding structure formation and evolution and even galaxy formation history is also being aided by observations of different redshift snapshots of the Universe, using various tracers of large-scale structure. This dissertation work covers aspects of large-scale structure from the baryon acoustic oscillation scale, to that of large scale filaments and galaxy clusters. First, I discuss a large- scale structure use for high precision cosmology. I investigate the reconstruction of Baryon Acoustic Oscillation (BAO) peak within the context of Lagrangian perturbation theory, testing its validity in a large suite of cosmological volume N-body simulations. Then I consider galaxy clusters and the large scale filaments surrounding them in a high resolution N-body simulation. I investigate the geometrical properties of galaxy cluster neighborhoods, focusing on the filaments connected to clusters. Using mock observations of galaxy clusters, I explore the correlations of scatter in galaxy cluster mass estimates from multi-wavelength observations and different measurement techniques. I also examine the sources of the correlated scatter by considering the intrinsic and environmental properties of clusters.

Application of Discrete Fracture Modeling and Upscaling Techniques to Complex Fractured Reservoirs

NASA Astrophysics Data System (ADS)

Karimi-Fard, M.; Lapene, A.; Pauget, L.

2012-12-01

During the last decade, an important effort has been made to improve data acquisition (seismic and borehole imaging) and workflow for reservoir characterization which has greatly benefited the description of fractured reservoirs. However, the geological models resulting from the interpretations need to be validated or calibrated against dynamic data. Flow modeling in fractured reservoirs remains a challenge due to the difficulty of representing mass transfers at different heterogeneity scales. The majority of the existing approaches are based on dual continuum representation where the fracture network and the matrix are represented separately and their interactions are modeled using transfer functions. These models are usually based on idealized representation of the fracture distribution which makes the integration of real data difficult. In recent years, due to increases in computer power, discrete fracture modeling techniques (DFM) are becoming popular. In these techniques the fractures are represented explicitly allowing the direct use of data. In this work we consider the DFM technique developed by Karimi-Fard et al. [1] which is based on an unstructured finite-volume discretization. The mass flux between two adjacent control-volumes is evaluated using an optimized two-point flux approximation. The result of the discretization is a list of control-volumes with the associated pore-volumes and positions, and a list of connections with the associated transmissibilities. Fracture intersections are simplified using a connectivity transformation which contributes considerably to the efficiency of the methodology. In addition, the method is designed for general purpose simulators and any connectivity based simulator can be used for flow simulations. The DFM technique is either used standalone or as part of an upscaling technique. The upscaling techniques are required for large reservoirs where the explicit representation of all fractures and faults is not possible. Karimi-Fard et al. [2] have developed an upscaling technique based on DFM representation. The original version of this technique was developed to construct a dual-porosity model from a discrete fracture description. This technique has been extended and generalized so it can be applied to a wide range of problems from reservoirs with a few or no fracture to highly fractured reservoirs. In this work, we present the application of these techniques to two three-dimensional fractured reservoirs constructed using real data. The first model contains more than 600 medium and large scale fractures. The fractures are not always connected which requires a general modeling technique. The reservoir has 50 wells (injectors and producers) and water flooding simulations are performed. The second test case is a larger reservoir with sparsely distributed faults. Single-phase simulations are performed with 5 producing wells. [1] Karimi-Fard M., Durlofsky L.J., and Aziz K. 2004. An efficient discrete-fracture model applicable for general-purpose reservoir simulators. SPE Journal, 9(2): 227-236. [2] Karimi-Fard M., Gong B., and Durlofsky L.J. 2006. Generation of coarse-scale continuum flow models from detailed fracture characterizations. Water Resources Research, 42(10): W10423.

Predicting the breakdown strength and lifetime of nanocomposites using a multi-scale modeling approach

NASA Astrophysics Data System (ADS)

Huang, Yanhui; Zhao, He; Wang, Yixing; Ratcliff, Tyree; Breneman, Curt; Brinson, L. Catherine; Chen, Wei; Schadler, Linda S.

2017-08-01

It has been found that doping dielectric polymers with a small amount of nanofiller or molecular additive can stabilize the material under a high field and lead to increased breakdown strength and lifetime. Choosing appropriate fillers is critical to optimizing the material performance, but current research largely relies on experimental trial and error. The employment of computer simulations for nanodielectric design is rarely reported. In this work, we propose a multi-scale modeling approach that employs ab initio, Monte Carlo, and continuum scales to predict the breakdown strength and lifetime of polymer nanocomposites based on the charge trapping effect of the nanofillers. The charge transfer, charge energy relaxation, and space charge effects are modeled in respective hierarchical scales by distinctive simulation techniques, and these models are connected together for high fidelity and robustness. The preliminary results show good agreement with the experimental data, suggesting its promise for use in the computer aided material design of high performance dielectrics.

Internal Fluid Dynamics and Frequency Scaling of Sweeping Jet Fluidic Oscillators

NASA Astrophysics Data System (ADS)

Seo, Jung Hee; Salazar, Erik; Mittal, Rajat

2017-11-01

Sweeping jet fluidic oscillators (SJFOs) are devices that produce a spatially oscillating jet solely based on intrinsic flow instability mechanisms without any moving parts. Recently, SJFOs have emerged as effective actuators for flow control, but the internal fluid dynamics of the device that drives the oscillatory flow mechanism is not yet fully understood. In the current study, the internal fluid dynamics of the fluidic oscillator with feedback channels has been investigated by employing incompressible flow simulations. The study is focused on the oscillation mechanisms and scaling laws that underpin the jet oscillation. Based on the simulation results, simple phenomenological models that connect the jet deflection to the feedback flow are developed. Several geometric modifications are considered in order to explore the characteristic length scales and phase relationships associated with the jet oscillation and to assess the proposed phenomenological model. A scaling law for the jet oscillation frequency is proposed based on the detailed analysis. This research is supported by AFOSR Grant FA9550-14-1-0289 monitored by Dr. Douglas Smith.

Modelling disease outbreaks in realistic urban social networks

NASA Astrophysics Data System (ADS)

Eubank, Stephen; Guclu, Hasan; Anil Kumar, V. S.; Marathe, Madhav V.; Srinivasan, Aravind; Toroczkai, Zoltán; Wang, Nan

2004-05-01

Most mathematical models for the spread of disease use differential equations based on uniform mixing assumptions or ad hoc models for the contact process. Here we explore the use of dynamic bipartite graphs to model the physical contact patterns that result from movements of individuals between specific locations. The graphs are generated by large-scale individual-based urban traffic simulations built on actual census, land-use and population-mobility data. We find that the contact network among people is a strongly connected small-world-like graph with a well-defined scale for the degree distribution. However, the locations graph is scale-free, which allows highly efficient outbreak detection by placing sensors in the hubs of the locations network. Within this large-scale simulation framework, we then analyse the relative merits of several proposed mitigation strategies for smallpox spread. Our results suggest that outbreaks can be contained by a strategy of targeted vaccination combined with early detection without resorting to mass vaccination of a population.

Large-scale tropospheric transport in the Chemistry-Climate Model Initiative (CCMI) simulations

NASA Astrophysics Data System (ADS)

Orbe, Clara; Yang, Huang; Waugh, Darryn W.; Zeng, Guang; Morgenstern, Olaf; Kinnison, Douglas E.; Lamarque, Jean-Francois; Tilmes, Simone; Plummer, David A.; Scinocca, John F.; Josse, Beatrice; Marecal, Virginie; Jöckel, Patrick; Oman, Luke D.; Strahan, Susan E.; Deushi, Makoto; Tanaka, Taichu Y.; Yoshida, Kohei; Akiyoshi, Hideharu; Yamashita, Yousuke; Stenke, Andreas; Revell, Laura; Sukhodolov, Timofei; Rozanov, Eugene; Pitari, Giovanni; Visioni, Daniele; Stone, Kane A.; Schofield, Robyn; Banerjee, Antara

2018-05-01

Understanding and modeling the large-scale transport of trace gases and aerosols is important for interpreting past (and projecting future) changes in atmospheric composition. Here we show that there are large differences in the global-scale atmospheric transport properties among the models participating in the IGAC SPARC Chemistry-Climate Model Initiative (CCMI). Specifically, we find up to 40 % differences in the transport timescales connecting the Northern Hemisphere (NH) midlatitude surface to the Arctic and to Southern Hemisphere high latitudes, where the mean age ranges between 1.7 and 2.6 years. We show that these differences are related to large differences in vertical transport among the simulations, in particular to differences in parameterized convection over the oceans. While stronger convection over NH midlatitudes is associated with slower transport to the Arctic, stronger convection in the tropics and subtropics is associated with faster interhemispheric transport. We also show that the differences among simulations constrained with fields derived from the same reanalysis products are as large as (and in some cases larger than) the differences among free-running simulations, most likely due to larger differences in parameterized convection. Our results indicate that care must be taken when using simulations constrained with analyzed winds to interpret the influence of meteorology on tropospheric composition.

Where Are All of the Gas-bearing Local Dwarf Galaxies? Quantifying Possible Impacts of Reionization

NASA Astrophysics Data System (ADS)

Tollerud, Erik J.; Peek, J. E. G.

2018-04-01

We present an approach for comparing the detections and non-detections of Local Group (LG) dwarf galaxies in large H I surveys to the predictions of a suite of n-body simulations of the LG. This approach depends primarily on a set of empirical scaling relations to connect the simulations to the observations, rather than making strong theoretical assumptions. We then apply this methodology to the Galactic Arecibo L-band Feed Array Hi (GALFA-HI) Compact Cloud Catalog (CCC), and compare it to the suite Exploring the Local Volume In Simulations (ELVIS) of simulations. This approach reveals a strong tension between the naïve results of the model and the observations: while there are no LG dwarfs in the GALFA-HI CCC, the simulations predict ∼10. Applying a simple model of reionization can resolve this tension by preventing low-mass halos from forming gas. However, and if this effect operates as expected, the observations provide a constraint on the mass scale of the dwarf galaxy that reionization impacts. Combined with the observed properties of Leo T, the halo virial mass scale at which reionization impacts dwarf galaxy gas content is constrained to be ∼ {10}8.5 {M}ȯ , independent of any assumptions about star formation.

Highly efficient spatial data filtering in parallel using the opensource library CPPPO

NASA Astrophysics Data System (ADS)

Municchi, Federico; Goniva, Christoph; Radl, Stefan

2016-10-01

CPPPO is a compilation of parallel data processing routines developed with the aim to create a library for "scale bridging" (i.e. connecting different scales by mean of closure models) in a multi-scale approach. CPPPO features a number of parallel filtering algorithms designed for use with structured and unstructured Eulerian meshes, as well as Lagrangian data sets. In addition, data can be processed on the fly, allowing the collection of relevant statistics without saving individual snapshots of the simulation state. Our library is provided with an interface to the widely-used CFD solver OpenFOAM®, and can be easily connected to any other software package via interface modules. Also, we introduce a novel, extremely efficient approach to parallel data filtering, and show that our algorithms scale super-linearly on multi-core clusters. Furthermore, we provide a guideline for choosing the optimal Eulerian cell selection algorithm depending on the number of CPU cores used. Finally, we demonstrate the accuracy and the parallel scalability of CPPPO in a showcase focusing on heat and mass transfer from a dense bed of particles.

Obscuring and Feeding Supermassive Black Holes with Evolving Nuclear Star Clusters

NASA Astrophysics Data System (ADS)

Schartmann, M.; Burkert, A.; Krause, M.; Camenzind, M.; Meisenheimer, K.; Davies, R. I.

2010-05-01

Recently, high-resolution observations made with the help of the near-infrared adaptive optics integral field spectrograph SINFONI at the VLT proved the existence of massive and young nuclear star clusters in the centers of a sample of Seyfert galaxies. With the help of high-resolution hydrodynamical simulations with the pluto code, we follow the evolution of such clusters, especially focusing on mass and energy feedback from young stars. This leads to a filamentary inflow of gas on large scales (tens of parsecs), whereas a turbulent and very dense disk builds up on the parsec scale. Here we concentrate on the long-term evolution of the nuclear disk in NGC 1068 with the help of an effective viscous disk model, using the mass input from the large-scale simulations and accounting for star formation in the disk. This two-stage modeling enables us to connect the tens-of-parsecs scale region (observable with SINFONI) with the parsec-scale environment (MIDI observations). At the current age of the nuclear star cluster, our simulations predict disk sizes of the order 0.8 to 0.9 pc, gas masses of order 106 M⊙, and mass transfer rates through the inner boundary of order 0.025 M⊙ yr-1, in good agreement with values derived from observations.

A connectivity-based modeling approach for representing hysteresis in macroscopic two-phase flow properties

DOE PAGES

Cihan, Abdullah; Birkholzer, Jens; Trevisan, Luca; ...

2014-12-31

During CO 2 injection and storage in deep reservoirs, the injected CO 2 enters into an initially brine saturated porous medium, and after the injection stops, natural groundwater flow eventually displaces the injected mobile-phase CO 2, leaving behind residual non-wetting fluid. Accurate modeling of two-phase flow processes are needed for predicting fate and transport of injected CO 2, evaluating environmental risks and designing more effective storage schemes. The entrapped non-wetting fluid saturation is typically a function of the spatially varying maximum saturation at the end of injection. At the pore-scale, distribution of void sizes and connectivity of void space playmore » a major role for the macroscopic hysteresis behavior and capillary entrapment of wetting and non-wetting fluids. This paper presents development of an approach based on the connectivity of void space for modeling hysteretic capillary pressure-saturation-relative permeability relationships. The new approach uses void-size distribution and a measure of void space connectivity to compute the hysteretic constitutive functions and to predict entrapped fluid phase saturations. Two functions, the drainage connectivity function and the wetting connectivity function, are introduced to characterize connectivity of fluids in void space during drainage and wetting processes. These functions can be estimated through pore-scale simulations in computer-generated porous media or from traditional experimental measurements of primary drainage and main wetting curves. The hysteresis model for saturation-capillary pressure is tested successfully by comparing the model-predicted residual saturation and scanning curves with actual data sets obtained from column experiments found in the literature. A numerical two-phase model simulator with the new hysteresis functions is tested against laboratory experiments conducted in a quasi-two-dimensional flow cell (91.4cm×5.6cm×61cm), packed with homogeneous and heterogeneous sands. Initial results show that the model can predict spatial and temporal distribution of injected fluid during the experiments reasonably well. However, further analyses are needed for comprehensively testing the ability of the model to predict transient two-phase flow processes and capillary entrapment in geological reservoirs during geological carbon sequestration.« less

Precomputing upscaled hydraulic conductivity for complex geological structures

NASA Astrophysics Data System (ADS)

Mariethoz, G.; Jha, S. K.; George, M.; Maheswarajah, S.; John, V.; De Re, D.; Smith, M.

2013-12-01

3D geological models are built to capture the geological heterogeneity at a fine scale. However groundwater modellers are often interested in the hydraulic conductivity (K) values at a much coarser scale to reduce the numerical burden. Upscaling is used to assign conductivity to large volumes, which necessarily causes a loss of information. Recent literature has shown that the connectivity in the channelized structures is an important feature that needs to be taken into account for accurate upscaling. In this work we study the effect of channel parameters, e.g. width, sinuosity, connectivity etc. on the upscaled values of the hydraulic conductivity and the associated uncertainty. We devise a methodology that derives correspondences between a lithological description and the equivalent hydraulic conductivity at a larger scale. The method uses multiple-point geostatistics simulations (MPS) and parameterizes the 3D structures by introducing continuous rotation and affinity parameters. Additional statistical characterization is obtained by transition probabilities and connectivity measures. Equivalent hydraulic conductivity is then estimated by solving a flow problem for the entire heterogeneous domain by applying steady state flow in horizontal and vertical directions. This is systematically performed for many random realisations of the small scale structures to enable a probability distribution for the equivalent upscaled hydraulic conductivity. This process allows deriving systematic relationships between a given depositional environment and precomputed equivalent parameters. A modeller can then exploit the prior knowledge of the depositional environment and expected geological heterogeneity to bypass the step of generating small-scale models, and directly work with upscaled values.

Generalized network modeling of capillary-dominated two-phase flow

NASA Astrophysics Data System (ADS)

Raeini, Ali Q.; Bijeljic, Branko; Blunt, Martin J.

2018-02-01

We present a generalized network model for simulating capillary-dominated two-phase flow through porous media at the pore scale. Three-dimensional images of the pore space are discretized using a generalized network—described in a companion paper [A. Q. Raeini, B. Bijeljic, and M. J. Blunt, Phys. Rev. E 96, 013312 (2017), 10.1103/PhysRevE.96.013312]—which comprises pores that are divided into smaller elements called half-throats and subsequently into corners. Half-throats define the connectivity of the network at the coarsest level, connecting each pore to half-throats of its neighboring pores from their narrower ends, while corners define the connectivity of pore crevices. The corners are discretized at different levels for accurate calculation of entry pressures, fluid volumes, and flow conductivities that are obtained using direct simulation of flow on the underlying image. This paper discusses the two-phase flow model that is used to compute the averaged flow properties of the generalized network, including relative permeability and capillary pressure. We validate the model using direct finite-volume two-phase flow simulations on synthetic geometries, and then present a comparison of the model predictions with a conventional pore-network model and experimental measurements of relative permeability in the literature.

Unveiling the Role of the Magnetic Field at the Smallest Scales of Star Formation

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

Hull, Charles L. H.; Mocz, Philip; Burkhart, Blakesley

We report Atacama Large Millimeter/submillimeter Array (ALMA) observations of polarized dust emission from the protostellar source Ser-emb 8 at a linear resolution of 140 au. Assuming models of dust-grain alignment hold, the observed polarization pattern gives a projected view of the magnetic field structure in this source. Contrary to expectations based on models of strongly magnetized star formation, the magnetic field in Ser-emb 8 does not exhibit an hourglass morphology. Combining the new ALMA data with previous observational studies, we can connect magnetic field structure from protostellar core (∼80,000 au) to disk (∼100 au) scales. We compare our observations withmore » four magnetohydrodynamic gravo-turbulence simulations made with the AREPO code that have initial conditions ranging from super-Alfvénic (weakly magnetized) to sub-Alfvénic (strongly magnetized). These simulations achieve the spatial dynamic range necessary to resolve the collapse of protostars from the parsec scale of star-forming clouds down to the ∼100 au scale probed by ALMA. Only in the very strongly magnetized simulation do we see both the preservation of the field direction from cloud to disk scales and an hourglass-shaped field at <1000 au scales. We conduct an analysis of the relative orientation of the magnetic field and the density structure in both the Ser-emb 8 ALMA observations and the synthetic observations of the four AREPO simulations. We conclude that the Ser-emb 8 data are most similar to the weakly magnetized simulations, which exhibit random alignment, in contrast to the strongly magnetized simulation, where the magnetic field plays a role in shaping the density structure in the source. In the weak-field case, it is turbulence—not the magnetic field—that shapes the material that forms the protostar, highlighting the dominant role that turbulence can play across many orders of magnitude in spatial scale.« less

Coarse-Grained Models for Protein-Cell Membrane Interactions

PubMed Central

Bradley, Ryan; Radhakrishnan, Ravi

2015-01-01

The physiological properties of biological soft matter are the product of collective interactions, which span many time and length scales. Recent computational modeling efforts have helped illuminate experiments that characterize the ways in which proteins modulate membrane physics. Linking these models across time and length scales in a multiscale model explains how atomistic information propagates to larger scales. This paper reviews continuum modeling and coarse-grained molecular dynamics methods, which connect atomistic simulations and single-molecule experiments with the observed microscopic or mesoscale properties of soft-matter systems essential to our understanding of cells, particularly those involved in sculpting and remodeling cell membranes. PMID:26613047

Epidemic dynamics and endemic states in complex networks

NASA Astrophysics Data System (ADS)

Pastor-Satorras, Romualdo; Vespignani, Alessandro

2001-06-01

We study by analytical methods and large scale simulations a dynamical model for the spreading of epidemics in complex networks. In networks with exponentially bounded connectivity we recover the usual epidemic behavior with a threshold defining a critical point below that the infection prevalence is null. On the contrary, on a wide range of scale-free networks we observe the absence of an epidemic threshold and its associated critical behavior. This implies that scale-free networks are prone to the spreading and the persistence of infections whatever spreading rate the epidemic agents might possess. These results can help understanding computer virus epidemics and other spreading phenomena on communication and social networks.

Advancement in Watershed Modelling Using Dynamic Lateral and Longitudinal Sediment (Dis)connectivity Prediction

NASA Astrophysics Data System (ADS)

Mahoney, D. T.; al Aamery, N. M. H.; Fox, J.

2017-12-01

The authors find that sediment (dis)connectivity has seldom taken precedence within watershed models, and the present study advances this modeling framework and applies the modeling within a bedrock-controlled system. Sediment (dis)connectivity, defined as the detachment and transport of sediment from source to sink between geomorphic zones, is a major control on sediment transport. Given the availability of high resolution geospatial data, coupling sediment connectivity concepts within sediment prediction models offers an approach to simulate sediment sources and pathways within a watershed's sediment cascade. Bedrock controlled catchments are potentially unique due to the presence of rock outcrops causing longitudinal impedance to sediment transport pathways in turn impacting the longitudinal distribution of the energy gradient responsible for conveying sediment. Therefore, the authors were motivated by the need to formulate a sediment transport model that couples sediment (dis)connectivity knowledge to predict sediment flux for bedrock controlled catchments. A watershed-scale sediment transport model was formulated that incorporates sediment (dis)connectivity knowledge collected via field reconnaissance and predicts sediment flux through coupling with the Partheniades equation and sediment continuity model. Sediment (dis)connectivity was formulated by coupling probabilistic upland lateral connectivity prediction with instream longitudinal connectivity assessments via discretization of fluid and sediment pathways. Flux predictions from the upland lateral connectivity model served as an input to the instream longitudinal connectivity model. Disconnectivity in the instream model was simulated via the discretization of stream reaches due to barriers such as bedrock outcroppings and man-made check dams. The model was tested for a bedrock controlled catchment in Kentucky, USA for which extensive historic water and sediment flux data was available. Predicted sediment flux was validated via sediment flux measurements collected by the authors. Watershed configuration and the distribution of lateral and longitudinal impedances to sediment transport were found to have significant influence on sediment connectivity and thus sediment flux.

The hydrologic implications of alternative prioritizations of landscape-scale geographically isolated wetlands conservation

NASA Astrophysics Data System (ADS)

Evenson, G. R.; Golden, H. E.; Lane, C.; Mclaughlin, D. L.; D'Amico, E.

2016-12-01

Geographically isolated wetlands (GIWs), defined as upland embedded wetlands, provide an array of ecosystem goods and services. Wetland conservation efforts aim to protect GIWs in the face of continued threats from anthropogenic activities. Given limited conservation resources, there is a critical need for methods capable of evaluating the watershed-scale hydrologic implications of alternative approaches to GIW conservation. Further, there is a need for methods that quantify the watershed-scale aggregate effects of GIWs to determine their regulatory status within the United States. We applied the Soil and Water Assessment Tool (SWAT), a popular watershed-scale hydrologic model, to represent the 1,700 km2 Pipestem Creek watershed in North Dakota, USA. We modified the model to incorporate an improved representation of GIW hydrologic processes via hydrologic response unit (HRU) redefinition and modifications to the model source code. We then used the model to evaluate the hydrologic effects of alternative approaches to GIW conservation prioritization by simulating the destruction/removal of GIWs by sub-classes defined by their relative position within the simulated fill-spill GIW network and their surface area characteristics. We evaluated the alternative conservation approaches as impacting (1) simulated streamflow at the Pipestem Creek watershed outlet; (2) simulated water-levels within the GIWs; and (3) simulated hydrologic connections between the GIWs. Our approach to modifying SWAT and evaluating alternative GIW conservation strategies may be replicated in different watersheds and physiographic regions to aid the development of GIW conservation priorities.

Examination of Wildland Fire Spread at Small Scales Using Direct Numerical Simulations and High-Speed Laser Diagnostics

NASA Astrophysics Data System (ADS)

Wimer, N. T.; Mackoweicki, A. S.; Poludnenko, A. Y.; Hoffman, C.; Daily, J. W.; Rieker, G. B.; Hamlington, P.

2017-12-01

Results are presented from a joint computational and experimental research effort focused on understanding and characterizing wildland fire spread at small scales (roughly 1m-1mm) using direct numerical simulations (DNS) with chemical kinetics mechanisms that have been calibrated using data from high-speed laser diagnostics. The simulations are intended to directly resolve, with high physical accuracy, all small-scale fluid dynamic and chemical processes relevant to wildland fire spread. The high fidelity of the simulations is enabled by the calibration and validation of DNS sub-models using data from high-speed laser diagnostics. These diagnostics have the capability to measure temperature and chemical species concentrations, and are used here to characterize evaporation and pyrolysis processes in wildland fuels subjected to an external radiation source. The chemical kinetics code CHEMKIN-PRO is used to study and reduce complex reaction mechanisms for water removal, pyrolysis, and gas phase combustion during solid biomass burning. Simulations are then presented for a gaseous pool fire coupled with the resulting multi-step chemical reaction mechanisms, and the results are connected to the fundamental structure and spread of wildland fires. It is anticipated that the combined computational and experimental approach of this research effort will provide unprecedented access to information about chemical species, temperature, and turbulence during the entire pyrolysis, evaporation, ignition, and combustion process, thereby permitting more complete understanding of the physics that must be represented by coarse-scale numerical models of wildland fire spread.

Connections with nature and environmental behaviors.

PubMed

Geng, Liuna; Xu, Jingke; Ye, Lijuan; Zhou, Wenjun; Zhou, Kexin

2015-01-01

The influence of environmental attitudes on environmental behaviors has long been discussed. However, few studies have addressed the foundation of such attitudes. In the present study, we explored primitive belief underlying environmental attitudes, i.e., connections with nature, and its relationship with pro-environmental behaviors. Specifically, we used scales, a computerized Implicit Association Test, and a situational simulation experiment to examine both explicit and implicit connections with nature, both deliberate and spontaneous environmental behaviors, and to find correlations between environmental connectedness and environmental behaviors. Results showed that explicit connectedness was positively correlated with deliberate environmental behaviors, while implicit connectedness was positively correlated with spontaneous environmental behaviors. Additionally, explicit and implicit connectedness was independent of each other. In conclusion, the current study confirms the positive role played by connections with nature in promoting environmental behavior, and accordingly suggests means to encourage pro-environmental behavior by enhancing people's connectedness to nature.

Connections with Nature and Environmental Behaviors

PubMed Central

Geng, Liuna; Xu, Jingke; Ye, Lijuan; Zhou, Wenjun; Zhou, Kexin

2015-01-01

The influence of environmental attitudes on environmental behaviors has long been discussed. However, few studies have addressed the foundation of such attitudes. In the present study, we explored primitive belief underlying environmental attitudes, i.e., connections with nature, and its relationship with pro-environmental behaviors. Specifically, we used scales, a computerized Implicit Association Test, and a situational simulation experiment to examine both explicit and implicit connections with nature, both deliberate and spontaneous environmental behaviors, and to find correlations between environmental connectedness and environmental behaviors. Results showed that explicit connectedness was positively correlated with deliberate environmental behaviors, while implicit connectedness was positively correlated with spontaneous environmental behaviors. Additionally, explicit and implicit connectedness was independent of each other. In conclusion, the current study confirms the positive role played by connections with nature in promoting environmental behavior, and accordingly suggests means to encourage pro-environmental behavior by enhancing people’s connectedness to nature. PMID:25985075

A modelling framework to evaluate human-induced alterations of network sediment connectivity and quantify their unplanned adverse impact

NASA Astrophysics Data System (ADS)

Bizzi, S.; Schmitt, R. J. P.; Giuliani, M.; Castelletti, A.

2016-12-01

World-wide human-induced alterations of sediment transport, e.g. due to dams, sand and gravel mining along rivers and channel maintenance, translated into geomorphic changes, which have had major effects on ecosystem integrity, human livelihoods, ultimately negatively impacting also on the expected benefit from building water infrastructures. Despite considerable recent advances in modelling basin-scale hydrological and geomorphological processes, our ability to quantitatively simulate network sediment transport, foresee effects of alternative scenarios of human development on fluvial morpho-dynamics, and design anticipatory planning adaptation measures is still limited. In this work, we demonstrate the potential of a novel modelling framework called CASCADE (CAtchment SEdiment Connectivity And Delivery (Schmitt et al., 2016)) to characterize sediment connectivity at the whole river network scale, predict the disturbing effect of dams on the sediment transport, and quantify the associated loss with respect to the level of benefits that provided the economic justification for their development. CASCADE allows tracking the fate of a sediment from its source to its multiple sinks across the network. We present the results from two major, transboundary river systems (3S and Red River) in South-East Asia. We first discuss the ability of CASCADE to properly represent sediment connectivity at the network scale using available remote sensing data and information from monitoring networks. Secondly, we assess the impacts on sediment connectivity induced by existing and planned dams in the 3S and Red River basins and compare these alterations with revenues in terms of hydropower production. CASCADE outputs support a broader understanding of sediment connectivity tailored for water management issues not yet available, and it is suitable to enrich assessments of food-energy-water nexus. The model framework can be embedded into the design of optimal siting and sizing of water infrastructures at the river basin scale. This enlarges the scope of the analysis to account for human-induced alterations of network sediment connectivity, and to explore the trade-off with respect to primary operational objectives, such as hydropower production, water supply, and flood control.

Potential Connectivity of Coldwater Black Coral Communities in the Northern Gulf of Mexico.

PubMed

Cardona, Yuley; Ruiz-Ramos, Dannise V; Baums, Iliana B; Bracco, Annalisa

2016-01-01

The black coral Leiopathes glaberrima is a foundation species of deep-sea benthic communities but little is known of the longevity of its larvae and the timing of spawning because it inhabits environments deeper than 50 m that are logistically challenging to observe. Here, the potential connectivity of L. glaberrima in the northern Gulf of Mexico was investigated using a genetic and a physical dispersal model. The genetic analysis focused on data collected at four sites distributed to the east and west of Mississippi Canyon, provided information integrated over many (~10,000) generations and revealed low but detectable realized connectivity. The physical dispersal model simulated the circulation in the northern Gulf at a 1km horizontal resolution with transport-tracking capabilities; virtual larvae were deployed 12 times over the course of 3 years and followed over intervals of 40 days. Connectivity between sites to the east and west of the canyon was hampered by the complex bathymetry, by differences in mean circulation to the east and west of the Mississippi Canyon, and by flow instabilities at scales of a few kilometers. Further, the interannual variability of the flow field surpassed seasonal changes. Together, these results suggest that a) dispersal among sites is limited, b) any recovery in the event of a large perturbation will depend on local larvae produced by surviving individuals, and c) a competency period longer than a month is required for the simulated potential connectivity to match the connectivity from multi-locus genetic data under the hypothesis that connectivity has not changed significantly over the past 10,000 generations.

Potential Connectivity of Coldwater Black Coral Communities in the Northern Gulf of Mexico

PubMed Central

Cardona, Yuley; Ruiz-Ramos, Dannise V.; Baums, Iliana B.; Bracco, Annalisa

2016-01-01

The black coral Leiopathes glaberrima is a foundation species of deep-sea benthic communities but little is known of the longevity of its larvae and the timing of spawning because it inhabits environments deeper than 50 m that are logistically challenging to observe. Here, the potential connectivity of L. glaberrima in the northern Gulf of Mexico was investigated using a genetic and a physical dispersal model. The genetic analysis focused on data collected at four sites distributed to the east and west of Mississippi Canyon, provided information integrated over many (~10,000) generations and revealed low but detectable realized connectivity. The physical dispersal model simulated the circulation in the northern Gulf at a 1km horizontal resolution with transport-tracking capabilities; virtual larvae were deployed 12 times over the course of 3 years and followed over intervals of 40 days. Connectivity between sites to the east and west of the canyon was hampered by the complex bathymetry, by differences in mean circulation to the east and west of the Mississippi Canyon, and by flow instabilities at scales of a few kilometers. Further, the interannual variability of the flow field surpassed seasonal changes. Together, these results suggest that a) dispersal among sites is limited, b) any recovery in the event of a large perturbation will depend on local larvae produced by surviving individuals, and c) a competency period longer than a month is required for the simulated potential connectivity to match the connectivity from multi-locus genetic data under the hypothesis that connectivity has not changed significantly over the past 10,000 generations. PMID:27218260

A micro-macro coupling approach of MD-SPH method for reactive energetic materials

NASA Astrophysics Data System (ADS)

Liu, Gui Rong; Wang, Guang Yu; Peng, Qing; De, Suvranu

2017-01-01

The simulation of reactive energetic materials has long been the interest of researchers because of the extensive applications of explosives. Much research has been done on the subject at macro scale in the past and research at micro scale has been initiated recently. Equation of state (EoS) is the relation between physical quantities (pressure, temperature, energy and volume) describing thermodynamic states of materials under a given set of conditions. It plays a significant role in determining the characteristics of energetic materials, including Chapman-Jouguet point and detonation velocity. Furthermore, EoS is the key to connect microscopic and macroscopic phenomenon when simulating the macro effects of an explosion. For instance, an ignition and growth model for high explosives uses two JWL EoSs, one for solid explosive and the other for gaseous products, which are often obtained from experiments that can be quite expensive and hazardous. Therefore, it is ideal to calculate the EoS of energetic materials through computational means. In this paper, the EoSs for both solid and gaseous products of β-HMX are calculated using molecular dynamics simulation with ReaxFF-d3, a reactive force field obtained from quantum mechanics. The microscopic simulation results are then compared with experiments and the continuum ignition and growth model. Good agreement is observed. Then, the EoSs obtained through micro-scale simulation is applied in a smoothed particle hydrodynamics (SPH) code to simulate the macro effects of explosions. Simulation results are compared with experiments.

Environmental controls, oceanography and population dynamics of pathogens and harmful algal blooms: connecting sources to human exposure.

PubMed

Dyble, Julianne; Bienfang, Paul; Dusek, Eva; Hitchcock, Gary; Holland, Fred; Laws, Ed; Lerczak, James; McGillicuddy, Dennis J; Minnett, Peter; Moore, Stephanie K; O'Kelly, Charles; Solo-Gabriele, Helena; Wang, John D

2008-11-07

Coupled physical-biological models are capable of linking the complex interactions between environmental factors and physical hydrodynamics to simulate the growth, toxicity and transport of infectious pathogens and harmful algal blooms (HABs). Such simulations can be used to assess and predict the impact of pathogens and HABs on human health. Given the widespread and increasing reliance of coastal communities on aquatic systems for drinking water, seafood and recreation, such predictions are critical for making informed resource management decisions. Here we identify three challenges to making this connection between pathogens/HABs and human health: predicting concentrations and toxicity; identifying the spatial and temporal scales of population and ecosystem interactions; and applying the understanding of population dynamics of pathogens/HABs to management strategies. We elaborate on the need to meet each of these challenges, describe how modeling approaches can be used and discuss strategies for moving forward in addressing these challenges.

Lateral eddy diffusivity estimates from simulated and observed drifter trajectories: a case study for the Agulhas Current system

NASA Astrophysics Data System (ADS)

Rühs, Siren; Zhurbas, Victor; Durgadoo, Jonathan V.; Biastoch, Arne

2017-04-01

The Lagrangian description of fluid motion by sets of individual particle trajectories is extensively used to characterize connectivity between distinct oceanic locations. One important factor influencing the connectivity is the average rate of particle dispersal, generally quantified as Lagrangian diffusivity. In addition to Lagrangian observing programs, Lagrangian analyses are performed by advecting particles with the simulated flow field of ocean general circulation models (OGCMs). However, depending on the spatio-temporal model resolution, not all scale-dependent processes are explicitly resolved in the simulated velocity fields. Consequently, the dispersal of advective Lagrangian trajectories has been assumed not to be sufficiently diffusive compared to observed particle spreading. In this study we present a detailed analysis of the spatially variable lateral eddy diffusivity characteristics of advective drifter trajectories simulated with realistically forced OGCMs and compare them with estimates based on observed drifter trajectories. The extended Agulhas Current system around South Africa, known for its intricate mesoscale dynamics, serves as a test case. We show that a state-of-the-art eddy-resolving OGCM indeed features theoretically derived dispersion characteristics for diffusive regimes and realistically represents Lagrangian eddy diffusivity characteristics obtained from observed surface drifter trajectories. The estimates for the maximum and asymptotic lateral single-particle eddy diffusivities obtained from the observed and simulated drifter trajectories show a good agreement in their spatial pattern and magnitude. We further assess the sensitivity of the simulated lateral eddy diffusivity estimates to the temporal and lateral OGCM output resolution and examine the impact of the different eddy diffusivity characteristics on the Lagrangian connectivity between the Indian Ocean and the South Atlantic.

Cascading failures mechanism based on betweenness-degree ratio distribution with different connecting preferences

NASA Astrophysics Data System (ADS)

Wang, Xiao Juan; Guo, Shi Ze; Jin, Lei; Chen, Mo

We study the structural robustness of the scale free network against the cascading failure induced by overload. In this paper, a failure mechanism based on betweenness-degree ratio distribution is proposed. In the cascading failure model we built the initial load of an edge which is proportional to the node betweenness of its ends. During the edge random deletion, we find a phase transition. Then based on the phase transition, we divide the process of the cascading failure into two parts: the robust area and the vulnerable area, and define the corresponding indicator to measure the performance of the networks in both areas. From derivation, we find that the vulnerability of the network is determined by the distribution of betweenness-degree ratio. After that we use the connection between the node ability coefficient and distribution of betweenness-degree ratio to explain the cascading failure mechanism. In simulations, we verify the correctness of our derivations. By changing connecting preferences, we find scale free networks with a slight assortativity, which performs better both in robust area and vulnerable area.

Global diffusion of cosmic rays in random magnetic fields

NASA Astrophysics Data System (ADS)

Snodin, A. P.; Shukurov, A.; Sarson, G. R.; Bushby, P. J.; Rodrigues, L. F. S.

2016-04-01

The propagation of charged particles, including cosmic rays, in a partially ordered magnetic field is characterized by a diffusion tensor whose components depend on the particle's Larmor radius RL and the degree of order in the magnetic field. Most studies of the particle diffusion presuppose a scale separation between the mean and random magnetic fields (e.g. there being a pronounced minimum in the magnetic power spectrum at intermediate scales). Scale separation is often a good approximation in laboratory plasmas, but not in most astrophysical environments such as the interstellar medium (ISM). Modern simulations of the ISM have numerical resolution of the order of 1 pc, so the Larmor radius of the cosmic rays that dominate in energy density is at least 106 times smaller than the resolved scales. Large-scale simulations of cosmic ray propagation in the ISM thus rely on oversimplified forms of the diffusion tensor. We take the first steps towards a more realistic description of cosmic ray diffusion for such simulations, obtaining direct estimates of the diffusion tensor from test particle simulations in random magnetic fields (with the Larmor radius scale being fully resolved), for a range of particle energies corresponding to 10-2 ≲ RL/lc ≲ 103, where lc is the magnetic correlation length. We obtain explicit expressions for the cosmic ray diffusion tensor for RL/lc ≪ 1, that might be used in a sub-grid model of cosmic ray diffusion. The diffusion coefficients obtained are closely connected with existing transport theories that include the random walk of magnetic lines.

Feedbacks Between Bioclogging and Infiltration in Losing River Systems

NASA Astrophysics Data System (ADS)

Newcomer, M. E.; Hubbard, S. S.; Fleckenstein, J. H.; Schmidt, C.; Maier, U.; Thullner, M.; Ulrich, C.; Rubin, Y.

2014-12-01

Reduction in riverbed permeability due to biomass growth is a well-recognized yet poorly understood process associated with losing connected and disconnected rivers. Although several studies have focused on riverbed bioclogging processes at the pore-scale, few studies have quantified bioclogging feedback cycles at the scale relevant for water resources management, or at the meander-scale. At this scale, often competing hydrological-biological processes influence biomass dynamics and infiltration. Disconnection begins when declines in the water table form an unsaturated zone beneath the river maximizing seepage. Simultaneously, bioclogging reduces the point-scale infiltration flux and can either limit the nutrient flux and reduce bioclogging, or preferentially focus infiltration elsewhere and enhance bioclogging. These feedbacks are highly dependent on geomorphology and seasonal patterns of discharge and water temperature. To assess the mutual influences of disconnection, biomass growth, and temperature changes on infiltration in a geomorphologically complex river system, we built a 3D numerical model, conditioned on field data, using the reactive-transport simulator MIN3P. Results show that in disconnected regions of the river, biomass growth reduced vertical seepage downward and extended the unsaturated zone length; however these changes were contingent upon disconnection. Mid-way through the seasonal cycle, biomass declined in these same regions due to limited nutrient flux. Seepage and biomass continued to oscillate with a lag correlation of 1 month. Connected regions, however, showed the largest infiltration rates, nutrient fluxes, and concentrations of biomass. Despite the reduction in conductivity from biomass, flow remains high in connected regions because the feedback between bioclogging and infiltration is not as pronounced due to the sharpening hydraulic gradient. Bioclogging ultimately shapes the pattern of flow, however geomorphology dominates the strength of connection. Recognition of the feedbacks between geomorphological patterns and heterogeneous biomass on meander scale hydrological processes can lead to better estimates of local water volumes and capacities, especially when these systems are used as municipal and public water supply sources.

Metapopulation responses to patch connectivity and quality are masked by successional habitat dynamics.

PubMed

Hodgson, Jenny A; Moilanen, Atte; Thomas, Chris D

2009-06-01

Many species have to track changes in the spatial distribution of suitable habitat from generation to generation. Understanding the dynamics of such species will likely require spatially explicit models, and patch-based metapopulation models are potentially appropriate. However, relatively little attention has been paid to developing metapopulation models that include habitat dynamics, and very little to testing the predictions of these models. We tested three predictions from theory about the differences between dynamic habitat metapopulations and their static counterparts using long-term survey data from two metapopulations of the butterfly Plebejus argus. As predicted, we showed first that the metapopulation inhabiting dynamic habitat had a lower level of habitat occupancy, which could not be accounted for by other differences between the metapopulations. Secondly, we found that patch occupancy did not significantly increase with increasing patch connectivity in dynamic habitat, whereas there was a strong positive connectivity-occupancy relationship in static habitat. Thirdly, we found no significant relationship between patch occupancy and patch quality in dynamic habitat, whereas there was a strong, positive quality-occupancy relationship in static habitat. Modeling confirmed that the differences in mean patch occupancy and connectivity-occupancy slope could arise without changing the species' metapopulation parameters-importantly, without changing the dependence of colonization upon connectivity. We found that, for a range of landscape scenarios, successional simulations always produced a lower connectivity-occupancy slope than comparable simulations with static patches, whether compared like-for-like or controlling for mean occupancy. We conclude that landscape-scale studies may often underestimate the importance of connectivity for species occurrence and persistence because habitat turnover can obscure the connectivity-occupancy relationship in commonly available snapshot data.

Exploring drivers of wetland hydrologic fluxes across parameters and space

NASA Astrophysics Data System (ADS)

Jones, C. N.; Cheng, F. Y.; Mclaughlin, D. L.; Basu, N. B.; Lang, M.; Alexander, L. C.

2017-12-01

Depressional wetlands provide diverse ecosystem services, ranging from critical habitat to the regulation of landscape hydrology. The latter is of particular interest, because while hydrologic connectivity between depressional wetlands and downstream waters has been a focus of both scientific research and policy, it remains difficult to quantify the mode, magnitude, and timing of this connectivity at varying spatial and temporary scales. To do so requires robust empirical and modeling tools that accurately represent surface and subsurface flowpaths between depressional wetlands and other landscape elements. Here, we utilize a parsimonious wetland hydrology model to explore drivers of wetland water fluxes in different archetypal wetland-rich landscapes. We validated the model using instrumented sites from regions that span North America: Prairie Pothole Region (south-central Canada), Delmarva Peninsula (Mid-Atlantic Coastal Plain), and Big Cypress Swamp (southern Florida). Then, using several national scale datasets (e.g., National Wetlands Inventory, USFWS; National Hydrography Dataset, USGS; Soil Survey Geographic Database, NRCS), we conducted a global sensitivity analysis to elucidate dominant drivers of simulated fluxes. Finally, we simulated and compared wetland hydrology in five contrasting landscapes dominated by depressional wetlands: prairie potholes, Carolina and Delmarva bays, pocosins, western vernal pools, and Texas coastal prairie wetlands. Results highlight specific drivers that vary across these regions. Largely, hydroclimatic variables (e.g., PET/P ratios) controlled the timing and magnitude of wetland connectivity, whereas both wetland morphology (e.g., storage capacity and watershed size) and soil characteristics (e.g., ksat and confining layer depth) controlled the duration and mode (surface vs. subsurface) of wetland connectivity. Improved understanding of the drivers of wetland hydrologic connectivity supports enhanced, region-specific management and conservation of these critical ecosystems through more informed decision-making. Findings and conclusions expressed in this article are those of the authors and do not necessarily reflect the views or policies of the US EPA or USFWS.

Competing forces in liquid metal electrodes and batteries

NASA Astrophysics Data System (ADS)

Ashour, Rakan F.; Kelley, Douglas H.; Salas, Alejandro; Starace, Marco; Weber, Norbert; Weier, Tom

2018-02-01

Liquid metal batteries are proposed for low-cost grid scale energy storage. During their operation, solid intermetallic phases often form in the cathode and are known to limit the capacity of the cell. Fluid flow in the liquid electrodes can enhance mass transfer and reduce the formation of localized intermetallics, and fluid flow can be promoted by careful choice of the locations and topology of a battery's electrical connections. In this context we study four phenomena that drive flow: Rayleigh-Bénard convection, internally heated convection, electro-vortex flow, and swirl flow, in both experiment and simulation. In experiments, we use ultrasound Doppler velocimetry (UDV) to measure the flow in a eutectic PbBi electrode at 160 °C and subject to all four phenomena. In numerical simulations, we isolate the phenomena and simulate each separately using OpenFOAM. Comparing simulated velocities to experiments via a UDV beam model, we find that all four phenomena can enhance mass transfer in LMBs. We explain the flow direction, describe how the phenomena interact, and propose dimensionless numbers for estimating their mutual relevance. A brief discussion of electrical connections summarizes the engineering implications of our work.

Connections between residence time distributions and watershed characteristics across the continental US

NASA Astrophysics Data System (ADS)

Condon, L. E.; Maxwell, R. M.; Kollet, S. J.; Maher, K.; Haggerty, R.; Forrester, M. M.

2016-12-01

Although previous studies have demonstrated fractal residence time distributions in small watersheds, analyzing residence time scaling over large spatial areas is difficult with existing observational methods. For this study we use a fully integrated groundwater surface water simulation combined with Lagrangian particle tracking to evaluate connections between residence time distributions and watershed characteristics such as geology, topography and climate. Our simulation spans more than six million square kilometers of the continental US, encompassing a broad range of watershed sizes and physiographic settings. Simulated results demonstrate power law residence time distributions with peak age rages from 1.5 to 10.5 years. These ranges agree well with previous observational work and demonstrate the feasibility of using integrated models to simulate residence times. Comparing behavior between eight major watersheds, we show spatial variability in both the peak and the variance of the residence time distributions that can be related to model inputs. Peak age is well correlated with basin averaged hydraulic conductivity and the semi-variance corresponds to aridity. While power law age distributions have previously been attributed to fractal topography, these results illustrate the importance of subsurface characteristics and macro climate as additional controls on groundwater configuration and residence times.

Climate change poised to threaten hydrologic connectivity and endemic fishes in dryland streams

PubMed Central

Jaeger, Kristin L.; Olden, Julian D.; Pelland, Noel A.

2014-01-01

Protecting hydrologic connectivity of freshwater ecosystems is fundamental to ensuring species persistence, ecosystem integrity, and human well-being. More frequent and severe droughts associated with climate change are poised to significantly alter flow intermittence patterns and hydrologic connectivity in dryland streams of the American Southwest, with deleterious effects on highly endangered fishes. By integrating local-scale hydrologic modeling with emerging approaches in landscape ecology, we quantify fine-resolution, watershed-scale changes in habitat size, spacing, and connectance under forecasted climate change in the Verde River Basin, United States. Model simulations project annual zero-flow day frequency to increase by 27% by midcentury, with differential seasonal consequences on continuity (temporal continuity at discrete locations) and connectivity (spatial continuity within the network). A 17% increase in the frequency of stream drying events is expected throughout the network with associated increases in the duration of these events. Flowing portions of the river network will diminish between 8% and 20% in spring and early summer and become increasingly isolated by more frequent and longer stretches of dry channel fragments, thus limiting the opportunity for native fishes to access spawning habitats and seasonally available refuges. Model predictions suggest that midcentury and late century climate will reduce network-wide hydrologic connectivity for native fishes by 6–9% over the course of a year and up to 12–18% during spring spawning months. Our work quantifies climate-induced shifts in stream drying and connectivity across a large river network and demonstrates their implications for the persistence of a globally endemic fish fauna. PMID:25136090

Time-frequency dynamics of resting-state brain connectivity measured with fMRI.

PubMed

Chang, Catie; Glover, Gary H

2010-03-01

Most studies of resting-state functional connectivity using fMRI employ methods that assume temporal stationarity, such as correlation and data-driven decompositions computed across the duration of the scan. However, evidence from both task-based fMRI studies and animal electrophysiology suggests that functional connectivity may exhibit dynamic changes within time scales of seconds to minutes. In the present study, we investigated the dynamic behavior of resting-state connectivity across the course of a single scan, performing a time-frequency coherence analysis based on the wavelet transform. We focused on the connectivity of the posterior cingulate cortex (PCC), a primary node of the default-mode network, examining its relationship with both the "anticorrelated" ("task-positive") network as well as other nodes of the default-mode network. It was observed that coherence and phase between the PCC and the anticorrelated network was variable in time and frequency, and statistical testing based on Monte Carlo simulations revealed the presence of significant scale-dependent temporal variability. In addition, a sliding-window correlation procedure identified other regions across the brain that exhibited variable connectivity with the PCC across the scan, which included areas previously implicated in attention and salience processing. Although it is unclear whether the observed coherence and phase variability can be attributed to residual noise or modulation of cognitive state, the present results illustrate that resting-state functional connectivity is not static, and it may therefore prove valuable to consider measures of variability, in addition to average quantities, when characterizing resting-state networks. Copyright (c) 2009 Elsevier Inc. All rights reserved.

Climate change poised to threaten hydrologic connectivity and endemic fishes in dryland streams.

PubMed

Jaeger, Kristin L; Olden, Julian D; Pelland, Noel A

2014-09-23

Protecting hydrologic connectivity of freshwater ecosystems is fundamental to ensuring species persistence, ecosystem integrity, and human well-being. More frequent and severe droughts associated with climate change are poised to significantly alter flow intermittence patterns and hydrologic connectivity in dryland streams of the American Southwest, with deleterious effects on highly endangered fishes. By integrating local-scale hydrologic modeling with emerging approaches in landscape ecology, we quantify fine-resolution, watershed-scale changes in habitat size, spacing, and connectance under forecasted climate change in the Verde River Basin, United States. Model simulations project annual zero-flow day frequency to increase by 27% by midcentury, with differential seasonal consequences on continuity (temporal continuity at discrete locations) and connectivity (spatial continuity within the network). A 17% increase in the frequency of stream drying events is expected throughout the network with associated increases in the duration of these events. Flowing portions of the river network will diminish between 8% and 20% in spring and early summer and become increasingly isolated by more frequent and longer stretches of dry channel fragments, thus limiting the opportunity for native fishes to access spawning habitats and seasonally available refuges. Model predictions suggest that midcentury and late century climate will reduce network-wide hydrologic connectivity for native fishes by 6-9% over the course of a year and up to 12-18% during spring spawning months. Our work quantifies climate-induced shifts in stream drying and connectivity across a large river network and demonstrates their implications for the persistence of a globally endemic fish fauna.

Informing conservation management about structural versus functional connectivity: a case-study of Cross River gorillas.

PubMed

Imong, Inaoyom; Robbins, Martha M; Mundry, Roger; Bergl, Richard; Kühl, Hjalmar S

2014-10-01

Connectivity among subpopulations is vital for the persistence of small and fragmented populations. For management interventions to be effective conservation planners have to make the critical distinction between structural connectivity (based on landscape structure) and functional connectivity (which considers both landscape structure and organism-specific behavioral attributes) which can differ considerably within a given context. We assessed spatial and temporal changes in structural and functional connectivity of the Cross River gorilla Gorilla gorilla diehli (CRG) population in a 12,000 km(2) landscape in the Nigeria-Cameroon border region over a 23-year period, comparing two periods: 1987-2000 and 2000-2010. Despite substantial forest connections between occupied areas, genetic evidence shows that only limited dispersal occurs among CRG subpopulations. We used remotely sensed land-cover data and simulated human pressure (using a spatially explicit agent-based model) to assess human impact on connectivity of the CRG population. We calculated cost-weighted distances between areas occupied by gorillas as measures of connectivity (structural based on land-cover only, functional based on both land-cover and simulated human pressure). Whereas structural connectivity decreased by 5% over the 23-year period, functional connectivity decreased by 11%, with both decreasing more during the latter compared to the earlier period. Our results highlight the increasing threat of isolation of CRG subpopulations due to human disturbance, and provide insight into how increasing human influence may lead to functional isolation of wildlife populations despite habitat continuity, a pressing and common issue in tropical Africa often not accounted for when deciding management interventions. In addition to quantifying threats to connectivity, our study provides crucial evidence for management authorities to identify actions that are more likely to be effective for conservation of species in human-dominated landscapes. Our approach can be easily applied to other species, regions, and scales. © 2014 Wiley Periodicals, Inc.

Cross-borehole flow analysis to characterize fracture connections in the Melechov Granite, Bohemian-Moravian Highland, Czech Republic

USGS Publications Warehouse

Paillet, Frederick L.; Williams, John H.; Urik, Joseph; Lukes, Joseph; Kobr, Miroslav; Mares, Stanislav

2012-01-01

Application of the cross-borehole flow method, in which short pumping cycles in one borehole are used to induce time-transient flow in another borehole, demonstrated that a simple hydraulic model can characterize the fracture connections in the bedrock mass between the two boreholes. The analysis determines the properties of fracture connections rather than those of individual fractures intersecting a single borehole; the model contains a limited number of adjustable parameters so that any correlation between measured and simulated flow test data is significant. The test was conducted in two 200-m deep boreholes spaced 21 m apart in the Melechov Granite in the Bohemian-Moravian Highland, Czech Republic. Transient flow was measured at depth stations between the identified transmissive fractures in one of the boreholes during short-term pumping and recovery periods in the other borehole. Simulated flows, based on simple model geometries, closely matched the measured flows. The relative transmissivity and storage of the inferred fracture connections were corroborated by tracer testing. The results demonstrate that it is possible to assess the properties of a fracture flow network despite being restricted to making measurements in boreholes in which a local population of discrete fractures regulates the hydraulic communication with the larger-scale aquifer system.

FRF-based structural damage detection of controlled buildings with podium structures: Experimental investigation

NASA Astrophysics Data System (ADS)

Xu, Y. L.; Huang, Q.; Zhan, S.; Su, Z. Q.; Liu, H. J.

2014-06-01

How to use control devices to enhance system identification and damage detection in relation to a structure that requires both vibration control and structural health monitoring is an interesting yet practical topic. In this study, the possibility of using the added stiffness provided by control devices and frequency response functions (FRFs) to detect damage in a building complex was explored experimentally. Scale models of a 12-storey main building and a 3-storey podium structure were built to represent a building complex. Given that the connection between the main building and the podium structure is most susceptible to damage, damage to the building complex was experimentally simulated by changing the connection stiffness. To simulate the added stiffness provided by a semi-active friction damper, a steel circular ring was designed and used to add the related stiffness to the building complex. By varying the connection stiffness using an eccentric wheel excitation system and by adding or not adding the circular ring, eight cases were investigated and eight sets of FRFs were measured. The experimental results were used to detect damage (changes in connection stiffness) using a recently proposed FRF-based damage detection method. The experimental results showed that the FRF-based damage detection method could satisfactorily locate and quantify damage.

Sensitivities of simulated satellite views of clouds to subgrid-scale overlap and condensate heterogeneity

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

Hillman, Benjamin R.; Marchand, Roger T.; Ackerman, Thomas P.

Satellite simulators are often used to account for limitations in satellite retrievals of cloud properties in comparisons between models and satellite observations. The purpose of the simulator framework is to enable more robust evaluation of model cloud properties, so that di erences between models and observations can more con dently be attributed to model errors. However, these simulators are subject to uncertainties themselves. A fundamental uncertainty exists in connecting the spatial scales at which cloud properties are retrieved with those at which clouds are simulated in global models. In this study, we create a series of sensitivity tests using 4more » km global model output from the Multiscale Modeling Framework to evaluate the sensitivity of simulated satellite retrievals when applied to climate models whose grid spacing is many tens to hundreds of kilometers. In particular, we examine the impact of cloud and precipitation overlap and of condensate spatial variability. We find the simulated retrievals are sensitive to these assumptions. Specifically, using maximum-random overlap with homogeneous cloud and precipitation condensate, which is often used in global climate models, leads to large errors in MISR and ISCCP-simulated cloud cover and in CloudSat-simulated radar reflectivity. To correct for these errors, an improved treatment of unresolved clouds and precipitation is implemented for use with the simulator framework and is shown to substantially reduce the identified errors.« less

Development of a Aerothermoelastic-Acoustics Simulation Capability of Flight Vehicles

NASA Technical Reports Server (NTRS)

Gupta, K. K.; Choi, S. B.; Ibrahim, A.

2010-01-01

A novel numerical, finite element based analysis methodology is presented in this paper suitable for accurate and efficient simulation of practical, complex flight vehicles. An associated computer code, developed in this connection, is also described in some detail. Thermal effects of high speed flow obtained from a heat conduction analysis are incorporated in the modal analysis which in turn affects the unsteady flow arising out of interaction of elastic structures with the air. Numerical examples pertaining to representative problems are given in much detail testifying to the efficacy of the advocated techniques. This is a unique implementation of temperature effects in a finite element CFD based multidisciplinary simulation analysis capability involving large scale computations.

The role of large scale motions on passive scalar transport

NASA Astrophysics Data System (ADS)

Dharmarathne, Suranga; Araya, Guillermo; Tutkun, Murat; Leonardi, Stefano; Castillo, Luciano

2014-11-01

We study direct numerical simulation (DNS) of turbulent channel flow at Reτ = 394 to investigate effect of large scale motions on fluctuating temperature field which forms a passive scalar field. Statistical description of the large scale features of the turbulent channel flow is obtained using two-point correlations of velocity components. Two-point correlations of fluctuating temperature field is also examined in order to identify possible similarities between velocity and temperature fields. The two-point cross-correlations betwen the velocity and temperature fluctuations are further analyzed to establish connections between these two fields. In addition, we use proper orhtogonal decompotion (POD) to extract most dominant modes of the fields and discuss the coupling of large scale features of turbulence and the temperature field.

A Multi-Stage Method for Connecting Participatory Sensing and Noise Simulations

PubMed Central

Hu, Mingyuan; Che, Weitao; Zhang, Qiuju; Luo, Qingli; Lin, Hui

2015-01-01

Most simulation-based noise maps are important for official noise assessment but lack local noise characteristics. The main reasons for this lack of information are that official noise simulations only provide information about expected noise levels, which is limited by the use of large-scale monitoring of noise sources, and are updated infrequently. With the emergence of smart cities and ubiquitous sensing, the possible improvements enabled by sensing technologies provide the possibility to resolve this problem. This study proposed an integrated methodology to propel participatory sensing from its current random and distributed sampling origins to professional noise simulation. The aims of this study were to effectively organize the participatory noise data, to dynamically refine the granularity of the noise features on road segments (e.g., different portions of a road segment), and then to provide a reasonable spatio-temporal data foundation to support noise simulations, which can be of help to researchers in understanding how participatory sensing can play a role in smart cities. This study first discusses the potential limitations of the current participatory sensing and simulation-based official noise maps. Next, we explain how participatory noise data can contribute to a simulation-based noise map by providing (1) spatial matching of the participatory noise data to the virtual partitions at a more microscopic level of road networks; (2) multi-temporal scale noise estimations at the spatial level of virtual partitions; and (3) dynamic aggregation of virtual partitions by comparing the noise values at the relevant temporal scale to form a dynamic segmentation of each road segment to support multiple spatio-temporal noise simulations. In this case study, we demonstrate how this method could play a significant role in a simulation-based noise map. Together, these results demonstrate the potential benefits of participatory noise data as dynamic input sources for noise simulations on multiple spatio-temporal scales. PMID:25621604

A multi-stage method for connecting participatory sensing and noise simulations.

PubMed

Hu, Mingyuan; Che, Weitao; Zhang, Qiuju; Luo, Qingli; Lin, Hui

2015-01-22

Most simulation-based noise maps are important for official noise assessment but lack local noise characteristics. The main reasons for this lack of information are that official noise simulations only provide information about expected noise levels, which is limited by the use of large-scale monitoring of noise sources, and are updated infrequently. With the emergence of smart cities and ubiquitous sensing, the possible improvements enabled by sensing technologies provide the possibility to resolve this problem. This study proposed an integrated methodology to propel participatory sensing from its current random and distributed sampling origins to professional noise simulation. The aims of this study were to effectively organize the participatory noise data, to dynamically refine the granularity of the noise features on road segments (e.g., different portions of a road segment), and then to provide a reasonable spatio-temporal data foundation to support noise simulations, which can be of help to researchers in understanding how participatory sensing can play a role in smart cities. This study first discusses the potential limitations of the current participatory sensing and simulation-based official noise maps. Next, we explain how participatory noise data can contribute to a simulation-based noise map by providing (1) spatial matching of the participatory noise data to the virtual partitions at a more microscopic level of road networks; (2) multi-temporal scale noise estimations at the spatial level of virtual partitions; and (3) dynamic aggregation of virtual partitions by comparing the noise values at the relevant temporal scale to form a dynamic segmentation of each road segment to support multiple spatio-temporal noise simulations. In this case study, we demonstrate how this method could play a significant role in a simulation-based noise map. Together, these results demonstrate the potential benefits of participatory noise data as dynamic input sources for noise simulations on multiple spatio-temporal scales.

Embedding Task-Based Neural Models into a Connectome-Based Model of the Cerebral Cortex.

PubMed

Ulloa, Antonio; Horwitz, Barry

2016-01-01

A number of recent efforts have used large-scale, biologically realistic, neural models to help understand the neural basis for the patterns of activity observed in both resting state and task-related functional neural imaging data. An example of the former is The Virtual Brain (TVB) software platform, which allows one to apply large-scale neural modeling in a whole brain framework. TVB provides a set of structural connectomes of the human cerebral cortex, a collection of neural processing units for each connectome node, and various forward models that can convert simulated neural activity into a variety of functional brain imaging signals. In this paper, we demonstrate how to embed a previously or newly constructed task-based large-scale neural model into the TVB platform. We tested our method on a previously constructed large-scale neural model (LSNM) of visual object processing that consisted of interconnected neural populations that represent, primary and secondary visual, inferotemporal, and prefrontal cortex. Some neural elements in the original model were "non-task-specific" (NS) neurons that served as noise generators to "task-specific" neurons that processed shapes during a delayed match-to-sample (DMS) task. We replaced the NS neurons with an anatomical TVB connectome model of the cerebral cortex comprising 998 regions of interest interconnected by white matter fiber tract weights. We embedded our LSNM of visual object processing into corresponding nodes within the TVB connectome. Reciprocal connections between TVB nodes and our task-based modules were included in this framework. We ran visual object processing simulations and showed that the TVB simulator successfully replaced the noise generation originally provided by NS neurons; i.e., the DMS tasks performed with the hybrid LSNM/TVB simulator generated equivalent neural and fMRI activity to that of the original task-based models. Additionally, we found partial agreement between the functional connectivities using the hybrid LSNM/TVB model and the original LSNM. Our framework thus presents a way to embed task-based neural models into the TVB platform, enabling a better comparison between empirical and computational data, which in turn can lead to a better understanding of how interacting neural populations give rise to human cognitive behaviors.

Rainfall simulation and Structure-from-Motion photogrammetry for the analysis of soil water erosion in Mediterranean vineyards.

PubMed

Prosdocimi, Massimo; Burguet, Maria; Di Prima, Simone; Sofia, Giulia; Terol, Enric; Rodrigo Comino, Jesús; Cerdà, Artemi; Tarolli, Paolo

2017-01-01

Soil water erosion is a serious problem, especially in agricultural lands. Among these, vineyards deserve attention, because they constitute for the Mediterranean areas a type of land use affected by high soil losses. A significant problem related to the study of soil water erosion in these areas consists in the lack of a standardized procedure of collecting data and reporting results, mainly due to a variability among the measurement methods applied. Given this issue and the seriousness of soil water erosion in Mediterranean vineyards, this works aims to quantify the soil losses caused by simulated rainstorms, and compare them with each other depending on two different methodologies: (i) rainfall simulation and (ii) surface elevation change-based, relying on high-resolution Digital Elevation Models (DEMs) derived from a photogrammetric technique (Structure-from-Motion or SfM). The experiments were carried out in a typical Mediterranean vineyard, located in eastern Spain, at very fine scales. SfM data were obtained from one reflex camera and a smartphone built-in camera. An index of sediment connectivity was also applied to evaluate the potential effect of connectivity within the plots. DEMs derived from the smartphone and the reflex camera were comparable with each other in terms of accuracy and capability of estimating soil loss. Furthermore, soil loss estimated with the surface elevation change-based method resulted to be of the same order of magnitude of that one obtained with rainfall simulation, as long as the sediment connectivity within the plot was considered. High-resolution topography derived from SfM revealed to be essential in the sediment connectivity analysis and, therefore, in the estimation of eroded materials, when comparing them to those derived from the rainfall simulation methodology. The fact that smartphones built-in cameras could produce as much satisfying results as those derived from reflex cameras is a high value added for using SfM. Copyright © 2016 Elsevier B.V. All rights reserved.

Progress on 3-D ICF simulations and Ray-Traced Power Deposition Method

NASA Astrophysics Data System (ADS)

Schmitt, Andrew J.; Fyfe, David E.

2016-10-01

We have performed 3D simulations of Omega-scale and NIF-scale spherical direct-drive targets with the massively parallel fastrad3d code. Of particular interest is the robustness of the targets to the low mode perturbations impressed on the target by the laser system and how it compares to the influence of the perturbations produced by laser imprinting. As part of this simulation capability, we have upgraded our smoothed 3D raytrace package to run in spherical geometry. This package, which connects rays to form bundles and performs power deposition calculations on the bundles, can decrease laser absorption noise while using fewer rays and less message passing. This model produces both the imprint and the low-mode asymmetry drive that we are interested in here. We show recent simulation results of directly-driven targets using conventional ignition drive, and report on the influences of the two sources - low mode asymmetry and laser imprint - as the pellet conditions (e.g. adiabat) are varied. Work supported by DoE/NNSA.

A Web-based Distributed Voluntary Computing Platform for Large Scale Hydrological Computations

NASA Astrophysics Data System (ADS)

Demir, I.; Agliamzanov, R.

2014-12-01

Distributed volunteer computing can enable researchers and scientist to form large parallel computing environments to utilize the computing power of the millions of computers on the Internet, and use them towards running large scale environmental simulations and models to serve the common good of local communities and the world. Recent developments in web technologies and standards allow client-side scripting languages to run at speeds close to native application, and utilize the power of Graphics Processing Units (GPU). Using a client-side scripting language like JavaScript, we have developed an open distributed computing framework that makes it easy for researchers to write their own hydrologic models, and run them on volunteer computers. Users will easily enable their websites for visitors to volunteer sharing their computer resources to contribute running advanced hydrological models and simulations. Using a web-based system allows users to start volunteering their computational resources within seconds without installing any software. The framework distributes the model simulation to thousands of nodes in small spatial and computational sizes. A relational database system is utilized for managing data connections and queue management for the distributed computing nodes. In this paper, we present a web-based distributed volunteer computing platform to enable large scale hydrological simulations and model runs in an open and integrated environment.

Railway bogie vibration analysis by mathematical simulation model and a scaled four-wheel railway bogie set

NASA Astrophysics Data System (ADS)

Visayataksin, Noppharat; Sooklamai, Manon

2018-01-01

The bogie is the part that connects and transfers all the load from the vehicle body onto the railway track; interestingly the interaction between wheels and rails is the critical point for derailment of the rail vehicles. However, observing or experimenting with real bogies on rail vehicles is impossible due to the operational rules and safety concerns. Therefore, this research aimed to develop a vibration analysis set for a four-wheel railway bogie by constructing a four-wheel bogie with scale of 1:4.5. The bogie structures, including wheels and axles, were made from an aluminium alloy, equipped with springs and dampers. The bogie was driven by an electric motor using 4 round wheels instead of 2 straight rails, with linear velocity between 0 to 11.22 m/s. The data collected from the vibration analysis set was compared to the mathematical simulation model to investigate the vibration behavior of the bogie, especially the hunting motion. The results showed that vibration behavior from a scaled four-wheel railway bogie set significantly agreed with the mathematical simulation model in terms of displacement and hunting frequency. The critical speed of the wheelset was found by executing the mathematical simulation model at 13 m/s.

Effect of tree thinning and skidding trails on hydrological connectivity in two Japanese forest catchments

NASA Astrophysics Data System (ADS)

López-Vicente, Manuel; Sun, Xinchao; Onda, Yuichi; Kato, Hiroaki; Gomi, Takashi; Hiraoka, Marino

2017-09-01

Land use composition and patterns influence the hydrological response in mountainous and forest catchments. In plantation forest, management operations (FMO) modify the spatial and temporal dynamics of overland flow processes. However, we found a gap in the literature focussed on modelling hydrological connectivity (HC) in plantation forest under different FMO. In this study, we simulated HC in two steep paired forest subcatchments (K2 and K3, 33.2 ha), composed of Japanese cypress (Chamaecyparis obtusa Endl.) and Japanese cedar (Cryptomeria japonica D. Don) plantations (59% of the total area) against a tree thinning intensity of 50% at different time. Additionally, construction of new skidding trails and vegetation recovery was simulated on five thinning-based scenarios that covered a 40-month test period (July 2010 - October 2013). As a future scenario, six check-dams located in the main streams were proposed to reduce sediment and radionuclide delivery. An updated version of Borselli's index of runoff and sediment connectivity was run, using the D-infinity flow accumulation algorithm and exploiting three 0.5-m resolution digital elevation models. On the basis of the pre-FMO scenario, HC increased at catchment scale owing to tree thinning and the new skidding trails. This change was more noticeable within the area affected by the FMO, where HC increased by 11.4% and 10.5% in the cypress and cedar plantations in K2 respectively and by 8.8% in the cedar plantation in K3. At hillslope plot and stream scales, the evolution in the values of HC was less evident, except the increment (by 5.4%) observed in the streams at K2 after the FMO. Progressive vegetation recovery after the FMO triggered a slight reduction of connectivity in all compartments of both subcatchments. Forest roads and especially skidding trails presented the highest values of HC, appearing as the most efficient features connecting the different vegetation patches with the stream network. The spatial and temporal evolution of HC over the five past scenarios correlated well with the observed changes in runoff yield, as well as with the available values of rainfall interception and throughfall before, during, and after the FMO. The simulation of the proposed scenario recommends the construction of check-dams as effective landscape features to somewhat reduce HC and thus to decrease the sediment and radionuclide delivery rates from the two subcatchments.

The signaling petri net-based simulator: a non-parametric strategy for characterizing the dynamics of cell-specific signaling networks.

PubMed

Ruths, Derek; Muller, Melissa; Tseng, Jen-Te; Nakhleh, Luay; Ram, Prahlad T

2008-02-29

Reconstructing cellular signaling networks and understanding how they work are major endeavors in cell biology. The scale and complexity of these networks, however, render their analysis using experimental biology approaches alone very challenging. As a result, computational methods have been developed and combined with experimental biology approaches, producing powerful tools for the analysis of these networks. These computational methods mostly fall on either end of a spectrum of model parameterization. On one end is a class of structural network analysis methods; these typically use the network connectivity alone to generate hypotheses about global properties. On the other end is a class of dynamic network analysis methods; these use, in addition to the connectivity, kinetic parameters of the biochemical reactions to predict the network's dynamic behavior. These predictions provide detailed insights into the properties that determine aspects of the network's structure and behavior. However, the difficulty of obtaining numerical values of kinetic parameters is widely recognized to limit the applicability of this latter class of methods. Several researchers have observed that the connectivity of a network alone can provide significant insights into its dynamics. Motivated by this fundamental observation, we present the signaling Petri net, a non-parametric model of cellular signaling networks, and the signaling Petri net-based simulator, a Petri net execution strategy for characterizing the dynamics of signal flow through a signaling network using token distribution and sampling. The result is a very fast method, which can analyze large-scale networks, and provide insights into the trends of molecules' activity-levels in response to an external stimulus, based solely on the network's connectivity. We have implemented the signaling Petri net-based simulator in the PathwayOracle toolkit, which is publicly available at http://bioinfo.cs.rice.edu/pathwayoracle. Using this method, we studied a MAPK1,2 and AKT signaling network downstream from EGFR in two breast tumor cell lines. We analyzed, both experimentally and computationally, the activity level of several molecules in response to a targeted manipulation of TSC2 and mTOR-Raptor. The results from our method agreed with experimental results in greater than 90% of the cases considered, and in those where they did not agree, our approach provided valuable insights into discrepancies between known network connectivities and experimental observations.

The Signaling Petri Net-Based Simulator: A Non-Parametric Strategy for Characterizing the Dynamics of Cell-Specific Signaling Networks

PubMed Central

Ruths, Derek; Muller, Melissa; Tseng, Jen-Te; Nakhleh, Luay; Ram, Prahlad T.

2008-01-01

Reconstructing cellular signaling networks and understanding how they work are major endeavors in cell biology. The scale and complexity of these networks, however, render their analysis using experimental biology approaches alone very challenging. As a result, computational methods have been developed and combined with experimental biology approaches, producing powerful tools for the analysis of these networks. These computational methods mostly fall on either end of a spectrum of model parameterization. On one end is a class of structural network analysis methods; these typically use the network connectivity alone to generate hypotheses about global properties. On the other end is a class of dynamic network analysis methods; these use, in addition to the connectivity, kinetic parameters of the biochemical reactions to predict the network's dynamic behavior. These predictions provide detailed insights into the properties that determine aspects of the network's structure and behavior. However, the difficulty of obtaining numerical values of kinetic parameters is widely recognized to limit the applicability of this latter class of methods. Several researchers have observed that the connectivity of a network alone can provide significant insights into its dynamics. Motivated by this fundamental observation, we present the signaling Petri net, a non-parametric model of cellular signaling networks, and the signaling Petri net-based simulator, a Petri net execution strategy for characterizing the dynamics of signal flow through a signaling network using token distribution and sampling. The result is a very fast method, which can analyze large-scale networks, and provide insights into the trends of molecules' activity-levels in response to an external stimulus, based solely on the network's connectivity. We have implemented the signaling Petri net-based simulator in the PathwayOracle toolkit, which is publicly available at http://bioinfo.cs.rice.edu/pathwayoracle. Using this method, we studied a MAPK1,2 and AKT signaling network downstream from EGFR in two breast tumor cell lines. We analyzed, both experimentally and computationally, the activity level of several molecules in response to a targeted manipulation of TSC2 and mTOR-Raptor. The results from our method agreed with experimental results in greater than 90% of the cases considered, and in those where they did not agree, our approach provided valuable insights into discrepancies between known network connectivities and experimental observations. PMID:18463702

Identifying Impacts of Hydropower Regulation on Salmonid Habitats to Guide River Restoration for Existing Schemes and Mitigate Adverse Effects of Future Developments

NASA Astrophysics Data System (ADS)

Buddendorf, B.; Geris, J.; Malcolm, I.; Wilkinson, M.; Soulsby, C.

2015-12-01

A decrease in longitudinal connectivity in riverine ecosystems resulting from the construction of transverse barriers has been identified as a major threat to biodiversity. For example, Atlantic Salmon (Salmo salar) have a seasonal variety of hydraulic habitat requirements for their different life stages. However, hydropower impoundments impact the spatial and temporal connectivity of natural habitat along many salmon rivers in ways that are not fully understood. Yet, these changes may affect the sustainability of habitat at local and regional scales and so ultimately the conservation of the species. Research is therefore needed both to aid the restoration and management of rivers impacted by previous hydropower development and guide new schemes to mitigate potentially adverse effects. To this end we assessed the effects of hydropower development on the flow related habitat conditions for different salmon life stages in Scottish rivers at different spatial scales. We used GIS techniques to map the changes in structural connectivity at regional scales, applying a weighting for habitat quality. Next, we used hydrological models to simulate past and present hydrologic conditions that in turn drive reach-scale hydraulic models to assess the impacts of regulation on habitat suitability in both space and time. Preliminary results indicate that: 1) impacts on connectivity depend on the location of the barrier within the river network; 2) multiple smaller barriers may have a potentially lower impact than a single larger barrier; 3) there is a relationship between habitat and connectivity where losing less but more suitable habitat potentially has a disproportionally large impact; 4) the impact of flow regulation can lead to a deterioration of habitat quality, though the effects are spatially variable and the extent of the impact depends on salmon life stage. This work can form a basis for using natural processes to perform targeted and cost-effective restoration of rivers.

An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation

PubMed Central

Wang, Yikai; Kang, Jian; Kemmer, Phebe B.; Guo, Ying

2016-01-01

Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant direct connections are between homologous brain locations in the left and right hemisphere. When comparing partial correlation derived under different sparse tuning parameters, an important finding is that the sparse regularization has more shrinkage effects on negative functional connections than on positive connections, which supports previous findings that many of the negative brain connections are due to non-neurophysiological effects. An R package “DensParcorr” can be downloaded from CRAN for implementing the proposed statistical methods. PMID:27242395

An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation.

PubMed

Wang, Yikai; Kang, Jian; Kemmer, Phebe B; Guo, Ying

2016-01-01

Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant direct connections are between homologous brain locations in the left and right hemisphere. When comparing partial correlation derived under different sparse tuning parameters, an important finding is that the sparse regularization has more shrinkage effects on negative functional connections than on positive connections, which supports previous findings that many of the negative brain connections are due to non-neurophysiological effects. An R package "DensParcorr" can be downloaded from CRAN for implementing the proposed statistical methods.

Scene segmentation by spike synchronization in reciprocally connected visual areas. II. Global assemblies and synchronization on larger space and time scales.

PubMed

Knoblauch, Andreas; Palm, Günther

2002-09-01

We present further simulation results of the model of two reciprocally connected visual areas proposed in the first paper [Knoblauch and Palm (2002) Biol Cybern 87:151-167]. One area corresponds to the orientation-selective subsystem of the primary visual cortex, the other is modeled as an associative memory representing stimulus objects according to Hebbian learning. We examine the scene-segmentation capability of our model on larger time and space scales, and relate it to experimental findings. Scene segmentation is achieved by attention switching on a time-scale longer than the gamma range. We find that the time-scale can vary depending on habituation parameters in the range of tens to hundreds of milliseconds. The switching process can be related to findings concerning attention and biased competition, and we reproduce experimental poststimulus time histograms (PSTHs) of single neurons under different stimulus and attentional conditions. In a larger variant the model exhibits traveling waves of activity on both slow and fast time-scales, with properties similar to those found in experiments. An apparent weakness of our standard model is the tendency to produce anti-phase correlations for fast activity from the two areas. Increasing the inter-areal delays in our model produces alternations of in-phase and anti-phase oscillations. The experimentally observed in-phase correlations can most naturally be obtained by the involvement of both fast and slow inter-areal connections; e.g., by two axon populations corresponding to fast-conducting myelinated and slow-conducting unmyelinated axons.

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator.

PubMed

Hahne, Jan; Dahmen, David; Schuecker, Jannis; Frommer, Andreas; Bolten, Matthias; Helias, Moritz; Diesmann, Markus

2017-01-01

Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation.

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator

PubMed Central

Hahne, Jan; Dahmen, David; Schuecker, Jannis; Frommer, Andreas; Bolten, Matthias; Helias, Moritz; Diesmann, Markus

2017-01-01

Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation. PMID:28596730

Inference of scale-free networks from gene expression time series.

PubMed

Daisuke, Tominaga; Horton, Paul

2006-04-01

Quantitative time-series observation of gene expression is becoming possible, for example by cell array technology. However, there are no practical methods with which to infer network structures using only observed time-series data. As most computational models of biological networks for continuous time-series data have a high degree of freedom, it is almost impossible to infer the correct structures. On the other hand, it has been reported that some kinds of biological networks, such as gene networks and metabolic pathways, may have scale-free properties. We hypothesize that the architecture of inferred biological network models can be restricted to scale-free networks. We developed an inference algorithm for biological networks using only time-series data by introducing such a restriction. We adopt the S-system as the network model, and a distributed genetic algorithm to optimize models to fit its simulated results to observed time series data. We have tested our algorithm on a case study (simulated data). We compared optimization under no restriction, which allows for a fully connected network, and under the restriction that the total number of links must equal that expected from a scale free network. The restriction reduced both false positive and false negative estimation of the links and also the differences between model simulation and the given time-series data.

Changes in Intense Precipitation Events in West Africa and the central U.S. under Global Warming

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

Cook, Kerry H.; Vizy, Edward

The purpose of the proposed project is to improve our understanding of the physical processes and large-scale connectivity of changes in intense precipitation events (high rainfall rates) under global warming in West Africa and the central U.S., including relationships with low-frequency modes of variability. This is in response to the requested subject area #2 “simulation of climate extremes under a changing climate … to better quantify the frequency, duration, and intensity of extreme events under climate change and elucidate the role of low frequency climate variability in modulating extremes.” We will use a regional climate model and emphasize an understandingmore » of the physical processes that lead to an intensification of rainfall. The project objectives are as follows: 1. Understand the processes responsible for simulated changes in warm-season rainfall intensity and frequency over West Africa and the Central U.S. associated with greenhouse gas-induced global warming 2. Understand the relationship between changes in warm-season rainfall intensity and frequency, which generally occur on regional space scales, and the larger-scale global warming signal by considering modifications of low-frequency modes of variability. 3. Relate changes simulated on regional space scales to global-scale theories of how and why atmospheric moisture levels and rainfall should change as climate warms.« less

Goal-oriented robot navigation learning using a multi-scale space representation.

PubMed

Llofriu, M; Tejera, G; Contreras, M; Pelc, T; Fellous, J M; Weitzenfeld, A

2015-12-01

There has been extensive research in recent years on the multi-scale nature of hippocampal place cells and entorhinal grid cells encoding which led to many speculations on their role in spatial cognition. In this paper we focus on the multi-scale nature of place cells and how they contribute to faster learning during goal-oriented navigation when compared to a spatial cognition system composed of single scale place cells. The task consists of a circular arena with a fixed goal location, in which a robot is trained to find the shortest path to the goal after a number of learning trials. Synaptic connections are modified using a reinforcement learning paradigm adapted to the place cells multi-scale architecture. The model is evaluated in both simulation and physical robots. We find that larger scale and combined multi-scale representations favor goal-oriented navigation task learning. Copyright © 2015 Elsevier Ltd. All rights reserved.

Functional Connectivity of Precipitation Networks in the Brazilian Rainforest-Savanna Transition Zone

NASA Astrophysics Data System (ADS)

Adera, S.; Larsen, L.; Levy, M. C.; Thompson, S. E.

2016-12-01

In the Brazilian rainforest-savanna transition zone, vegetation change has the potential to significantly affect precipitation patterns. Deforestation, in particular, can affect precipitation patterns by increasing land surface albedo, increasing aerosol loading to the atmosphere, changing land surface roughness, and reducing transpiration. Understanding land surface-precipitation couplings in this region is important not only for sustaining Amazon and Cerrado ecosystems, but also for cattle ranching and agriculture, hydropower generation, and drinking water management. Simulations suggest complex, scale-dependent interactions between precipitation and land cover. For example, the size and distribution of deforested patches has been found to affect precipitation patterns. We take an empirical approach to ask: (1) what are the dominant spatial and temporal length scales of precipitation coupling in the Brazilian rainforest-savanna transition zone? (2) How do these length scales change over time? (3) How does the connectivity of precipitation change over time? The answers to these questions will help address fundamental questions about the impacts of deforestation on precipitation. We use rain gauge data from 1100 rain gauges intermittently covering the period 1980 - 2013, a period of intensive land cover change in the region. The dominant spatial and temporal length scales of precipitation coupling are resolved using transfer entropy, a metric from information theory. Connectivity of the emergent network of couplings is quantified using network statistics. Analyses using transfer entropy and network statistics reveal the spatial and temporal interdependencies of rainfall events occurring in different parts of the study domain.

Computational Modeling of Resting-State Activity Demonstrates Markers of Normalcy in Children with Prenatal or Perinatal Stroke

PubMed Central

Raja Beharelle, Anjali; Griffa, Alessandra; Hagmann, Patric; Solodkin, Ana; McIntosh, Anthony R.; Small, Steven L.; Deco, Gustavo

2015-01-01

Children who sustain a prenatal or perinatal brain injury in the form of a stroke develop remarkably normal cognitive functions in certain areas, with a particular strength in language skills. A dominant explanation for this is that brain regions from the contralesional hemisphere “take over” their functions, whereas the damaged areas and other ipsilesional regions play much less of a role. However, it is difficult to tease apart whether changes in neural activity after early brain injury are due to damage caused by the lesion or by processes related to postinjury reorganization. We sought to differentiate between these two causes by investigating the functional connectivity (FC) of brain areas during the resting state in human children with early brain injury using a computational model. We simulated a large-scale network consisting of realistic models of local brain areas coupled through anatomical connectivity information of healthy and injured participants. We then compared the resulting simulated FC values of healthy and injured participants with the empirical ones. We found that the empirical connectivity values, especially of the damaged areas, correlated better with simulated values of a healthy brain than those of an injured brain. This result indicates that the structural damage caused by an early brain injury is unlikely to have an adverse and sustained impact on the functional connections, albeit during the resting state, of damaged areas. Therefore, these areas could continue to play a role in the development of near-normal function in certain domains such as language in these children. PMID:26063923

Turbulent Nuclear Burning of Carbon Fuel in Double-Degenerate White Dwarfs

NASA Astrophysics Data System (ADS)

Mozumdar, Pritom; Fisher, Robert

2018-01-01

Type Ia supernovae (SNe Ia) are of interest as standardizable cosmological candles, though their stellar progenitors are still poorly understood. The double-degenerate (DD) channel is promising, but the mechanism for the explosion remains a matter of active investigation. A long-standing problem in modeling SNe Ia is the fact that 3D simulations leave the length scales crucial for a possible detonation unresolved. In this work, we have performed local 3D hydrodynamical adaptive mesh refinement simulations of driven turbulence for various initial conditions characteristic of the DD scenario, which are capable of capturing length scales relevant to the Zel’dovich gradient mechanism. Because the carbon burning rate is highly sensitive to temperature in this regime, we demonstrate that turbulence can dramatically enhance the nuclear burning rate, and we investigate the connection to a possible detonation.

Initial Validation for the Estimation of Resting-State fMRI Effective Connectivity by a Generalization of the Correlation Approach.

PubMed

Xu, Nan; Spreng, R Nathan; Doerschuk, Peter C

2017-01-01

Resting-state functional MRI (rs-fMRI) is widely used to noninvasively study human brain networks. Network functional connectivity is often estimated by calculating the timeseries correlation between blood-oxygen-level dependent (BOLD) signal from different regions of interest (ROIs). However, standard correlation cannot characterize the direction of information flow between regions. In this paper, we introduce and test a new concept, prediction correlation, to estimate effective connectivity in functional brain networks from rs-fMRI. In this approach, the correlation between two BOLD signals is replaced by a correlation between one BOLD signal and a prediction of this signal via a causal system driven by another BOLD signal. Three validations are described: (1) Prediction correlation performed well on simulated data where the ground truth was known, and outperformed four other methods. (2) On simulated data designed to display the "common driver" problem, prediction correlation did not introduce false connections between non-interacting driven ROIs. (3) On experimental data, prediction correlation recovered the previously identified network organization of human brain. Prediction correlation scales well to work with hundreds of ROIs, enabling it to assess whole brain interregional connectivity at the single subject level. These results provide an initial validation that prediction correlation can capture the direction of information flow and estimate the duration of extended temporal delays in information flow between regions of interest ROIs based on BOLD signal. This approach not only maintains the high sensitivity to network connectivity provided by the correlation analysis, but also performs well in the estimation of causal information flow in the brain.

Connectivity strategies for higher-order neural networks applied to pattern recognition

NASA Technical Reports Server (NTRS)

Spirkovska, Lilly; Reid, Max B.

1990-01-01

Different strategies for non-fully connected HONNs (higher-order neural networks) are discussed, showing that by using such strategies an input field of 128 x 128 pixels can be attained while still achieving in-plane rotation and translation-invariant recognition. These techniques allow HONNs to be used with the larger input scenes required for practical pattern-recognition applications. The number of interconnections that must be stored has been reduced by a factor of approximately 200,000 in a T/C case and about 2000 in a Space Shuttle/F-18 case by using regional connectivity. Third-order networks have been simulated using several connection strategies. The method found to work best is regional connectivity. The main advantages of this strategy are the following: (1) it considers features of various scales within the image and thus gets a better sample of what the image looks like; (2) it is invariant to shape-preserving geometric transformations, such as translation and rotation; (3) the connections are predetermined so that no extra computations are necessary during run time; and (4) it does not require any extra storage for recording which connections were formed.

Groundwater flow associated with coalbed gas production, Ferron Sandstone, east-central Utah

USGS Publications Warehouse

Anna, L.O.

2003-01-01

The flow and distribution of water associated with coalbed gas production in the Ferron Sandstone was characterized utilizing a discrete fracture network model and a porous media model. A discrete fracture network model calculated fluid flux through volumes of various scales to determine scale effects, directional bulk permeability, and connectivity. The mean directional permeabilities varied by less than a factor of 6, with the northwest-southeast direction (face cleat direction) as the most conductive. Northwest southeast directed hydrofracture simulations increased permeability in all directions except the northeast-southwest, although the permeability increase was not more than a factor of 3. Cluster analysis showed that the simulated cleat network was very well connected at all simulated scales. For thick coals, the entire cleat network formed one compartment, whereas thin coals formed several compartments. Convex hulls of the compartments confirmed that the directional bulk permeability was nearly isotropic. Volumetric calculations of the Ferron coal indicated that all the water produced to date can be accounted for from the coal cleat porosity system and does not depend on contributions of water from contiguous units.Flow paths, determined from porous media modeling from recharge to discharge, indicate that the three coalbed gas (CBG) fields assessed in this study could have different groundwater chemical compositions as confirmed by geochemical data. Simulated water production from 185 wells from 1993 to 1998 showed that in 1998 the maximum head drawdown from the Drunkards Wash field was more than 365 m, and the cone of depression extended to within a short distance of the Ferron outcrop. Maximum drawdown in the Helper field was 120 m, and the maximum drawdown in the Buzzards Bench field was just over 60 m. The cone of depression for the Helper field was half the size of the Drunkards Wash field, and the cone of depression for the Buzzards Bench field was limited to just outside the field unit. Water budget calculations from the simulation indicate that none of the stream flows are affected by coalbed gas associated water production. ?? 2003 Elsevier B.V. All rights reserved.

Emulsion droplet interactions: a front-tracking treatment

NASA Astrophysics Data System (ADS)

Mason, Lachlan; Juric, Damir; Chergui, Jalel; Shin, Seungwon; Craster, Richard V.; Matar, Omar K.

2017-11-01

Emulsion coalescence influences a multitude of industrial applications including solvent extraction, oil recovery and the manufacture of fast-moving consumer goods. Droplet interaction models are vital for the design and scale-up of processing systems, however predictive modelling at the droplet-scale remains a research challenge. This study simulates industrially relevant moderate-inertia collisions for which a high degree of droplet deformation occurs. A hybrid front-tracking/level-set approach is used to automatically account for interface merging without the need for `bookkeeping' of interface connectivity. The model is implemented in Code BLUE using a parallel multi-grid solver, allowing both film and droplet-scale dynamics to be resolved efficiently. Droplet interaction simulations are validated using experimental sequences from the literature in the presence and absence of background turbulence. The framework is readily extensible for modelling the influence of surfactants and non-Newtonian fluids on droplet interaction processes. EPSRC, UK, MEMPHIS program Grant (EP/K003976/1), RAEng Research Chair (OKM), PETRONAS.

Endogenous network of firms and systemic risk

NASA Astrophysics Data System (ADS)

Ma, Qianting; He, Jianmin; Li, Shouwei

2018-02-01

We construct an endogenous network characterized by commercial credit relationships connecting the upstream and downstream firms. Simulation results indicate that the endogenous network model displays a scale-free property which exists in real-world firm systems. In terms of the network structure, with the expansion of the scale of network nodes, the systemic risk increases significantly, while the heterogeneities of network nodes have no effect on systemic risk. As for firm micro-behaviors, including the selection range of trading partners, actual output, labor requirement, price of intermediate products and employee salaries, increase of all these parameters will lead to higher systemic risk.

Role of local network oscillations in resting-state functional connectivity.

PubMed

Cabral, Joana; Hugues, Etienne; Sporns, Olaf; Deco, Gustavo

2011-07-01

Spatio-temporally organized low-frequency fluctuations (<0.1 Hz), observed in BOLD fMRI signal during rest, suggest the existence of underlying network dynamics that emerge spontaneously from intrinsic brain processes. Furthermore, significant correlations between distinct anatomical regions-or functional connectivity (FC)-have led to the identification of several widely distributed resting-state networks (RSNs). This slow dynamics seems to be highly structured by anatomical connectivity but the mechanism behind it and its relationship with neural activity, particularly in the gamma frequency range, remains largely unknown. Indeed, direct measurements of neuronal activity have revealed similar large-scale correlations, particularly in slow power fluctuations of local field potential gamma frequency range oscillations. To address these questions, we investigated neural dynamics in a large-scale model of the human brain's neural activity. A key ingredient of the model was a structural brain network defined by empirically derived long-range brain connectivity together with the corresponding conduction delays. A neural population, assumed to spontaneously oscillate in the gamma frequency range, was placed at each network node. When these oscillatory units are integrated in the network, they behave as weakly coupled oscillators. The time-delayed interaction between nodes is described by the Kuramoto model of phase oscillators, a biologically-based model of coupled oscillatory systems. For a realistic setting of axonal conduction speed, we show that time-delayed network interaction leads to the emergence of slow neural activity fluctuations, whose patterns correlate significantly with the empirically measured FC. The best agreement of the simulated FC with the empirically measured FC is found for a set of parameters where subsets of nodes tend to synchronize although the network is not globally synchronized. Inside such clusters, the simulated BOLD signal between nodes is found to be correlated, instantiating the empirically observed RSNs. Between clusters, patterns of positive and negative correlations are observed, as described in experimental studies. These results are found to be robust with respect to a biologically plausible range of model parameters. In conclusion, our model suggests how resting-state neural activity can originate from the interplay between the local neural dynamics and the large-scale structure of the brain. Copyright © 2011 Elsevier Inc. All rights reserved.

The Material Point Method and Simulation of Wave Propagation in Heterogeneous Media

NASA Astrophysics Data System (ADS)

Bardenhagen, S. G.; Greening, D. R.; Roessig, K. M.

2004-07-01

The mechanical response of polycrystalline materials, particularly under shock loading, is of significant interest in a variety of munitions and industrial applications. Homogeneous continuum models have been developed to describe material response, including Equation of State, strength, and reactive burn models. These models provide good estimates of bulk material response. However, there is little connection to underlying physics and, consequently, they cannot be applied far from their calibrated regime with confidence. Both explosives and metals have important structure at the (energetic or single crystal) grain scale. The anisotropic properties of the individual grains and the presence of interfaces result in the localization of energy during deformation. In explosives energy localization can lead to initiation under weak shock loading, and in metals to material ejecta under strong shock loading. To develop accurate, quantitative and predictive models it is imperative to develop a sound physical understanding of the grain-scale material response. Numerical simulations are performed to gain insight into grain-scale material response. The Generalized Interpolation Material Point Method family of numerical algorithms, selected for their robust treatment of large deformation problems and convenient framework for implementing material interface models, are reviewed. A three-dimensional simulation of wave propagation through a granular material indicates the scale and complexity of a representative grain-scale computation. Verification and validation calculations on model bimaterial systems indicate the minimum numerical algorithm complexity required for accurate simulation of wave propagation across material interfaces and demonstrate the importance of interfacial decohesion. Preliminary results are presented which predict energy localization at the grain boundary in a metallic bicrystal.

Out of the net: An agent-based model to study human movements influence on local-scale malaria transmission.

PubMed

Pizzitutti, Francesco; Pan, William; Feingold, Beth; Zaitchik, Ben; Álvarez, Carlos A; Mena, Carlos F

2018-01-01

Though malaria control initiatives have markedly reduced malaria prevalence in recent decades, global eradication is far from actuality. Recent studies show that environmental and social heterogeneities in low-transmission settings have an increased weight in shaping malaria micro-epidemiology. New integrated and more localized control strategies should be developed and tested. Here we present a set of agent-based models designed to study the influence of local scale human movements on local scale malaria transmission in a typical Amazon environment, where malaria is transmission is low and strongly connected with seasonal riverine flooding. The agent-based simulations show that the overall malaria incidence is essentially not influenced by local scale human movements. In contrast, the locations of malaria high risk spatial hotspots heavily depend on human movements because simulated malaria hotspots are mainly centered on farms, were laborers work during the day. The agent-based models are then used to test the effectiveness of two different malaria control strategies both designed to reduce local scale malaria incidence by targeting hotspots. The first control scenario consists in treat against mosquito bites people that, during the simulation, enter at least once inside hotspots revealed considering the actual sites where human individuals were infected. The second scenario involves the treatment of people entering in hotspots calculated assuming that the infection sites of every infected individual is located in the household where the individual lives. Simulations show that both considered scenarios perform better in controlling malaria than a randomized treatment, although targeting household hotspots shows slightly better performance.

A Collection of Nonlinear Aircraft Simulations in MATLAB

NASA Technical Reports Server (NTRS)

Garza, Frederico R.; Morelli, Eugene A.

2003-01-01

Nonlinear six degree-of-freedom simulations for a variety of aircraft were created using MATLAB. Data for aircraft geometry, aerodynamic characteristics, mass / inertia properties, and engine characteristics were obtained from open literature publications documenting wind tunnel experiments and flight tests. Each nonlinear simulation was implemented within a common framework in MATLAB, and includes an interface with another commercially-available program to read pilot inputs and produce a three-dimensional (3-D) display of the simulated airplane motion. Aircraft simulations include the General Dynamics F-16 Fighting Falcon, Convair F-106B Delta Dart, Grumman F-14 Tomcat, McDonnell Douglas F-4 Phantom, NASA Langley Free-Flying Aircraft for Sub-scale Experimental Research (FASER), NASA HL-20 Lifting Body, NASA / DARPA X-31 Enhanced Fighter Maneuverability Demonstrator, and the Vought A-7 Corsair II. All nonlinear simulations and 3-D displays run in real time in response to pilot inputs, using contemporary desktop personal computer hardware. The simulations can also be run in batch mode. Each nonlinear simulation includes the full nonlinear dynamics of the bare airframe, with a scaled direct connection from pilot inputs to control surface deflections to provide adequate pilot control. Since all the nonlinear simulations are implemented entirely in MATLAB, user-defined control laws can be added in a straightforward fashion, and the simulations are portable across various computing platforms. Routines for trim, linearization, and numerical integration are included. The general nonlinear simulation framework and the specifics for each particular aircraft are documented.

Photovoltaic Grid-Connected Modeling and Characterization Based on Experimental Results.

PubMed

Humada, Ali M; Hojabri, Mojgan; Sulaiman, Mohd Herwan Bin; Hamada, Hussein M; Ahmed, Mushtaq N

2016-01-01

A grid-connected photovoltaic (PV) system operates under fluctuated weather condition has been modeled and characterized based on specific test bed. A mathematical model of a small-scale PV system has been developed mainly for residential usage, and the potential results have been simulated. The proposed PV model based on three PV parameters, which are the photocurrent, IL, the reverse diode saturation current, Io, the ideality factor of diode, n. Accuracy of the proposed model and its parameters evaluated based on different benchmarks. The results showed that the proposed model fitting the experimental results with high accuracy compare to the other models, as well as the I-V characteristic curve. The results of this study can be considered valuable in terms of the installation of a grid-connected PV system in fluctuated climatic conditions.

Photovoltaic Grid-Connected Modeling and Characterization Based on Experimental Results

PubMed Central

Humada, Ali M.; Hojabri, Mojgan; Sulaiman, Mohd Herwan Bin; Hamada, Hussein M.; Ahmed, Mushtaq N.

2016-01-01

A grid-connected photovoltaic (PV) system operates under fluctuated weather condition has been modeled and characterized based on specific test bed. A mathematical model of a small-scale PV system has been developed mainly for residential usage, and the potential results have been simulated. The proposed PV model based on three PV parameters, which are the photocurrent, IL, the reverse diode saturation current, Io, the ideality factor of diode, n. Accuracy of the proposed model and its parameters evaluated based on different benchmarks. The results showed that the proposed model fitting the experimental results with high accuracy compare to the other models, as well as the I-V characteristic curve. The results of this study can be considered valuable in terms of the installation of a grid-connected PV system in fluctuated climatic conditions. PMID:27035575

A coupled modeling system for connecting prescribed fire activity data through CMAQ for simulating regional scale air quality

Treesearch

Gary L. Achtemeier; Scott Goodrick; Yongqiang Liu

2005-01-01

The southeastern United Stats - states extending from Virginia to Texas and from the Ohio River southward - (hereafter called the "South") compromise one of the most productive forested areas in the United States. Although the South represents only 24 percent of the U.S. land area, approximately 200 million acres (81 million ha) or 40 percent of the Nation...

The principle of ‘maximum energy dissipation’: a novel thermodynamic perspective on rapid water flow in connected soil structures

PubMed Central

Zehe, Erwin; Blume, Theresa; Blöschl, Günter

2010-01-01

Preferential flow in biological soil structures is of key importance for infiltration and soil water flow at a range of scales. In the present study, we treat soil water flow as a dissipative process in an open non-equilibrium thermodynamic system, to better understand this key process. We define the chemical potential and Helmholtz free energy based on soil physical quantities, parametrize a physically based hydrological model based on field data and simulate the evolution of Helmholtz free energy in a cohesive soil with different populations of worm burrows for a range of rainfall scenarios. The simulations suggest that flow in connected worm burrows allows a more efficient redistribution of water within the soil, which implies a more efficient dissipation of free energy/higher production of entropy. There is additional evidence that the spatial pattern of worm burrow density at the hillslope scale is a major control of energy dissipation. The pattern typically found in the study is more efficient in dissipating energy/producing entropy than other patterns. This is because upslope run-off accumulates and infiltrates via the worm burrows into the dry soil in the lower part of the hillslope, which results in an overall more efficient dissipation of free energy. PMID:20368256

Present and future connection of Asian-Pacific Oscillation to large-scale atmospheric circulations and East Asian rainfall: results of CMIP5

NASA Astrophysics Data System (ADS)

Zhou, Botao; Xu, Ying; Shi, Ying

2018-01-01

The summer Asian-Pacific oscillation (APO), one of the major modes of climate variability over the Asian-Pacific sector, has a pronounced effect on variations of large-scale atmospheric circulations and climate. This study evaluated the capability of 30 state-of-the-art climate models among the Coupled Model Intercomparison Project Phase 5 (CMIP5) in simulating its association with the atmospheric circulations over the Asian-Pacific region and the precipitation over East Asia. Furthermore, their future connections under the RCP8.5 scenario were examined. The evaluation results show that 5 out of 30 climate models can well capture the observed APO-related features in a comprehensive way, including the strengthened South Asian high (SAH), deepened North Pacific trough (NPT) and northward East Asian jet (EAJ) in the upper troposphere; an intensification of the Asian low and the North Pacific subtropical high (NPSH) as well as a northward shift of the western Pacific subtropical high (WPSH) in the lower troposphere; and a decrease in East Asian summer rainfall (EASR) under the positive APO phase. Based on the five CMIP5 models' simulations, the dynamic linkages of the APO to the SAH, NPT, AL, and NPSH are projected to maintain during the second half of the twenty-first century. However, its connection with the EASR tends to reduce significantly. Such a reduction might result from the weakening of the linkage of the APO to the meridional displacement of the EAJ and WPSH as a response to the warming scenario.

Spatiotemporal dynamics of surface water networks across a global biodiversity hotspot—implications for conservation

NASA Astrophysics Data System (ADS)

Tulbure, Mirela G.; Kininmonth, Stuart; Broich, Mark

2014-11-01

The concept of habitat networks represents an important tool for landscape conservation and management at regional scales. Previous studies simulated degradation of temporally fixed networks but few quantified the change in network connectivity from disintegration of key features that undergo naturally occurring spatiotemporal dynamics. This is particularly of concern for aquatic systems, which typically show high natural spatiotemporal variability. Here we focused on the Swan Coastal Plain, a bioregion that encompasses a global biodiversity hotspot in Australia with over 1500 water bodies of high biodiversity. Using graph theory, we conducted a temporal analysis of water body connectivity over 13 years of variable climate. We derived large networks of surface water bodies using Landsat data (1999-2011). We generated an ensemble of 278 potential networks at three dispersal distances approximating the maximum dispersal distance of different water dependent organisms. We assessed network connectivity through several network topology metrics and quantified the resilience of the network topology during wet and dry phases. We identified ‘stepping stone’ water bodies across time and compared our networks with theoretical network models with known properties. Results showed a highly dynamic seasonal pattern of variability in network topology metrics. A decline in connectivity over the 13 years was noted with potential negative consequences for species with limited dispersal capacity. The networks described here resemble theoretical scale-free models, also known as ‘rich get richer’ algorithm. The ‘stepping stone’ water bodies are located in the area around the Peel-Harvey Estuary, a Ramsar listed site, and some are located in a national park. Our results describe a powerful approach that can be implemented when assessing the connectivity for a particular organism with known dispersal distance. The approach of identifying the surface water bodies that act as ‘stepping stone’ over time may help prioritize surface water bodies that are essential for maintaining regional scale connectivity.

A novel explicit approach to model bromide and pesticide transport in connected soil structures

NASA Astrophysics Data System (ADS)

Klaus, J.; Zehe, E.

2011-07-01

The present study tests whether an explicit treatment of worm burrows and tile drains as connected structures is feasible for simulating water flow, bromide and pesticide transport in structured heterogeneous soils at hillslope scale. The essence is to represent worm burrows as morphologically connected paths of low flow resistance in a hillslope model. A recent Monte Carlo study (Klaus and Zehe, 2010, Hydrological Processes, 24, p. 1595-1609) revealed that this approach allowed successful reproduction of tile drain event discharge recorded during an irrigation experiment at a tile drained field site. However, several "hillslope architectures" that were all consistent with the available extensive data base allowed a good reproduction of tile drain flow response. Our second objective was thus to find out whether this "equifinality" in spatial model setups may be reduced when including bromide tracer data in the model falsification process. We thus simulated transport of bromide for the 13 spatial model setups that performed best with respect to reproduce tile drain event discharge, without any further calibration. All model setups allowed a very good prediction of the temporal dynamics of cumulated bromide leaching into the tile drain, while only four of them matched the accumulated water balance and accumulated bromide loss into the tile drain. The number of behavioural model architectures could thus be reduced to four. One of those setups was used for simulating transport of Isoproturon, using different parameter combinations to characterise adsorption according to the Footprint data base. Simulations could, however, only reproduce the observed leaching behaviour, when we allowed for retardation coefficients that were very close to one.

A Machine Learning Method for the Prediction of Receptor Activation in the Simulation of Synapses

PubMed Central

Montes, Jesus; Gomez, Elena; Merchán-Pérez, Angel; DeFelipe, Javier; Peña, Jose-Maria

2013-01-01

Chemical synaptic transmission involves the release of a neurotransmitter that diffuses in the extracellular space and interacts with specific receptors located on the postsynaptic membrane. Computer simulation approaches provide fundamental tools for exploring various aspects of the synaptic transmission under different conditions. In particular, Monte Carlo methods can track the stochastic movements of neurotransmitter molecules and their interactions with other discrete molecules, the receptors. However, these methods are computationally expensive, even when used with simplified models, preventing their use in large-scale and multi-scale simulations of complex neuronal systems that may involve large numbers of synaptic connections. We have developed a machine-learning based method that can accurately predict relevant aspects of the behavior of synapses, such as the percentage of open synaptic receptors as a function of time since the release of the neurotransmitter, with considerably lower computational cost compared with the conventional Monte Carlo alternative. The method is designed to learn patterns and general principles from a corpus of previously generated Monte Carlo simulations of synapses covering a wide range of structural and functional characteristics. These patterns are later used as a predictive model of the behavior of synapses under different conditions without the need for additional computationally expensive Monte Carlo simulations. This is performed in five stages: data sampling, fold creation, machine learning, validation and curve fitting. The resulting procedure is accurate, automatic, and it is general enough to predict synapse behavior under experimental conditions that are different to the ones it has been trained on. Since our method efficiently reproduces the results that can be obtained with Monte Carlo simulations at a considerably lower computational cost, it is suitable for the simulation of high numbers of synapses and it is therefore an excellent tool for multi-scale simulations. PMID:23894367

Secure Large-Scale Airport Simulations Using Distributed Computational Resources

NASA Technical Reports Server (NTRS)

McDermott, William J.; Maluf, David A.; Gawdiak, Yuri; Tran, Peter; Clancy, Dan (Technical Monitor)

2001-01-01

To fully conduct research that will support the far-term concepts, technologies and methods required to improve the safety of Air Transportation a simulation environment of the requisite degree of fidelity must first be in place. The Virtual National Airspace Simulation (VNAS) will provide the underlying infrastructure necessary for such a simulation system. Aerospace-specific knowledge management services such as intelligent data-integration middleware will support the management of information associated with this complex and critically important operational environment. This simulation environment, in conjunction with a distributed network of supercomputers, and high-speed network connections to aircraft, and to Federal Aviation Administration (FAA), airline and other data-sources will provide the capability to continuously monitor and measure operational performance against expected performance. The VNAS will also provide the tools to use this performance baseline to obtain a perspective of what is happening today and of the potential impact of proposed changes before they are introduced into the system.

Dynamic Average-Value Modeling of Doubly-Fed Induction Generator Wind Energy Conversion Systems

NASA Astrophysics Data System (ADS)

Shahab, Azin

In a Doubly-fed Induction Generator (DFIG) wind energy conversion system, the rotor of a wound rotor induction generator is connected to the grid via a partial scale ac/ac power electronic converter which controls the rotor frequency and speed. In this research, detailed models of the DFIG wind energy conversion system with Sinusoidal Pulse-Width Modulation (SPWM) scheme and Optimal Pulse-Width Modulation (OPWM) scheme for the power electronic converter are developed in detail in PSCAD/EMTDC. As the computer simulation using the detailed models tends to be computationally extensive, time consuming and even sometimes not practical in terms of speed, two modified approaches (switching-function modeling and average-value modeling) are proposed to reduce the simulation execution time. The results demonstrate that the two proposed approaches reduce the simulation execution time while the simulation results remain close to those obtained using the detailed model simulation.

Flagellar dynamics of a connected chain of active, polar, Brownian particles

PubMed Central

Chelakkot, Raghunath; Gopinath, Arvind; Mahadevan, L.; Hagan, Michael F.

2014-01-01

We show that active, self-propelled particles that are connected together to form a single chain that is anchored at one end can produce the graceful beating motions of flagella. Changing the boundary condition from a clamp to a pivot at the anchor leads to steadily rotating tight coils. Strong noise in the system disrupts the regularity of the oscillations. We use a combination of detailed numerical simulations, mean-field scaling analysis and first passage time theory to characterize the phase diagram as a function of the filament length, passive elasticity, propulsion force and noise. Our study suggests minimal experimental tests for the onset of oscillations in an active polar chain. PMID:24352670

Flagellar dynamics of a connected chain of active, polar, Brownian particles.

PubMed

Chelakkot, Raghunath; Gopinath, Arvind; Mahadevan, L; Hagan, Michael F

2014-03-06

We show that active, self-propelled particles that are connected together to form a single chain that is anchored at one end can produce the graceful beating motions of flagella. Changing the boundary condition from a clamp to a pivot at the anchor leads to steadily rotating tight coils. Strong noise in the system disrupts the regularity of the oscillations. We use a combination of detailed numerical simulations, mean-field scaling analysis and first passage time theory to characterize the phase diagram as a function of the filament length, passive elasticity, propulsion force and noise. Our study suggests minimal experimental tests for the onset of oscillations in an active polar chain.

Performance optimization of internet firewalls

NASA Astrophysics Data System (ADS)

Chiueh, Tzi-cker; Ballman, Allen

1997-01-01

Internet firewalls control the data traffic in and out of an enterprise network by checking network packets against a set of rules that embodies an organization's security policy. Because rule checking is computationally more expensive than routing-table look-up, it could become a potential bottleneck for scaling up the performance of IP routers, which typically implement firewall functions in software. in this paper, we analyzed the performance problems associated with firewalls, particularly packet filters, propose a good connection cache to amortize the costly security check over the packets in a connection, and report the preliminary performance results of a trace-driven simulation that show the average packet check time can be reduced by a factor of 2.5 at the least.

The Destabilization of Protected Soil Organic Carbon Following Experimental Drought at the Pore and Core scale

NASA Astrophysics Data System (ADS)

Smith, A. P.; Bond-Lamberty, B. P.; Tfaily, M. M.; Todd-Brown, K. E.; Bailey, V. L.

2015-12-01

The movement of water and solutes through the pore matrix controls the distribution and transformation of carbon (C) in soils. Thus, a change in the hydrologic connectivity, such as increased saturation, disturbance or drought, may alter C mineralization and greenhouse gas (GHG) fluxes to the atmosphere. While these processes occur at the pore scale, they are often investigated at coarser scale. This project investigates pore- and core-scale soil C dynamics with varying hydrologic factors (simulated precipitation, groundwater-led saturation, and drought) to assess how climate-change induced shifts in hydrologic connectivity influences the destabilization of protected C in soils. Surface soil cores (0-15 cm depth) were collected from the Disney Wilderness Preserve, Florida, USA where water dynamics, particularly water table rise and fall, appear to exert a strong control on the emissions of GHGs and the persistence of soil organic matter in these soils. We measured CO2 and CH4 from soils allowed to freely imbibe water from below to a steady state starting from either field moist conditions or following experimental drought. Parallel treatments included the addition of similar quantities of water from above to simulate precipitation. Overall respiration increased in soil cores subjected to drought compared to field moist cores independent of wetting type. Cumulative CH4 production was higher in drought-induced soils, especially in the soils subjected to experimental groundwater-led saturation. Overall, the more C (from CO2 and CH4) was lost in drought-induced soils compared to field moist cores. Our results indicate that future drought events could have profound effects on the destabilization of protected C, especially in groundwater-fed soils. Our next steps focus on how to accurately capture drought-induced C destabilization mechanisms in earth system models.

Simulating synchronization in neuronal networks

NASA Astrophysics Data System (ADS)

Fink, Christian G.

2016-06-01

We discuss several techniques used in simulating neuronal networks by exploring how a network's connectivity structure affects its propensity for synchronous spiking. Network connectivity is generated using the Watts-Strogatz small-world algorithm, and two key measures of network structure are described. These measures quantify structural characteristics that influence collective neuronal spiking, which is simulated using the leaky integrate-and-fire model. Simulations show that adding a small number of random connections to an otherwise lattice-like connectivity structure leads to a dramatic increase in neuronal synchronization.

A multi-scale Lattice Boltzmann model for simulating solute transport in 3D X-ray micro-tomography images of aggregated porous materials

NASA Astrophysics Data System (ADS)

Zhang, Xiaoxian; Crawford, John W.; Flavel, Richard J.; Young, Iain M.

2016-10-01

The Lattice Boltzmann (LB) model and X-ray computed tomography (CT) have been increasingly used in combination over the past decade to simulate water flow and chemical transport at pore scale in porous materials. Because of its limitation in resolution and the hierarchical structure of most natural soils, the X-ray CT tomography can only identify pores that are greater than its resolution and treats other pores as solid. As a result, the so-called solid phase in X-ray images may in reality be a grey phase, containing substantial connected pores capable of conducing fluids and solute. Although modified LB models have been developed to simulate fluid flow in such media, models for solute transport are relatively limited. In this paper, we propose a LB model for simulating solute transport in binary soil images containing permeable solid phase. The model is based on the single-relaxation time approach and uses a modified partial bounce-back method to describe the resistance caused by the permeable solid phase to chemical transport. We derive the relationship between the diffusion coefficient and the parameter introduced in the partial bounce-back method, and test the model against analytical solution for movement of a pulse of tracer. We also validate it against classical finite volume method for solute diffusion in a simple 2D image, and then apply the model to a soil image acquired using X-ray tomography at resolution of 30 μm in attempts to analyse how the ability of the solid phase to diffuse solute at micron-scale affects the behaviour of the solute at macro-scale after a volumetric average. Based on the simulated results, we discuss briefly the danger in interpreting experimental results using the continuum model without fully understanding the pore-scale processes, as well as the potential of using pore-scale modelling and tomography to help improve the continuum models.

Localization Algorithm Based on a Spring Model (LASM) for Large Scale Wireless Sensor Networks.

PubMed

Chen, Wanming; Mei, Tao; Meng, Max Q-H; Liang, Huawei; Liu, Yumei; Li, Yangming; Li, Shuai

2008-03-15

A navigation method for a lunar rover based on large scale wireless sensornetworks is proposed. To obtain high navigation accuracy and large exploration area, highnode localization accuracy and large network scale are required. However, thecomputational and communication complexity and time consumption are greatly increasedwith the increase of the network scales. A localization algorithm based on a spring model(LASM) method is proposed to reduce the computational complexity, while maintainingthe localization accuracy in large scale sensor networks. The algorithm simulates thedynamics of physical spring system to estimate the positions of nodes. The sensor nodesare set as particles with masses and connected with neighbor nodes by virtual springs. Thevirtual springs will force the particles move to the original positions, the node positionscorrespondingly, from the randomly set positions. Therefore, a blind node position can bedetermined from the LASM algorithm by calculating the related forces with the neighbornodes. The computational and communication complexity are O(1) for each node, since thenumber of the neighbor nodes does not increase proportionally with the network scale size.Three patches are proposed to avoid local optimization, kick out bad nodes and deal withnode variation. Simulation results show that the computational and communicationcomplexity are almost constant despite of the increase of the network scale size. The time consumption has also been proven to remain almost constant since the calculation steps arealmost unrelated with the network scale size.

Advanced manned space flight simulation and training: An investigation of simulation host computer system concepts

NASA Technical Reports Server (NTRS)

Montag, Bruce C.; Bishop, Alfred M.; Redfield, Joe B.

1989-01-01

The findings of a preliminary investigation by Southwest Research Institute (SwRI) in simulation host computer concepts is presented. It is designed to aid NASA in evaluating simulation technologies for use in spaceflight training. The focus of the investigation is on the next generation of space simulation systems that will be utilized in training personnel for Space Station Freedom operations. SwRI concludes that NASA should pursue a distributed simulation host computer system architecture for the Space Station Training Facility (SSTF) rather than a centralized mainframe based arrangement. A distributed system offers many advantages and is seen by SwRI as the only architecture that will allow NASA to achieve established functional goals and operational objectives over the life of the Space Station Freedom program. Several distributed, parallel computing systems are available today that offer real-time capabilities for time critical, man-in-the-loop simulation. These systems are flexible in terms of connectivity and configurability, and are easily scaled to meet increasing demands for more computing power.

A Landscape Approach to Invasive Species Management.

PubMed

Lurgi, Miguel; Wells, Konstans; Kennedy, Malcolm; Campbell, Susan; Fordham, Damien A

2016-01-01

Biological invasions are not only a major threat to biodiversity, they also have major impacts on local economies and agricultural production systems. Once established, the connection of local populations into metapopulation networks facilitates dispersal at landscape scales, generating spatial dynamics that can impact the outcome of pest-management actions. Much planning goes into landscape-scale invasive species management. However, effective management requires knowledge on the interplay between metapopulation network topology and management actions. We address this knowledge gap using simulation models to explore the effectiveness of two common management strategies, applied across different extents and according to different rules for selecting target localities in metapopulations with different network topologies. These management actions are: (i) general population reduction, and (ii) reduction of an obligate resource. The reduction of an obligate resource was generally more efficient than population reduction for depleting populations at landscape scales. However, the way in which local populations are selected for management is important when the topology of the metapopulation is heterogeneous in terms of the distribution of connections among local populations. We tested these broad findings using real-world scenarios of European rabbits (Oryctolagus cuniculus) infesting agricultural landscapes in Western Australia. Although management strategies targeting central populations were more effective in simulated heterogeneous metapopulation structures, no difference was observed in real-world metapopulation structures that are highly homogeneous. In large metapopulations with high proximity and connectivity of neighbouring populations, different spatial management strategies yield similar outcomes. Directly considering spatial attributes in pest-management actions will be most important for metapopulation networks with heterogeneously distributed links. Our modelling framework provides a simple approach for identifying the best possible management strategy for invasive species based on metapopulation structure and control capacity. This information can be used by managers trying to devise efficient landscape-oriented management strategies for invasive species and can also generate insights for conservation purposes.

A New Dual-Pore Formation Factor Model: A Percolation Network Study and Comparison to Experimental Data

NASA Astrophysics Data System (ADS)

Tang, Y. B.; Li, M.; Bernabe, Y.

2014-12-01

We modeled the electrical transport behavior of dual-pore carbonate rocks in this paper. Based on experimental data of a carbonate reservoir in China, we simply considered the low porosity samples equivalent to the matrix (micro-pore system) of the high porosity samples. For modeling the bimodal porous media, we considered that the matrix is homogeneous and interconnected. The connectivity and the pore size distribution of macro-pore system are varied randomly. Both pore systems are supposed to act electrically in parallel, connected at the nodes, where the fluid exchange takes place, an approach previously used by Bauer et al. (2012). Then, the effect of the properties of matrix, the pore size distribution and connectivity of macro-pore system on petrophysical properties of carbonates can be investigated. We simulated electrical current through networks in three-dimensional simple cubic (SC) and body-center cubic (BCC) with different coordination numbers and different pipe radius distributions of macro-pore system. Based on the simulation results, we found that the formation factor obeys a "universal" scaling relationship (i.e. independent of lattice type), 1/F∝eγz, where γ is a function of the normalized standard deviation of the pore radius distribution of macro-pore system and z is the coordination number of macro-pore system. This relationship is different from the classic "universal power law" in percolation theory. A formation factor model was inferred on the basis of the scaling relationship mentioned above and several scale-invariant quantities (such as hydraulic radius rH and throat length l of macro-pore). Several methods were developed to estimate corresponding parameters of the new model with conventional core analyses. It was satisfactorily tested against experimental data, including some published experimental data. Furthermore, the relationship between water saturation and resistivity in dual-pore carbonates was discussed based on the new model.

Numerical Simulation of DC Coronal Heating

NASA Astrophysics Data System (ADS)

Dahlburg, Russell B.; Einaudi, G.; Taylor, Brian D.; Ugarte-Urra, Ignacio; Warren, Harry; Rappazzo, A. F.; Velli, Marco

2016-05-01

Recent research on observational signatures of turbulent heating of a coronal loop will be discussed. The evolution of the loop is is studied by means of numerical simulations of the fully compressible three-dimensional magnetohydrodynamic equations using the HYPERION code. HYPERION calculates the full energy cycle involving footpoint convection, magnetic reconnection, nonlinear thermal conduction and optically thin radiation. The footpoints of the loop magnetic field are convected by random photospheric motions. As a consequence the magnetic field in the loop is energized and develops turbulent nonlinear dynamics characterized by the continuous formation and dissipation of field-aligned current sheets: energy is deposited at small scales where heating occurs. Dissipation is non-uniformly distributed so that only a fraction of thecoronal mass and volume gets heated at any time. Temperature and density are highly structured at scales which, in the solar corona, remain observationally unresolved: the plasma of the simulated loop is multi thermal, where highly dynamical hotter and cooler plasma strands are scattered throughout the loop at sub-observational scales. Typical simulated coronal loops are 50000 km length and have axial magnetic field intensities ranging from 0.01 to 0.04 Tesla. To connect these simulations to observations the computed number densities and temperatures are used to synthesize the intensities expected in emission lines typically observed with the Extreme ultraviolet Imaging Spectrometer (EIS) on Hinode. These intensities are then employed to compute differential emission measure distributions, which are found to be very similar to those derived from observations of solar active regions.

North American water availability under stress and duress: building understanding from simulations, observations and data products

NASA Astrophysics Data System (ADS)

Maxwell, R. M.; Condon, L. E.; Atchley, A. L.; Hector, B.

2017-12-01

Quantifying the available freshwater for human use and ecological function depends on fluxes and stores that are hard to observe. Evapotranspiration (ET) is the largest terrestrial flux of water behind precipitation but is observed with low spatial density. Likewise, groundwater is the largest freshwater store, yet is equally uncertain. The ability to upscale observations of these variables is an additional complication; point measurements are made at scales orders of magnitude smaller than remote sensing data products. Integrated hydrologic models that simulate continental extents at fine spatial resolution are now becoming an additional tool to constrain fluxes and address interconnections. For example, recent work has shown connections between water table depth and transpiration partitioning, and demonstrated the ability to reconcile point observations and large-scale inferences. Here we explore the dynamics of large hydrologic systems experiencing change and stress across continental North America using integrated model simulations, observations and data products. Simulations of aquifer depletion due to pervasive groundwater pumping diagnose both stream depletion and changes in ET. Simulations of systematic increases in temperature are used to understand the relationship between snowpack dynamics, surface and groundwater flow, ET and a changing climate. Remotely sensed products including the GRACE estimates of total storage change are downscaled using model simulations to better understand human impacts to the hydrologic cycle. These example applications motivate a path forward to better use simulations to understand water availability.

Feedforward Inhibition Allows Input Summation to Vary in Recurrent Cortical Networks

PubMed Central

2018-01-01

Abstract Brain computations depend on how neurons transform inputs to spike outputs. Here, to understand input-output transformations in cortical networks, we recorded spiking responses from visual cortex (V1) of awake mice of either sex while pairing sensory stimuli with optogenetic perturbation of excitatory and parvalbumin-positive inhibitory neurons. We found that V1 neurons’ average responses were primarily additive (linear). We used a recurrent cortical network model to determine whether these data, as well as past observations of nonlinearity, could be described by a common circuit architecture. Simulations showed that cortical input-output transformations can be changed from linear to sublinear with moderate (∼20%) strengthening of connections between inhibitory neurons, but this change away from linear scaling depends on the presence of feedforward inhibition. Simulating a variety of recurrent connection strengths showed that, compared with when input arrives only to excitatory neurons, networks produce a wider range of output spiking responses in the presence of feedforward inhibition. PMID:29682603

Environmental controls, oceanography and population dynamics of pathogens and harmful algal blooms: connecting sources to human exposure

PubMed Central

Dyble, Julianne; Bienfang, Paul; Dusek, Eva; Hitchcock, Gary; Holland, Fred; Laws, Ed; Lerczak, James; McGillicuddy, Dennis J; Minnett, Peter; Moore, Stephanie K; O'Kelly, Charles; Solo-Gabriele, Helena; Wang, John D

2008-01-01

Coupled physical-biological models are capable of linking the complex interactions between environmental factors and physical hydrodynamics to simulate the growth, toxicity and transport of infectious pathogens and harmful algal blooms (HABs). Such simulations can be used to assess and predict the impact of pathogens and HABs on human health. Given the widespread and increasing reliance of coastal communities on aquatic systems for drinking water, seafood and recreation, such predictions are critical for making informed resource management decisions. Here we identify three challenges to making this connection between pathogens/HABs and human health: predicting concentrations and toxicity; identifying the spatial and temporal scales of population and ecosystem interactions; and applying the understanding of population dynamics of pathogens/HABs to management strategies. We elaborate on the need to meet each of these challenges, describe how modeling approaches can be used and discuss strategies for moving forward in addressing these challenges. PMID:19025676

Towards cortex sized artificial neural systems.

PubMed

Johansson, Christopher; Lansner, Anders

2007-01-01

We propose, implement, and discuss an abstract model of the mammalian neocortex. This model is instantiated with a sparse recurrently connected neural network that has spiking leaky integrator units and continuous Hebbian learning. First we study the structure, modularization, and size of neocortex, and then we describe a generic computational model of the cortical circuitry. A characterizing feature of the model is that it is based on the modularization of neocortex into hypercolumns and minicolumns. Both a floating- and fixed-point arithmetic implementation of the model are presented along with simulation results. We conclude that an implementation on a cluster computer is not communication but computation bounded. A mouse and rat cortex sized version of our model executes in 44% and 23% of real-time respectively. Further, an instance of the model with 1.6 x 10(6) units and 2 x 10(11) connections performed noise reduction and pattern completion. These implementations represent the current frontier of large-scale abstract neural network simulations in terms of network size and running speed.

Computer simulations of melts of randomly branching polymers

NASA Astrophysics Data System (ADS)

Rosa, Angelo; Everaers, Ralf

2016-10-01

Randomly branching polymers with annealed connectivity are model systems for ring polymers and chromosomes. In this context, the branched structure represents transient folding induced by topological constraints. Here we present computer simulations of melts of annealed randomly branching polymers of 3 ≤ N ≤ 1800 segments in d = 2 and d = 3 dimensions. In all cases, we perform a detailed analysis of the observed tree connectivities and spatial conformations. Our results are in excellent agreement with an asymptotic scaling of the average tree size of R ˜ N1/d, suggesting that the trees behave as compact, territorial fractals. The observed swelling relative to the size of ideal trees, R ˜ N1/4, demonstrates that excluded volume interactions are only partially screened in melts of annealed trees. Overall, our results are in good qualitative agreement with the predictions of Flory theory. In particular, we find that the trees swell by the combination of modified branching and path stretching. However, the former effect is subdominant and difficult to detect in d = 3 dimensions.

Observational Signatures of Magnetic Reconnection

NASA Technical Reports Server (NTRS)

Savage, Sabrina

2014-01-01

Magnetic reconnection is often referred to as the primary source of energy release during solar flares. Directly observing reconnection occurring in the solar atmosphere, however, is not trivial considering that the scale size of the diffusion region is magnitudes smaller than the observational capabilities of current instrumentation, and coronal magnetic field measurements are not currently sufficient to capture the process. Therefore, predicting and studying observationally feasible signatures of the precursors and consequences of reconnection is necessary for guiding and verifying the simulations that dominate our understanding. I will present a set of such observations, particularly in connection with long-duration solar events, and compare them with recent simulations and theoretical predictions.

Object oriented design (OOD) in real-time hardware-in-the-loop (HWIL) simulations

NASA Astrophysics Data System (ADS)

Morris, Joe; Richard, Henri; Lowman, Alan; Youngren, Rob

2006-05-01

Using Object Oriented Design (OOD) concepts in AMRDEC's Hardware-in-the Loop (HWIL) real-time simulations allows the user to interchange parts of the simulation to meet test requirements. A large-scale three-spectral band simulator connected via a high speed reflective memory ring for time-critical data transfers to PC controllers connected by non real-time Ethernet protocols is used to separate software objects from logical entities close to their respective controlled hardware. Each standalone object does its own dynamic initialization, real-time processing, and end of run processing; therefore it can be easily maintained and updated. A Resource Allocation Program (RAP) is also utilized along with a device table to allocate, organize, and document the communication protocol between the software and hardware components. A GUI display program lists all allocations and deallocations of HWIL memory and hardware resources. This interactive program is also used to clean up defunct allocations of dead processes. Three examples are presented using the OOD and RAP concepts. The first is the control of an ACUTRONICS built three-axis flight table using the same control for calibration and real-time functions. The second is the transportability of a six-degree-of-freedom (6-DOF) simulation from an Onyx residence to a Linux-PC. The third is the replacement of the 6-DOF simulation with a replay program to drive the facility with archived run data for demonstration or analysis purposes.

Supermassive Black Holes and Galaxy Evolution

NASA Technical Reports Server (NTRS)

Merritt, D.

2004-01-01

Supermassive black holes appear to be generic components of galactic nuclei. The formation and growth of black holes is intimately connected with the evolution of galaxies on a wide range of scales. For instance, mergers between galaxies containing nuclear black holes would produce supermassive binaries which eventually coalesce via the emission of gravitational radiation. The formation and decay of these binaries is expected to produce a number of observable signatures in the stellar distribution. Black holes can also affect the large-scale structure of galaxies by perturbing the orbits of stars that pass through the nucleus. Large-scale N-body simulations are beginning to generate testable predictions about these processes which will allow us to draw inferences about the formation history of supermassive black holes.

Application and Evaluation of an Explicit Prognostic Cloud-Cover Scheme in GRAPES Global Forecast System

NASA Astrophysics Data System (ADS)

Ma, Zhanshan; Liu, Qijun; Zhao, Chuanfeng; Shen, Xueshun; Wang, Yuan; Jiang, Jonathan H.; Li, Zhe; Yung, Yuk

2018-03-01

An explicit prognostic cloud-cover scheme (PROGCS) is implemented into the Global/Regional Assimilation and Prediction System (GRAPES) for global middle-range numerical weather predication system (GRAPES_GFS) to improve the model performance in simulating cloud cover and radiation. Unlike the previous diagnostic cloud-cover scheme (DIAGCS), PROGCS considers the formation and dissipation of cloud cover by physically connecting it to the cumulus convection and large-scale stratiform condensation processes. Our simulation results show that clouds in mid-high latitudes arise mainly from large-scale stratiform condensation processes, while cumulus convection and large-scale condensation processes jointly determine cloud cover in low latitudes. Compared with DIAGCS, PROGCS captures more consistent vertical distributions of cloud cover with the observations from Atmospheric Radiation Measurements (ARM) program at the Southern Great Plains (SGP) site and simulates more realistic diurnal cycle of marine stratocumulus with the ERA-Interim reanalysis data. The low, high, and total cloud covers that are determined via PROGCS appear to be more realistic than those simulated via DIAGCS when both are compared with satellite retrievals though the former maintains slight negative biases. In addition, the simulations of outgoing longwave radiation (OLR) at the top of the atmosphere (TOA) from PROGCS runs have been considerably improved as well, resulting in less biases in radiative heating rates at heights below 850 hPa and above 400 hPa of GRAPES_GFS. Our results indicate that a prognostic method of cloud-cover calculation has significant advantage over the conventional diagnostic one, and it should be adopted in both weather and climate simulation and forecast.

Effectiveness of the Multilayered Caries Model and Visuo-tactile Virtual Reality Simulator for Minimally Invasive Caries Removal: A Randomized Controlled Trial.

PubMed

Dwisaptarini, A P; Suebnukarn, S; Rhienmora, P; Haddawy, P; Koontongkaew, S

This work presents the multilayered caries model with a visuo-tactile virtual reality simulator and a randomized controlled trial protocol to determine the effectiveness of the simulator in training for minimally invasive caries removal. A three-dimensional, multilayered caries model was reconstructed from 10 micro-computed tomography (CT) images of deeply carious extracted human teeth before and after caries removal. The full grey scale 0-255 yielded a median grey scale value of 0-9, 10-18, 19-25, 26-52, and 53-80 regarding dental pulp, infected carious dentin, affected carious dentin, normal dentin, and normal enamel, respectively. The simulator was connected to two haptic devices for a handpiece and mouth mirror. The visuo-tactile feedback during the operation varied depending on the grey scale. Sixth-year dental students underwent a pretraining assessment of caries removal on extracted teeth. The students were then randomly assigned to train on either the simulator (n=16) or conventional extracted teeth (n=16) for 3 days, after which the assessment was repeated. The posttraining performance of caries removal improved compared with pretraining in both groups (Wilcoxon, p<0.05). The equivalence test for proportional differences (two 1-sided t-tests) with a 0.2 margin confirmed that the participants in both groups had identical posttraining performance scores (95% CI=0.92, 1; p=0.00). In conclusion, training on the micro-CT multilayered caries model with the visuo-tactile virtual reality simulator and conventional extracted tooth had equivalent effects on improving performance of minimally invasive caries removal.

Comparison of dislocation density tensor fields derived from discrete dislocation dynamics and crystal plasticity simulations of torsion

DOE PAGES

Jones, Reese E.; Zimmerman, Jonathan A.; Po, Giacomo; ...

2016-02-01

Accurate simulation of the plastic deformation of ductile metals is important to the design of structures and components to performance and failure criteria. Many techniques exist that address the length scales relevant to deformation processes, including dislocation dynamics (DD), which models the interaction and evolution of discrete dislocation line segments, and crystal plasticity (CP), which incorporates the crystalline nature and restricted motion of dislocations into a higher scale continuous field framework. While these two methods are conceptually related, there have been only nominal efforts focused at the global material response that use DD-generated information to enhance the fidelity of CPmore » models. To ascertain to what degree the predictions of CP are consistent with those of DD, we compare their global and microstructural response in a number of deformation modes. After using nominally homogeneous compression and shear deformation dislocation dynamics simulations to calibrate crystal plasticity ow rule parameters, we compare not only the system-level stress-strain response of prismatic wires in torsion but also the resulting geometrically necessary dislocation density fields. To establish a connection between explicit description of dislocations and the continuum assumed with crystal plasticity simulations we ascertain the minimum length-scale at which meaningful dislocation density fields appear. Furthermore, our results show that, for the case of torsion, that the two material models can produce comparable spatial dislocation density distributions.« less

Module-based multiscale simulation of angiogenesis in skeletal muscle

PubMed Central

2011-01-01

Background Mathematical modeling of angiogenesis has been gaining momentum as a means to shed new light on the biological complexity underlying blood vessel growth. A variety of computational models have been developed, each focusing on different aspects of the angiogenesis process and occurring at different biological scales, ranging from the molecular to the tissue levels. Integration of models at different scales is a challenging and currently unsolved problem. Results We present an object-oriented module-based computational integration strategy to build a multiscale model of angiogenesis that links currently available models. As an example case, we use this approach to integrate modules representing microvascular blood flow, oxygen transport, vascular endothelial growth factor transport and endothelial cell behavior (sensing, migration and proliferation). Modeling methodologies in these modules include algebraic equations, partial differential equations and agent-based models with complex logical rules. We apply this integrated model to simulate exercise-induced angiogenesis in skeletal muscle. The simulation results compare capillary growth patterns between different exercise conditions for a single bout of exercise. Results demonstrate how the computational infrastructure can effectively integrate multiple modules by coordinating their connectivity and data exchange. Model parameterization offers simulation flexibility and a platform for performing sensitivity analysis. Conclusions This systems biology strategy can be applied to larger scale integration of computational models of angiogenesis in skeletal muscle, or other complex processes in other tissues under physiological and pathological conditions. PMID:21463529

Simulation of Consensus Model of Deffuant et al. on a BARABÁSI-ALBERT Network

NASA Astrophysics Data System (ADS)

Stauffer, D.; Meyer-Ortmanns, H.

In the consensus model with bounded confidence, studied by Deffuant et al. (2000), two randomly selected people who differ not too much in their opinion both shift their opinions towards each other. Now we restrict this exchange of information to people connected by a scale-free network. As a result, the number of different final opinions (when no complete consensus is formed) is proportional to the number of people.

Computational modeling of resting-state activity demonstrates markers of normalcy in children with prenatal or perinatal stroke.

PubMed

Adhikari, Mohit H; Raja Beharelle, Anjali; Griffa, Alessandra; Hagmann, Patric; Solodkin, Ana; McIntosh, Anthony R; Small, Steven L; Deco, Gustavo

2015-06-10

Children who sustain a prenatal or perinatal brain injury in the form of a stroke develop remarkably normal cognitive functions in certain areas, with a particular strength in language skills. A dominant explanation for this is that brain regions from the contralesional hemisphere "take over" their functions, whereas the damaged areas and other ipsilesional regions play much less of a role. However, it is difficult to tease apart whether changes in neural activity after early brain injury are due to damage caused by the lesion or by processes related to postinjury reorganization. We sought to differentiate between these two causes by investigating the functional connectivity (FC) of brain areas during the resting state in human children with early brain injury using a computational model. We simulated a large-scale network consisting of realistic models of local brain areas coupled through anatomical connectivity information of healthy and injured participants. We then compared the resulting simulated FC values of healthy and injured participants with the empirical ones. We found that the empirical connectivity values, especially of the damaged areas, correlated better with simulated values of a healthy brain than those of an injured brain. This result indicates that the structural damage caused by an early brain injury is unlikely to have an adverse and sustained impact on the functional connections, albeit during the resting state, of damaged areas. Therefore, these areas could continue to play a role in the development of near-normal function in certain domains such as language in these children. Copyright © 2015 the authors 0270-6474/15/358914-11$15.00/0.

A New Approach to Modeling Jupiter's Magnetosphere

NASA Astrophysics Data System (ADS)

Fukazawa, K.; Katoh, Y.; Walker, R. J.; Kimura, T.; Tsuchiya, F.; Murakami, G.; Kita, H.; Tao, C.; Murata, K. T.

2017-12-01

The scales in planetary magnetospheres range from 10s of planetary radii to kilometers. For a number of years we have studied the magnetospheres of Jupiter and Saturn by using 3-dimensional magnetohydrodynamic (MHD) simulations. However, we have not been able to reach even the limits of the MHD approximation because of the large amount of computer resources required. Recently thanks to the progress in supercomputer systems, we have obtained the capability to simulate Jupiter's magnetosphere with 1000 times the number of grid points used in our previous simulations. This has allowed us to combine the high resolution global simulation with a micro-scale simulation of the Jovian magnetosphere. In particular we can combine a hybrid (kinetic ions and fluid electrons) simulation with the MHD simulation. In addition, the new capability enables us to run multi-parameter survey simulations of the Jupiter-solar wind system. In this study we performed a high-resolution simulation of Jovian magnetosphere to connect with the hybrid simulation, and lower resolution simulations under the various solar wind conditions to compare with Hisaki and Juno observations. In the high-resolution simulation we used a regular Cartesian gird with 0.15 RJ grid spacing and placed the inner boundary at 7 RJ. From these simulation settings, we provide the magnetic field out to around 20 RJ from Jupiter as a background field for the hybrid simulation. For the first time we have been able to resolve Kelvin Helmholtz waves on the magnetopause. We have investigated solar wind dynamic pressures between 0.01 and 0.09 nPa for a number of IMF values. These simulation data are open for the registered users to download the raw data. We have compared the results of these simulations with Hisaki auroral observations.

Initial Validation for the Estimation of Resting-State fMRI Effective Connectivity by a Generalization of the Correlation Approach

PubMed Central

Xu, Nan; Spreng, R. Nathan; Doerschuk, Peter C.

2017-01-01

Resting-state functional MRI (rs-fMRI) is widely used to noninvasively study human brain networks. Network functional connectivity is often estimated by calculating the timeseries correlation between blood-oxygen-level dependent (BOLD) signal from different regions of interest (ROIs). However, standard correlation cannot characterize the direction of information flow between regions. In this paper, we introduce and test a new concept, prediction correlation, to estimate effective connectivity in functional brain networks from rs-fMRI. In this approach, the correlation between two BOLD signals is replaced by a correlation between one BOLD signal and a prediction of this signal via a causal system driven by another BOLD signal. Three validations are described: (1) Prediction correlation performed well on simulated data where the ground truth was known, and outperformed four other methods. (2) On simulated data designed to display the “common driver” problem, prediction correlation did not introduce false connections between non-interacting driven ROIs. (3) On experimental data, prediction correlation recovered the previously identified network organization of human brain. Prediction correlation scales well to work with hundreds of ROIs, enabling it to assess whole brain interregional connectivity at the single subject level. These results provide an initial validation that prediction correlation can capture the direction of information flow and estimate the duration of extended temporal delays in information flow between regions of interest ROIs based on BOLD signal. This approach not only maintains the high sensitivity to network connectivity provided by the correlation analysis, but also performs well in the estimation of causal information flow in the brain. PMID:28559793

Quantum annealing with all-to-all connected nonlinear oscillators

PubMed Central

Puri, Shruti; Andersen, Christian Kraglund; Grimsmo, Arne L.; Blais, Alexandre

2017-01-01

Quantum annealing aims at solving combinatorial optimization problems mapped to Ising interactions between quantum spins. Here, with the objective of developing a noise-resilient annealer, we propose a paradigm for quantum annealing with a scalable network of two-photon-driven Kerr-nonlinear resonators. Each resonator encodes an Ising spin in a robust degenerate subspace formed by two coherent states of opposite phases. A fully connected optimization problem is mapped to local fields driving the resonators, which are connected with only local four-body interactions. We describe an adiabatic annealing protocol in this system and analyse its performance in the presence of photon loss. Numerical simulations indicate substantial resilience to this noise channel, leading to a high success probability for quantum annealing. Finally, we propose a realistic circuit QED implementation of this promising platform for implementing a large-scale quantum Ising machine. PMID:28593952

Deforestation and rainfall recycling in Brazil: Is decreased forest cover connectivity associated with decreased rainfall connectivity?

NASA Astrophysics Data System (ADS)

Adera, S.; Larsen, L.; Levy, M. C.; Thompson, S. E.

2017-12-01

In the Brazilian rainforest-savanna transition zone, deforestation has the potential to significantly affect rainfall by disrupting rainfall recycling, the process by which regional evapotranspiration contributes to regional rainfall. Understanding rainfall recycling in this region is important not only for sustaining Amazon and Cerrado ecosystems, but also for cattle ranching, agriculture, hydropower generation, and drinking water management. Simulations in previous studies suggest complex, scale-dependent interactions between forest cover connectivity and rainfall. For example, the size and distribution of deforested patches has been found to affect rainfall quantity and spatial distribution. Here we take an empirical approach, using the spatial connectivity of rainfall as an indicator of rainfall recycling, to ask: as forest cover connectivity decreased from 1981 - 2015, how did the spatial connectivity of rainfall change in the Brazilian rainforest-savanna transition zone? We use satellite forest cover and rainfall data covering this period of intensive forest cover loss in the region (forest cover from the Hansen Global Forest Change dataset; rainfall from the Climate Hazards Infrared Precipitation with Stations dataset). Rainfall spatial connectivity is quantified using transfer entropy, a metric from information theory, and summarized using network statistics. Networks of connectivity are quantified for paired deforested and non-deforested regions before deforestation (1981-1995) and during/after deforestation (2001-2015). Analyses reveal a decline in spatial connectivity networks of rainfall following deforestation.

Python as a federation tool for GENESIS 3.0.

PubMed

Cornelis, Hugo; Rodriguez, Armando L; Coop, Allan D; Bower, James M

2012-01-01

The GENESIS simulation platform was one of the first broad-scale modeling systems in computational biology to encourage modelers to develop and share model features and components. Supported by a large developer community, it participated in innovative simulator technologies such as benchmarking, parallelization, and declarative model specification and was the first neural simulator to define bindings for the Python scripting language. An important feature of the latest version of GENESIS is that it decomposes into self-contained software components complying with the Computational Biology Initiative federated software architecture. This architecture allows separate scripting bindings to be defined for different necessary components of the simulator, e.g., the mathematical solvers and graphical user interface. Python is a scripting language that provides rich sets of freely available open source libraries. With clean dynamic object-oriented designs, they produce highly readable code and are widely employed in specialized areas of software component integration. We employ a simplified wrapper and interface generator to examine an application programming interface and make it available to a given scripting language. This allows independent software components to be 'glued' together and connected to external libraries and applications from user-defined Python or Perl scripts. We illustrate our approach with three examples of Python scripting. (1) Generate and run a simple single-compartment model neuron connected to a stand-alone mathematical solver. (2) Interface a mathematical solver with GENESIS 3.0 to explore a neuron morphology from either an interactive command-line or graphical user interface. (3) Apply scripting bindings to connect the GENESIS 3.0 simulator to external graphical libraries and an open source three dimensional content creation suite that supports visualization of models based on electron microscopy and their conversion to computational models. Employed in this way, the stand-alone software components of the GENESIS 3.0 simulator provide a framework for progressive federated software development in computational neuroscience.

Python as a Federation Tool for GENESIS 3.0

PubMed Central

Cornelis, Hugo; Rodriguez, Armando L.; Coop, Allan D.; Bower, James M.

2012-01-01

The GENESIS simulation platform was one of the first broad-scale modeling systems in computational biology to encourage modelers to develop and share model features and components. Supported by a large developer community, it participated in innovative simulator technologies such as benchmarking, parallelization, and declarative model specification and was the first neural simulator to define bindings for the Python scripting language. An important feature of the latest version of GENESIS is that it decomposes into self-contained software components complying with the Computational Biology Initiative federated software architecture. This architecture allows separate scripting bindings to be defined for different necessary components of the simulator, e.g., the mathematical solvers and graphical user interface. Python is a scripting language that provides rich sets of freely available open source libraries. With clean dynamic object-oriented designs, they produce highly readable code and are widely employed in specialized areas of software component integration. We employ a simplified wrapper and interface generator to examine an application programming interface and make it available to a given scripting language. This allows independent software components to be ‘glued’ together and connected to external libraries and applications from user-defined Python or Perl scripts. We illustrate our approach with three examples of Python scripting. (1) Generate and run a simple single-compartment model neuron connected to a stand-alone mathematical solver. (2) Interface a mathematical solver with GENESIS 3.0 to explore a neuron morphology from either an interactive command-line or graphical user interface. (3) Apply scripting bindings to connect the GENESIS 3.0 simulator to external graphical libraries and an open source three dimensional content creation suite that supports visualization of models based on electron microscopy and their conversion to computational models. Employed in this way, the stand-alone software components of the GENESIS 3.0 simulator provide a framework for progressive federated software development in computational neuroscience. PMID:22276101

Approximating natural connectivity of scale-free networks based on largest eigenvalue

NASA Astrophysics Data System (ADS)

Tan, S.-Y.; Wu, J.; Li, M.-J.; Lu, X.

2016-06-01

It has been recently proposed that natural connectivity can be used to efficiently characterize the robustness of complex networks. The natural connectivity has an intuitive physical meaning and a simple mathematical formulation, which corresponds to an average eigenvalue calculated from the graph spectrum. However, as a network model close to the real-world system that widely exists, the scale-free network is found difficult to obtain its spectrum analytically. In this article, we investigate the approximation of natural connectivity based on the largest eigenvalue in both random and correlated scale-free networks. It is demonstrated that the natural connectivity of scale-free networks can be dominated by the largest eigenvalue, which can be expressed asymptotically and analytically to approximate natural connectivity with small errors. Then we show that the natural connectivity of random scale-free networks increases linearly with the average degree given the scaling exponent and decreases monotonically with the scaling exponent given the average degree. Moreover, it is found that, given the degree distribution, the more assortative a scale-free network is, the more robust it is. Experiments in real networks validate our methods and results.

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

Investigation related to hydrogen isotopes separation by cryogenic distillation

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

Bornea, A.; Zamfirache, M.; Stefanescu, I.

2008-07-15

Research conducted in the last fifty years has shown that one of the most efficient techniques of removing tritium from the heavy water used as moderator and coolant in CANDU reactors (as that operated at Cernavoda (Romania)) is hydrogen cryogenic distillation. Designing and implementing the concept of cryogenic distillation columns require experiments to be conducted as well as computer simulations. Particularly, computer simulations are of great importance when designing and evaluating the performances of a column or a series of columns. Experimental data collected from laboratory work will be used as input for computer simulations run at larger scale (formore » The Pilot Plant for Tritium and Deuterium Separation) in order to increase the confidence in the simulated results. Studies carried out were focused on the following: - Quantitative analyses of important parameters such as the number of theoretical plates, inlet area, reflux flow, flow-rates extraction, working pressure, etc. - Columns connected in series in such a way to fulfil the separation requirements. Experiments were carried out on a laboratory-scale installation to investigate the performance of contact elements with continuous packing. The packing was manufactured in our institute. (authors)« less

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.

NIMROD simulations and physics assessment of possible designs for a next generation Steady Inductive Helicity Injection HIT device

NASA Astrophysics Data System (ADS)

Penna, James; Morgan, Kyle; Grubb, Isaac; Jarboe, Thomas

2017-10-01

The Helicity Injected Torus - Steady Inductive 3 (HIT-SI3) experiment forms and maintains spheromaks via Steady Inductive Helicity Injection (SIHI) using discrete injectors that inject magnetic helicity via a non-axisymmetric perturbation and drive toroidally symmetric current. Newer designs for larger SIHI-driven spheromaks incorporate a set of injectors connected to a single external manifold to allow more freedom for the toroidal structure of the applied perturbation. Simulations have been carried out using the NIMROD code to assess the effectiveness of various imposed mode structures and injector schema in driving current via Imposed Dynamo Current Drive (IDCD). The results are presented here for varying flux conserver shapes on a device approximately 1.5 times larger than the current HIT-SI3 experiment. The imposed mode structures and spectra of simulated spheromaks are analyzed in order to examine magnetic structure and stability and determine an optimal regime for IDCD sustainment in a large device. The development of scaling laws for manifold operation is also presented, and simulation results are analyzed and assessed as part of the development path for the large scale device.

A robust and scalable neuromorphic communication system by combining synaptic time multiplexing and MIMO-OFDM.

PubMed

Srinivasa, Narayan; Zhang, Deying; Grigorian, Beayna

2014-03-01

This paper describes a novel architecture for enabling robust and efficient neuromorphic communication. The architecture combines two concepts: 1) synaptic time multiplexing (STM) that trades space for speed of processing to create an intragroup communication approach that is firing rate independent and offers more flexibility in connectivity than cross-bar architectures and 2) a wired multiple input multiple output (MIMO) communication with orthogonal frequency division multiplexing (OFDM) techniques to enable a robust and efficient intergroup communication for neuromorphic systems. The MIMO-OFDM concept for the proposed architecture was analyzed by simulating large-scale spiking neural network architecture. Analysis shows that the neuromorphic system with MIMO-OFDM exhibits robust and efficient communication while operating in real time with a high bit rate. Through combining STM with MIMO-OFDM techniques, the resulting system offers a flexible and scalable connectivity as well as a power and area efficient solution for the implementation of very large-scale spiking neural architectures in hardware.

Multi-scale dynamics and relaxation of a tethered membrane in a solvent by Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Pandey, Ras; Anderson, Kelly; Farmer, Barry

2006-03-01

A tethered membrane modeled by a flexible sheet dissipates entropy as it wrinkles and crumples. Nodes of a coarse grained membrane are connected via multiple pathways for dynamical modes to propagate. We consider a sheet with nodes connected by fluctuating bonds on a cubic lattice. The empty lattice sites constitute an effective solvent medium via node-solvent interaction. Each node execute its stochastic motion with the Metropolis algorithm subject to bond fluctuations, excluded volume constraints, and interaction energy. Dynamics and conformation of the sheet are examined at a low and a high temperature with attractive and repulsive node-node interactions for the contrast in an attractive solvent medium. Variations of the mean square displacement of the center node of the sheet and that of its center of mass with the time steps are examined in detail which show different power-law motion from short to long time regimes. Relaxation of the gyration radius and scaling of its asymptotic value with the molecular weight are examined.

JDFTx: Software for joint density-functional theory

DOE PAGES

Sundararaman, Ravishankar; Letchworth-Weaver, Kendra; Schwarz, Kathleen A.; ...

2017-11-14

Density-functional theory (DFT) has revolutionized computational prediction of atomic-scale properties from first principles in physics, chemistry and materials science. Continuing development of new methods is necessary for accurate predictions of new classes of materials and properties, and for connecting to nano- and mesoscale properties using coarse-grained theories. JDFTx is a fully-featured open-source electronic DFT software designed specifically to facilitate rapid development of new theories, models and algorithms. Using an algebraic formulation as an abstraction layer, compact C++11 code automatically performs well on diverse hardware including GPUs (Graphics Processing Units). This code hosts the development of joint density-functional theory (JDFT) thatmore » combines electronic DFT with classical DFT and continuum models of liquids for first-principles calculations of solvated and electrochemical systems. In addition, the modular nature of the code makes it easy to extend and interface with, facilitating the development of multi-scale toolkits that connect to ab initio calculations, e.g. photo-excited carrier dynamics combining electron and phonon calculations with electromagnetic simulations.« less

JDFTx: Software for joint density-functional theory

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

Sundararaman, Ravishankar; Letchworth-Weaver, Kendra; Schwarz, Kathleen A.

Density-functional theory (DFT) has revolutionized computational prediction of atomic-scale properties from first principles in physics, chemistry and materials science. Continuing development of new methods is necessary for accurate predictions of new classes of materials and properties, and for connecting to nano- and mesoscale properties using coarse-grained theories. JDFTx is a fully-featured open-source electronic DFT software designed specifically to facilitate rapid development of new theories, models and algorithms. Using an algebraic formulation as an abstraction layer, compact C++11 code automatically performs well on diverse hardware including GPUs (Graphics Processing Units). This code hosts the development of joint density-functional theory (JDFT) thatmore » combines electronic DFT with classical DFT and continuum models of liquids for first-principles calculations of solvated and electrochemical systems. In addition, the modular nature of the code makes it easy to extend and interface with, facilitating the development of multi-scale toolkits that connect to ab initio calculations, e.g. photo-excited carrier dynamics combining electron and phonon calculations with electromagnetic simulations.« less

A Local to National Scale Catchment Model Simulation Framework for Hydrological Predictions and Impact Assessments Under Uncertainty

NASA Astrophysics Data System (ADS)

Freer, Jim; Coxon, Gemma; Quinn, Niall; Dunne, Toby; Lane, Rosie; Bates, Paul; Wagener, Thorsten; Woods, Ross; Neal, Jeff; Howden, Nicholas; Musuuza, Jude

2017-04-01

There is a huge challenge in developing hydrological model structures that can be used for hypothesis testing, prediction, impact assessment and risk analyses over a wide range of spatial scales. There are many reasons why this is the case, from computational demands, to how we define and characterize different features and pathway connectivities in the landscape, that differ depending on the objectives of the study. However there is certainly a need more than ever to explore the trade-offs between the complexity of modelling applied (i.e. spatial discretization, levels of process representation, complexity of landscape representation) compared to the benefits realized in terms of predictive capability and robustness of these predictions during hydrological extremes and during change. Furthermore, there is a further balance, particularly associated with prediction uncertainties, in that it is not desirable to have modelling systems that are too complex compared to the observed data that would ever be available to apply them. This is particularly the case when models are applied to quantify national impact assessments, especially if these are based on validation assessments from smaller more detailed case studies. Therefore the hydrological community needs modelling tools and approaches that enable these trade-offs to be explored and to understand the level of representation needed in models to be 'fit-for-purpose' for a given application. This paper presents a catchment scale national modelling framework based on Dynamic-TOPMODEL specifically setup to fulfil these aims. A key component of the modelling framework is it's structural flexibility, as is the ability to assess model outputs using Monte Carlo simulation techniques. The model build has been automated to work at any spatial scale to the national scale, and within that to control the level of spatial discretisation and connectivity of locally accounted landscape elements in the form of hydrological response units (HRU's). This allows for the explicit consideration of spatial rainfall fields, landscape, soils and geological attributes and the spatial connectivity of hydrological flow pathways to explore what level of modelling complexity we need for different prediction problems. We shall present this framework and show how it can be used in flood and drought risk analyses as well as include attributes and features within the landscape to explore societal and climate impacts effectively within an uncertainty analyses framework.

Tropical Cyclone Activity in the High-Resolution Community Earth System Model and the Impact of Ocean Coupling

NASA Astrophysics Data System (ADS)

Li, Hui; Sriver, Ryan L.

2018-01-01

High-resolution Atmosphere General Circulation Models (AGCMs) are capable of directly simulating realistic tropical cyclone (TC) statistics, providing a promising approach for TC-climate studies. Active air-sea coupling in a coupled model framework is essential to capturing TC-ocean interactions, which can influence TC-climate connections on interannual to decadal time scales. Here we investigate how the choices of ocean coupling can affect the directly simulated TCs using high-resolution configurations of the Community Earth System Model (CESM). We performed a suite of high-resolution, multidecadal, global-scale CESM simulations in which the atmosphere (˜0.25° grid spacing) is configured with three different levels of ocean coupling: prescribed climatological sea surface temperature (SST) (ATM), mixed layer ocean (SLAB), and dynamic ocean (CPL). We find that different levels of ocean coupling can influence simulated TC frequency, geographical distributions, and storm intensity. ATM simulates more storms and higher overall storm intensity than the coupled simulations. It also simulates higher TC track density over the eastern Pacific and the North Atlantic, while TC tracks are relatively sparse within CPL and SLAB for these regions. Storm intensification and the maximum wind speed are sensitive to the representations of local surface flux feedbacks in different coupling configurations. Key differences in storm number and distribution can be attributed to variations in the modeled large-scale climate mean state and variability that arise from the combined effect of intrinsic model biases and air-sea interactions. Results help to improve our understanding about the representation of TCs in high-resolution coupled Earth system models, with important implications for TC-climate applications.

Buckling Causes Nonlinear Dynamics of Filamentous Viruses Driven through Nanopores.

PubMed

McMullen, Angus; de Haan, Hendrick W; Tang, Jay X; Stein, Derek

2018-02-16

Measurements and Langevin dynamics simulations of filamentous viruses driven through solid-state nanopores reveal a superlinear rise in the translocation velocity with driving force. The mobility also scales with the length of the virus in a nontrivial way that depends on the force. These dynamics are consequences of the buckling of the leading portion of a virus as it emerges from the nanopore and is put under compressive stress by the viscous forces it encounters. The leading tip of a buckled virus stalls and this reduces the total viscous drag force. We present a scaling theory that connects the solid mechanics to the nonlinear dynamics of polyelectrolytes translocating nanopores.

Buckling Causes Nonlinear Dynamics of Filamentous Viruses Driven through Nanopores

NASA Astrophysics Data System (ADS)

McMullen, Angus; de Haan, Hendrick W.; Tang, Jay X.; Stein, Derek

2018-02-01

Measurements and Langevin dynamics simulations of filamentous viruses driven through solid-state nanopores reveal a superlinear rise in the translocation velocity with driving force. The mobility also scales with the length of the virus in a nontrivial way that depends on the force. These dynamics are consequences of the buckling of the leading portion of a virus as it emerges from the nanopore and is put under compressive stress by the viscous forces it encounters. The leading tip of a buckled virus stalls and this reduces the total viscous drag force. We present a scaling theory that connects the solid mechanics to the nonlinear dynamics of polyelectrolytes translocating nanopores.

A Science Cloud: OneSpaceNet

NASA Astrophysics Data System (ADS)

Morikawa, Y.; Murata, K. T.; Watari, S.; Kato, H.; Yamamoto, K.; Inoue, S.; Tsubouchi, K.; Fukazawa, K.; Kimura, E.; Tatebe, O.; Shimojo, S.

2010-12-01

Main methodologies of Solar-Terrestrial Physics (STP) so far are theoretical, experimental and observational, and computer simulation approaches. Recently "informatics" is expected as a new (fourth) approach to the STP studies. Informatics is a methodology to analyze large-scale data (observation data and computer simulation data) to obtain new findings using a variety of data processing techniques. At NICT (National Institute of Information and Communications Technology, Japan) we are now developing a new research environment named "OneSpaceNet". The OneSpaceNet is a cloud-computing environment specialized for science works, which connects many researchers with high-speed network (JGN: Japan Gigabit Network). The JGN is a wide-area back-born network operated by NICT; it provides 10G network and many access points (AP) over Japan. The OneSpaceNet also provides with rich computer resources for research studies, such as super-computers, large-scale data storage area, licensed applications, visualization devices (like tiled display wall: TDW), database/DBMS, cluster computers (4-8 nodes) for data processing and communication devices. What is amazing in use of the science cloud is that a user simply prepares a terminal (low-cost PC). Once connecting the PC to JGN2plus, the user can make full use of the rich resources of the science cloud. Using communication devices, such as video-conference system, streaming and reflector servers, and media-players, the users on the OneSpaceNet can make research communications as if they belong to a same (one) laboratory: they are members of a virtual laboratory. The specification of the computer resources on the OneSpaceNet is as follows: The size of data storage we have developed so far is almost 1PB. The number of the data files managed on the cloud storage is getting larger and now more than 40,000,000. What is notable is that the disks forming the large-scale storage are distributed to 5 data centers over Japan (but the storage system performs as one disk). There are three supercomputers allocated on the cloud, one from Tokyo, one from Osaka and the other from Nagoya. One's simulation job data on any supercomputers are saved on the cloud data storage (same directory); it is a kind of virtual computing environment. The tiled display wall has 36 panels acting as one display; the pixel (resolution) size of it is as large as 18000x4300. This size is enough to preview or analyze the large-scale computer simulation data. It also allows us to take a look of multiple (e.g., 100 pictures) on one screen together with many researchers. In our talk we also present a brief report of the initial results using the OneSpaceNet for Global MHD simulations as an example of successful use of our science cloud; (i) Ultra-high time resolution visualization of Global MHD simulations on the large-scale storage and parallel processing system on the cloud, (ii) Database of real-time Global MHD simulation and statistic analyses of the data, and (iii) 3D Web service of Global MHD simulations.

Is Earth F**ked? Dynamical Futility of Global Environmental Management and Possibilities for Sustainability via Direct Action Activism

NASA Astrophysics Data System (ADS)

wErnEr, B.

2012-12-01

Environmental challenges are dynamically generated within the dominant global culture principally by the mismatch between short-time-scale market and political forces driving resource extraction/use and longer-time-scale accommodations of the Earth system to these changes. Increasing resource demand is leading to the development of two-way, nonlinear interactions between human societies and environmental systems that are becoming global in extent, either through globalized markets and other institutions or through coupling to global environmental systems such as climate. These trends are further intensified by dissipation-reducing technological advances in transactions, communication and transport, which suppress emergence of longer-time-scale economic and political levels of description and facilitate long-distance connections, and by predictive environmental modeling, which strengthens human connections to a short-time-scale virtual Earth, and weakens connections to the longer time scales of the actual Earth. Environmental management seeks to steer fast scale economic and political interests of a coupled human-environmental system towards longer-time-scale consideration of benefits and costs by operating within the confines of the dominant culture using a linear, engineering-type connection to the system. Perhaps as evidenced by widespread inability to meaningfully address such global environmental challenges as climate change and soil degradation, nonlinear connections reduce the ability of managers to operate outside coupled human-environmental systems, decreasing their effectiveness in steering towards sustainable interactions and resulting in managers slaved to short-to-intermediate-term interests. In sum, the dynamics of the global coupled human-environmental system within the dominant culture precludes management for stable, sustainable pathways and promotes instability. Environmental direct action, resistance taken from outside the dominant culture, as in protests, blockades and sabotage by indigenous peoples, workers, anarchists and other activist groups, increases dissipation within the coupled system over fast to intermediate scales and pushes for changes in the dominant culture that favor transition to a stable, sustainable attractor. These dynamical relationships are illustrated and explored using a numerical model that simulates the short-, intermediate- and long-time-scale dynamics of the coupled human-environmental system. At fast scales, economic and political interests exploit environmental resources through a maze of environmental management and resistance, guided by virtual Earth predictions. At intermediate scales, managers become slaved to economic and political interests, which adapt to and repress resistance, and resistance is guided by patterns of environmental destruction. At slow scales, resistance interacts with the cultural context, which co-evolves with the environment. The transition from unstable dynamics to sustainability is sensitively dependent on the level of participation in and repression of resistance. Because of their differing impact inside and outside the dominant culture, virtual Earth predictions can either promote or oppose sustainability. Supported by the National Science Foundation, Geomorphology and Land Use Dynamics Program.

Warm dark matter

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

Horiuchi, Shunsaku, E-mail: horiuchi@vt.edu

2016-06-21

The cold dark matter paradigm has been extremely successful in explaining the large-scale structure of the Universe. However, it continues to face issues when confronted by observations on sub-Galactic scales. A major caveat, now being addressed, has been the incomplete treatment of baryon physics. We first summarize the small-scale issues surrounding cold dark matter and discuss the solutions explored by modern state-of-the-art numerical simulations including treatment of baryonic physics. We identify the too big to fail in field galaxies as among the best targets to study modifications to dark matter, and discuss the particular connection with sterile neutrino warm darkmore » matter. We also discuss how the recently detected anomalous 3.55 keV X-ray lines, when interpreted as sterile neutrino dark matter decay, provide a very good description of small-scale observations of the Local Group.« less

Embedding Task-Based Neural Models into a Connectome-Based Model of the Cerebral Cortex

PubMed Central

Ulloa, Antonio; Horwitz, Barry

2016-01-01

A number of recent efforts have used large-scale, biologically realistic, neural models to help understand the neural basis for the patterns of activity observed in both resting state and task-related functional neural imaging data. An example of the former is The Virtual Brain (TVB) software platform, which allows one to apply large-scale neural modeling in a whole brain framework. TVB provides a set of structural connectomes of the human cerebral cortex, a collection of neural processing units for each connectome node, and various forward models that can convert simulated neural activity into a variety of functional brain imaging signals. In this paper, we demonstrate how to embed a previously or newly constructed task-based large-scale neural model into the TVB platform. We tested our method on a previously constructed large-scale neural model (LSNM) of visual object processing that consisted of interconnected neural populations that represent, primary and secondary visual, inferotemporal, and prefrontal cortex. Some neural elements in the original model were “non-task-specific” (NS) neurons that served as noise generators to “task-specific” neurons that processed shapes during a delayed match-to-sample (DMS) task. We replaced the NS neurons with an anatomical TVB connectome model of the cerebral cortex comprising 998 regions of interest interconnected by white matter fiber tract weights. We embedded our LSNM of visual object processing into corresponding nodes within the TVB connectome. Reciprocal connections between TVB nodes and our task-based modules were included in this framework. We ran visual object processing simulations and showed that the TVB simulator successfully replaced the noise generation originally provided by NS neurons; i.e., the DMS tasks performed with the hybrid LSNM/TVB simulator generated equivalent neural and fMRI activity to that of the original task-based models. Additionally, we found partial agreement between the functional connectivities using the hybrid LSNM/TVB model and the original LSNM. Our framework thus presents a way to embed task-based neural models into the TVB platform, enabling a better comparison between empirical and computational data, which in turn can lead to a better understanding of how interacting neural populations give rise to human cognitive behaviors. PMID:27536235

Multi-thread parallel algorithm for reconstructing 3D large-scale porous structures

NASA Astrophysics Data System (ADS)

Ju, Yang; Huang, Yaohui; Zheng, Jiangtao; Qian, Xu; Xie, Heping; Zhao, Xi

2017-04-01

Geomaterials inherently contain many discontinuous, multi-scale, geometrically irregular pores, forming a complex porous structure that governs their mechanical and transport properties. The development of an efficient reconstruction method for representing porous structures can significantly contribute toward providing a better understanding of the governing effects of porous structures on the properties of porous materials. In order to improve the efficiency of reconstructing large-scale porous structures, a multi-thread parallel scheme was incorporated into the simulated annealing reconstruction method. In the method, four correlation functions, which include the two-point probability function, the linear-path functions for the pore phase and the solid phase, and the fractal system function for the solid phase, were employed for better reproduction of the complex well-connected porous structures. In addition, a random sphere packing method and a self-developed pre-conditioning method were incorporated to cast the initial reconstructed model and select independent interchanging pairs for parallel multi-thread calculation, respectively. The accuracy of the proposed algorithm was evaluated by examining the similarity between the reconstructed structure and a prototype in terms of their geometrical, topological, and mechanical properties. Comparisons of the reconstruction efficiency of porous models with various scales indicated that the parallel multi-thread scheme significantly shortened the execution time for reconstruction of a large-scale well-connected porous model compared to a sequential single-thread procedure.

Atomistic Simulation of Single Asperity Contact

NASA Astrophysics Data System (ADS)

Philip; Kromer; Marder, Michael

2003-03-01

In the standard (Bowden and Tabor) model of friction, the macroscopic behavior of sliding results from the deformation of microscopic asperities in contact. A recent idea instead extracts macroscopic friction from the aggregate behavior of traveling, self-healing interfacial cracks: certain families of cracks are found to be mathematically forbidden, and the envelope of allowed cracks dictates the familiar Coulomb law of friction. To explore the connection between the new and traditional pictures of friction, we conducted molecular dynamics (MD) simulations of single-asperity contact subjected to an oscillatory sliding force -- a geometry important for the problem of fretting (damage due to small-scale vibratory contact). Our simulations reveal the importance of traveling interface cracks to the dynamics of slip at the interface, and illuminate the dynamics of crack initiation and suppression.

A Multi-Scale Integrated Approach to Representing Watershed Systems: Significance and Challenges

NASA Astrophysics Data System (ADS)

Kim, J.; Ivanov, V. Y.; Katopodes, N.

2013-12-01

A range of processes associated with supplying services and goods to human society originate at the watershed level. Predicting watershed response to forcing conditions has been of high interest to many practical societal problems, however, remains challenging due to two significant properties of the watershed systems, i.e., connectivity and non-linearity. Connectivity implies that disturbances arising at any larger scale will necessarily propagate and affect local-scale processes; their local effects consequently influence other processes, and often convey nonlinear relationships. Physically-based, process-scale modeling is needed to approach the understanding and proper assessment of non-linear effects between the watershed processes. We have developed an integrated model simulating hydrological processes, flow dynamics, erosion and sediment transport, tRIBS-OFM-HRM (Triangulated irregular network - based Real time Integrated Basin Simulator-Overland Flow Model-Hairsine and Rose Model). This coupled model offers the advantage of exploring the hydrological effects of watershed physical factors such as topography, vegetation, and soil, as well as their feedback mechanisms. Several examples investigating the effects of vegetation on flow movement, the role of soil's substrate on sediment dynamics, and the driving role of topography on morphological processes are illustrated. We show how this comprehensive modeling tool can help understand interconnections and nonlinearities of the physical system, e.g., how vegetation affects hydraulic resistance depending on slope, vegetation cover fraction, discharge, and bed roughness condition; how the soil's substrate condition impacts erosion processes with an non-unique characteristic at the scale of a zero-order catchment; and how topographic changes affect spatial variations of morphologic variables. Due to feedback and compensatory nature of mechanisms operating in different watershed compartments, our conclusion is that a key to representing watershed systems lies in an integrated, interdisciplinary approach, whereby a physically-based model is used for assessments/evaluations associated with future changes in landuse, climate, and ecosystems.

Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balance

NASA Astrophysics Data System (ADS)

Tang, G.; Bartlein, P. J.

2012-01-01

Water balance models of simple structure are easier to grasp and more clearly connect cause and effect than models of complex structure. Such models are essential for studying large spatial scale land surface water balance in the context of climate and land cover change, both natural and anthropogenic. This study aims to (i) develop a large spatial scale water balance model by modifying a dynamic global vegetation model (DGVM), and (ii) test the model's performance in simulating actual evapotranspiration (ET), soil moisture and surface runoff for the coterminous United States (US). Toward these ends, we first introduced development of the "LPJ-Hydrology" (LH) model by incorporating satellite-based land covers into the Lund-Potsdam-Jena (LPJ) DGVM instead of dynamically simulating them. We then ran LH using historical (1982-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells. The simulated ET, soil moisture and surface runoff were compared to existing sets of observed or simulated data for the US. The results indicated that LH captures well the variation of monthly actual ET (R2 = 0.61, p < 0.01) in the Everglades of Florida over the years 1996-2001. The modeled monthly soil moisture for Illinois of the US agrees well (R2 = 0.79, p < 0.01) with the observed over the years 1984-2001. The modeled monthly stream flow for most 12 major rivers in the US is consistent R2 > 0.46, p < 0.01; Nash-Sutcliffe Coefficients >0.52) with observed values over the years 1982-2006, respectively. The modeled spatial patterns of annual ET and surface runoff are in accordance with previously published data. Compared to its predecessor, LH simulates better monthly stream flow in winter and early spring by incorporating effects of solar radiation on snowmelt. Overall, this study proves the feasibility of incorporating satellite-based land-covers into a DGVM for simulating large spatial scale land surface water balance. LH developed in this study should be a useful tool for studying effects of climate and land cover change on land surface hydrology at large spatial scales.

Multiscale modeling of fluid flow and mass transport

NASA Astrophysics Data System (ADS)

Masuoka, K.; Yamamoto, H.; Bijeljic, B.; Lin, Q.; Blunt, M. J.

2017-12-01

In recent years, there are some reports on a simulation of fluid flow in pore spaces of rocks using Navier-Stokes equations. These studies mostly adopt a X-ray CT to create 3-D numerical grids of the pores in micro-scale. However, results may be of low accuracy when the rock has a large pore size distribution, because pores, whose size is smaller than resolution of the X-ray CT may be neglected. We recently found out by tracer tests in a laboratory using a brine saturated Ryukyu limestone and inject fresh water that a decrease of chloride concentration took longer time. This phenomenon can be explained due to weak connectivity of the porous networks. Therefore, it is important to simulate entire pore spaces even those of very small sizes in which diffusion is dominant. We have developed a new methodology for multi-level modeling for pore scale fluid flow in porous media. The approach is to combine pore-scale analysis with Darcy-flow analysis using two types of X-ray CT images in different resolutions. Results of the numerical simulations showed a close match with the experimental results. The proposed methodology is an enhancement for analyzing mass transport and flow phenomena in rocks with complicated pore structure.

Slow transition of the Osborne Reynolds pipe flow: A direct numerical simulation study.

NASA Astrophysics Data System (ADS)

Wu, Xiaohua; Moin, Parviz; Adrian, Ronald J.; Baltzer, Jon R.

2015-11-01

Osborne Reynolds' pipe transition experiment marked the onset of fundamental turbulence research, yet the precise dynamics carrying the laminar state to fully-developed turbulence has been quite elusive. Our spatially-developing direct numerical simulation of this problem reveals interesting connections with theory and experiments. In particular, during transition the energy norms of localized, weakly finite inlet perturbations grow exponentially, rather than algebraically, with axial distance, in agreement with the edge-state based temporal results of Schneider et al. (PRL, 034502, 2007). When inlet disturbance is the core region, helical vortex filaments evolve into large-scale reverse hairpin vortices. The interaction of these reverse hairpins among themselves or with the near-wall flow produces small-scale hairpin packets. When inlet disturbance is near the wall, optimally positioned quasi-spanwise structure is stretched into a Lambda vortex, which grows into a turbulent spot of concentrated small-scale hairpin vortices. Waves of hairpin-like structures were observed by Mullin (Ann. Rev. Fluid Mech., Vol.43, 2011) in their experiment with very weak blowing and suction. This vortex dynamics is broadly analogous to that in the boundary layer bypass transition and in the secondary instability and breakdown stage of natural transition. Further details of our simulation are reported in Wu et al. (PNAS, 1509451112, 2015).

Laboratory simulations show diabatic heating drives cumulus-cloud evolution and entrainment

PubMed Central

Narasimha, Roddam; Diwan, Sourabh Suhas; Duvvuri, Subrahmanyam; Sreenivas, K. R.; Bhat, G. S.

2011-01-01

Clouds are the largest source of uncertainty in climate science, and remain a weak link in modeling tropical circulation. A major challenge is to establish connections between particulate microphysics and macroscale turbulent dynamics in cumulus clouds. Here we address the issue from the latter standpoint. First we show how to create bench-scale flows that reproduce a variety of cumulus-cloud forms (including two genera and three species), and track complete cloud life cycles—e.g., from a “cauliflower” congestus to a dissipating fractus. The flow model used is a transient plume with volumetric diabatic heating scaled dynamically to simulate latent-heat release from phase changes in clouds. Laser-based diagnostics of steady plumes reveal Riehl–Malkus type protected cores. They also show that, unlike the constancy implied by early self-similar plume models, the diabatic heating raises the Taylor entrainment coefficient just above cloud base, depressing it at higher levels. This behavior is consistent with cloud-dilution rates found in recent numerical simulations of steady deep convection, and with aircraft-based observations of homogeneous mixing in clouds. In-cloud diabatic heating thus emerges as the key driver in cloud development, and could well provide a major link between microphysics and cloud-scale dynamics. PMID:21918112

Transduction between worlds: using virtual and mixed reality for earth and planetary science

NASA Astrophysics Data System (ADS)

Hedley, N.; Lochhead, I.; Aagesen, S.; Lonergan, C. D.; Benoy, N.

2017-12-01

Virtual reality (VR) and augmented reality (AR) have the potential to transform the way we visualize multidimensional geospatial datasets in support of geoscience research, exploration and analysis. The beauty of virtual environments is that they can be built at any scale, users can view them at many levels of abstraction, move through them in unconventional ways, and experience spatial phenomena as if they had superpowers. Similarly, augmented reality allows you to bring the power of virtual 3D data visualizations into everyday spaces. Spliced together, these interface technologies hold incredible potential to support 21st-century geoscience. In my ongoing research, my team and I have made significant advances to connect data and virtual simulations with real geographic spaces, using virtual environments, geospatial augmented reality and mixed reality. These research efforts have yielded new capabilities to connect users with spatial data and phenomena. These innovations include: geospatial x-ray vision; flexible mixed reality; augmented 3D GIS; situated augmented reality 3D simulations of tsunamis and other phenomena interacting with real geomorphology; augmented visual analytics; and immersive GIS. These new modalities redefine the ways in which we can connect digital spaces of spatial analysis, simulation and geovisualization, with geographic spaces of data collection, fieldwork, interpretation and communication. In a way, we are talking about transduction between real and virtual worlds. Taking a mixed reality approach to this, we can link real and virtual worlds. This paper presents a selection of our 3D geovisual interface projects in terrestrial, coastal, underwater and other environments. Using rigorous applied geoscience data, analyses and simulations, our research aims to transform the novelty of virtual and augmented reality interface technologies into game-changing mixed reality geoscience.

Bridging the scales in atmospheric composition simulations using a nudging technique

NASA Astrophysics Data System (ADS)

D'Isidoro, Massimo; Maurizi, Alberto; Russo, Felicita; Tampieri, Francesco

2010-05-01

Studying the interaction between climate and anthropogenic activities, specifically those concentrated in megacities/hot spots, requires the description of processes in a very wide range of scales from local, where anthropogenic emissions are concentrated to global where we are interested to study the impact of these sources. The description of all the processes at all scales within the same numerical implementation is not feasible because of limited computer resources. Therefore, different phenomena are studied by means of different numerical models that can cover different range of scales. The exchange of information from small to large scale is highly non-trivial though of high interest. In fact uncertainties in large scale simulations are expected to receive large contribution from the most polluted areas where the highly inhomogeneous distribution of sources connected to the intrinsic non-linearity of the processes involved can generate non negligible departures between coarse and fine scale simulations. In this work a new method is proposed and investigated in a case study (August 2009) using the BOLCHEM model. Monthly simulations at coarse (0.5° European domain, run A) and fine (0.1° Central Mediterranean domain, run B) horizontal resolution are performed using the coarse resolution as boundary condition for the fine one. Then another coarse resolution run (run C) is performed, in which the high resolution fields remapped on to the coarse grid are used to nudge the concentrations on the Po Valley area. The nudging is applied to all gas and aerosol species of BOLCHEM. Averaged concentrations and variances over Po Valley and other selected areas for O3 and PM are computed. It is observed that although the variance of run B is markedly larger than that of run A, the variance of run C is smaller because the remapping procedure removes large portion of variance from run B fields. Mean concentrations show some differences depending on species: in general mean values of run C lie between run A and run B. A propagation of the signal outside the nudging region is observed, and is evaluated in terms of differences between coarse resolution (with and without nudging) and fine resolution simulations.

Impact of the 1997-1998 El-Nino of Regional Hydrology

NASA Technical Reports Server (NTRS)

Lakshmi, Venkataraman; Susskind, Joel

1998-01-01

The 1997-1998 El-Nino brought with it a range of severe local-regional hydrological phenomena. Record high temperatures and extremely dry soil conditions in Texas is an example of this regional effect. The El-Nino and La-Nina change the continental weather patterns considerably. However, connections between continental weather anomalies and regional or local anomalies have not been established to a high degree of confidence. There are several unique features of the recent El-Nino and La-Nina. Due to the recognition of the present El-Nino well in advance, there have been several coupled model studies on global and regional scales. Secondly, there is a near real-time monitoring of the situation using data from satellite sensors, namely, SeaWIFS, TOVS, AVHRR and GOES. Both observations and modeling characterize the large scale features of this El-Nino fairly well. However the connection to the local and regional hydrological phenomenon still needs to be made. This paper will use satellite observations and analysis data to establish a relation between local hydrology and large scale weather patterns. This will be the first step in using satellite data to perform regional hydrological simulations of surface temperature and soil moisture.

Coarse-coded higher-order neural networks for PSRI object recognition. [position, scale, and rotation invariant

NASA Technical Reports Server (NTRS)

Spirkovska, Lilly; Reid, Max B.

1993-01-01

A higher-order neural network (HONN) can be designed to be invariant to changes in scale, translation, and inplane rotation. Invariances are built directly into the architecture of a HONN and do not need to be learned. Consequently, fewer training passes and a smaller training set are required to learn to distinguish between objects. The size of the input field is limited, however, because of the memory required for the large number of interconnections in a fully connected HONN. By coarse coding the input image, the input field size can be increased to allow the larger input scenes required for practical object recognition problems. We describe a coarse coding technique and present simulation results illustrating its usefulness and its limitations. Our simulations show that a third-order neural network can be trained to distinguish between two objects in a 4096 x 4096 pixel input field independent of transformations in translation, in-plane rotation, and scale in less than ten passes through the training set. Furthermore, we empirically determine the limits of the coarse coding technique in the object recognition domain.

Nano Liquid Crystal Droplet Impact on Solid Surfaces

NASA Astrophysics Data System (ADS)

Zhang, Rui; de Pablo, Juan; dePablo Team

2015-03-01

Liquid droplet impaction on solid surfaces is an important problem with a wide range of applications in everyday life. Liquid crystals (LCs) are anisotropic liquids whose internal structure gives rise to rich optical and morphological phenomena. In this work we study the liquid crystal droplet impaction on solid surfaces by molecular dynamics simulations. We employ a widely used Gay-Berne model to describe the elongated liquid crystal molecules and their interactions. Our work shows that, in contrast to isotropic liquids, drop deformation is symmetric unless an instability kicks in, in which case a nano scale liquid crystal droplet exhibits distinct anisotropic spreading modes that do not occur in simple liquids. The drop prefers spreading along the low viscosity direction, but inertia can in some cases overcome that bias. The effects of the director field of the droplet, preferred anchoring direction and the anchoring strength of the wall are investigated. Large scale (0.1 micron) simulations are performed to connect our nano scale results to the experiments. Our studies indicate that LCs could provide an interesting alternative for development of next-generation printing inks.

Construction of Interaction Layer on Socio-Environmental Simulation

NASA Astrophysics Data System (ADS)

Torii, Daisuke; Ishida, Toru

In this study, we propose a method to construct a system based on a legacy socio-environmental simulator which enables to design more realistic interaction models in socio-environmetal simulations. First, to provide a computational model suitable for agent interactions, an interaction layer is constructed and connected from outside of a legacy socio-environmental simulator. Next, to configure the agents interacting ability, connection description for controlling the flow of information in the connection area is provided. As a concrete example, we realized an interaction layer by Q which is a scenario description language and connected it to CORMAS, a socio-envirionmental simulator. Finally, we discuss the capability of our method, using the system, in the Fire-Fighter domain.

Prisoner's dilemma on scale-free networks

NASA Astrophysics Data System (ADS)

Gallos, Lazaros

2005-07-01

In this work, we study via computer simulations the spatial prisoner's dilemma (PD) game for the general case where the distribution of the connections between the individuals playing the game obeys a power law. This distribution has been shown to describe many aspects of social acquaintances, while the PD game is a powerful tool for studying mutual trust and cooperation among individuals. We study this model under different conditions, such as varying degree of connectivity and payoff value. Depending on the exact conditions of the game, we observe a plethora of behaviors for the percentage of cooperating agents. For example, the same network may settle in an equilibrium configuration of either low or high percentage of cooperators, or induce a transition between these two regimes.

Simulations of inorganic-bioorganic interfaces to discover new materials: insights, comparisons to experiment, challenges, and opportunities.

PubMed

Heinz, Hendrik; Ramezani-Dakhel, Hadi

2016-01-21

Natural and man-made materials often rely on functional interfaces between inorganic and organic compounds. Examples include skeletal tissues and biominerals, drug delivery systems, catalysts, sensors, separation media, energy conversion devices, and polymer nanocomposites. Current laboratory techniques are limited to monitor and manipulate assembly on the 1 to 100 nm scale, time-consuming, and costly. Computational methods have become increasingly reliable to understand materials assembly and performance. This review explores the merit of simulations in comparison to experiment at the 1 to 100 nm scale, including connections to smaller length scales of quantum mechanics and larger length scales of coarse-grain models. First, current simulation methods, advances in the understanding of chemical bonding, in the development of force fields, and in the development of chemically realistic models are described. Then, the recognition mechanisms of biomolecules on nanostructured metals, semimetals, oxides, phosphates, carbonates, sulfides, and other inorganic materials are explained, including extensive comparisons between modeling and laboratory measurements. Depending on the substrate, the role of soft epitaxial binding mechanisms, ion pairing, hydrogen bonds, hydrophobic interactions, and conformation effects is described. Applications of the knowledge from simulation to predict binding of ligands and drug molecules to the inorganic surfaces, crystal growth and shape development, catalyst performance, as well as electrical properties at interfaces are examined. The quality of estimates from molecular dynamics and Monte Carlo simulations is validated in comparison to measurements and design rules described where available. The review further describes applications of simulation methods to polymer composite materials, surface modification of nanofillers, and interfacial interactions in building materials. The complexity of functional multiphase materials creates opportunities to further develop accurate force fields, including reactive force fields, and chemically realistic surface models, to enable materials discovery at a million times lower computational cost compared to quantum mechanical methods. The impact of modeling and simulation could further be increased by the advancement of a uniform simulation platform for organic and inorganic compounds across the periodic table and new simulation methods to evaluate system performance in silico.

Analysis of the Flicker Level Produced by a Fixed-Speed Wind Turbine

NASA Astrophysics Data System (ADS)

Suppioni, Vinicius; P. Grilo, Ahda

2013-10-01

In this article, the analysis of the flicker emission during continuous operation of a mid-scale fixed-speed wind turbine connected to a distribution system is presented. Flicker emission is investigated based on simulation results, and the dependence of flicker emission on short-circuit capacity, grid impedance angle, mean wind speed, and wind turbulence is analyzed. The simulations were conducted in different programs in order to provide a more realistic wind emulation and detailed model of mechanical and electrical components of the wind turbine. Such aim is accomplished by using FAST (Fatigue, Aerodynamics, Structures, and Turbulence) to simulate the mechanical parts of the wind turbine, Simulink/MatLab to simulate the electrical system, and TurbSim to obtain the wind model. The results show that, even for a small wind generator, the flicker level can limit the wind power capacity installed in a distribution system.

An Engineering Methodology for Implementing and Testing VLSI (Very Large Scale Integrated) Circuits

DTIC Science & Technology

1989-03-01

the pad frame and associated routing, conducted additional testing. and submitted the finished design effort to MOSIS for manufacturing. Throughout...register bank TSTCON Allows the XNOR circuitry to enter the TEST register bank PADIN Test signal to check operation of the input pad VCC Power connection...MOSSIM II simulation program. but the design offered little observability within the circuit. The initial design used 35 pins of a 40 pin pad frame

Quantifying non-linear dynamics of mass-springs in series oscillators via asymptotic approach

NASA Astrophysics Data System (ADS)

Starosta, Roman; Sypniewska-Kamińska, Grażyna; Awrejcewicz, Jan

2017-05-01

Dynamical regular response of an oscillator with two serially connected springs with nonlinear characteristics of cubic type and governed by a set of differential-algebraic equations (DAEs) is studied. The classical approach of the multiple scales method (MSM) in time domain has been employed and appropriately modified to solve the governing DAEs of two systems, i.e. with one- and two degrees-of-freedom. The approximate analytical solutions have been verified by numerical simulations.

Identifying effective connectivity parameters in simulated fMRI: a direct comparison of switching linear dynamic system, stochastic dynamic causal, and multivariate autoregressive models

PubMed Central

Smith, Jason F.; Chen, Kewei; Pillai, Ajay S.; Horwitz, Barry

2013-01-01

The number and variety of connectivity estimation methods is likely to continue to grow over the coming decade. Comparisons between methods are necessary to prune this growth to only the most accurate and robust methods. However, the nature of connectivity is elusive with different methods potentially attempting to identify different aspects of connectivity. Commonalities of connectivity definitions across methods upon which base direct comparisons can be difficult to derive. Here, we explicitly define “effective connectivity” using a common set of observation and state equations that are appropriate for three connectivity methods: dynamic causal modeling (DCM), multivariate autoregressive modeling (MAR), and switching linear dynamic systems for fMRI (sLDSf). In addition while deriving this set, we show how many other popular functional and effective connectivity methods are actually simplifications of these equations. We discuss implications of these connections for the practice of using one method to simulate data for another method. After mathematically connecting the three effective connectivity methods, simulated fMRI data with varying numbers of regions and task conditions is generated from the common equation. This simulated data explicitly contains the type of the connectivity that the three models were intended to identify. Each method is applied to the simulated data sets and the accuracy of parameter identification is analyzed. All methods perform above chance levels at identifying correct connectivity parameters. The sLDSf method was superior in parameter estimation accuracy to both DCM and MAR for all types of comparisons. PMID:23717258

How does the connectivity of open-framework conglomerates within multi-scale hierarchical fluvial architecture affect oil-sweep efficiency in waterflooding?

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

Gershenzon, Naum I.; Soltanian, Mohamad Reza; Ritzi, Robert W.

Understanding multi-phase fluid flow and transport processes within aquifers, candidate reservoirs for CO 2 sequestration, and petroleum reservoirs requires understanding a diverse set of geologic properties of the aquifer or reservoir, over a wide range of spatial and temporal scales. We focus on multiphase flow dynamics with wetting (e.g., water) and non-wetting (e.g., gas or oil) fluids, with one invading another. This problem is of general interest in a number of fields and is illustrated here by considering the sweep efficiency of oil during a waterflood. Using a relatively fine-resolution grid throughout a relatively large domain in these simulations andmore » probing the results with advanced scientific visualization tools (Reservoir Visualization Analysis [RVA]/ ParaView software) promote a better understanding of how smaller-scale features affect the aggregate behavior at larger scales. We studied the effects on oil-sweep efficiency of the proportion, hierarchical organization, and connectivity of high-permeability open-framework conglomerate (OFC) cross-sets within the multi-scale stratal architecture found in fluvial deposits. We further analyzed oil production rate, water breakthrough time, and spatial and temporal distribution of residual oil saturation. As expected, the effective permeability of the reservoir exhibits large-scale anisotropy created by the organization of OFC cross-sets within unit bars, and the organization of unit bars within compound- bars. As a result, oil-sweep efficiency critically depends on the direction of the pressure gradient. However, contrary to expectations, the total amount of trapped oil due to the effect of capillary trapping does not depend on the magnitude of the pressure gradient within the examined range. Hence the pressure difference between production and injection wells does not affect sweep efficiency; although the spatial distribution of oil remaining in the reservoir depends on this value. Whether or not clusters of connected OFC span the domain affects only the absolute rate of oil production—not sweep efficiency.« less

How does the connectivity of open-framework conglomerates within multi-scale hierarchical fluvial architecture affect oil-sweep efficiency in waterflooding?

DOE PAGES

Gershenzon, Naum I.; Soltanian, Mohamad Reza; Ritzi, Robert W.; ...

2015-10-23

Understanding multi-phase fluid flow and transport processes within aquifers, candidate reservoirs for CO 2 sequestration, and petroleum reservoirs requires understanding a diverse set of geologic properties of the aquifer or reservoir, over a wide range of spatial and temporal scales. We focus on multiphase flow dynamics with wetting (e.g., water) and non-wetting (e.g., gas or oil) fluids, with one invading another. This problem is of general interest in a number of fields and is illustrated here by considering the sweep efficiency of oil during a waterflood. Using a relatively fine-resolution grid throughout a relatively large domain in these simulations andmore » probing the results with advanced scientific visualization tools (Reservoir Visualization Analysis [RVA]/ ParaView software) promote a better understanding of how smaller-scale features affect the aggregate behavior at larger scales. We studied the effects on oil-sweep efficiency of the proportion, hierarchical organization, and connectivity of high-permeability open-framework conglomerate (OFC) cross-sets within the multi-scale stratal architecture found in fluvial deposits. We further analyzed oil production rate, water breakthrough time, and spatial and temporal distribution of residual oil saturation. As expected, the effective permeability of the reservoir exhibits large-scale anisotropy created by the organization of OFC cross-sets within unit bars, and the organization of unit bars within compound- bars. As a result, oil-sweep efficiency critically depends on the direction of the pressure gradient. However, contrary to expectations, the total amount of trapped oil due to the effect of capillary trapping does not depend on the magnitude of the pressure gradient within the examined range. Hence the pressure difference between production and injection wells does not affect sweep efficiency; although the spatial distribution of oil remaining in the reservoir depends on this value. Whether or not clusters of connected OFC span the domain affects only the absolute rate of oil production—not sweep efficiency.« less

Inflight IFR procedures simulator

NASA Technical Reports Server (NTRS)

Parker, L. C. (Inventor)

1984-01-01

An inflight IFR procedures simulator for generating signals and commands to conventional instruments provided in an airplane is described. The simulator includes a signal synthesizer which generates predetermined simulated signals corresponding to signals normally received from remote sources upon being activated. A computer is connected to the signal synthesizer and causes the signal synthesizer to produce simulated signals responsive to programs fed into the computer. A switching network is connected to the signal synthesizer, the antenna of the aircraft, and navigational instruments and communication devices for selectively connecting instruments and devices to the synthesizer and disconnecting the antenna from the navigational instruments and communication device. Pressure transducers are connected to the altimeter and speed indicator for supplying electrical signals to the computer indicating the altitude and speed of the aircraft. A compass is connected for supply electrical signals for the computer indicating the heading of the airplane. The computer upon receiving signals from the pressure transducer and compass, computes the signals that are fed to the signal synthesizer which, in turn, generates simulated navigational signals.

Impact of spatially correlated pore-scale heterogeneity on drying porous media

NASA Astrophysics Data System (ADS)

Borgman, Oshri; Fantinel, Paolo; Lühder, Wieland; Goehring, Lucas; Holtzman, Ran

2017-07-01

We study the effect of spatially-correlated heterogeneity on isothermal drying of porous media. We combine a minimal pore-scale model with microfluidic experiments with the same pore geometry. Our simulated drying behavior compares favorably with experiments, considering the large sensitivity of the emergent behavior to the uncertainty associated with even small manufacturing errors. We show that increasing the correlation length in particle sizes promotes preferential drying of clusters of large pores, prolonging liquid connectivity and surface wetness and thus higher drying rates for longer periods. Our findings improve our quantitative understanding of how pore-scale heterogeneity impacts drying, which plays a role in a wide range of processes ranging from fuel cells to curing of paints and cements to global budgets of energy, water and solutes in soils.

Experiments and Dynamic Finite Element Analysis of a Wire-Rope Rockfall Protective Fence

NASA Astrophysics Data System (ADS)

Tran, Phuc Van; Maegawa, Koji; Fukada, Saiji

2013-09-01

The imperative need to protect structures in mountainous areas against rockfall has led to the development of various protection methods. This study introduces a new type of rockfall protection fence made of posts, wire ropes, wire netting and energy absorbers. The performance of this rock fence was verified in both experiments and dynamic finite element analysis. In collision tests, a reinforced-concrete block rolled down a natural slope and struck the rock fence at the end of the slope. A specialized system of measuring instruments was employed to accurately measure the acceleration of the block without cable connection. In particular, the performance of two energy absorbers, which contribute also to preventing wire ropes from breaking, was investigated to determine the best energy absorber. In numerical simulation, a commercial finite element code having explicit dynamic capabilities was employed to create models of the two full-scale tests. To facilitate simulation, certain simplifying assumptions for mechanical data of each individual component of the rock fence and geometrical data of the model were adopted. Good agreement between numerical simulation and experimental data validated the numerical simulation. Furthermore, the results of numerical simulation helped highlight limitations of the testing method. The results of numerical simulation thus provide a deeper understanding of the structural behavior of individual components of the rock fence during rockfall impact. More importantly, numerical simulations can be used not only as supplements to or substitutes for full-scale tests but also in parametric study and design.

Design and Analysis of Windmill Simulation and Pole by Solidwork Program

NASA Astrophysics Data System (ADS)

Mulyana, Tatang; Sebayang, Darwin; R, Akmal Muamar. D.; A, Jauharah H. D.; Yahya Shomit, M.

2018-03-01

The Indonesian state of archipelago has great wind energy potential. For micro-scale power generation, the energy obtained from the windmill can be connected directly to the electrical load and can be used without problems. However, for macro-scale power generation, problems will arise such as the design of vane shapes, there should be a simulation and an accurate experiment to produce blades with a special shape that can capture wind energy. In addition, daily and yearly wind and wind rate calculations are also required to ensure the best latitude and longitude positions for building windmills. This paper presents a solution to solve the problem of how to produce a windmill which in the builder is very practical and very mobile can be moved its location. Before a windmill prototype is built it should have obtained the best windmill design result. Therefore, the simulation of the designed windmill is of crucial importance. Solid simulation express is a tool that serves to generate simulation of a design. Some factors that can affect a design result include the power part and the rest part of the part, material selection, the load is given, the security of the design power made, and changes in shape due to treat the load given to the design made. In this paper, static and thermal simulations of windmills have been designed. Based on the simulation result on the designed windmill, it shows that the design has been made very satisfactory so that it can be done prototyping fabrication process.

From Sub-basin to Grid Scale Soil Moisture Disaggregation in SMART, A Semi-distributed Hydrologic Modeling Framework

NASA Astrophysics Data System (ADS)

Ajami, H.; Sharma, A.

2016-12-01

A computationally efficient, semi-distributed hydrologic modeling framework is developed to simulate water balance at a catchment scale. The Soil Moisture and Runoff simulation Toolkit (SMART) is based upon the delineation of contiguous and topologically connected Hydrologic Response Units (HRUs). In SMART, HRUs are delineated using thresholds obtained from topographic and geomorphic analysis of a catchment, and simulation elements are distributed cross sections or equivalent cross sections (ECS) delineated in first order sub-basins. ECSs are formulated by aggregating topographic and physiographic properties of the part or entire first order sub-basins to further reduce computational time in SMART. Previous investigations using SMART have shown that temporal dynamics of soil moisture are well captured at a HRU level using the ECS delineation approach. However, spatial variability of soil moisture within a given HRU is ignored. Here, we examined a number of disaggregation schemes for soil moisture distribution in each HRU. The disaggregation schemes are either based on topographic based indices or a covariance matrix obtained from distributed soil moisture simulations. To assess the performance of the disaggregation schemes, soil moisture simulations from an integrated land surface-groundwater model, ParFlow.CLM in Baldry sub-catchment, Australia are used. ParFlow is a variably saturated sub-surface flow model that is coupled to the Common Land Model (CLM). Our results illustrate that the statistical disaggregation scheme performs better than the methods based on topographic data in approximating soil moisture distribution at a 60m scale. Moreover, the statistical disaggregation scheme maintains temporal correlation of simulated daily soil moisture while preserves the mean sub-basin soil moisture. Future work is focused on assessing the performance of this scheme in catchments with various topographic and climate settings.

Green infrastructure retrofits on residential parcels: Ecohydrologic modeling for stormwater design

NASA Astrophysics Data System (ADS)

Miles, B.; Band, L. E.

2014-12-01

To meet water quality goals stormwater utilities and not-for-profit watershed organizations in the U.S. are working with citizens to design and implement green infrastructure on residential land. Green infrastructure, as an alternative and complement to traditional (grey) stormwater infrastructure, has the potential to contribute to multiple ecosystem benefits including stormwater volume reduction, carbon sequestration, urban heat island mitigation, and to provide amenities to residents. However, in small (1-10-km2) medium-density urban watersheds with heterogeneous land cover it is unclear whether stormwater retrofits on residential parcels significantly contributes to reduce stormwater volume at the watershed scale. In this paper, we seek to improve understanding of how small-scale redistribution of water at the parcel scale as part of green infrastructure implementation affects urban water budgets and stormwater volume across spatial scales. As study sites we use two medium-density headwater watersheds in Baltimore, MD and Durham, NC. We develop ecohydrology modeling experiments to evaluate the effectiveness of redirecting residential rooftop runoff to un-altered pervious surfaces and to engineered rain gardens to reduce stormwater runoff. As baselines for these experiments, we performed field surveys of residential rooftop hydrologic connectivity to adjacent impervious surfaces, and found low rates of connectivity. Through simulations of pervasive adoption of downspout disconnection to un-altered pervious areas or to rain garden stormwater control measures (SCM) in these catchments, we find that most parcel-scale changes in stormwater fate are attenuated at larger spatial scales and that neither SCM alone is likely to provide significant changes in streamflow at the watershed scale.

Connecting the molecular scale to the continuum scale for diffusion processes in smectite-rich porous media.

PubMed

Bourg, Ian C; Sposito, Garrison

2010-03-15

In this paper, we address the manner in which the continuum-scale diffusive properties of smectite-rich porous media arise from their molecular- and pore-scale features. Our starting point is a successful model of the continuum-scale apparent diffusion coefficient for water tracers and cations, which decomposes it as a sum of pore-scale terms describing diffusion in macropore and interlayer "compartments." We then apply molecular dynamics (MD) simulations to determine molecular-scale diffusion coefficients D(interlayer) of water tracers and representative cations (Na(+), Cs(+), Sr(2+)) in Na-smectite interlayers. We find that a remarkably simple expression relates D(interlayer) to the pore-scale parameter δ(nanopore) ≤ 1, a constrictivity factor that accounts for the lower mobility in interlayers as compared to macropores: δ(nanopore) = D(interlayer)/D(0), where D(0) is the diffusion coefficient in bulk liquid water. Using this scaling expression, we can accurately predict the apparent diffusion coefficients of tracers H(2)0, Na(+), Sr(2+), and Cs(+) in compacted Na-smectite-rich materials.

Finding the ‘lost years’ in green turtles: insights from ocean circulation models and genetic analysis

PubMed Central

Putman, Nathan F.; Naro-Maciel, Eugenia

2013-01-01

Organismal movement is an essential component of ecological processes and connectivity among ecosystems. However, estimating connectivity and identifying corridors of movement are challenging in oceanic organisms such as young turtles that disperse into the open sea and remain largely unobserved during a period known as ‘the lost years’. Using predictions of transport within an ocean circulation model and data from published genetic analysis, we present to our knowledge, the first basin-scale hypothesis of distribution and connectivity among major rookeries and foraging grounds (FGs) of green turtles (Chelonia mydas) during their ‘lost years’. Simulations indicate that transatlantic dispersal is likely to be common and that recurrent connectivity between the southwestern Indian Ocean and the South Atlantic is possible. The predicted distribution of pelagic juvenile turtles suggests that many ‘lost years hotspots’ are presently unstudied and located outside protected areas. These models, therefore, provide new information on possible dispersal pathways that link nesting beaches with FGs. These pathways may be of exceptional conservation concern owing to their importance for sea turtles during a critical developmental period. PMID:23945687

Species- and sex-specific connectivity effects of habitat fragmentation in a suite of woodland birds.

PubMed

Amos, Nevil; Harrisson, Katherine A; Radford, James Q; White, Matt; Newell, Graeme; Mac Nally, Ralph; Sunnucks, Paul; Pavlova, Alexandra

2014-06-01

Loss of functional connectivity following habitat loss and fragmentation could drive species declines. A comprehensive understanding of fragmentation effects on functional connectivity of an ecological assemblage requires investigation of multiple species with different mobilities, at different spatial scales, for each sex, and in different landscapes. Based on published data on mobility and ecological responses to fragmentation of 10 woodland-dependent birds, and using simulation studies, we predicted that (1) fragmentation would impede dispersal and gene flow of eight "decliners" (species that disappear from suitable patches when landscape-level tree cover falls below species-specific thresholds), but not of two "tolerant" species (whose occurrence in suitable habitat patches is independent of landscape tree cover); and that fragmentation effects would be stronger (2) in the least mobile species, (3) in the more philopatric sex, and (4) in the more fragmented region. We tested these predictions by evaluating spatially explicit isolation-by-landscape-resistance models of gene flow in fragmented landscapes across a 50 x 170 km study area in central Victoria, Australia, using individual and population genetic distances. To account for sex-biased dispersal and potential scale- and configuration-specific effects, we fitted models specific to sex and geographic zones. As predicted, four of the least mobile decliners showed evidence of reduced genetic connectivity. The responses were strongly sex specific, but in opposite directions in the two most sedentary species. Both tolerant species and (unexpectedly) four of the more mobile decliners showed no reduction in gene flow. This is unlikely to be due to time lags because more mobile species develop genetic signatures of fragmentation faster than do less mobile ones. Weaker genetic effects were observed in the geographic zone with more aggregated vegetation, consistent with gene flow being unimpeded by landscape structure. Our results indicate that for all but the most sedentary species in our system, the movement of the more dispersive sex (females in most cases) maintains overall genetic connectivity across fragmented landscapes in the study area, despite some small-scale effects on the more philopatric sex for some species. Nevertheless, to improve population viability for the less mobile bird species, structural landscape connectivity must be increased.

Dark matter self-interactions and small scale structure

NASA Astrophysics Data System (ADS)

Tulin, Sean; Yu, Hai-Bo

2018-02-01

We review theories of dark matter (DM) beyond the collisionless paradigm, known as self-interacting dark matter (SIDM), and their observable implications for astrophysical structure in the Universe. Self-interactions are motivated, in part, due to the potential to explain long-standing (and more recent) small scale structure observations that are in tension with collisionless cold DM (CDM) predictions. Simple particle physics models for SIDM can provide a universal explanation for these observations across a wide range of mass scales spanning dwarf galaxies, low and high surface brightness spiral galaxies, and clusters of galaxies. At the same time, SIDM leaves intact the success of ΛCDM cosmology on large scales. This report covers the following topics: (1) small scale structure issues, including the core-cusp problem, the diversity problem for rotation curves, the missing satellites problem, and the too-big-to-fail problem, as well as recent progress in hydrodynamical simulations of galaxy formation; (2) N-body simulations for SIDM, including implications for density profiles, halo shapes, substructure, and the interplay between baryons and self-interactions; (3) semi-analytic Jeans-based methods that provide a complementary approach for connecting particle models with observations; (4) merging systems, such as cluster mergers (e.g., the Bullet Cluster) and minor infalls, along with recent simulation results for mergers; (5) particle physics models, including light mediator models and composite DM models; and (6) complementary probes for SIDM, including indirect and direct detection experiments, particle collider searches, and cosmological observations. We provide a summary and critical look for all current constraints on DM self-interactions and an outline for future directions.

Scaling laws and dynamics of bubble coalescence

NASA Astrophysics Data System (ADS)

Anthony, Christopher R.; Kamat, Pritish M.; Thete, Sumeet S.; Munro, James P.; Lister, John R.; Harris, Michael T.; Basaran, Osman A.

2017-08-01

The coalescence of bubbles and drops plays a central role in nature and industry. During coalescence, two bubbles or drops touch and merge into one as the neck connecting them grows from microscopic to macroscopic scales. The hydrodynamic singularity that arises when two bubbles or drops have just touched and the flows that ensue have been studied thoroughly when two drops coalesce in a dynamically passive outer fluid. In this paper, the coalescence of two identical and initially spherical bubbles, which are idealized as voids that are surrounded by an incompressible Newtonian liquid, is analyzed by numerical simulation. This problem has recently been studied (a) experimentally using high-speed imaging and (b) by asymptotic analysis in which the dynamics is analyzed by determining the growth of a hole in the thin liquid sheet separating the two bubbles. In the latter, advantage is taken of the fact that the flow in the thin sheet of nonconstant thickness is governed by a set of one-dimensional, radial extensional flow equations. While these studies agree on the power law scaling of the variation of the minimum neck radius with time, they disagree with respect to the numerical value of the prefactors in the scaling laws. In order to reconcile these differences and also provide insights into the dynamics that are difficult to probe by either of the aforementioned approaches, simulations are used to access both earlier times than has been possible in the experiments and also later times when asymptotic analysis is no longer applicable. Early times and extremely small length scales are attained in the new simulations through the use of a truncated domain approach. Furthermore, it is shown by direct numerical simulations in which the flow within the bubbles is also determined along with the flow exterior to them that idealizing the bubbles as passive voids has virtually no effect on the scaling laws relating minimum neck radius and time.

Applying network theory to prioritize multispecies habitat networks that are robust to climate and land-use change.

PubMed

Albert, Cécile H; Rayfield, Bronwyn; Dumitru, Maria; Gonzalez, Andrew

2017-12-01

Designing connected landscapes is among the most widespread strategies for achieving biodiversity conservation targets. The challenge lies in simultaneously satisfying the connectivity needs of multiple species at multiple spatial scales under uncertain climate and land-use change. To evaluate the contribution of remnant habitat fragments to the connectivity of regional habitat networks, we developed a method to integrate uncertainty in climate and land-use change projections with the latest developments in network-connectivity research and spatial, multipurpose conservation prioritization. We used land-use change simulations to explore robustness of species' habitat networks to alternative development scenarios. We applied our method to 14 vertebrate focal species of periurban Montreal, Canada. Accounting for connectivity in spatial prioritization strongly modified conservation priorities and the modified priorities were robust to uncertain climate change. Setting conservation priorities based on habitat quality and connectivity maintained a large proportion of the region's connectivity, despite anticipated habitat loss due to climate and land-use change. The application of connectivity criteria alongside habitat-quality criteria for protected-area design was efficient with respect to the amount of area that needs protection and did not necessarily amplify trade-offs among conservation criteria. Our approach and results are being applied in and around Montreal and are well suited to the design of ecological networks and green infrastructure for the conservation of biodiversity and ecosystem services in other regions, in particular regions around large cities, where connectivity is critically low. © 2017 Society for Conservation Biology.

Quantum Monte Carlo tunneling from quantum chemistry to quantum annealing

NASA Astrophysics Data System (ADS)

Mazzola, Guglielmo; Smelyanskiy, Vadim N.; Troyer, Matthias

2017-10-01

Quantum tunneling is ubiquitous across different fields, from quantum chemical reactions and magnetic materials to quantum simulators and quantum computers. While simulating the real-time quantum dynamics of tunneling is infeasible for high-dimensional systems, quantum tunneling also shows up in quantum Monte Carlo (QMC) simulations, which aim to simulate quantum statistics with resources growing only polynomially with the system size. Here we extend the recent results obtained for quantum spin models [Phys. Rev. Lett. 117, 180402 (2016), 10.1103/PhysRevLett.117.180402], and we study continuous-variable models for proton transfer reactions. We demonstrate that QMC simulations efficiently recover the scaling of ground-state tunneling rates due to the existence of an instanton path, which always connects the reactant state with the product. We discuss the implications of our results in the context of quantum chemical reactions and quantum annealing, where quantum tunneling is expected to be a valuable resource for solving combinatorial optimization problems.

Hydrologic connectivity as a framework for understanding biogeochemical flux through watersheds and along fluvial networks

NASA Astrophysics Data System (ADS)

Covino, Tim

2017-01-01

Hydrologic connections can link hillslopes to channel networks, streams to lakes, subsurface to surface, land to atmosphere, terrestrial to aquatic, and upstream to downstream. These connections can develop across vertical, lateral, and longitudinal dimensions and span spatial and temporal scales. Each of these dimensions and scales are interconnected, creating a mosaic of nested hydrologic connections and associated processes. In turn, these interacting and nested processes influence the transport, cycling, and transformation of organic material and inorganic nutrients through watersheds and along fluvial networks. Although hydrologic connections span dimensions and spatiotemporal scales, relationships between connectivity and carbon and nutrient dynamics are rarely evaluated within this framework. The purpose of this paper is to provide a cross-disciplinary view of hydrologic connectivity - highlighting the various forms of hydrologic connectivity that control fluxes of organic material and nutrients - and to help stimulate integration across scales and dimensions, and collaboration among disciplines.

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

Phillips, Carolyn L.; Guo, Hanqi; Peterka, Tom

In type-II superconductors, the dynamics of magnetic flux vortices determine their transport properties. In the Ginzburg-Landau theory, vortices correspond to topological defects in the complex order parameter field. Earlier, in Phillips et al. [Phys. Rev. E 91, 023311 (2015)], we introduced a method for extracting vortices from the discretized complex order parameter field generated by a large-scale simulation of vortex matter. With this method, at a fixed time step, each vortex [simplistically, a one-dimensional (1D) curve in 3D space] can be represented as a connected graph extracted from the discretized field. Here we extend this method as a function ofmore » time as well. A vortex now corresponds to a 2D space-time sheet embedded in 4D space time that can be represented as a connected graph extracted from the discretized field over both space and time. Vortices that interact by merging or splitting correspond to disappearance and appearance of holes in the connected graph in the time direction. This method of tracking vortices, which makes no assumptions about the scale or behavior of the vortices, can track the vortices with a resolution as good as the discretization of the temporally evolving complex scalar field. Additionally, even details of the trajectory between time steps can be reconstructed from the connected graph. With this form of vortex tracking, the details of vortex dynamics in a model of a superconducting materials can be understood in greater detail than previously possible.« less

Tracking vortices in superconductors: Extracting singularities from a discretized complex scalar field evolving in time

DOE PAGES

Phillips, Carolyn L.; Guo, Hanqi; Peterka, Tom; ...

2016-02-19

In type-II superconductors, the dynamics of magnetic flux vortices determine their transport properties. In the Ginzburg-Landau theory, vortices correspond to topological defects in the complex order parameter field. Earlier, we introduced a method for extracting vortices from the discretized complex order parameter field generated by a large-scale simulation of vortex matter. With this method, at a fixed time step, each vortex [simplistically, a one-dimensional (1D) curve in 3D space] can be represented as a connected graph extracted from the discretized field. Here we extend this method as a function of time as well. A vortex now corresponds to a 2Dmore » space-time sheet embedded in 4D space time that can be represented as a connected graph extracted from the discretized field over both space and time. Vortices that interact by merging or splitting correspond to disappearance and appearance of holes in the connected graph in the time direction. This method of tracking vortices, which makes no assumptions about the scale or behavior of the vortices, can track the vortices with a resolution as good as the discretization of the temporally evolving complex scalar field. In addition, even details of the trajectory between time steps can be reconstructed from the connected graph. With this form of vortex tracking, the details of vortex dynamics in a model of a superconducting materials can be understood in greater detail than previously possible.« less

From structure to function, via dynamics

NASA Astrophysics Data System (ADS)

Stetter, O.; Soriano, J.; Geisel, T.; Battaglia, D.

2013-01-01

Neurons in the brain are wired into a synaptic network that spans multiple scales, from local circuits within cortical columns to fiber tracts interconnecting distant areas. However, brain function require the dynamic control of inter-circuit interactions on time-scales faster than synaptic changes. In particular, strength and direction of causal influences between neural populations (described by the so-called directed functional connectivity) must be reconfigurable even when the underlying structural connectivity is fixed. Such directed functional influences can be quantified resorting to causal analysis of time-series based on tools like Granger Causality or Transfer Entropy. The ability to quickly reorganize inter-areal interactions is a chief requirement for performance in a changing natural environment. But how can manifold functional networks stem "on demand" from an essentially fixed structure? We explore the hypothesis that the self-organization of neuronal synchronous activity underlies the control of brain functional connectivity. Based on simulated and real recordings of critical neuronal cultures in vitro, as well as on mean-field and spiking network models of interacting brain areas, we have found that "function follows dynamics", rather than structure. Different dynamic states of a same structural network, characterized by different synchronization properties, are indeed associated to different functional digraphs (functional multiplicity). We also highlight the crucial role of dynamics in establishing a structure-to-function link, by showing that whenever different structural topologies lead to similar dynamical states, than the associated functional connectivities are also very similar (structural degeneracy).

Habitat connectivity and ecosystem productivity: implications from a simple model.

USGS Publications Warehouse

Cloern, J.E.

2007-01-01

The import of resources (food, nutrients) sustains biological production and food webs in resource-limited habitats. Resource export from donor habitats subsidizes production in recipient habitats, but the ecosystem-scale consequences of resource translocation are generally unknown. Here, I use a nutrient-phytoplankton-zooplankton model to show how dispersive connectivity between a shallow autotrophic habitat and a deep heterotrophic pelagic habitat can amplify overall system production in metazoan food webs. This result derives from the finite capacity of suspension feeders to capture and assimilate food particles: excess primary production in closed autotrophic habitats cannot be assimilated by consumers; however, if excess phytoplankton production is exported to food-limited heterotrophic habitats, it can be assimilated by zooplankton to support additional secondary production. Transport of regenerated nutrients from heterotrophic to autotrophic habitats sustains higher system primary production. These simulation results imply that the ecosystem-scale efficiency of nutrient transformation into metazoan biomass can be constrained by the rate of resource exchange across habitats and that it is optimized when the transport rate matches the growth rate of primary producers. Slower transport (i.e., reduced connectivity) leads to nutrient limitation of primary production in autotrophic habitats and food limitation of secondary production in heterotrophic habitats. Habitat fragmentation can therefore impose energetic constraints on the carrying capacity of aquatic ecosystems. The outcomes of ecosystem restoration through habitat creation will be determined by both functions provided by newly created aquatic habitats and the rates of hydraulic connectivity between them.

The finite scaling for S = 1 XXZ chains with uniaxial single-ion-type anisotropy

NASA Astrophysics Data System (ADS)

Wang, Honglei; Xiong, Xingliang

2014-03-01

The scaling behavior of criticality for spin-1 XXZ chains with uniaxial single-ion-type anisotropy is investigated by employing the infinite matrix product state representation with the infinite time evolving block decimation method. At criticality, the accuracy of the ground state of a system is limited by the truncation dimension χ of the local Hilbert space. We present four evidences for the scaling of the entanglement entropy, the largest eigenvalue of the Schmidt decomposition, the correlation length, and the connection between the actual correlation length ξ and the energy. The result shows that the finite scalings are governed by the central charge of the critical system. Also, it demonstrates that the infinite time evolving block decimation algorithm by the infinite matrix product state representation can be a quite accurate method to simulate the critical properties at criticality.

The Origin of Scales and Scaling Laws in Star Formation

NASA Astrophysics Data System (ADS)

Guszejnov, David; Hopkins, Philip; Grudich, Michael

2018-01-01

Star formation is one of the key processes of cosmic evolution as it influences phenomena from the formation of galaxies to the formation of planets, and the development of life. Unfortunately, there is no comprehensive theory of star formation, despite intense effort on both the theoretical and observational sides, due to the large amount of complicated, non-linear physics involved (e.g. MHD, gravity, radiation). A possible approach is to formulate simple, easily testable models that allow us to draw a clear connection between phenomena and physical processes.In the first part of the talk I will focus on the origin of the IMF peak, the characteristic scale of stars. There is debate in the literature about whether the initial conditions of isothermal turbulence could set the IMF peak. Using detailed numerical simulations, I will demonstrate that not to be the case, the initial conditions are "forgotten" through the fragmentation cascade. Additional physics (e.g. feedback) is required to set the IMF peak.In the second part I will use simulated galaxies from the Feedback in Realistic Environments (FIRE) project to show that most star formation theories are unable to reproduce the near universal IMF peak of the Milky Way.Finally, I will present analytic arguments (supported by simulations) that a large number of observables (e.g. IMF slope) are the consequences of scale-free structure formation and are (to first order) unsuitable for differentiating between star formation theories.

DO NOT FORGET THE FOREST FOR THE TREES: THE STELLAR-MASS HALO-MASS RELATION IN DIFFERENT ENVIRONMENTS

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

Tonnesen, Stephanie; Cen, Renyue, E-mail: stonnes@gmail.com, E-mail: cen@astro.princeton.edu

2015-10-20

The connection between dark matter halos and galactic baryons is often not well constrained nor well resolved in cosmological hydrodynamical simulations. Thus, halo occupation distribution models that assign galaxies to halos based on halo mass are frequently used to interpret clustering observations, even though it is well known that the assembly history of dark matter halos is related to their clustering. In this paper we use high-resolution hydrodynamical cosmological simulations to compare the halo and stellar mass growth of galaxies in a large-scale overdensity to those in a large-scale underdensity (on scales of about 20 Mpc). The simulation reproduces assemblymore » bias, in which halos have earlier formation times in overdense environments than in underdense regions. We find that the ratio of stellar mass to halo mass is larger in overdense regions in central galaxies residing in halos with masses between 10{sup 11} and 10{sup 12.9} M{sub ⊙}. When we force the local density (within 2 Mpc) at z = 0 to be the same for galaxies in the large-scale over- and underdensities, we find the same results. We posit that this difference can be explained by a combination of earlier formation times, more interactions at early times with neighbors, and more filaments feeding galaxies in overdense regions. This result puts the standard practice of assigning stellar mass to halos based only on their mass, rather than considering their larger environment, into question.« less

Length-scale crossover of the hydrophobic interaction in a coarse-grained water model

NASA Astrophysics Data System (ADS)

Chaimovich, Aviel; Shell, M. Scott

2013-11-01

It has been difficult to establish a clear connection between the hydrophobic interaction among small molecules typically studied in molecular simulations (a weak, oscillatory force) and that found between large, macroscopic surfaces in experiments (a strong, monotonic force). Here, we show that both types of interaction can emerge with a simple, core-softened water model that captures water's unique pairwise structure. As in hydrophobic hydration, we find that the hydrophobic interaction manifests a length-scale dependence, exhibiting distinct driving forces in the molecular and macroscopic regimes. Moreover, the ability of this simple model to capture both regimes suggests that several features of the hydrophobic force can be understood merely through water's pair correlations.

Length-scale crossover of the hydrophobic interaction in a coarse-grained water model.

PubMed

Chaimovich, Aviel; Shell, M Scott

2013-11-01

It has been difficult to establish a clear connection between the hydrophobic interaction among small molecules typically studied in molecular simulations (a weak, oscillatory force) and that found between large, macroscopic surfaces in experiments (a strong, monotonic force). Here, we show that both types of interaction can emerge with a simple, core-softened water model that captures water's unique pairwise structure. As in hydrophobic hydration, we find that the hydrophobic interaction manifests a length-scale dependence, exhibiting distinct driving forces in the molecular and macroscopic regimes. Moreover, the ability of this simple model to capture both regimes suggests that several features of the hydrophobic force can be understood merely through water's pair correlations.

An elevated source/drain-on-insulator structure to maximize the intrinsic performance of extremely scaled MOSFETs

NASA Astrophysics Data System (ADS)

Zhang, Zhikuan; Zhang, Shengdong; Feng, Chuguang; Chan, Mansun

2003-10-01

In this paper, a source/drain structure separated from the silicon substrate by oxide isolation is fabricated and studied. The source/drain diffusion regions are connected to the shallow source/drain extension through a smaller opening defined by a double spacer process. Experimental results indicate that the source/drain on insulator significantly reduces the parasitic capacitance. Further optimization by simulation indicates a reduction of series resistance and band-to-band drain leakage at off-state can be achieved in extremely scaled devices. Compared with the conventional planner source/drain structure, the reduction of parasitic capacitance and series resistance can be as much as 80% and 30% respectively.

Patterns of resting state connectivity in human primary visual cortical areas: a 7T fMRI study.

PubMed

Raemaekers, Mathijs; Schellekens, Wouter; van Wezel, Richard J A; Petridou, Natalia; Kristo, Gert; Ramsey, Nick F

2014-01-01

The nature and origin of fMRI resting state fluctuations and connectivity are still not fully known. More detailed knowledge on the relationship between resting state patterns and brain function may help to elucidate this matter. We therefore performed an in depth study of how resting state fluctuations map to the well known architecture of the visual system. We investigated resting state connectivity at both a fine and large scale within and across visual areas V1, V2 and V3 in ten human subjects using a 7Tesla scanner. We found evidence for several coexisting and overlapping connectivity structures at different spatial scales. At the fine-scale level we found enhanced connectivity between the same topographic locations in the fieldmaps of V1, V2 and V3, enhanced connectivity to the contralateral functional homologue, and to a lesser extent enhanced connectivity between iso-eccentric locations within the same visual area. However, by far the largest proportion of the resting state fluctuations occurred within large-scale bilateral networks. These large-scale networks mapped to some extent onto the architecture of the visual system and could thereby obscure fine-scale connectivity. In fact, most of the fine-scale connectivity only became apparent after the large-scale network fluctuations were filtered from the timeseries. We conclude that fMRI resting state fluctuations in the visual cortex may in fact be a composite signal of different overlapping sources. Isolating the different sources could enhance correlations between BOLD and electrophysiological correlates of resting state activity. © 2013 Elsevier Inc. All rights reserved.

Modeling the Webgraph: How Far We Are

NASA Astrophysics Data System (ADS)

Donato, Debora; Laura, Luigi; Leonardi, Stefano; Millozzi, Stefano

The following sections are included: * Introduction * Preliminaries * WebBase * In-degree and out-degree * PageRank * Bipartite cliques * Strongly connected components * Stochastic models of the webgraph * Models of the webgraph * A multi-layer model * Large scale simulation * Algorithmic techniques for generating and measuring webgraphs * Data representation and multifiles * Generating webgraphs * Traversal with two bits for each node * Semi-external breadth first search * Semi-external depth first search * Computation of the SCCs * Computation of the bow-tie regions * Disjoint bipartite cliques * PageRank * Summary and outlook

Large-Scale Habitat Corridors for Biodiversity Conservation: A Forest Corridor in Madagascar

PubMed Central

Ramiadantsoa, Tanjona; Ovaskainen, Otso; Rybicki, Joel; Hanski, Ilkka

2015-01-01

In biodiversity conservation, habitat corridors are assumed to increase landscape-level connectivity and to enhance the viability of otherwise isolated populations. While the role of corridors is supported by empirical evidence, studies have typically been conducted at small spatial scales. Here, we assess the quality and the functionality of a large 95-km long forest corridor connecting two large national parks (416 and 311 km2) in the southeastern escarpment of Madagascar. We analyze the occurrence of 300 species in 5 taxonomic groups in the parks and in the corridor, and combine high-resolution forest cover data with a simulation model to examine various scenarios of corridor destruction. At present, the corridor contains essentially the same communities as the national parks, reflecting its breadth which on average matches that of the parks. In the simulation model, we consider three types of dispersers: passive dispersers, which settle randomly around the source population; active dispersers, which settle only in favorable habitat; and gap-avoiding active dispersers, which avoid dispersing across non-habitat. Our results suggest that long-distance passive dispersers are most sensitive to ongoing degradation of the corridor, because increasing numbers of propagules are lost outside the forest habitat. For a wide range of dispersal parameters, the national parks are large enough to sustain stable populations until the corridor becomes severely broken, which will happen around 2065 if the current rate of forest loss continues. A significant decrease in gene flow along the corridor is expected after 2040, and this will exacerbate the adverse consequences of isolation. Our results demonstrate that simulation studies assessing the role of habitat corridors should pay close attention to the mode of dispersal and the effects of regional stochasticity. PMID:26200351

Large-Scale Habitat Corridors for Biodiversity Conservation: A Forest Corridor in Madagascar.

PubMed

Ramiadantsoa, Tanjona; Ovaskainen, Otso; Rybicki, Joel; Hanski, Ilkka

2015-01-01

In biodiversity conservation, habitat corridors are assumed to increase landscape-level connectivity and to enhance the viability of otherwise isolated populations. While the role of corridors is supported by empirical evidence, studies have typically been conducted at small spatial scales. Here, we assess the quality and the functionality of a large 95-km long forest corridor connecting two large national parks (416 and 311 km2) in the southeastern escarpment of Madagascar. We analyze the occurrence of 300 species in 5 taxonomic groups in the parks and in the corridor, and combine high-resolution forest cover data with a simulation model to examine various scenarios of corridor destruction. At present, the corridor contains essentially the same communities as the national parks, reflecting its breadth which on average matches that of the parks. In the simulation model, we consider three types of dispersers: passive dispersers, which settle randomly around the source population; active dispersers, which settle only in favorable habitat; and gap-avoiding active dispersers, which avoid dispersing across non-habitat. Our results suggest that long-distance passive dispersers are most sensitive to ongoing degradation of the corridor, because increasing numbers of propagules are lost outside the forest habitat. For a wide range of dispersal parameters, the national parks are large enough to sustain stable populations until the corridor becomes severely broken, which will happen around 2065 if the current rate of forest loss continues. A significant decrease in gene flow along the corridor is expected after 2040, and this will exacerbate the adverse consequences of isolation. Our results demonstrate that simulation studies assessing the role of habitat corridors should pay close attention to the mode of dispersal and the effects of regional stochasticity.

Internet use and health: Connecting secondary data through spatial microsimulation

PubMed Central

Deetjen, Ulrike; Powell, John A

2016-01-01

Objective Internet use may affect health and health service use, and is seen as a potential lever for empowering patients, levelling inequalities and managing costs in the health system. However, supporting evidence is scant, partially due to a lack of data to investigate the relationship on a larger scale. This paper presents an approach for connecting existing datasets to generate new insights. Methods Spatial microsimulation offers a way to combine a random sample survey on Internet use with aggregate census data and other routine data from the health system based on small geographic areas to examine the relationship between Internet use, perceived health and health service use. While health research has primarily used spatial microsimulation to estimate the geographic distribution of a certain phenomenon, this research highlights this simulation technique as a way to link datasets for joint analysis, with location as the connecting element. Results Internet use is associated with higher perceived health and lower health service use independently of whether Internet use was conceptualised in terms of access, support or usage, and controlling for sociodemographic covariates. Internal validation confirms that differences between actual and simulated data are small; external validation shows that the simulated dataset is a good reflection of the real world. Conclusion Spatial microsimulation helps to generate new insights through linking secondary data in a privacy-preserving and cost-effective way. This allows for better understanding the relationship between Internet use and health, enabling theoretical insights and practical implications for policy with insights down to the local level. PMID:29942566

Connecting source aggregating areas with distributive regions via Optimal Transportation theory.

NASA Astrophysics Data System (ADS)

Lanzoni, S.; Putti, M.

2016-12-01

We study the application of Optimal Transport (OT) theory to the transfer of water and sediments from a distributed aggregating source to a distributing area connected by a erodible hillslope. Starting from the Monge-Kantorovich equations, We derive a global energy functional that nonlinearly combines the cost of constructing the drainage network over the entire domain and the cost of water and sediment transportation through the network. It can be shown that the minimization of this functional is equivalent to the infinite time solution of a system of diffusion partial differential equations coupled with transient ordinary differential equations, that closely resemble the classical conservation laws of water and sediments mass and momentum. We present several numerical simulations applied to realstic test cases. For example, the solution of the proposed model forms network configurations that share strong similiratities with rill channels formed on an hillslope. At a larger scale, we obtain promising results in simulating the network patterns that ensure a progressive and continuous transition from a drainage drainage area to a distributive receiving region.

A discrete dislocation dynamics model of creeping single crystals

NASA Astrophysics Data System (ADS)

Rajaguru, M.; Keralavarma, S. M.

2018-04-01

Failure by creep is a design limiting issue for metallic materials used in several high temperature applications. Current theoretical models of creep are phenomenological with little connection to the underlying microscopic mechanisms. In this paper, a bottom-up simulation framework based on the discrete dislocation dynamics method is presented for dislocation creep aided by the diffusion of vacancies, known to be the rate controlling mechanism at high temperature and stress levels. The time evolution of the creep strain and the dislocation microstructure in a periodic unit cell of a nominally infinite single crystal is simulated using the kinetic Monte Carlo method, together with approximate constitutive laws formulated for the rates of thermal activation of dislocations over local pinning obstacles. The deformation of the crystal due to dislocation glide between individual thermal activation events is simulated using a standard dislocation dynamics algorithm, extended to account for constant stress periodic boundary conditions. Steady state creep conditions are obtained in the simulations with the predicted creep rates as a function of stress and temperature in good agreement with experimentally reported values. Arrhenius scaling of the creep rates as a function of temperature and power-law scaling with the applied stress are also reproduced, with the values of the power-law exponents in the high stress regime in good agreement with experiments.

The edge of galaxy formation - I. Formation and evolution of MW-satellite analogues before accretion

NASA Astrophysics Data System (ADS)

Macciò, Andrea V.; Frings, Jonas; Buck, Tobias; Penzo, Camilla; Dutton, Aaron A.; Blank, Marvin; Obreja, Aura

2017-12-01

The satellites of the Milky Way and Andromeda represent the smallest galaxies we can observe in our Universe. In this series of papers, we aim to shed light on their formation and evolution using cosmological hydrodynamical simulations. In this first paper, we focus on the galaxy properties before accretion, by simulating 27 haloes with masses between 5 × 108 and 1010 M⊙. Out of this set 19 haloes successfully form stars, while 8 remain dark. The simulated galaxies match quite well present day observed scaling relations between stellar mass, size and metallicity, showing that such relations are in place before accretion. Our galaxies show a large variety of star formation histories, from extended star formation periods to single bursts. As in more massive galaxies, large star formation bursts are connected with major mergers events, which greatly contribute to the overall stellar mass build up. The intrinsic stochasticity of mergers induces a large scatter in the stellar mass-halo mass relation, up to two orders of magnitude. Despite the bursty star formation history, on these mass scales baryons are very ineffective in modifying the dark matter profiles, and galaxies with a stellar mass below ≈106 M⊙ retain their cuspy central dark matter distribution, very similar to results from pure N-body simulations.

ARENA - A Collaborative Immersive Environment for Virtual Fieldwork

NASA Astrophysics Data System (ADS)

Kwasnitschka, T.

2012-12-01

Whenever a geoscientific study area is not readily accessible, as is the case on the deep seafloor, it is difficult to apply traditional but effective methods of fieldwork, which often require physical presence of the observer. The Artificial Research Environment for Networked Analysis (ARENA), developed at GEOMAR | Helmholtz Centre for Ocean Research Kiel within the Cluster of Excellence "The Future Ocean", provides a backend solution to robotic research on the seafloor by means of an immersive simulation environment for marine research: A hemispherical screen of 6m diameter covering the entire lower hemisphere surrounds a group of up to four researchers at once. A variety of open source (e.g. Microsoft Research World Wide Telescope) and commercial software platforms allow the interaction with e.g. in-situ recorded video, vector maps, terrain, textured geometry, point cloud and volumetric data in four dimensions. Data can be put into a holistic, georeferenced context and viewed on scales stretching from centimeters to global. Several input devices from joysticks to gestures and vocalized commands allow interaction with the simulation, depending on individual preference. Annotations added to the dataset during the simulation session catalyze the following quantitative evaluation. Both the special simulator design, making data perception a group experience, and the ability to connect remote instances or scaled down versions of ARENA over the Internet are significant advantages over established immersive simulation environments.

Temporally structured replay of neural activity in a model of entorhinal cortex, hippocampus and postsubiculum

PubMed Central

Hasselmo, Michael E.

2008-01-01

The spiking activity of hippocampal neurons during REM sleep exhibits temporally structured replay of spiking occurring during previously experienced trajectories (Louie and Wilson, 2001). Here, temporally structured replay of place cell activity during REM sleep is modeled in a large-scale network simulation of grid cells, place cells and head direction cells. During simulated waking behavior, the movement of the simulated rat drives activity of a population of head direction cells that updates the activity of a population of entorhinal grid cells. The population of grid cells drives the activity of place cells coding individual locations. Associations between location and movement direction are encoded by modification of excitatory synaptic connections from place cells to speed modulated head direction cells. During simulated REM sleep, the population of place cells coding an experienced location activates the head direction cells coding the associated movement direction. Spiking of head direction cells then causes frequency shifts within the population of entorhinal grid cells to update a phase representation of location. Spiking grid cells then activate new place cells that drive new head direction activity. In contrast to models that perform temporally compressed sequence retrieval similar to sharp wave activity, this model can simulate data on temporally structured replay of hippocampal place cell activity during REM sleep at time scales similar to those observed during waking. These mechanisms could be important for episodic memory of trajectories. PMID:18973557

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

ALAM,TODD M.

Monte Carlo simulations of phosphate tetrahedron connectivity distributions in alkali and alkaline earth phosphate glasses are reported. By utilizing a discrete bond model, the distribution of next-nearest neighbor connectivities between phosphate polyhedron for random, alternating and clustering bonding scenarios was evaluated as a function of the relative bond energy difference. The simulated distributions are compared to experimentally observed connectivities reported for solid-state two-dimensional exchange and double-quantum NMR experiments of phosphate glasses. These Monte Carlo simulations demonstrate that the polyhedron connectivity is best described by a random distribution in lithium phosphate and calcium phosphate glasses.

A hierarchical pyramid method for managing large-scale high-resolution drainage networks extracted from DEM

NASA Astrophysics Data System (ADS)

Bai, Rui; Tiejian, Li; Huang, Yuefei; Jiaye, Li; Wang, Guangqian; Yin, Dongqin

2015-12-01

The increasing resolution of Digital Elevation Models (DEMs) and the development of drainage network extraction algorithms make it possible to develop high-resolution drainage networks for large river basins. These vector networks contain massive numbers of river reaches with associated geographical features, including topological connections and topographical parameters. These features create challenges for efficient map display and data management. Of particular interest are the requirements of data management for multi-scale hydrological simulations using multi-resolution river networks. In this paper, a hierarchical pyramid method is proposed, which generates coarsened vector drainage networks from the originals iteratively. The method is based on the Horton-Strahler's (H-S) order schema. At each coarsening step, the river reaches with the lowest H-S order are pruned, and their related sub-basins are merged. At the same time, the topological connections and topographical parameters of each coarsened drainage network are inherited from the former level using formulas that are presented in this study. The method was applied to the original drainage networks of a watershed in the Huangfuchuan River basin extracted from a 1-m-resolution airborne LiDAR DEM and applied to the full Yangtze River basin in China, which was extracted from a 30-m-resolution ASTER GDEM. In addition, a map-display and parameter-query web service was published for the Mississippi River basin, and its data were extracted from the 30-m-resolution ASTER GDEM. The results presented in this study indicate that the developed method can effectively manage and display massive amounts of drainage network data and can facilitate multi-scale hydrological simulations.

Exploiting Synoptic-Scale Climate Processes to Develop Nonstationary, Probabilistic Flood Hazard Projections

NASA Astrophysics Data System (ADS)

Spence, C. M.; Brown, C.; Doss-Gollin, J.

2016-12-01

Climate model projections are commonly used for water resources management and planning under nonstationarity, but they do not reliably reproduce intense short-term precipitation and are instead more skilled at broader spatial scales. To provide a credible estimate of flood trend that reflects climate uncertainty, we present a framework that exploits the connections between synoptic-scale oceanic and atmospheric patterns and local-scale flood-producing meteorological events to develop long-term flood hazard projections. We demonstrate the method for the Iowa River, where high flow episodes have been found to correlate with tropical moisture exports that are associated with a pressure dipole across the eastern continental United States We characterize the relationship between flooding on the Iowa River and this pressure dipole through a nonstationary Pareto-Poisson peaks-over-threshold probability distribution estimated based on the historic record. We then combine the results of a trend analysis of dipole index in the historic record with the results of a trend analysis of the dipole index as simulated by General Circulation Models (GCMs) under climate change conditions through a Bayesian framework. The resulting nonstationary posterior distribution of dipole index, combined with the dipole-conditioned peaks-over-threshold flood frequency model, connects local flood hazard to changes in large-scale atmospheric pressure and circulation patterns that are related to flooding in a process-driven framework. The Iowa River example demonstrates that the resulting nonstationary, probabilistic flood hazard projection may be used to inform risk-based flood adaptation decisions.

Hubble Space Telescope Imaging of the Circumnuclear Environments of the CfA Seyfert Galaxies: Nuclear Spirals and Fueling

NASA Technical Reports Server (NTRS)

Pogge, Richard W.; Martini, Paul

2002-01-01

We present archival Hubble Space Telescope (HST) images of the nuclear regions of 43 of the 46 Seyfert galaxies found in the volume limited,spectroscopically complete CfA Redshift Survey sample. Using an improved method of image contrast enhancement, we created detailed high-quality " structure maps " that allow us to study the distributions of dust, star clusters, and emission-line gas in the circumnuclear regions (100-1000 pc scales) and in the associated host galaxy. Essentially all of these Seyfert galaxies have circumnuclear dust structures with morphologies ranging from grand-design two-armed spirals to chaotic dusty disks. In most Seyfert galaxies there is a clear physical connection between the nuclear dust spirals on hundreds of parsec scales and large-scale bars and spiral arms in the host galaxies proper. These connections are particularly striking in the interacting and barred galaxies. Such structures are predicted by numerical simulations of gas flows in barred and interacting galaxies and may be related to the fueling of active galactic nuclei by matter inflow from the host galaxy disks. We see no significant differences in the circumnuclear dust morphologies of Seyfert 1s and 2s, and very few Seyfert 2 nuclei are obscured by large-scale dust structures in the host galaxies. If Sevfert 2s are obscured Sevfert Is, then the obscuration must occur on smaller scales than those probed by HST.

Reconstruction of networks from one-step data by matching positions

NASA Astrophysics Data System (ADS)

Wu, Jianshe; Dang, Ni; Jiao, Yang

2018-05-01

It is a challenge in estimating the topology of a network from short time series data. In this paper, matching positions is developed to reconstruct the topology of a network from only one-step data. We consider a general network model of coupled agents, in which the phase transformation of each node is determined by its neighbors. From the phase transformation information from one step to the next, the connections of the tail vertices are reconstructed firstly by the matching positions. Removing the already reconstructed vertices, and repeatedly reconstructing the connections of tail vertices, the topology of the entire network is reconstructed. For sparse scale-free networks with more than ten thousands nodes, we almost obtain the actual topology using only the one-step data in simulations.

OpenSoC Fabric

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

2014-08-21

Recent advancements in technology scaling have shown a trend towards greater integration with large-scale chips containing thousands of processors connected to memories and other I/O devices using non-trivial network topologies. Software simulation proves insufficient to study the tradeoffs in such complex systems due to slow execution time, whereas hardware RTL development is too time-consuming. We present OpenSoC Fabric, an on-chip network generation infrastructure which aims to provide a parameterizable and powerful on-chip network generator for evaluating future high performance computing architectures based on SoC technology. OpenSoC Fabric leverages a new hardware DSL, Chisel, which contains powerful abstractions provided by itsmore » base language, Scala, and generates both software (C++) and hardware (Verilog) models from a single code base. The OpenSoC Fabric2 infrastructure is modeled after existing state-of-the-art simulators, offers large and powerful collections of configuration options, and follows object-oriented design and functional programming to make functionality extension as easy as possible.« less

The scale effect on soil erosion. A plot approach to understand connectivity on slopes under cultivation at variable plot sizes and under Mediterranean climatic conditions

NASA Astrophysics Data System (ADS)

Cerdà, Artemi; Bagarello, Vicenzo; Ferro, Vito; Iovino, Massimo; Borja, Manuel Estaban Lucas; Francisco Martínez Murillo, Juan; González Camarena, Rafael

2017-04-01

It is well known that soil erosion changes along time and seasons and attention was paid to this issue in the past (González Hidalgo et al., 2010; 2012). However, although the scientific community knows that soil erosion is also a time spatial scale-scale dependent process (Parsons et al., 1990; Cerdà et al., 2009; González Hidalgo et al., 2013; Sadeghi et al., 2015) very little is done on this topic. This is due to the fact that at different scales, different soil erosion mechanisms (splash, sheetflow, rill development) are active and their rates change with the scale of measurement (Wainwright et al., 2002; López-Vicente et al., 2015). This is making the research on soil erosion complex and difficult, and it is necessary to develop a conceptual framework but also measurements that will inform about the soil erosion behaviour. Connectivity is the key concept to understand how changes in the scale results in different rates of soil and water losses (Parsons et al., 1996; Parsons et al., 2015; Poeppl et al., 2016). Most of the research developed around the connectivity concept was applied in watershed or basin scales (Galdino et al., 2016; Martínez-Casasnovas et al., 2016; López Vicente et al., 2016; Marchamalo et al., 2015; Masselink et al., 2016), but very little is known about the connectivity issue at slope scale (Cerdà and Jurgensen, 2011). El Teularet (Eastern Iberian Peninsula) and Sparacia (Sicily) soil erosion experimental stations are being active for 15 years and data collected on different plots sizes can shed light into the effect of scale on runoff generation and soil losses at different scales and give information to understand how the transport of materials is determined by the connectivity between pedon to slope scale (Cerdà et al., 2014; Bagarello et al., 2015a; 2015b). The comparison of the results of the two research stations will shed light into the rates of soil erosion and mechanisms involved that act under different scales. Our research share information collected during the last 15 years in the Sparacia and El Teularet soil erosion experimental stations under the same management and research how the concept of connectivity can help us to have a better understanding of the soil erosion process, and the effect of scale. All the data will be treated to show the runoff and sediment eroded at different plot sizes to understand how the sediment is transported at event scale. The rainfall characteristics will be also analysed to understand the soil erosion processes at different scales. Acknowledgements The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n 603498 (RECARE project) and the CGL2013- 47862-C2-1-R and CGL2016-75178-C2-2-R national research projects. References Bagarello, V., Ferro, V., Pampalone, V. 2015b. A new version of the USLE-MM for predicting bare plot soil loss at the Sparacia (South Italy) experimental site. Hydrological Processes, 29(19), 4210-4219. Bagarello, V., Ferro, V., Giordano, G., Mannocchi, F., Pampalone, V., Todisco, F. 2015a. A modified applicative criterion of the physical model concept for evaluating plot soil erosion predictions. Catena, 126, 53-58. Cerdà, A. and M. F. Jurgensen. 2011. Ant Mounds as a Source of Sediment on Citrus Orchard Plantations in Eastern Spain. A Three-Scale Rainfall Simulation Approach. Catena 85 (3): 231-236. doi:10.1016/j.catena.2011.01.008. Cerdà, A., Giménez-Morera, A., Jordan, A., Pereira, P., Novara, A., Keesstra, S., Sinoga, J. D. R. 2015. Shrubland as a soil and water conservation agent in Mediterranean-type ecosystems: The Sierra de Enguera study site contribution. Monitoring and Modelling Dynamic Environments, 45. Cerdà, A., R. Brazier, M. Nearing, and J. de Vente. 2013. Scales and Erosion. Catena 102: 1-2. doi:10.1016/j.catena.2011.09.006. Galdino, S., E. E. Sano, R. G. Andrade, C. R. Grego, S. F. Nogueira, C. Bragantini, and A. H. G. Flosi. 2016. Large-Scale Modeling of Soil Erosion with RUSLE for Conservationist Planning of Degraded Cultivated Brazilian Pastures. Land Degradation and Development 27 (3): 773-784. doi:10.1002/ldr.2414. Gonzalez-Hidalgo, J. C., R. J. Batalla, A. Cerdá, and M. de Luis. 2010. Contribution of the Largest Events to Suspended Sediment Transport Across the USA. Land Degradation and Development 21 (2): 83-91. doi:10.1002/ldr.897. Gonzalez-Hidalgo, J. C., R. J. Batalla, A. Cerdà, and M. de Luis. 2012. A Regional Analysis of the Effects of Largest Events on Soil Erosion. Catena 95: 85-90. doi:10.1016/j.catena.2012.03.006. Gonzalez-Hidalgo, J. C., R. J. Batalla, and A. Cerdà. 2013. Catchment Size and Contribution of the Largest Daily Events to Suspended Sediment Load on a Continental Scale. Catena 102: 40-45. doi:10.1016/j.catena.2010.10.011. López-Vicente, M., E. Nadal-Romero, and E. L. H. Cammeraat. 2016. Hydrological Connectivity does Change Over 70 Years of Abandonment and Afforestation in the Spanish Pyrenees. Land Degradation and Development. doi:10.1002/ldr.2531. López-Vicente, M., L. Quijano, L. Palazón, L. Gaspar, and A. Navas. 2015. Assessment of Soil Redistribution at Catchment Scale by Coupling a Soil Erosion Model and a Sediment Connectivity Index (Central Spanish Pre-Pyrenees). Cuadernos De Investigacion Geografica 41 (1): 127-147. doi:10.18172/cig.2649. Marchamalo, M., J. M. Hooke, and P. J. Sandercock. 2016. Flow and Sediment Connectivity in Semi-Arid Landscapes in SE Spain: Patterns and Controls. Land Degradation and Development 27 (4): 1032-1044. doi:10.1002/ldr.2352. Martínez-Casasnovas, J. A., M. C. Ramos, and G. Benites. 2016. Soil and Water Assessment Tool Soil Loss Simulation at the Sub-Basin Scale in the Alt Penedès-Anoia Vineyard Region (Ne Spain) in the 2000s. Land Degradation and Development 27 (2): 160-170. doi:10.1002/ldr.2240. Masselink, R.J.H., S.D. Keesstra, A J.A.M. Temme, M. Seeger, R. Giménez, J. Casalí. 2016. Modelling Discharge and Sediment Yield at Catchment Scale using Connectivity Components. Land Degradation and Development 27 (4): 933-945. doi:10.1002/ldr.2512. Parsons, A.J., Abrahams, A.D., Luk, S.H. 1990. Hydraulics of interrill overland flow on a semi-arid hillslope, southern Arizona. Journal of Hydrology, 117(1), 255-273. Parsons, A.J., Abrahams, A. D., Wainwright, J. 1996. Responses of interrill runoff and erosion rates to vegetation change in southern Arizona. Geomorphology, 14(4), 311-317. Parsons A.J., Bracken L., Peoppl , R., Wainwright J., Keesstra, S.D., 2015. Editorial: Introduction to special issue on connectivity in water and sediment dynamics. In press in Earth Surface Processes and Landforms. DOI: 10.1002/esp.3714 Poeppl, R.,E. Maroulis, J., Keesstra, S.D., 2016. Geomorphology. A conceptual connectivity framework for understanding geomorphic change in human-impacted fluvial systems. http://dx.doi.org/10.1016/j.geomorph.2016.07.033 Sadeghi, S.H.R., Gholami, L., Sharifi, E., Khaledi Darvishan, A., Homaee, M. Scale effect on runoff and soil loss control using rice straw mulch under laboratory conditions. (2015) Solid Earth, 6 (1), pp. 1-8.. DOI: http://dx.doi.org/10.5194/se-6-1-2015 Wainwright, J., Parsons, A.J., Schlesinger, W.H., Abrahams, A.D. 2002. Hydrology-vegetation interactions in areas of discontinuous flow on a semi-arid bajada, southern New Mexico. Journal of Arid Environments, 51(3), 319-338.

Running climate model on a commercial cloud computing environment: A case study using Community Earth System Model (CESM) on Amazon AWS

NASA Astrophysics Data System (ADS)

Chen, Xiuhong; Huang, Xianglei; Jiao, Chaoyi; Flanner, Mark G.; Raeker, Todd; Palen, Brock

2017-01-01

The suites of numerical models used for simulating climate of our planet are usually run on dedicated high-performance computing (HPC) resources. This study investigates an alternative to the usual approach, i.e. carrying out climate model simulations on commercially available cloud computing environment. We test the performance and reliability of running the CESM (Community Earth System Model), a flagship climate model in the United States developed by the National Center for Atmospheric Research (NCAR), on Amazon Web Service (AWS) EC2, the cloud computing environment by Amazon.com, Inc. StarCluster is used to create virtual computing cluster on the AWS EC2 for the CESM simulations. The wall-clock time for one year of CESM simulation on the AWS EC2 virtual cluster is comparable to the time spent for the same simulation on a local dedicated high-performance computing cluster with InfiniBand connections. The CESM simulation can be efficiently scaled with the number of CPU cores on the AWS EC2 virtual cluster environment up to 64 cores. For the standard configuration of the CESM at a spatial resolution of 1.9° latitude by 2.5° longitude, increasing the number of cores from 16 to 64 reduces the wall-clock running time by more than 50% and the scaling is nearly linear. Beyond 64 cores, the communication latency starts to outweigh the benefit of distributed computing and the parallel speedup becomes nearly unchanged.

Structural connectivity allows for multi-threading during rest: the structure of the cortex leads to efficient alternation between resting state exploratory behavior and default mode processing.

PubMed

Senden, Mario; Goebel, Rainer; Deco, Gustavo

2012-05-01

Despite the absence of stimulation or task conditions the cortex exhibits highly structured spatio-temporal activity patterns. These patterns are known as resting state networks (RSNs) and emerge as low-frequency fluctuations (<0.1 Hz) observed in the fMRI signal of human subjects during rest. We are interested in the relationship between structural connectivity of the cortex and the fluctuations exhibited during resting conditions. We are especially interested in the effect of degree of connectivity on resting state dynamics as the default mode network (DMN) is highly connected. We find in experimental resting fMRI data that the DMN is the functional network that is most frequently active and for the longest time. In large-scale computational simulations of the cortex based on the corresponding underlying DTI/DSI based neuroanatomical connectivity matrix, we additionally find a strong correlation between the mean degree of functional networks and the proportion of time they are active. By artificially modifying different types of neuroanatomical connectivity matrices in the model, we were able to demonstrate that only models based on structural connectivity containing hubs give rise to this relationship. We conclude that, during rest, the cortex alternates efficiently between explorations of its externally oriented functional repertoire and internally oriented processing as a consequence of the DMN's high degree of connectivity. Copyright © 2012 Elsevier Inc. All rights reserved.

Investigation of load current feed-forward control strategy for wind power grid connected inverter through VSC-HVDC

NASA Astrophysics Data System (ADS)

Liu, Hongbo; Liu, Haihan; Liu, Sitong; Peng, Huanhuan

2018-06-01

The VSC-HVDC connection system will be the effective transmission method for the large scale and long distance integrated wind farm. Because of the fluctuating power, the DC voltage will be over-voltage or under-voltage in transmission line which will affect the steady operation of the wind power integrating system. In order to mitigate the DC voltage variation of the grid-connected inverter on the grid side and improve the dynamic response of the system, a load current feed-forward control scheme is put forward. Firstly, this paper analyses stability of a system without additional feed-forward control based on double close loop. Secondly, the load current which can indicate the power changes is introduced to counteract the fluctuation of DC voltage in the improvement control scheme. By simulating the results show that the proposed control strategy can improve the dynamic response performance and mitigate the fluctuation of the active power output of the wind farm.

Behavior of susceptible-infected-susceptible epidemics on heterogeneous networks with saturation

NASA Astrophysics Data System (ADS)

Joo, Jaewook; Lebowitz, Joel L.

2004-06-01

We investigate saturation effects in susceptible-infected-susceptible models of the spread of epidemics in heterogeneous populations. The structure of interactions in the population is represented by networks with connectivity distribution P(k) , including scale-free (SF) networks with power law distributions P(k)˜ k-γ . Considering cases where the transmission of infection between nodes depends on their connectivity, we introduce a saturation function C(k) which reduces the infection transmission rate λ across an edge going from a node with high connectivity k . A mean-field approximation with the neglect of degree-degree correlation then leads to a finite threshold λc >0 for SF networks with 2<γ⩽3 . We also find, in this approximation, the fraction of infected individuals among those with degree k for λ close to λc . We investigate via computer simulation the contact process on a heterogeneous regular lattice and compare the results with those obtained from mean-field theory with and without neglect of degree-degree correlations.

A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks

PubMed Central

Sotiropoulos, Stamatios N.; Brookes, Matthew J.; Woolrich, Mark W.

2018-01-01

Over long timescales, neuronal dynamics can be robust to quite large perturbations, such as changes in white matter connectivity and grey matter structure through processes including learning, aging, development and certain disease processes. One possible explanation is that robust dynamics are facilitated by homeostatic mechanisms that can dynamically rebalance brain networks. In this study, we simulate a cortical brain network using the Wilson-Cowan neural mass model with conduction delays and noise, and use inhibitory synaptic plasticity (ISP) to dynamically achieve a spatially local balance between excitation and inhibition. Using MEG data from 55 subjects we find that ISP enables us to simultaneously achieve high correlation with multiple measures of functional connectivity, including amplitude envelope correlation and phase locking. Further, we find that ISP successfully achieves local E/I balance, and can consistently predict the functional connectivity computed from real MEG data, for a much wider range of model parameters than is possible with a model without ISP. PMID:29474352

Toward a geoinformatics framework for understanding the social and biophysical influences on urban nutrient pollution due to residential impervious service connectivity

NASA Astrophysics Data System (ADS)

Miles, B.; Band, L. E.

2012-12-01

Water sustainability has been recognized as a fundamental problem of science whose solution relies in part on high-performance computing. Stormwater management is a major concern of urban sustainability. Understanding interactions between urban landcover and stormwater nutrient pollution requires consideration of fine-scale residential stormwater management, which in turn requires high-resolution LIDAR and landcover data not provided through national spatial data infrastructure, as well as field observation at the household scale. The objectives of my research are twofold: (1) advance understanding of the relationship between residential stormwater management practices and the export of nutrient pollution from stormwater in urbanized ecosystems; and (2) improve the informatics workflows used in community ecohydrology modeling as applied to heterogeneous urbanized ecosystems. In support of these objectives, I present preliminary results from initial work to: (1) develop an ecohydrology workflow platform that automates data preparation while maintaining data provenance and model metadata to yield reproducible workflows and support model benchmarking; (2) perform field observation of existing patterns of residential rooftop impervious surface connectivity to stormwater networks; and (3) develop Regional Hydro-Ecological Simulation System (RHESSys) models for watersheds in Baltimore, MD (as part of the Baltimore Ecosystem Study (BES) NSF Long-Term Ecological Research (LTER) site) and Durham, NC (as part of the NSF Urban Long-Term Research Area (ULTRA) program); these models will be used to simulate nitrogen loading resulting from both baseline residential rooftop impervious connectivity and for disconnection scenarios (e.g. roof drainage to lawn v. engineered rain garden, upslope v. riparian). This research builds on work done as part of the NSF EarthCube Layered Architecture Concept Award where a RHESSys workflow is being implemented in an iRODS (integrated Rule-Oriented Data System) environment. Modeling the ecohydrology of urban ecosystems in a reliable and reproducible manner requires a flexible scientific workflow platform that allows rapid prototyping with large-scale spatial datasets and model refinement integrating expert knowledge with local datasets and household surveys.

Differentially Private Distributed Sensing

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

Fink, Glenn A.

The growth of the Internet of Things (IoT) creates the possibility of decentralized systems of sensing and actuation, potentially on a global scale. IoT devices connected to cloud networks can offer Sensing and Actuation as a Service (SAaaS) enabling networks of sensors to grow to a global scale. But extremely large sensor networks can violate privacy, especially in the case where IoT devices are mobile and connected directly to the behaviors of people. The thesis of this paper is that by adapting differential privacy (adding statistically appropriate noise to query results) to groups of geographically distributed sensors privacy could bemore » maintained without ever sending all values up to a central curator and without compromising the overall accuracy of the data collected. This paper outlines such a scheme and performs an analysis of differential privacy techniques adapted to edge computing in a simulated sensor network where ground truth is known. The positive and negative outcomes of employing differential privacy in distributed networks of devices are discussed and a brief research agenda is presented.« less

Toward direct pore-scale modeling of three-phase displacements

NASA Astrophysics Data System (ADS)

Mohammadmoradi, Peyman; Kantzas, Apostolos

2017-12-01

A stable spreading film between water and gas can extract a significant amount of bypassed non-aqueous phase liquid (NAPL) through immiscible three-phase gas/water injection cycles. In this study, the pore-scale displacement mechanisms by which NAPL is mobilized are incorporated into a three-dimensional pore morphology-based model under water-wet and capillary equilibrium conditions. The approach is pixel-based and the sequence of invasions is determined by the fluids' connectivity and the threshold capillary pressure of the advancing interfaces. In addition to the determination of three-phase spatial saturation profiles, residuals, and capillary pressure curves, dynamic finite element simulations are utilized to predict the effective permeabilities of the rock microtomographic images as reasonable representations of the geological formations under study. All the influential features during immiscible fluid flow in pore-level domains including wetting and spreading films, saturation hysteresis, capillary trapping, connectivity, and interface development strategies are taken into account. The capabilities of the model are demonstrated by the successful prediction of saturation functions for Berea sandstone and the accurate reconstruction of three-phase fluid occupancies through a micromodel.

Value of peripheral nodes in controlling multilayer scale-free networks

NASA Astrophysics Data System (ADS)

Zhang, Yan; Garas, Antonios; Schweitzer, Frank

2016-01-01

We analyze the controllability of a two-layer network, where driver nodes can be chosen randomly only from one layer. Each layer contains a scale-free network with directed links and the node dynamics depends on the incoming links from other nodes. We combine the in-degree and out-degree values to assign an importance value w to each node, and distinguish between peripheral nodes with low w and central nodes with high w . Based on numerical simulations, we find that the controllable part of the network is larger when choosing low w nodes to connect the two layers. The control is as efficient when peripheral nodes are driver nodes as it is for the case of more central nodes. However, if we assume a cost to utilize nodes that is proportional to their overall degree, utilizing peripheral nodes to connect the two layers or to act as driver nodes is not only the most cost-efficient solution, it is also the one that performs best in controlling the two-layer network among the different interconnecting strategies we have tested.

Spontaneous scale-free structure in adaptive networks with synchronously dynamical linking

NASA Astrophysics Data System (ADS)

Yuan, Wu-Jie; Zhou, Jian-Fang; Li, Qun; Chen, De-Bao; Wang, Zhen

2013-08-01

Inspired by the anti-Hebbian learning rule in neural systems, we study how the feedback from dynamical synchronization shapes network structure by adding new links. Through extensive numerical simulations, we find that an adaptive network spontaneously forms scale-free structure, as confirmed in many real systems. Moreover, the adaptive process produces two nontrivial power-law behaviors of deviation strength from mean activity of the network and negative degree correlation, which exists widely in technological and biological networks. Importantly, these scalings are robust to variation of the adaptive network parameters, which may have meaningful implications in the scale-free formation and manipulation of dynamical networks. Our study thus suggests an alternative adaptive mechanism for the formation of scale-free structure with negative degree correlation, which means that nodes of high degree tend to connect, on average, with others of low degree and vice versa. The relevance of the results to structure formation and dynamical property in neural networks is briefly discussed as well.

Unsteady loads due to propulsive lift configurations. Part D: The development of an experimental facility for the investigation of scaling effects on propulsive lift configurations

NASA Technical Reports Server (NTRS)

Haviland, J. K.; Herling, W. W.

1978-01-01

The design and construction of an experimental facility for the investigation of scaling effects in propulsive lift configurations are described. The facility was modeled after an existing full size NASA facility which consisted of a coaxial turbofan jet engine with a rectangular nozzle in a blown surface configuration. The flow field of the model facility was examined with and without a simulated wing surface in place at several locations downstream of the nozzle exit plane. Emphasis was placed on obtaining pressure measurements which were made with static probes and surface pressure ports connected via plastic tubing to condenser microphones for fluctuating measurements. Several pressure spectra were compared with those obtained from the NASA facility, and were used in a preliminary evaluation of scaling laws.

INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Consensus of Multi-Agent Systems with Prestissimo Scale-Free Networks

NASA Astrophysics Data System (ADS)

Yang, Hong-Yong; Lu, Lan; Cao, Ke-Cai; Zhang, Si-Ying

2010-04-01

In this paper, the relations of the network topology and the moving consensus of multi-agent systems are studied. A consensus-prestissimo scale-free network model with the static preferential-consensus attachment is presented on the rewired link of the regular network. The effects of the static preferential-consensus BA network on the algebraic connectivity of the topology graph are compared with the regular network. The robustness gain to delay is analyzed for variable network topology with the same scale. The time to reach the consensus is studied for the dynamic network with and without communication delays. By applying the computer simulations, it is validated that the speed of the convergence of multi-agent systems can be greatly improved in the preferential-consensus BA network model with different configuration.

North American extreme temperature events and related large scale meteorological patterns: A review of statistical methods, dynamics, modeling, and trends

DOE PAGES

Grotjahn, Richard; Black, Robert; Leung, Ruby; ...

2015-05-22

This paper reviews research approaches and open questions regarding data, statistical analyses, dynamics, modeling efforts, and trends in relation to temperature extremes. Our specific focus is upon extreme events of short duration (roughly less than 5 days) that affect parts of North America. These events are associated with large scale meteorological patterns (LSMPs). Methods used to define extreme events statistics and to identify and connect LSMPs to extreme temperatures are presented. Recent advances in statistical techniques can connect LSMPs to extreme temperatures through appropriately defined covariates that supplements more straightforward analyses. A wide array of LSMPs, ranging from synoptic tomore » planetary scale phenomena, have been implicated as contributors to extreme temperature events. Current knowledge about the physical nature of these contributions and the dynamical mechanisms leading to the implicated LSMPs is incomplete. There is a pressing need for (a) systematic study of the physics of LSMPs life cycles and (b) comprehensive model assessment of LSMP-extreme temperature event linkages and LSMP behavior. Generally, climate models capture the observed heat waves and cold air outbreaks with some fidelity. However they overestimate warm wave frequency and underestimate cold air outbreaks frequency, and underestimate the collective influence of low-frequency modes on temperature extremes. Climate models have been used to investigate past changes and project future trends in extreme temperatures. Overall, modeling studies have identified important mechanisms such as the effects of large-scale circulation anomalies and land-atmosphere interactions on changes in extreme temperatures. However, few studies have examined changes in LSMPs more specifically to understand the role of LSMPs on past and future extreme temperature changes. Even though LSMPs are resolvable by global and regional climate models, they are not necessarily well simulated so more research is needed to understand the limitations of climate models and improve model skill in simulating extreme temperatures and their associated LSMPs. Furthermore, the paper concludes with unresolved issues and research questions.« less

Single molecule translocation in smectics illustrates the challenge for time-mapping in simulations on multiple scales

NASA Astrophysics Data System (ADS)

Mukherjee, Biswaroop; Peter, Christine; Kremer, Kurt

2017-09-01

Understanding the connections between the characteristic dynamical time scales associated with a coarse-grained (CG) and a detailed representation is central to the applicability of the coarse-graining methods to understand molecular processes. The process of coarse graining leads to an accelerated dynamics, owing to the smoothening of the underlying free-energy landscapes. Often a single time-mapping factor is used to relate the time scales associated with the two representations. We critically examine this idea using a model system ideally suited for this purpose. Single molecular transport properties are studied via molecular dynamics simulations of the CG and atomistic representations of a liquid crystalline, azobenzene containing mesogen, simulated in the smectic and the isotropic phases. The out-of-plane dynamics in the smectic phase occurs via molecular hops from one smectic layer to the next. Hopping can occur via two mechanisms, with and without significant reorientation. The out-of-plane transport can be understood as a superposition of two (one associated with each mode of transport) independent continuous time random walks for which a single time-mapping factor would be rather inadequate. A comparison of the free-energy surfaces, relevant to the out-of-plane transport, qualitatively supports the above observations. Thus, this work underlines the need for building CG models that exhibit both structural and dynamical consistency to the underlying atomistic model.

A large-scale dynamo and magnetoturbulence in rapidly rotating core-collapse supernovae.

PubMed

Mösta, Philipp; Ott, Christian D; Radice, David; Roberts, Luke F; Schnetter, Erik; Haas, Roland

2015-12-17

Magnetohydrodynamic turbulence is important in many high-energy astrophysical systems, where instabilities can amplify the local magnetic field over very short timescales. Specifically, the magnetorotational instability and dynamo action have been suggested as a mechanism for the growth of magnetar-strength magnetic fields (of 10(15) gauss and above) and for powering the explosion of a rotating massive star. Such stars are candidate progenitors of type Ic-bl hypernovae, which make up all supernovae that are connected to long γ-ray bursts. The magnetorotational instability has been studied with local high-resolution shearing-box simulations in three dimensions, and with global two-dimensional simulations, but it is not known whether turbulence driven by this instability can result in the creation of a large-scale, ordered and dynamically relevant field. Here we report results from global, three-dimensional, general-relativistic magnetohydrodynamic turbulence simulations. We show that hydromagnetic turbulence in rapidly rotating protoneutron stars produces an inverse cascade of energy. We find a large-scale, ordered toroidal field that is consistent with the formation of bipolar magnetorotationally driven outflows. Our results demonstrate that rapidly rotating massive stars are plausible progenitors for both type Ic-bl supernovae and long γ-ray bursts, and provide a viable mechanism for the formation of magnetars. Moreover, our findings suggest that rapidly rotating massive stars might lie behind potentially magnetar-powered superluminous supernovae.

Comparing Shock geometry from MHD simulation to that from the Q/A-scaling analysis

NASA Astrophysics Data System (ADS)

Li, G.; Zhao, L.; Jin, M.

2017-12-01

In large SEP events, ions can be accelerated at CME-driven shocks to very high energies. Spectra of heavy ions in many large SEP events show features such as roll-overs or spectral breaks. In some events when the spectra are plotted in energy/nucleon they can be shifted relatively to each other so that the spectra align. The amount of shift is charge-to-mass ratio (Q/A) dependent and varies from event to event. In the work of Li et al. (2009), the Q/A dependences of the scaling is related to shock geometry when the CME-driven shock is close to the Sun. For events where multiple in-situ spacecraft observations exist, one may expect that different spacecraft are connected to different portions of the CME-driven shock that have different shock geometries, therefore yielding different Q/A dependence. At the same time, shock geometry can be also obtained from MHD simulations. This means we can compare shock geometry from two completely different approaches: one from MHD simulation and the other from in-situ spectral fitting. In this work, we examine this comparison for selected events.

A multi-scale experimental and simulation approach for fractured subsurface systems

NASA Astrophysics Data System (ADS)

Viswanathan, H. S.; Carey, J. W.; Frash, L.; Karra, S.; Hyman, J.; Kang, Q.; Rougier, E.; Srinivasan, G.

2017-12-01

Fractured systems play an important role in numerous subsurface applications including hydraulic fracturing, carbon sequestration, geothermal energy and underground nuclear test detection. Fractures that range in scale from microns to meters and their structure control the behavior of these systems which provide over 85% of our energy and 50% of US drinking water. Determining the key mechanisms in subsurface fractured systems has been impeded due to the lack of sophisticated experimental methods to measure fracture aperture and connectivity, multiphase permeability, and chemical exchange capacities at the high temperature, pressure, and stresses present in the subsurface. In this study, we developed and use microfluidic and triaxial core flood experiments required to reveal the fundamental dynamics of fracture-fluid interactions. In addition we have developed high fidelity fracture propagation and discrete fracture network flow models to simulate these fractured systems. We also have developed reduced order models of these fracture simulators in order to conduct uncertainty quantification for these systems. We demonstrate an integrated experimental/modeling approach that allows for a comprehensive characterization of fractured systems and develop models that can be used to optimize the reservoir operating conditions over a range of subsurface conditions.

Habitat continuity and stepping-stone oceanographic distances explain population genetic connectivity of the brown alga Cystoseira amentacea.

PubMed

Buonomo, Roberto; Assis, Jorge; Fernandes, Francisco; Engelen, Aschwin H; Airoldi, Laura; Serrão, Ester A

2017-02-01

Effective predictive and management approaches for species occurring in a metapopulation structure require good understanding of interpopulation connectivity. In this study, we ask whether population genetic structure of marine species with fragmented distributions can be predicted by stepping-stone oceanographic transport and habitat continuity, using as model an ecosystem-structuring brown alga, Cystoseira amentacea var. stricta. To answer this question, we analysed the genetic structure and estimated the connectivity of populations along discontinuous rocky habitat patches in southern Italy, using microsatellite markers at multiple scales. In addition, we modelled the effect of rocky habitat continuity and ocean circulation on gene flow by simulating Lagrangian particle dispersal based on ocean surface currents allowing multigenerational stepping-stone dynamics. Populations were highly differentiated, at scales from few metres up to thousands of kilometres. The best possible model fit to explain the genetic results combined current direction, rocky habitat extension and distance along the coast among rocky sites. We conclude that a combination of variable suitable habitat and oceanographic transport is a useful predictor of genetic structure. This relationship provides insight into the mechanisms of dispersal and the role of life-history traits. Our results highlight the importance of spatially explicit modelling of stepping-stone dynamics and oceanographic directional transport coupled with habitat suitability, to better describe and predict marine population structure and differentiation. This study also suggests the appropriate spatial scales for the conservation, restoration and management of species that are increasingly affected by habitat modifications. © 2016 John Wiley & Sons Ltd.

Persistent shoreline shape induced from offshore geologic framework: Effects of shoreface connected ridges

USGS Publications Warehouse

Safak, Ilgar; List, Jeffrey; Warner, John C.; Schwab, William C.

2017-01-01

Mechanisms relating offshore geologic framework to shoreline evolution are determined through geologic investigations, oceanographic deployments, and numerical modeling. Analysis of shoreline positions from the past 50 years along Fire Island, New York, a 50 km long barrier island, demonstrates a persistent undulating shape along the western half of the island. The shelf offshore of these persistent undulations is characterized with shoreface-connected sand ridges (SFCR) of a similar alongshore length scale, leading to a hypothesis that the ridges control the shoreline shape through the modification of flow. To evaluate this, a hydrodynamic model was configured to start with the US East Coast and scale down to resolve the Fire Island nearshore. The model was validated using observations along western Fire Island and buoy data, and used to compute waves, currents and sediment fluxes. To isolate the influence of the SFCR on the generation of the persistent shoreline shape, simulations were performed with a linearized nearshore bathymetry to remove alongshore transport gradients associated with shoreline shape. The model accurately predicts the scale and variation of the alongshore transport that would generate the persistent shoreline undulations. In one location, however, the ridge crest connects to the nearshore and leads to an offshore-directed transport that produces a difference in the shoreline shape. This qualitatively supports the hypothesized effect of cross-shore fluxes on coastal evolution. Alongshore flows in the nearshore during a representative storm are driven by wave breaking, vortex force, advection and pressure gradient, all of which are affected by the SFCR.

Hyporheic less-mobile porosity and solute transport in porous media

NASA Astrophysics Data System (ADS)

MahmoodPoorDehkordy, F.; Briggs, M. A.; Day-Lewis, F. D.; Scruggs, C.; Singha, K.; Zarnetske, J. P.; Lane, J. W., Jr.; Bagtzoglou, A. C.

2017-12-01

Solute transport and reactive processes are strongly influenced by hydrodynamic exchange with the hyporheic zone. Contaminant transport and redox zonation in the hyporheic zone and near-stream aquifer can be impacted by the exchange between mobile and less-mobile porosity zones in heterogeneous porous media. Less-mobile porosity zones can be created by fine materials with tight pore throats (e.g. clay, organics) and in larger, well-connected pores down gradient of flow obstructions (e.g. sand behind cobbles). Whereas fluid sampling is primarily responsive to the more-mobile domain, tracking solute tracer dynamics by geoelectrical methods provides direct information about both more- and less-mobile zones. During tracer injection through porous media of varied pore connectivity, a lag between fluid and bulk electrical conductivity is observed, creating a hysteresis loop when plotted in conductivity space. Thus, the combination of simultaneous fluid and bulk electrical conductivity measurements enables a much improved quantification of less-mobile solute dynamics compared to traditional fluid-only sampling approaches. We have demonstrated the less-mobile porosity exchange in laboratory-scale column experiments verified by simulation models. The experimental approach has also been applied to streambed sediments in column and reach-scale field experiments and verified using numerical simulation. Properties of the resultant hysteresis loops can be used to estimate exchange parameters of less-mobile porosity. Our integrated approach combining field experiments, laboratory experiments, and numerical modeling provides new insights into the effect of less-mobile porosity on solute transport in the hyporheic zone.

Dispersion in 2D network: Effects of mixing rule at nodes and molecular diffusion

NASA Astrophysics Data System (ADS)

Wang, Y.; Tao, Q.; Li, M.

2017-12-01

We simulate solute transport in 2D network backbone characterized by pore connectivity and pore heterogeneity by particle-tracking method. In order to ensure the dispersion coefficient reaching an asymptotic value, we upscale dispersion from pore-scale to meter-scale by using periodic boundary condition. As comparison, two different flow mechanisms without or with dispersion in a capillary tube, namely mean flow and Taylor-Aris dispersion, are introduced to investigate the evolution of solute spreading. The longitudinal dispersion coefficient DLM without dispersion in a pipe can roughly be regarded as a parameter to quantify the impact of microscopic structure of porous media on solute spreading, which is smaller than that value DL of Taylor-Aris dispersion. The difference between them decreases with the enhancement of the disorder. The mixing rule at nodes has a minor effect on longitudinal spreading, but has a significant effect on transverse spreading, especially for the nearly homogeneous media. An increase of the disorder in network achieved by increasing pore size heterogeneity or/and decreasing pore connectivity diminishes the difference between two mixing rules. Besides, the evolution of longitudinal dispersion coefficient over diffusion presents three different patterns at different velocities for homogenous media, such as monotonically increasing trend, decreasing first and then increasing trend and monotonically decreasing trend. But all are replaced by power law for a high disorder. The simulation results also accurately predict the experimental dependence of the longitudinal coefficient on Peclet number Pe.

Prominence Mass Supply and the Cavity

NASA Technical Reports Server (NTRS)

Schmit, Donald J.; Gibson, S.; Luna, M.; Karpen, J.; Innes, D.

2013-01-01

A prevalent but untested paradigm is often used to describe the prominence-cavity system; the cavity is under-dense because it it evacuated by supplying mass to the condensed prominence. The thermal non-equilibrium (TNE) model of prominence formation offers a theoretical framework to predict the thermodynamic evolutin of the prominence and the surrounding corona. We examine the evidence for a prominence-cavity connection by comparing the TNE model and diagnostics of dynamic extreme ultraviolet (EUV) emission surrounding the prominence, specifically prominence horns. Horns are correlated extensions of prminence plasma and coronal plasma which appear to connect the prominence and cavity. The TNE model predicts that large-scale brightenings will occur in the Solar Dynamics Observatory Atmospheric Imaging Assembly 171 A badpass near he prominence that are associated with the cooling phase of condensation formation. In our simulations, variations in the magnitude of footpoint heating lead to variations in the duration, spatial scale, and temporal offset between emission enhancements in the other EUV bandpasses. While these predictions match well a subset of the horn observations, the range of variations in the observed structures is not captured by the model. We discuss the implications of one-dimensional loop simulations for the three-dimensional time-averaged equilibrium in the prominence and the cavity. Evidence suggests that horns are likely caused by condensing prominence plasma, but the larger question of whether this process produces a density-depleted cavity requires a more tightly constrained model of heating and better knowledge of the associated magnetic structure.

Critical Dynamics of Gravito-Convective Mixing in Geological Carbon Sequestration

PubMed Central

Soltanian, Mohamad Reza; Amooie, Mohammad Amin; Dai, Zhenxue; Cole, David; Moortgat, Joachim

2016-01-01

When CO2 is injected in saline aquifers, dissolution causes a local increase in brine density that can cause Rayleigh-Taylor-type gravitational instabilities. Depending on the Rayleigh number, density-driven flow may mix dissolved CO2 throughout the aquifer at fast advective time-scales through convective mixing. Heterogeneity can impact density-driven flow to different degrees. Zones with low effective vertical permeability may suppress fingering and reduce vertical spreading, while potentially increasing transverse mixing. In more complex heterogeneity, arising from the spatial organization of sedimentary facies, finger propagation is reduced in low permeability facies, but may be enhanced through more permeable facies. The connectivity of facies is critical in determining the large-scale transport of CO2-rich brine. We perform high-resolution finite element simulations of advection-diffusion transport of CO2 with a focus on facies-based bimodal heterogeneity. Permeability fields are generated by a Markov Chain approach, which represent facies architecture by commonly observed characteristics such as volume fractions. CO2 dissolution and phase behavior are modeled with the cubic-plus-association equation-of-state. Our results show that the organization of high-permeability facies and their connectivity control the dynamics of gravitationally unstable flow. We discover new flow regimes in both homogeneous and heterogeneous media and present quantitative scaling relations for their temporal evolution. PMID:27808178

3D Reconnection and SEP Considerations in the CME-Flare Problem

NASA Astrophysics Data System (ADS)

Moschou, S. P.; Cohen, O.; Drake, J. J.; Sokolov, I.; Borovikov, D.; Alvarado Gomez, J. D.; Garraffo, C.

2017-12-01

Reconnection is known to play a major role in particle acceleration in both solar and astrophysical regimes, yet little is known about its connection with the global scales and its comparative contribution in the generation of SEPs with respect to other acceleration mechanisms, such as the shock at a fast CME front, in the presence of a global structure such as a CME. Coupling efforts, combining both particle and global scales, are necessary to answer questions about the fundamentals of the energetic processes evolved. We present such a coupling modeling effort that looks into particle acceleration through reconnection in a self-consistent CME-flare model in both particle and fluid regimes. Of special interest is the supra-thermal component of the acceleration due to the reconnection that will at a later time interact colliding with the solar atmospheric material of the more dense chromospheric layer and radiate in hard X- and γ-rays for super-thermal electrons and protons respectively. Two cutting edge computational codes are used to capture the global CME and flare dynamics, specifically a two fluid MHD code and a 3D PIC code for the flare scales. Finally, we are connecting the simulations with current observations in different wavelengths in an effort to shed light to the unified CME-flare picture.

Variability in oceanographic barriers to coral larval dispersal: Do currents shape biodiversity?

NASA Astrophysics Data System (ADS)

Thompson, D. M.; Kleypas, J.; Castruccio, F.; Curchitser, E. N.; Pinsky, M. L.; Jönsson, B.; Watson, J. R.

2018-07-01

The global center of marine biodiversity is located in the western tropical Pacific in a region known as the "Coral Triangle" (CT). This region is also considered the most threatened of all coral reef regions, because multiple impacts, including rising temperatures and coral bleaching, have already caused high mortality of reef corals over large portions of the CT. Larval dispersal and recruitment play a critical role in reef recovery after such disturbances, but our understanding of reproductive connectivity between reefs is limited by a paucity of observations. Oceanographic modeling can provide an economical and efficient way to augment our understanding of reef connectivity, particularly over an area as large as the CT, where marine ecosystem management has become a priority. This work combines daily averaged surface current velocity and direction from a Regional Ocean Modeling System developed for the CT region (CT-ROMS) with a Lagrangian particle tracking tool (TRACMASS) to investigate the probability of larval transport between reefs for a typical broadcasting coral. A 47-year historical simulation (1960-2006) was used to analyze the potential connectivity, the physical drivers of larval transport, and its variability following bi-annual spawning events in April and September. Potential connectivity between reefs was highly variable from year to year, emphasizing the need for long simulations. The results suggest that although reefs in this region are highly self-seeded, comparatively rare long-distance dispersal events may play a vital role in shaping regional patterns of reef biodiversity and recovery following disturbance. The spatial pattern of coral "subpopulations," which are based on the potential connectivity between reefs, agrees with observed regional-scale patterns of biodiversity, suggesting that the physical barriers to larval dispersal are a first-order driver of coral biodiversity in the CT region. These physical barriers persist through the 21st Century when the model is forced with the Community Earth System Model (CESM) RCP8.5 climate scenario, despite some regional changes in connectivity between reefs.

Temperature dependence of creep compliance of highly cross-linked epoxy: A molecular simulation study

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

Khabaz, Fardin, E-mail: rajesh.khare@ttu.edu; Khare, Ketan S., E-mail: rajesh.khare@ttu.edu; Khare, Rajesh, E-mail: rajesh.khare@ttu.edu

2014-05-15

We have used molecular dynamics (MD) simulations to study the effect of temperature on the creep compliance of neat cross-linked epoxy. Experimental studies of mechanical behavior of cross-linked epoxy in literature commonly report creep compliance values, whereas molecular simulations of these systems have primarily focused on the Young’s modulus. In this work, in order to obtain a more direct comparison between experiments and simulations, atomistically detailed models of the cross-linked epoxy are used to study their creep compliance as a function of temperature using MD simulations. The creep tests are performed by applying a constant tensile stress and monitoring themore » resulting strain in the system. Our results show that simulated values of creep compliance increase with an increase in both time and temperature. We believe that such calculations of the creep compliance, along with the use of time temperature superposition, hold great promise in connecting the molecular insight obtained from molecular simulation at small length- and time-scales with the experimental behavior of such materials. To the best of our knowledge, this work is the first reported effort that investigates the creep compliance behavior of cross-linked epoxy using MD simulations.« less

Effect of simulated rill erosion on overland flow connectivity in synthetically generated fields

NASA Astrophysics Data System (ADS)

Penuela Fernandez, Andres; Rocio Rodriguez Pleguezuelo, Carmen; Javaux, Mathieu; Bielders, Charles L.

2014-05-01

Preferential flow paths developed during rill erosion processes connect different parts of the soil surface that may increase the degree of connectivity and hence the hydrological response of the soil surface. However, few studies have tried to quantify the effect of rill networks on overland flow connectivity. For this purpose, simulated rill networks were generated by the RillGrow erosion model (Favis-Mortlock, 1998; Favis-Mortlock et al. 2000) on synthetically generated fields. To characterize the hydrological connectivity a functional connectivity indicator called the relative surface connection function (RSCf) (Antoine et al. 2009) was used. This indicator, which relates the area connected to the outflow boundary to the degree of filling of maximum depression storage (MDS), is fast to compute and was previously shown to be able to efficiently discriminate between contrasted connectivity scenarios. The RSCf function was calculated for different DEM obtained at different times during the development of the simulated rill networks. The evolution of overland flow connectivity was then quantified and compared at these different time steps. The results of this study showed that the changes in microtopography resulting from the simulated rill erosion have a strong impact on the hydrological connectivity as reflected in the RSCf. Furthermore, the results show that the evolution of the RSCf may allow identifying different types of erosion since the shape of the RSCf only starts to change when rill networks are visualized on the surface.

Rediscovering the doldrums in high resolution simulations of the tropical Atlantic

NASA Astrophysics Data System (ADS)

Klocke, Daniel; Brueck, Matthias; Stevens, Bjorn

2017-04-01

When sailors started crossing the tropics, they quickly discovered and learned to fear the belt of calm and variable winds around the ITCZ. They named this region the doldrums. The doldrums are such a persistent and dominant part of the general circulation that they were marked and described in the earliest maps and studies concerned with the winds over the oceans. After the invention of steam ships the interest in the doldrums faded and the doldrums mainly lived on in colloquial language as an expression for stagnation, listlessness and depression describing the experience of the sailors rather than the region. The research focus shifted to the ITCZ, which describes more the position of a variable front of strong convergence and maximum precipitation residing in the doldrums. GCMs continue to correctly simulate the position of the ITCZ, which is partly determined by small scale processes which are parameterized. In support of the NARVAL measurement campaign, convection permitting simulations were conducted for a winter and a summer months covering the tropical Atlantic (9000x3300 km) with the Icosahedral Nonhydrostatic Model (ICON). These simulations reveal the doldrums with their embedded convective structures including cold pools, convective storms and squall lines. The calms and the high variability of the wind direction between the trades connected to convective activity in the ITCZ is presented using the high resolution simulations and are compared to historical and current observations. Comparisons with current NWP models using parameterized convection show that parameterized models struggle to reproduce some of the essential features connected to the doldrums.

Dynamic neural network models of the premotoneuronal circuitry controlling wrist movements in primates.

PubMed

Maier, M A; Shupe, L E; Fetz, E E

2005-10-01

Dynamic recurrent neural networks were derived to simulate neuronal populations generating bidirectional wrist movements in the monkey. The models incorporate anatomical connections of cortical and rubral neurons, muscle afferents, segmental interneurons and motoneurons; they also incorporate the response profiles of four populations of neurons observed in behaving monkeys. The networks were derived by gradient descent algorithms to generate the eight characteristic patterns of motor unit activations observed during alternating flexion-extension wrist movements. The resulting model generated the appropriate input-output transforms and developed connection strengths resembling those in physiological pathways. We found that this network could be further trained to simulate additional tasks, such as experimentally observed reflex responses to limb perturbations that stretched or shortened the active muscles, and scaling of response amplitudes in proportion to inputs. In the final comprehensive network, motor units are driven by the combined activity of cortical, rubral, spinal and afferent units during step tracking and perturbations. The model displayed many emergent properties corresponding to physiological characteristics. The resulting neural network provides a working model of premotoneuronal circuitry and elucidates the neural mechanisms controlling motoneuron activity. It also predicts several features to be experimentally tested, for example the consequences of eliminating inhibitory connections in cortex and red nucleus. It also reveals that co-contraction can be achieved by simultaneous activation of the flexor and extensor circuits without invoking features specific to co-contraction.

Synapse-Centric Mapping of Cortical Models to the SpiNNaker Neuromorphic Architecture

PubMed Central

Knight, James C.; Furber, Steve B.

2016-01-01

While the adult human brain has approximately 8.8 × 1010 neurons, this number is dwarfed by its 1 × 1015 synapses. From the point of view of neuromorphic engineering and neural simulation in general this makes the simulation of these synapses a particularly complex problem. SpiNNaker is a digital, neuromorphic architecture designed for simulating large-scale spiking neural networks at speeds close to biological real-time. Current solutions for simulating spiking neural networks on SpiNNaker are heavily inspired by work on distributed high-performance computing. However, while SpiNNaker shares many characteristics with such distributed systems, its component nodes have much more limited resources and, as the system lacks global synchronization, the computation performed on each node must complete within a fixed time step. We first analyze the performance of the current SpiNNaker neural simulation software and identify several problems that occur when it is used to simulate networks of the type often used to model the cortex which contain large numbers of sparsely connected synapses. We then present a new, more flexible approach for mapping the simulation of such networks to SpiNNaker which solves many of these problems. Finally we analyze the performance of our new approach using both benchmarks, designed to represent cortical connectivity, and larger, functional cortical models. In a benchmark network where neurons receive input from 8000 STDP synapses, our new approach allows 4× more neurons to be simulated on each SpiNNaker core than has been previously possible. We also demonstrate that the largest plastic neural network previously simulated on neuromorphic hardware can be run in real time using our new approach: double the speed that was previously achieved. Additionally this network contains two types of plastic synapse which previously had to be trained separately but, using our new approach, can be trained simultaneously. PMID:27683540

Comparison of neuronal spike exchange methods on a Blue Gene/P supercomputer.

PubMed

Hines, Michael; Kumar, Sameer; Schürmann, Felix

2011-01-01

For neural network simulations on parallel machines, interprocessor spike communication can be a significant portion of the total simulation time. The performance of several spike exchange methods using a Blue Gene/P (BG/P) supercomputer has been tested with 8-128 K cores using randomly connected networks of up to 32 M cells with 1 k connections per cell and 4 M cells with 10 k connections per cell, i.e., on the order of 4·10(10) connections (K is 1024, M is 1024(2), and k is 1000). The spike exchange methods used are the standard Message Passing Interface (MPI) collective, MPI_Allgather, and several variants of the non-blocking Multisend method either implemented via non-blocking MPI_Isend, or exploiting the possibility of very low overhead direct memory access (DMA) communication available on the BG/P. In all cases, the worst performing method was that using MPI_Isend due to the high overhead of initiating a spike communication. The two best performing methods-the persistent Multisend method using the Record-Replay feature of the Deep Computing Messaging Framework DCMF_Multicast; and a two-phase multisend in which a DCMF_Multicast is used to first send to a subset of phase one destination cores, which then pass it on to their subset of phase two destination cores-had similar performance with very low overhead for the initiation of spike communication. Departure from ideal scaling for the Multisend methods is almost completely due to load imbalance caused by the large variation in number of cells that fire on each processor in the interval between synchronization. Spike exchange time itself is negligible since transmission overlaps with computation and is handled by a DMA controller. We conclude that ideal performance scaling will be ultimately limited by imbalance between incoming processor spikes between synchronization intervals. Thus, counterintuitively, maximization of load balance requires that the distribution of cells on processors should not reflect neural net architecture but be randomly distributed so that sets of cells which are burst firing together should be on different processors with their targets on as large a set of processors as possible.

Using SMAP Data to Investigate the Role of Soil Moisture Variability on Realtime Flood Forecasting

NASA Astrophysics Data System (ADS)

Krajewski, W. F.; Jadidoleslam, N.; Mantilla, R.

2017-12-01

The Iowa Flood Center has developed a regional high-resolution flood-forecasting model for the state of Iowa that decomposes the landscape into hillslopes of about 0.1 km2. For the model to benefit, through data assimilation, from SMAP observations of soil moisture (SM) at scales of approximately 100 km2, we are testing a framework to connect SMAP-scale observations to the small-scale SM variability calculated by our rainfall-runoff models. As a step in this direction, we performed data analyses of 15-min point SM observations using a network of about 30 TDR instruments spread throughout the state. We developed a stochastic point-scale SM model that captures 1) SM increases due to rainfall inputs, and 2) SM decay during dry periods. We use a power law model to describe soil moisture decay during dry periods, and a single parameter logistic curve to describe precipitation feedback on soil moisture. We find that the parameters of the models behave as time-independent random variables with stationary distributions. Using data-based simulation, we explore differences in the dynamical range of variability of hillslope and SMAP-scale domains. The simulations allow us to predict the runoff field and streamflow hydrographs for the state of Iowa during the three largest flooding periods (2008, 2014, and 2016). We also use the results to determine the reduction in forecast uncertainty from assimilation of unbiased SMAP-scale soil moisture observations.

The effects of habitat connectivity and regional heterogeneity on artificial pond metacommunities.

PubMed

Pedruski, Michael T; Arnott, Shelley E

2011-05-01

Habitat connectivity and regional heterogeneity represent two factors likely to affect biodiversity across different spatial scales. We performed a 3 × 2 factorial design experiment to investigate the effects of connectivity, heterogeneity, and their interaction on artificial pond communities of freshwater invertebrates at the local (α), among-community (β), and regional (γ) scales. Despite expectations that the effects of connectivity would depend on levels of regional heterogeneity, no significant interactions were found for any diversity index investigated at any spatial scale. While observed responses of biodiversity to connectivity and heterogeneity depended to some extent on the diversity index and spatial partitioning formula used, the general pattern shows that these factors largely act at the β scale, as opposed to the α or γ scales. We conclude that the major role of connectivity in aquatic invertebrate communities is to act as a homogenizing force with relatively little effect on diversity at the α or γ levels. Conversely, heterogeneity acts as a force maintaining differences between communities.

Mean-cluster approach indicates cell sorting time scales are determined by collective dynamics

NASA Astrophysics Data System (ADS)

Beatrici, Carine P.; de Almeida, Rita M. C.; Brunnet, Leonardo G.

2017-03-01

Cell migration is essential to cell segregation, playing a central role in tissue formation, wound healing, and tumor evolution. Considering random mixtures of two cell types, it is still not clear which cell characteristics define clustering time scales. The mass of diffusing clusters merging with one another is expected to grow as td /d +2 when the diffusion constant scales with the inverse of the cluster mass. Cell segregation experiments deviate from that behavior. Explanations for that could arise from specific microscopic mechanisms or from collective effects, typical of active matter. Here we consider a power law connecting diffusion constant and cluster mass to propose an analytic approach to model cell segregation where we explicitly take into account finite-size corrections. The results are compared with active matter model simulations and experiments available in the literature. To investigate the role played by different mechanisms we considered different hypotheses describing cell-cell interaction: differential adhesion hypothesis and different velocities hypothesis. We find that the simulations yield normal diffusion for long time intervals. Analytic and simulation results show that (i) cluster evolution clearly tends to a scaling regime, disrupted only at finite-size limits; (ii) cluster diffusion is greatly enhanced by cell collective behavior, such that for high enough tendency to follow the neighbors, cluster diffusion may become independent of cluster size; (iii) the scaling exponent for cluster growth depends only on the mass-diffusion relation, not on the detailed local segregation mechanism. These results apply for active matter systems in general and, in particular, the mechanisms found underlying the increase in cell sorting speed certainly have deep implications in biological evolution as a selection mechanism.

Large-Eddy Simulations of Radiatively Driven Convection: Sensitivities to the Representation of Small Scales.

NASA Astrophysics Data System (ADS)

Stevens, Bjorn; Moeng, Chin-Hoh; Sullivan, Peter P.

1999-12-01

Large-eddy simulations of a smoke cloud are examined with respect to their sensitivity to small scales as manifest in either the grid spacing or the subgrid-scale (SGS) model. Calculations based on a Smagorinsky SGS model are found to be more sensitive to the effective resolution of the simulation than are calculations based on the prognostic turbulent kinetic energy (TKE) SGS model. The difference between calculations based on the two SGS models is attributed to the advective transport, diffusive transport, and/or time-rate-of-change terms in the TKE equation. These terms are found to be leading order in the entrainment zone and allow the SGS TKE to behave in a way that tends to compensate for changes that result in larger or smaller resolved scale entrainment fluxes. This compensating behavior of the SGS TKE model is attributed to the fact that changes that reduce the resolved entrainment flux (viz., values of the eddy viscosity in the upper part of the PBL) simultaneously tend to increase the buoyant production of SGS TKE in the radiatively destabilized portion of the smoke cloud. Increased production of SGS TKE in this region then leads to increased amounts of transported, or fossil, SGS TKE in the entrainment zone itself, which in turn leads to compensating increases in the SGS entrainment fluxes. In the Smagorinsky model, the absence of a direct connection between SGS TKE in the entrainment and radiatively destabilized zones prevents this compensating mechanism from being active, and thus leads to calculations whose entrainment rate sensitivities as a whole reflect the sensitivities of the resolved-scale fluxes to values of upper PBL eddy viscosities.

Transition from Connected to Fragmented Vegetation across an Environmental Gradient: Scaling Laws in Ecotone Geometry.

PubMed

Gastner, Michael T; Oborny, Beata; Zimmermann, D K; Pruessner, Gunnar

2009-07-01

A change in the environmental conditions across space-for example, altitude or latitude-can cause significant changes in the density of a vegetation type and, consequently, in spatial connectivity. We use spatially explicit simulations to study the transition from connected to fragmented vegetation. A static (gradient percolation) model is compared to dynamic (gradient contact process) models. Connectivity is characterized from the perspective of various species that use this vegetation type for habitat and differ in dispersal or migration range, that is, "step length" across the landscape. The boundary of connected vegetation delineated by a particular step length is termed the " hull edge." We found that for every step length and for every gradient, the hull edge is a fractal with dimension 7/4. The result is the same for different spatial models, suggesting that there are universal laws in ecotone geometry. To demonstrate that the model is applicable to real data, a hull edge of fractal dimension 7/4 is shown on a satellite image of a piñon-juniper woodland on a hillside. We propose to use the hull edge to define the boundary of a vegetation type unambiguously. This offers a new tool for detecting a shift of the boundary due to a climate change.

Looking at the Disordered Proteins through the Computational Microscope.

PubMed

Das, Payel; Matysiak, Silvina; Mittal, Jeetain

2018-05-23

Intrinsically disordered proteins (IDPs) have attracted wide interest over the past decade due to their surprising prevalence in the proteome and versatile roles in cell physiology and pathology. A large selection of IDPs has been identified as potential targets for therapeutic intervention. Characterizing the structure-function relationship of disordered proteins is therefore an essential but daunting task, as these proteins can adapt transient structure, necessitating a new paradigm for connecting structural disorder to function. Molecular simulation has emerged as a natural complement to experiments for atomic-level characterizations and mechanistic investigations of this intriguing class of proteins. The diverse range of length and time scales involved in IDP function requires performing simulations at multiple levels of resolution. In this Outlook, we focus on summarizing available simulation methods, along with a few interesting example applications. We also provide an outlook on how these simulation methods can be further improved in order to provide a more accurate description of IDP structure, binding, and assembly.

Influence of grid resolution, parcel size and drag models on bubbling fluidized bed simulation

DOE PAGES

Lu, Liqiang; Konan, Arthur; Benyahia, Sofiane

2017-06-02

Here in this paper, a bubbling fluidized bed is simulated with different numerical parameters, such as grid resolution and parcel size. We examined also the effect of using two homogeneous drag correlations and a heterogeneous drag based on the energy minimization method. A fast and reliable bubble detection algorithm was developed based on the connected component labeling. The radial and axial solids volume fraction profiles are compared with experiment data and previous simulation results. These results show a significant influence of drag models on bubble size and voidage distributions and a much less dependence on numerical parameters. With a heterogeneousmore » drag model that accounts for sub-scale structures, the void fraction in the bubbling fluidized bed can be well captured with coarse grid and large computation parcels. Refining the CFD grid and reducing the parcel size can improve the simulation results but with a large increase in computation cost.« less

IGMS: An Integrated ISO-to-Appliance Scale Grid Modeling System

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

Palmintier, Bryan; Hale, Elaine; Hansen, Timothy M.

This paper describes the Integrated Grid Modeling System (IGMS), a novel electric power system modeling platform for integrated transmission-distribution analysis that co-simulates off-the-shelf tools on high performance computing (HPC) platforms to offer unprecedented resolution from ISO markets down to appliances and other end uses. Specifically, the system simultaneously models hundreds or thousands of distribution systems in co-simulation with detailed Independent System Operator (ISO) markets and AGC-level reserve deployment. IGMS uses a new MPI-based hierarchical co-simulation framework to connect existing sub-domain models. Our initial efforts integrate opensource tools for wholesale markets (FESTIV), bulk AC power flow (MATPOWER), and full-featured distribution systemsmore » including physics-based end-use and distributed generation models (many instances of GridLAB-D[TM]). The modular IGMS framework enables tool substitution and additions for multi-domain analyses. This paper describes the IGMS tool, characterizes its performance, and demonstrates the impacts of the coupled simulations for analyzing high-penetration solar PV and price responsive load scenarios.« less

Looking at the Disordered Proteins through the Computational Microscope

PubMed Central

2018-01-01

Intrinsically disordered proteins (IDPs) have attracted wide interest over the past decade due to their surprising prevalence in the proteome and versatile roles in cell physiology and pathology. A large selection of IDPs has been identified as potential targets for therapeutic intervention. Characterizing the structure–function relationship of disordered proteins is therefore an essential but daunting task, as these proteins can adapt transient structure, necessitating a new paradigm for connecting structural disorder to function. Molecular simulation has emerged as a natural complement to experiments for atomic-level characterizations and mechanistic investigations of this intriguing class of proteins. The diverse range of length and time scales involved in IDP function requires performing simulations at multiple levels of resolution. In this Outlook, we focus on summarizing available simulation methods, along with a few interesting example applications. We also provide an outlook on how these simulation methods can be further improved in order to provide a more accurate description of IDP structure, binding, and assembly.

What We Know About the Brain Structure-Function Relationship.

PubMed

Batista-García-Ramó, Karla; Fernández-Verdecia, Caridad Ivette

2018-04-18

How the human brain works is still a question, as is its implication with brain architecture: the non-trivial structure–function relationship. The main hypothesis is that the anatomic architecture conditions, but does not determine, the neural network dynamic. The functional connectivity cannot be explained only considering the anatomical substrate. This involves complex and controversial aspects of the neuroscience field and that the methods and methodologies to obtain structural and functional connectivity are not always rigorously applied. The goal of the present article is to discuss about the progress made to elucidate the structure–function relationship of the Central Nervous System, particularly at the brain level, based on results from human and animal studies. The current novel systems and neuroimaging techniques with high resolutive physio-structural capacity have brought about the development of an integral framework of different structural and morphometric tools such as image processing, computational modeling and graph theory. Different laboratories have contributed with in vivo, in vitro and computational/mathematical models to study the intrinsic neural activity patterns based on anatomical connections. We conclude that multi-modal techniques of neuroimaging are required such as an improvement on methodologies for obtaining structural and functional connectivity. Even though simulations of the intrinsic neural activity based on anatomical connectivity can reproduce much of the observed patterns of empirical functional connectivity, future models should be multifactorial to elucidate multi-scale relationships and to infer disorder mechanisms.

Explaining the heterogeneity of functional connectivity findings in multiple sclerosis: An empirically informed modeling study.

PubMed

Tewarie, Prejaas; Steenwijk, Martijn D; Brookes, Matthew J; Uitdehaag, Bernard M J; Geurts, Jeroen J G; Stam, Cornelis J; Schoonheim, Menno M

2018-06-01

To understand the heterogeneity of functional connectivity results reported in the literature, we analyzed the separate effects of grey and white matter damage on functional connectivity and networks in multiple sclerosis. For this, we employed a biophysical thalamo-cortical model consisting of interconnected cortical and thalamic neuronal populations, informed and amended by empirical diffusion MRI tractography data, to simulate functional data that mimic neurophysiological signals. Grey matter degeneration was simulated by decreasing within population connections and white matter degeneration by lowering between population connections, based on lesion predilection sites in multiple sclerosis. For all simulations, functional connectivity and functional network organization are quantified by phase synchronization and network integration, respectively. Modeling results showed that both cortical and thalamic grey matter damage induced a global increase in functional connectivity, whereas white matter damage induced an initially increased connectivity followed by a global decrease. Both white and especially grey matter damage, however, induced a decrease in network integration. These empirically informed simulations show that specific topology and timing of structural damage are nontrivial aspects in explaining functional abnormalities in MS. Insufficient attention to these aspects likely explains contradictory findings in multiple sclerosis functional imaging studies so far. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Two-dimensional Ising model on random lattices with constant coordination number

NASA Astrophysics Data System (ADS)

Schrauth, Manuel; Richter, Julian A. J.; Portela, Jefferson S. E.

2018-02-01

We study the two-dimensional Ising model on networks with quenched topological (connectivity) disorder. In particular, we construct random lattices of constant coordination number and perform large-scale Monte Carlo simulations in order to obtain critical exponents using finite-size scaling relations. We find disorder-dependent effective critical exponents, similar to diluted models, showing thus no clear universal behavior. Considering the very recent results for the two-dimensional Ising model on proximity graphs and the coordination number correlation analysis suggested by Barghathi and Vojta [Phys. Rev. Lett. 113, 120602 (2014), 10.1103/PhysRevLett.113.120602], our results indicate that the planarity and connectedness of the lattice play an important role on deciding whether the phase transition is stable against quenched topological disorder.

Overview of LIDS Docking Seals Development

NASA Technical Reports Server (NTRS)

Dunlap, Pat; Steinetz, Bruce; Daniels, Chris

2008-01-01

NASA is developing a new docking system to support future space exploration missions to low-Earth orbit, the Moon, and Mars. This mechanism, called the Low Impact Docking System (LIDS), is designed to connect pressurized space vehicles and structures including the Crew Exploration Vehicle, International Space Station, and lunar lander. NASA Glenn Research Center (GRC) is playing a key role in developing the main interface seal for this new docking system. These seals will be approximately 147 cm (58 in.) in diameter. GRC is evaluating the performance of candidate seal designs under simulated operating conditions at both sub-scale and full-scale levels. GRC is ultimately responsible for delivering flight hardware seals to NASA Johnson Space Center around 2013 for integration into LIDS flight units.

Estimating time-dependent connectivity in marine systems

USGS Publications Warehouse

Defne, Zafer; Ganju, Neil K.; Aretxabaleta, Alfredo

2016-01-01

Hydrodynamic connectivity describes the sources and destinations of water parcels within a domain over a given time. When combined with biological models, it can be a powerful concept to explain the patterns of constituent dispersal within marine ecosystems. However, providing connectivity metrics for a given domain is a three-dimensional problem: two dimensions in space to define the sources and destinations and a time dimension to evaluate connectivity at varying temporal scales. If the time scale of interest is not predefined, then a general approach is required to describe connectivity over different time scales. For this purpose, we have introduced the concept of a “retention clock” that highlights the change in connectivity through time. Using the example of connectivity between protected areas within Barnegat Bay, New Jersey, we show that a retention clock matrix is an informative tool for multitemporal analysis of connectivity.

Critiquing ';pore connectivity' as basis for in situ flow in geothermal systems

NASA Astrophysics Data System (ADS)

Kenedi, C. L.; Leary, P.; Malin, P.

2013-12-01

Geothermal system in situ flow systematics derived from detailed examination of grain-scale structures, fabrics, mineral alteration, and pore connectivity may be extremely misleading if/when extrapolated to reservoir-scale flow structure. In oil/gas field clastic reservoir operations, it is standard to assume that small scale studies of flow fabric - notably the Kozeny-Carman and Archie's Law treatments at the grain-scale and well-log/well-bore sampling of formations/reservoirs at the cm-m scale - are adequate to define the reservoir-scale flow properties. In the case of clastic reservoirs, however, a wide range of reservoir-scale data wholly discredits this extrapolation: Well-log data show that grain-scale fracture density fluctuation power scales inversely with spatial frequency k, S(k) ~ 1/k^β, 1.0 < β < 1.2, 1cycle/km < k < 1cycle/cm; the scaling is a ';universal' feature of well-logs (neutron porosity, sonic velocity, chemical abundance, mass density, resistivity, in many forms of clastic rock and instances of shale bodies, for both horizontal and vertical wells). Grain-scale fracture density correlates with in situ porosity; spatial fluctuations of porosity φ in well-core correlate with spatial fluctuations in the logarithm of well-core permeability, δφ ~ δlog(κ) with typical correlation coefficient ~ 85%; a similar relation is observed in consolidating sediments/clays, indicating a generic coupling between fluid pressure and solid deformation at pore sites. In situ macroscopic flow systems are lognormally distributed according to κ ~ κ0 exp(α(φ-φ0)), α >>1 an empirical parameter for degree of in situ fracture connectivity; the lognormal distribution applies to well-productivities in US oil fields and NZ geothermal fields, ';frack productivity' in oil/gas shale body reservoirs, ore grade distributions, and trace element abundances. Although presently available evidence for these properties in geothermal reservoirs is limited, there are indications that geothermal system flow essentially obeys the same ';universal' in situ flow rules as does clastic rock: Well-log data from Los Azufres, MX, show power-law scaling S(k) ~ 1/k^β, 1.2 < β < 1.4, for spatial frequency range 2cycles/km to 0.5cycle/m; higher β-values are likely due to the relatively fresh nature of geothermal systems; Well-core at Bulalo (PH) and Ohaaki (NZ) show statistically significant spatial correlation, δφ ~ δlog(κ) Well productivity at Ohaaki/Ngawha (NZ) and in geothermal systems elsewhere are lognormally distributed; K/Th/U abundances lognormally distributed in Los Azufres well-logs We therefore caution that small-scale evidence for in situ flow fabric in geothermal systems that is interpreted in terms of ';pore connectivity' may in fact not reflect how small-scale chemical processes are integrated into a large-scale geothermal flow structure. Rather such small scale studies should (perhaps) be considered in term of the above flow rules. These flow rules are easily incorporated into standard flow simulation codes, in particular the OPM = Open Porous Media open-source industry-standard flow code. Geochemical transport data relevant to geothermal systems can thus be expected to be well modeled by OPM or equivalent (e.g., INL/LANL) codes.

A probabilistic approach to quantifying spatial patterns of flow regimes and network-scale connectivity

NASA Astrophysics Data System (ADS)

Garbin, Silvia; Alessi Celegon, Elisa; Fanton, Pietro; Botter, Gianluca

2017-04-01

The temporal variability of river flow regime is a key feature structuring and controlling fluvial ecological communities and ecosystem processes. In particular, streamflow variability induced by climate/landscape heterogeneities or other anthropogenic factors significantly affects the connectivity between streams with notable implication for river fragmentation. Hydrologic connectivity is a fundamental property that guarantees species persistence and ecosystem integrity in riverine systems. In riverine landscapes, most ecological transitions are flow-dependent and the structure of flow regimes may affect ecological functions of endemic biota (i.e., fish spawning or grazing of invertebrate species). Therefore, minimum flow thresholds must be guaranteed to support specific ecosystem services, like fish migration, aquatic biodiversity and habitat suitability. In this contribution, we present a probabilistic approach aiming at a spatially-explicit, quantitative assessment of hydrologic connectivity at the network-scale as derived from river flow variability. Dynamics of daily streamflows are estimated based on catchment-scale climatic and morphological features, integrating a stochastic, physically based approach that accounts for the stochasticity of rainfall with a water balance model and a geomorphic recession flow model. The non-exceedance probability of ecologically meaningful flow thresholds is used to evaluate the fragmentation of individual stream reaches, and the ensuing network-scale connectivity metrics. A multi-dimensional Poisson Process for the stochastic generation of rainfall is used to evaluate the impact of climate signature on reach-scale and catchment-scale connectivity. The analysis shows that streamflow patterns and network-scale connectivity are influenced by the topology of the river network and the spatial variability of climatic properties (rainfall, evapotranspiration). The framework offers a robust basis for the prediction of the impact of land-use/land-cover changes and river regulation on network-scale connectivity.

Ecosystem function in complex mountain terrain: Combining models and long-term observations to advance process-based understanding

NASA Astrophysics Data System (ADS)

Wieder, William R.; Knowles, John F.; Blanken, Peter D.; Swenson, Sean C.; Suding, Katharine N.

2017-04-01

Abiotic factors structure plant community composition and ecosystem function across many different spatial scales. Often, such variation is considered at regional or global scales, but here we ask whether ecosystem-scale simulations can be used to better understand landscape-level variation that might be particularly important in complex terrain, such as high-elevation mountains. We performed ecosystem-scale simulations by using the Community Land Model (CLM) version 4.5 to better understand how the increased length of growing seasons may impact carbon, water, and energy fluxes in an alpine tundra landscape. The model was forced with meteorological data and validated with observations from the Niwot Ridge Long Term Ecological Research Program site. Our results demonstrate that CLM is capable of reproducing the observed carbon, water, and energy fluxes for discrete vegetation patches across this heterogeneous ecosystem. We subsequently accelerated snowmelt and increased spring and summer air temperatures in order to simulate potential effects of climate change in this region. We found that vegetation communities that were characterized by different snow accumulation dynamics showed divergent biogeochemical responses to a longer growing season. Contrary to expectations, wet meadow ecosystems showed the strongest decreases in plant productivity under extended summer scenarios because of disruptions in hydrologic connectivity. These findings illustrate how Earth system models such as CLM can be used to generate testable hypotheses about the shifting nature of energy, water, and nutrient limitations across space and through time in heterogeneous landscapes; these hypotheses may ultimately guide further experimental work and model development.

UNICOR: a species connectivity and corridor network simulator

Treesearch

E. L. Landguth; B. K. Hand; J. Glassy; S. A. Cushman; M. A. Sawaya

2012-01-01

We introduce UNIversal CORridor network simulator (UNICOR), a species connectivity and corridor identifi cation tool. UNICOR applies Dijkstra's shortest path algorithm to individual-based simulations. Outputs can be used to designate movement corridors, identify isolated populations, and prioritize conservation plans to promote species persistence. The key...

On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series

PubMed Central

Fransson, Peter

2016-01-01

Abstract Assessment of dynamic functional brain connectivity based on functional magnetic resonance imaging (fMRI) data is an increasingly popular strategy to investigate temporal dynamics of the brain's large-scale network architecture. Current practice when deriving connectivity estimates over time is to use the Fisher transformation, which aims to stabilize the variance of correlation values that fluctuate around varying true correlation values. It is, however, unclear how well the stabilization of signal variance performed by the Fisher transformation works for each connectivity time series, when the true correlation is assumed to be fluctuating. This is of importance because many subsequent analyses either assume or perform better when the time series have stable variance or adheres to an approximate Gaussian distribution. In this article, using simulations and analysis of resting-state fMRI data, we analyze the effect of applying different variance stabilization strategies on connectivity time series. We focus our investigation on the Fisher transformation, the Box–Cox (BC) transformation and an approach that combines both transformations. Our results show that, if the intention of stabilizing the variance is to use metrics on the time series, where stable variance or a Gaussian distribution is desired (e.g., clustering), the Fisher transformation is not optimal and may even skew connectivity time series away from being Gaussian. Furthermore, we show that the suboptimal performance of the Fisher transformation can be substantially improved by including an additional BC transformation after the dynamic functional connectivity time series has been Fisher transformed. PMID:27784176

On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series.

PubMed

Thompson, William Hedley; Fransson, Peter

2016-12-01

Assessment of dynamic functional brain connectivity based on functional magnetic resonance imaging (fMRI) data is an increasingly popular strategy to investigate temporal dynamics of the brain's large-scale network architecture. Current practice when deriving connectivity estimates over time is to use the Fisher transformation, which aims to stabilize the variance of correlation values that fluctuate around varying true correlation values. It is, however, unclear how well the stabilization of signal variance performed by the Fisher transformation works for each connectivity time series, when the true correlation is assumed to be fluctuating. This is of importance because many subsequent analyses either assume or perform better when the time series have stable variance or adheres to an approximate Gaussian distribution. In this article, using simulations and analysis of resting-state fMRI data, we analyze the effect of applying different variance stabilization strategies on connectivity time series. We focus our investigation on the Fisher transformation, the Box-Cox (BC) transformation and an approach that combines both transformations. Our results show that, if the intention of stabilizing the variance is to use metrics on the time series, where stable variance or a Gaussian distribution is desired (e.g., clustering), the Fisher transformation is not optimal and may even skew connectivity time series away from being Gaussian. Furthermore, we show that the suboptimal performance of the Fisher transformation can be substantially improved by including an additional BC transformation after the dynamic functional connectivity time series has been Fisher transformed.

Polyelectrolyte scaling laws for microgel yielding near jamming.

PubMed

Bhattacharjee, Tapomoy; Kabb, Christopher P; O'Bryan, Christopher S; Urueña, Juan M; Sumerlin, Brent S; Sawyer, W Gregory; Angelini, Thomas E

2018-02-28

Micro-scale hydrogel particles, known as microgels, are used in industry to control the rheology of numerous different products, and are also used in experimental research to study the origins of jamming and glassy behavior in soft-sphere model systems. At the macro-scale, the rheological behaviour of densely packed microgels has been thoroughly characterized; at the particle-scale, careful investigations of jamming, yielding, and glassy-dynamics have been performed through experiment, theory, and simulation. However, at low packing fractions near jamming, the connection between microgel yielding phenomena and the physics of their constituent polymer chains has not been made. Here we investigate whether basic polymer physics scaling laws predict macroscopic yielding behaviours in packed microgels. We measure the yield stress and cross-over shear-rate in several different anionic microgel systems prepared at packing fractions just above the jamming transition, and show that our data can be predicted from classic polyelectrolyte physics scaling laws. We find that diffusive relaxations of microgel deformation during particle re-arrangements can predict the shear-rate at which microgels yield, and the elastic stress associated with these particle deformations predict the yield stress.

Spectral kinetic energy transfer in turbulent premixed reacting flows.

PubMed

Towery, C A Z; Poludnenko, A Y; Urzay, J; O'Brien, J; Ihme, M; Hamlington, P E

2016-05-01

Spectral kinetic energy transfer by advective processes in turbulent premixed reacting flows is examined using data from a direct numerical simulation of a statistically planar turbulent premixed flame. Two-dimensional turbulence kinetic-energy spectra conditioned on the planar-averaged reactant mass fraction are computed through the flame brush and variations in the spectra are connected to terms in the spectral kinetic energy transport equation. Conditional kinetic energy spectra show that turbulent small-scale motions are suppressed in the burnt combustion products, while the energy content of the mean flow increases. An analysis of spectral kinetic energy transfer further indicates that, contrary to the net down-scale transfer of energy found in the unburnt reactants, advective processes transfer energy from small to large scales in the flame brush close to the products. Triadic interactions calculated through the flame brush show that this net up-scale transfer of energy occurs primarily at spatial scales near the laminar flame thermal width. The present results thus indicate that advective processes in premixed reacting flows contribute to energy backscatter near the scale of the flame.

Strategies for Interactive Visualization of Large Scale Climate Simulations

NASA Astrophysics Data System (ADS)

Xie, J.; Chen, C.; Ma, K.; Parvis

2011-12-01

With the advances in computational methods and supercomputing technology, climate scientists are able to perform large-scale simulations at unprecedented resolutions. These simulations produce data that are time-varying, multivariate, and volumetric, and the data may contain thousands of time steps with each time step having billions of voxels and each voxel recording dozens of variables. Visualizing such time-varying 3D data to examine correlations between different variables thus becomes a daunting task. We have been developing strategies for interactive visualization and correlation analysis of multivariate data. The primary task is to find connection and correlation among data. Given the many complex interactions among the Earth's oceans, atmosphere, land, ice and biogeochemistry, and the sheer size of observational and climate model data sets, interactive exploration helps identify which processes matter most for a particular climate phenomenon. We may consider time-varying data as a set of samples (e.g., voxels or blocks), each of which is associated with a vector of representative or collective values over time. We refer to such a vector as a temporal curve. Correlation analysis thus operates on temporal curves of data samples. A temporal curve can be treated as a two-dimensional function where the two dimensions are time and data value. It can also be treated as a point in the high-dimensional space. In this case, to facilitate effective analysis, it is often necessary to transform temporal curve data from the original space to a space of lower dimensionality. Clustering and segmentation of temporal curve data in the original or transformed space provides us a way to categorize and visualize data of different patterns, which reveals connection or correlation of data among different variables or at different spatial locations. We have employed the power of GPU to enable interactive correlation visualization for studying the variability and correlations of a single or a pair of variables. It is desired to create a succinct volume classification that summarizes the connection among all correlation volumes with respect to various reference locations. Providing a reference location must correspond to a voxel position, the number of correlation volumes equals the total number of voxels. A brute-force solution takes all correlation volumes as the input and classifies their corresponding voxels according to their correlation volumes' distance. For large-scale time-varying multivariate data, calculating all these correlation volumes on-the-fly and analyzing the relationships among them is not feasible. We have developed a sampling-based approach for volume classification in order to reduce the computation cost of computing the correlation volumes. Users are able to employ their domain knowledge in selecting important samples. The result is a static view that captures the essence of correlation relationships; i.e., for all voxels in the same cluster, their corresponding correlation volumes are similar. This sampling-based approach enables us to obtain an approximation of correlation relations in a cost-effective manner, thus leading to a scalable solution to investigate large-scale data sets. These techniques empower climate scientists to study large data from their simulations.

Inclusion of Topological Measurements into Analytic Estimates of Effective Permeability in Fractured Media

NASA Astrophysics Data System (ADS)

Sævik, P. N.; Nixon, C. W.

2017-11-01

We demonstrate how topology-based measures of connectivity can be used to improve analytical estimates of effective permeability in 2-D fracture networks, which is one of the key parameters necessary for fluid flow simulations at the reservoir scale. Existing methods in this field usually compute fracture connectivity using the average fracture length. This approach is valid for ideally shaped, randomly distributed fractures, but is not immediately applicable to natural fracture networks. In particular, natural networks tend to be more connected than randomly positioned fractures of comparable lengths, since natural fractures often terminate in each other. The proposed topological connectivity measure is based on the number of intersections and fracture terminations per sampling area, which for statistically stationary networks can be obtained directly from limited outcrop exposures. To evaluate the method, numerical permeability upscaling was performed on a large number of synthetic and natural fracture networks, with varying topology and geometry. The proposed method was seen to provide much more reliable permeability estimates than the length-based approach, across a wide range of fracture patterns. We summarize our results in a single, explicit formula for the effective permeability.

STDP in lateral connections creates category-based perceptual cycles for invariance learning with multiple stimuli.

PubMed

Evans, Benjamin D; Stringer, Simon M

2015-04-01

Learning to recognise objects and faces is an important and challenging problem tackled by the primate ventral visual system. One major difficulty lies in recognising an object despite profound differences in the retinal images it projects, due to changes in view, scale, position and other identity-preserving transformations. Several models of the ventral visual system have been successful in coping with these issues, but have typically been privileged by exposure to only one object at a time. In natural scenes, however, the challenges of object recognition are typically further compounded by the presence of several objects which should be perceived as distinct entities. In the present work, we explore one possible mechanism by which the visual system may overcome these two difficulties simultaneously, through segmenting unseen (artificial) stimuli using information about their category encoded in plastic lateral connections. We demonstrate that these experience-guided lateral interactions robustly organise input representations into perceptual cycles, allowing feed-forward connections trained with spike-timing-dependent plasticity to form independent, translation-invariant output representations. We present these simulations as a functional explanation for the role of plasticity in the lateral connectivity of visual cortex.

A novel algorithm for delineating wetland depressions and ...

EPA Pesticide Factsheets

In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In reality, however, many depressions in the DEM are actual wetland landscape features that are seldom fully filled with water. For instance, wetland depressions in the Prairie Pothole Region (PPR) are seasonally to permanently flooded wetlands characterized by nested hierarchical structures with dynamic filling- spilling-merging surface-water hydrological processes. The objectives of this study were to delineate hierarchical wetland catchments and model their hydrologic connectivity using high-resolution LiDAR data and aerial imagery. We proposed a novel algorithm delineate the hierarchical wetland catchments and characterize their geometric and topological properties. Potential hydrologic connectivity between wetlands and streams were simulated using the least-cost path algorithm. The resulting flow network delineated putative temporary or seasonal flow paths connecting wetland depressions to each other or to the river network at scales finer than available through the National Hydrography Dataset. The results demonstrated that our proposed framework is promising for improving overland flow modeling and hydrologic connectivity analysis. Presentation at AWRA Spring Specialty Conference in Sn

Network-State Modulation of Power-Law Frequency-Scaling in Visual Cortical Neurons

PubMed Central

Béhuret, Sébastien; Baudot, Pierre; Yger, Pierre; Bal, Thierry; Destexhe, Alain; Frégnac, Yves

2009-01-01

Various types of neural-based signals, such as EEG, local field potentials and intracellular synaptic potentials, integrate multiple sources of activity distributed across large assemblies. They have in common a power-law frequency-scaling structure at high frequencies, but it is still unclear whether this scaling property is dominated by intrinsic neuronal properties or by network activity. The latter case is particularly interesting because if frequency-scaling reflects the network state it could be used to characterize the functional impact of the connectivity. In intracellularly recorded neurons of cat primary visual cortex in vivo, the power spectral density of Vm activity displays a power-law structure at high frequencies with a fractional scaling exponent. We show that this exponent is not constant, but depends on the visual statistics used to drive the network. To investigate the determinants of this frequency-scaling, we considered a generic recurrent model of cortex receiving a retinotopically organized external input. Similarly to the in vivo case, our in computo simulations show that the scaling exponent reflects the correlation level imposed in the input. This systematic dependence was also replicated at the single cell level, by controlling independently, in a parametric way, the strength and the temporal decay of the pairwise correlation between presynaptic inputs. This last model was implemented in vitro by imposing the correlation control in artificial presynaptic spike trains through dynamic-clamp techniques. These in vitro manipulations induced a modulation of the scaling exponent, similar to that observed in vivo and predicted in computo. We conclude that the frequency-scaling exponent of the Vm reflects stimulus-driven correlations in the cortical network activity. Therefore, we propose that the scaling exponent could be used to read-out the “effective” connectivity responsible for the dynamical signature of the population signals measured at different integration levels, from Vm to LFP, EEG and fMRI. PMID:19779556

Network-state modulation of power-law frequency-scaling in visual cortical neurons.

PubMed

El Boustani, Sami; Marre, Olivier; Béhuret, Sébastien; Baudot, Pierre; Yger, Pierre; Bal, Thierry; Destexhe, Alain; Frégnac, Yves

2009-09-01

Various types of neural-based signals, such as EEG, local field potentials and intracellular synaptic potentials, integrate multiple sources of activity distributed across large assemblies. They have in common a power-law frequency-scaling structure at high frequencies, but it is still unclear whether this scaling property is dominated by intrinsic neuronal properties or by network activity. The latter case is particularly interesting because if frequency-scaling reflects the network state it could be used to characterize the functional impact of the connectivity. In intracellularly recorded neurons of cat primary visual cortex in vivo, the power spectral density of V(m) activity displays a power-law structure at high frequencies with a fractional scaling exponent. We show that this exponent is not constant, but depends on the visual statistics used to drive the network. To investigate the determinants of this frequency-scaling, we considered a generic recurrent model of cortex receiving a retinotopically organized external input. Similarly to the in vivo case, our in computo simulations show that the scaling exponent reflects the correlation level imposed in the input. This systematic dependence was also replicated at the single cell level, by controlling independently, in a parametric way, the strength and the temporal decay of the pairwise correlation between presynaptic inputs. This last model was implemented in vitro by imposing the correlation control in artificial presynaptic spike trains through dynamic-clamp techniques. These in vitro manipulations induced a modulation of the scaling exponent, similar to that observed in vivo and predicted in computo. We conclude that the frequency-scaling exponent of the V(m) reflects stimulus-driven correlations in the cortical network activity. Therefore, we propose that the scaling exponent could be used to read-out the "effective" connectivity responsible for the dynamical signature of the population signals measured at different integration levels, from Vm to LFP, EEG and fMRI.

The Q continuum simulation: Harnessing the power of GPU accelerated supercomputers

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

Heitmann, Katrin; Frontiere, Nicholas; Sewell, Chris

2015-08-01

Modeling large-scale sky survey observations is a key driver for the continuing development of high-resolution, large-volume, cosmological simulations. We report the first results from the "Q Continuum" cosmological N-body simulation run carried out on the GPU-accelerated supercomputer Titan. The simulation encompasses a volume of (1300 Mpc)(3) and evolves more than half a trillion particles, leading to a particle mass resolution of m(p) similar or equal to 1.5 . 10(8) M-circle dot. At thismass resolution, the Q Continuum run is currently the largest cosmology simulation available. It enables the construction of detailed synthetic sky catalogs, encompassing different modeling methodologies, including semi-analyticmore » modeling and sub-halo abundance matching in a large, cosmological volume. Here we describe the simulation and outputs in detail and present first results for a range of cosmological statistics, such as mass power spectra, halo mass functions, and halo mass-concentration relations for different epochs. We also provide details on challenges connected to running a simulation on almost 90% of Titan, one of the fastest supercomputers in the world, including our usage of Titan's GPU accelerators.« less

Evolving network simulation study. From regular lattice to scale free network

NASA Astrophysics Data System (ADS)

Makowiec, D.

2005-12-01

The Watts-Strogatz algorithm of transferring the square lattice to a small world network is modified by introducing preferential rewiring constrained by connectivity demand. The evolution of the network is two-step: sequential preferential rewiring of edges controlled by p and updating the information about changes done. The evolving system self-organizes into stationary states. The topological transition in the graph structure is noticed with respect to p. Leafy phase a graph formed by multiple connected vertices (graph skeleton) with plenty of leaves attached to each skeleton vertex emerges when p is small enough to pretend asynchronous evolution. Tangling phase where edges of a graph circulate frequently among low degree vertices occurs when p is large. There exist conditions at which the resulting stationary network ensemble provides networks which degree distribution exhibit power-law decay in large interval of degrees.

Critical dynamics on a large human Open Connectome network

NASA Astrophysics Data System (ADS)

Ódor, Géza

2016-12-01

Extended numerical simulations of threshold models have been performed on a human brain network with N =836 733 connected nodes available from the Open Connectome Project. While in the case of simple threshold models a sharp discontinuous phase transition without any critical dynamics arises, variable threshold models exhibit extended power-law scaling regions. This is attributed to fact that Griffiths effects, stemming from the topological or interaction heterogeneity of the network, can become relevant if the input sensitivity of nodes is equalized. I have studied the effects of link directness, as well as the consequence of inhibitory connections. Nonuniversal power-law avalanche size and time distributions have been found with exponents agreeing with the values obtained in electrode experiments of the human brain. The dynamical critical region occurs in an extended control parameter space without the assumption of self-organized criticality.

Computer Drawing Method for Operating Characteristic Curve of PV Power Plant Array Unit

NASA Astrophysics Data System (ADS)

Tan, Jianbin

2018-02-01

According to the engineering design of large-scale grid-connected photovoltaic power stations and the research and development of many simulation and analysis systems, it is necessary to draw a good computer graphics of the operating characteristic curves of photovoltaic array elements and to propose a good segmentation non-linear interpolation algorithm. In the calculation method, Component performance parameters as the main design basis, the computer can get 5 PV module performances. At the same time, combined with the PV array series and parallel connection, the computer drawing of the performance curve of the PV array unit can be realized. At the same time, the specific data onto the module of PV development software can be calculated, and the good operation of PV array unit can be improved on practical application.

Dynamics of a fluctuating semi-flexible membrane

NASA Astrophysics Data System (ADS)

Tukdarian, Nathaniel; Huang, Aiqun; Adhikari, Ramesh; Bhattacharya, Aniket

2015-03-01

We report our preliminary studies of conformations and dynamics of a fluctuating semi-flexible membrane. Our model of membrane with linear dimension L consists of N2 (L = Nbl) excluded volume beads connected by anharmonic springs. The stiffness of the membrane is controlled by adjusting the strength κb of the bending potential Ubend =κb(1-n̂i .n̂j) between adjacent elementary plaquettes consisting of three beads at the corners connected by bonds and characterized by normal unit vectors n̂i and n̂j. We study the conformations and dynamic fluctuations of the membrane using Brownian dynamics simulation. We show how the radius of gyration scales with N and κb, and study characteristics of the transverse fluctuations, the root-mean-square displacement of the center of mass, and the dynamics of the end monomers at each corner.

Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

NASA Astrophysics Data System (ADS)

Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

2018-01-01

Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are weak, especially when more stringent conditions are imposed (i.e. when T is very high), except at the monthly scale.

HIFiRE Direct-Connect Rig (HDCR) Phase I Scramjet Test Results from the NASA Langley Arc-Heated Scramjet Test Facility

NASA Technical Reports Server (NTRS)

Cabell, Karen; Hass, Neal; Storch, Andrea; Gruber, Mark

2011-01-01

A series of hydrocarbon-fueled direct-connect scramjet ground tests has been completed in the NASA Langley Arc-Heated Scramjet Test Facility (AHSTF) at simulated Mach 8 flight conditions. These experiments were part of an initial test phase to support Flight 2 of the Hypersonic International Flight Research Experimentation (HIFiRE) Program. In this flight experiment, a hydrocarbon-fueled scramjet is intended to demonstrate transition from dual-mode to scramjet-mode operation and verify the scramjet performance prediction and design tools A performance goal is the achievement of a combusted fuel equivalence ratio greater than 0.7 while in scramjet mode. The ground test rig, designated the HIFiRE Direct Connect Rig (HDCR), is a full-scale, heat sink test article that duplicates both the flowpath lines and a majority of the instrumentation layout of the isolator and combustor portion of the flight test hardware. The primary objectives of the HDCR Phase I tests were to verify the operability of the HIFiRE isolator/combustor across the simulated Mach 6-8 flight regime and to establish a fuel distribution schedule to ensure a successful mode transition. Both of these objectives were achieved prior to the HiFIRE Flight 2 payload Critical Design Review. Mach 8 ground test results are presented in this report, including flowpath surface pressure distributions that demonstrate the operation of the flowpath in scramjet-mode over a small range of test conditions around the nominal Mach 8 simulation, as well as over a range of fuel equivalence ratios. Flowpath analysis using ground test data is presented elsewhere; however, limited comparisons with analytical predictions suggest that both scramjet-mode operation and the combustion performance objective are achieved at Mach 8 conditions.

The COPD Knowledge Base: enabling data analysis and computational simulation in translational COPD research.

PubMed

Cano, Isaac; Tényi, Ákos; Schueller, Christine; Wolff, Martin; Huertas Migueláñez, M Mercedes; Gomez-Cabrero, David; Antczak, Philipp; Roca, Josep; Cascante, Marta; Falciani, Francesco; Maier, Dieter

2014-11-28

Previously we generated a chronic obstructive pulmonary disease (COPD) specific knowledge base (http://www.copdknowledgebase.eu) from clinical and experimental data, text-mining results and public databases. This knowledge base allowed the retrieval of specific molecular networks together with integrated clinical and experimental data. The COPDKB has now been extended to integrate over 40 public data sources on functional interaction (e.g. signal transduction, transcriptional regulation, protein-protein interaction, gene-disease association). In addition we integrated COPD-specific expression and co-morbidity networks connecting over 6 000 genes/proteins with physiological parameters and disease states. Three mathematical models describing different aspects of systemic effects of COPD were connected to clinical and experimental data. We have completely redesigned the technical architecture of the user interface and now provide html and web browser-based access and form-based searches. A network search enables the use of interconnecting information and the generation of disease-specific sub-networks from general knowledge. Integration with the Synergy-COPD Simulation Environment enables multi-scale integrated simulation of individual computational models while integration with a Clinical Decision Support System allows delivery into clinical practice. The COPD Knowledge Base is the only publicly available knowledge resource dedicated to COPD and combining genetic information with molecular, physiological and clinical data as well as mathematical modelling. Its integrated analysis functions provide overviews about clinical trends and connections while its semantically mapped content enables complex analysis approaches. We plan to further extend the COPDKB by offering it as a repository to publish and semantically integrate data from relevant clinical trials. The COPDKB is freely available after registration at http://www.copdknowledgebase.eu.

Final report of “A Detailed Study of the Physical Mechanisms Controlling CO2-Brine Capillary Trapping in the Subsurface” (University of Arizona, DE-SC0006696)

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

Schaap, Marcel G.

Carbon capture and storage (CCS) of carbon dioxide emissions generated by production or combustion of fossil fuels is a technologically viable means to reduce the build-up of CO2 in the atmosphere and oceans. Using advantages of scale and location, CCS is particularly suitable for large point sources near ubiquitous deep saline aquifers, depleted gas reservoirs, or at production reservoirs for enhanced oil recovery (EOR). In the BES-funded research project, Oregon State University (OSU) carried out capillary trapping experiments with proxy fluids that mimic the properties of the scCO2/brine system under ambient temperatures and pressures, and successfully developed a unique andmore » novel x-ray compatible, high-pressure, elevated temperature setup to study the scCO2/brine system under challenging reservoir conditions. Both methodologies were applied to a variety of porous media, including synthetic (glass bead) and geologic (Bentheimer sandstone) materials. The University of Arizona (UA) developed pore-scale lattice Boltzmann (LB) models which are able to handle the experimental conditions for proxy fluids, as well as the scCO2/brine system, that are capable of simulating permeability in volumes of tens of millions of fluid elements. We reached the following summary findings (main institute indicated): 1. (OSU/UA) To understand capillary trapping in a multiphase fluid-porous medium system, the system must be analyzed from a pore-scale force balance perspective; trapping can be enhanced by manipulating wetting and nonwetting phase fluid properties. 2. (OSU) Pore-scale fluid connectivity and topology has a clear and direct effect on nonwetting phase capillary trapping efficiency. 3. (OSU) Rock type and flow regime also have a pronounced effects on capillary trapping. 4. (OSU/UA) There is a predictable relationship between NWP connectivity and NWP saturation, which allows for development of injection strategies that optimize trapping. The commonly used Land model (Land, 1968) does not predict amount of trapped NWP accurately. 5. (UA) There are ambiguities regarding the segmentation of large-volume gray-scale CT data into pore-volumes suitable for pore-scale modeling. Simulated permeabilities vary by three orders of magnitude and do not resemble observed values very well. Small-volume synchrotron-based CT data (such as produced by OSU) does not suffer significantly from segmentation ambiguities. 6. (UA) A standard properly parameterized Shan-Chen model LB model is useful for simulating porous media with proxy fluids as well as the scCO2/brine system and produces results that are consistent with tomographic observations. 7. (UA) A LB model with fluid-interactions defined by a (modified) Peng-Robinson Equation of State is able to handle the scCO2/brine system with variable solid phase wettability. This model is numerically stable at temperatures between 0 and 250 °C and pressures between 3 and 50 MPa, and produces appropriate densities above the critical point of CO2 and exhibits three-phase separation below. Based on above findings OSU and UA have proposed continued experimentation and pore-scale modeling of the scCO2/brine system. The reported research has extensively covered capillary trapping using proxy fluids, but due to limited beam-time availability we were unable to apply our high-pressure CO2 setup to sufficient variation in fluid properties, and initial scCO2 connectivity. New data will also allow us to test, calibrate and apply our LB models to reservoir conditions beyond those that are currently feasible experimentally. Such experiments and simulations will also allow us to provide information how suitable proxy fluids are for the scCO2/brine system. We believe it would be worthwhile to pursue the following new research questions: 1. What are the fundamental differences in the physics underlying capillary trapping at ambient vs. supercritical conditions? 2. Do newly developed pore-scale trapping interactions and relationships translate to continuum scales? A motivation for these questions was elaborated in “Capillary Trapping of Super-Critical CO2: Linking Pore and Continuum Scales to Verify new Relationships” that was submitted to DOE-BES in 2015.« less

Neural Networks For Demodulation Of Phase-Modulated Signals

NASA Technical Reports Server (NTRS)

Altes, Richard A.

1995-01-01

Hopfield neural networks proposed for demodulating quadrature phase-shift-keyed (QPSK) signals carrying digital information. Networks solve nonlinear integral equations prior demodulation circuits cannot solve. Consists of set of N operational amplifiers connected in parallel, with weighted feedback from output terminal of each amplifier to input terminals of other amplifiers. Used to solve signal processing problems. Implemented as analog very-large-scale integrated circuit that achieves rapid convergence. Alternatively, implemented as digital simulation of such circuit. Also used to improve phase estimation performance over that of phase-locked loop.

Robust autoassociative memory with coupled networks of Kuramoto-type oscillators

NASA Astrophysics Data System (ADS)

Heger, Daniel; Krischer, Katharina

2016-08-01

Uncertain recognition success, unfavorable scaling of connection complexity, or dependence on complex external input impair the usefulness of current oscillatory neural networks for pattern recognition or restrict technical realizations to small networks. We propose a network architecture of coupled oscillators for pattern recognition which shows none of the mentioned flaws. Furthermore we illustrate the recognition process with simulation results and analyze the dynamics analytically: Possible output patterns are isolated attractors of the system. Additionally, simple criteria for recognition success are derived from a lower bound on the basins of attraction.

Sudden Relaminarization and Lifetimes in Forced Isotropic Turbulence.

PubMed

Linkmann, Moritz F; Morozov, Alexander

2015-09-25

We demonstrate an unexpected connection between isotropic turbulence and wall-bounded shear flows. We perform direct numerical simulations of isotropic turbulence forced at large scales at moderate Reynolds numbers and observe sudden transitions from a chaotic dynamics to a spatially simple flow, analogous to the laminar state in wall bounded shear flows. We find that the survival probabilities of turbulence are exponential and the typical lifetimes increase superexponentially with the Reynolds number. Our results suggest that both isotropic turbulence and wall-bounded shear flows qualitatively share the same phase-space dynamics.

Efficient radiologic reading environment by using an open-source macro program as connection software.

PubMed

Lee, Young Han

2012-01-01

The objectives are (1) to introduce an easy open-source macro program as connection software and (2) to illustrate the practical usages in radiologic reading environment by simulating the radiologic reading process. The simulation is a set of radiologic reading process to do a practical task in the radiologic reading room. The principal processes are: (1) to view radiologic images on the Picture Archiving and Communicating System (PACS), (2) to connect the HIS/EMR (Hospital Information System/Electronic Medical Record) system, (3) to make an automatic radiologic reporting system, and (4) to record and recall information of interesting cases. This simulation environment was designed by using open-source macro program as connection software. The simulation performed well on the Window-based PACS workstation. Radiologists practiced the steps of the simulation comfortably by utilizing the macro-powered radiologic environment. This macro program could automate several manual cumbersome steps in the radiologic reading process. This program successfully acts as connection software for the PACS software, EMR/HIS, spreadsheet, and other various input devices in the radiologic reading environment. A user-friendly efficient radiologic reading environment could be established by utilizing open-source macro program as connection software. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Time domain simulations of preliminary breakdown pulses in natural lightning.

PubMed

Carlson, B E; Liang, C; Bitzer, P; Christian, H

2015-06-16

Lightning discharge is a complicated process with relevant physical scales spanning many orders of magnitude. In an effort to understand the electrodynamics of lightning and connect physical properties of the channel to observed behavior, we construct a simulation of charge and current flow on a narrow conducting channel embedded in three-dimensional space with the time domain electric field integral equation, the method of moments, and the thin-wire approximation. The method includes approximate treatment of resistance evolution due to lightning channel heating and the corona sheath of charge surrounding the lightning channel. Focusing our attention on preliminary breakdown in natural lightning by simulating stepwise channel extension with a simplified geometry, our simulation reproduces the broad features observed in data collected with the Huntsville Alabama Marx Meter Array. Some deviations in pulse shape details are evident, suggesting future work focusing on the detailed properties of the stepping mechanism. Preliminary breakdown pulses can be reproduced by simulated channel extension Channel heating and corona sheath formation are crucial to proper pulse shape Extension processes and channel orientation significantly affect observations.

Time domain simulations of preliminary breakdown pulses in natural lightning

PubMed Central

Carlson, B E; Liang, C; Bitzer, P; Christian, H

2015-01-01

Lightning discharge is a complicated process with relevant physical scales spanning many orders of magnitude. In an effort to understand the electrodynamics of lightning and connect physical properties of the channel to observed behavior, we construct a simulation of charge and current flow on a narrow conducting channel embedded in three-dimensional space with the time domain electric field integral equation, the method of moments, and the thin-wire approximation. The method includes approximate treatment of resistance evolution due to lightning channel heating and the corona sheath of charge surrounding the lightning channel. Focusing our attention on preliminary breakdown in natural lightning by simulating stepwise channel extension with a simplified geometry, our simulation reproduces the broad features observed in data collected with the Huntsville Alabama Marx Meter Array. Some deviations in pulse shape details are evident, suggesting future work focusing on the detailed properties of the stepping mechanism. Key Points Preliminary breakdown pulses can be reproduced by simulated channel extension Channel heating and corona sheath formation are crucial to proper pulse shape Extension processes and channel orientation significantly affect observations PMID:26664815

MaMiCo: Software design for parallel molecular-continuum flow simulations

NASA Astrophysics Data System (ADS)

Neumann, Philipp; Flohr, Hanno; Arora, Rahul; Jarmatz, Piet; Tchipev, Nikola; Bungartz, Hans-Joachim

2016-03-01

The macro-micro-coupling tool (MaMiCo) was developed to ease the development of and modularize molecular-continuum simulations, retaining sequential and parallel performance. We demonstrate the functionality and performance of MaMiCo by coupling the spatially adaptive Lattice Boltzmann framework waLBerla with four molecular dynamics (MD) codes: the light-weight Lennard-Jones-based implementation SimpleMD, the node-level optimized software ls1 mardyn, and the community codes ESPResSo and LAMMPS. We detail interface implementations to connect each solver with MaMiCo. The coupling for each waLBerla-MD setup is validated in three-dimensional channel flow simulations which are solved by means of a state-based coupling method. We provide sequential and strong scaling measurements for the four molecular-continuum simulations. The overhead of MaMiCo is found to come at 10%-20% of the total (MD) runtime. The measurements further show that scalability of the hybrid simulations is reached on up to 500 Intel SandyBridge, and more than 1000 AMD Bulldozer compute cores.

Impact of Aerosols on Convective Clouds and Precipitation

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chen, Jen-Ping; Li, Zhanqing; Wang, Chien; Zhang, Chidong

2011-01-01

Aerosols are a critical factor in the atmospheric hydrological cycle and radiation budget. As a major reason for clouds to form and a significant attenuator of solar radiation, aerosols affect climate in several ways. Current research suggests that aerosol effects on clouds could further extend to precipitation, both through the formation of cloud particles and by exerting persistent radiative forcing on the climate system that disturbs dynamics. However, the various mechanisms behind these effects, in particular the ones connected to precipitation, are not yet well understood. The atmospheric and climate communities have long been working to gain a better grasp of these critical effects and hence to reduce the significant uncertainties in climate prediction resulting from such a lack of adequate knowledge. The central theme of this paper is to review past efforts and summarize our current understanding of the effect of aerosols on precipitation processes from theoretical analysis of microphysics, observational evidence, and a range of numerical model simulations. In addition, the discrepancy between results simulated by models, as well as that between simulations and observations will be presented. Specifically, this paper will address the following topics: (1) fundamental theories of aerosol effects on microphysics and precipitation processes, (2) observational evidence of the effect of aerosols on precipitation processes, (3) signatures of the aerosol impact on precipitation from large-scale analyses, (4) results from cloud-resolving model simulations, and (5) results from large-scale numerical model simulations. Finally, several future research directions on aerosol - precipitation interactions are suggested.

Counting on β-Diversity to Safeguard the Resilience of Estuaries

PubMed Central

de Juan, Silvia; Thrush, Simon F.; Hewitt, Judi E.

2013-01-01

Coastal ecosystems are often stressed by non-point source and cumulative effects that can lead to local-scale community homogenisation and a concomitant loss of large-scale ecological connectivity. Here we investigate the use of β-diversity as a measure of both community heterogeneity and ecological connectivity. To understand the consequences of different environmental scenarios on heterogeneity and connectivity, it is necessary to understand the scale at which different environmental factors affect β-diversity. We sampled macrofauna from intertidal sites in nine estuaries from New Zealand’s North Island that represented different degrees of stress derived from land-use. We used multiple regression models to identify relationships between β-diversity and local sediment variables, factors related to the estuarine and catchment hydrodynamics and morphology and land-based stressors. At local scales, we found higher β-diversity at sites with a relatively high total richness. At larger scales, β-diversity was positively related to γ-diversity, suggesting that a large regional species pool was linked with large-scale heterogeneity in these systems. Local environmental heterogeneity influenced β-diversity at both local and regional scales, although variables at the estuarine and catchment scales were both needed to explain large scale connectivity. The estuaries expected a priori to be the most stressed exhibited higher variance in community dissimilarity between sites and connectivity to the estuary species pool. This suggests that connectivity and heterogeneity metrics could be used to generate early warning signals of cumulative stress. PMID:23755252

Key issues in the computational simulation of GPCR function: representation of loop domains

NASA Astrophysics Data System (ADS)

Mehler, E. L.; Periole, X.; Hassan, S. A.; Weinstein, H.

2002-11-01

Some key concerns raised by molecular modeling and computational simulation of functional mechanisms for membrane proteins are discussed and illustrated for members of the family of G protein coupled receptors (GPCRs). Of particular importance are issues related to the modeling and computational treatment of loop regions. These are demonstrated here with results from different levels of computational simulations applied to the structures of rhodopsin and a model of the 5-HT2A serotonin receptor, 5-HT2AR. First, comparative Molecular Dynamics (MD) simulations are reported for rhodopsin in vacuum and embedded in an explicit representation of the membrane and water environment. It is shown that in spite of a partial accounting of solvent screening effects by neutralization of charged side chains, vacuum MD simulations can lead to severe distortions of the loop structures. The primary source of the distortion appears to be formation of artifactual H-bonds, as has been repeatedly observed in vacuum simulations. To address such shortcomings, a recently proposed approach that has been developed for calculating the structure of segments that connect elements of secondary structure with known coordinates, is applied to 5-HT2AR to obtain an initial representation of the loops connecting the transmembrane (TM) helices. The approach consists of a simulated annealing combined with biased scaled collective variables Monte Carlo technique, and is applied to loops connecting the TM segments on both the extra-cellular and the cytoplasmic sides of the receptor. Although this initial calculation treats the loops as independent structural entities, the final structure exhibits a number of interloop interactions that may have functional significance. Finally, it is shown here that in the case where a given loop from two different GPCRs (here rhodopsin and 5-HT2AR) has approximately the same length and some degree of sequence identity, the fold adopted by the loops can be similar. Thus, in such special cases homology modeling might be used to obtain initial structures of these loops. Notably, however, all other loops in these two receptors appear to be very different in sequence and structure, so that their conformations can be found reliably only by ab initio, energy based methods and not by homology modeling.

Robustness of Controllability for Networks Based on Edge-Attack

PubMed Central

Nie, Sen; Wang, Xuwen; Zhang, Haifeng; Li, Qilang; Wang, Binghong

2014-01-01

We study the controllability of networks in the process of cascading failures under two different attacking strategies, random and intentional attack, respectively. For the highest-load edge attack, it is found that the controllability of Erdős-Rényi network, that with moderate average degree, is less robust, whereas the Scale-free network with moderate power-law exponent shows strong robustness of controllability under the same attack strategy. The vulnerability of controllability under random and intentional attacks behave differently with the increasing of removal fraction, especially, we find that the robustness of control has important role in cascades for large removal fraction. The simulation results show that for Scale-free networks with various power-law exponents, the network has larger scale of cascades do not mean that there will be more increments of driver nodes. Meanwhile, the number of driver nodes in cascading failures is also related to the edges amount in strongly connected components. PMID:24586507

Robustness of controllability for networks based on edge-attack.

PubMed

Nie, Sen; Wang, Xuwen; Zhang, Haifeng; Li, Qilang; Wang, Binghong

2014-01-01

We study the controllability of networks in the process of cascading failures under two different attacking strategies, random and intentional attack, respectively. For the highest-load edge attack, it is found that the controllability of Erdős-Rényi network, that with moderate average degree, is less robust, whereas the Scale-free network with moderate power-law exponent shows strong robustness of controllability under the same attack strategy. The vulnerability of controllability under random and intentional attacks behave differently with the increasing of removal fraction, especially, we find that the robustness of control has important role in cascades for large removal fraction. The simulation results show that for Scale-free networks with various power-law exponents, the network has larger scale of cascades do not mean that there will be more increments of driver nodes. Meanwhile, the number of driver nodes in cascading failures is also related to the edges amount in strongly connected components.

Common origin of kinetic scale turbulence and the electron halo in the solar wind – Connection to nanoflares

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

Che, Haihong; Goddard Space Flight Center, NASA, Greenbelt, MD, 20771

2016-03-25

We summarize our recent studies on the origin of solar wind kinetic scale turbulence and electron halo in the electron velocity distribution function. Increasing observations of nanoflares and microscopic type III radio bursts strongly suggest that nanoflares and accelerated electron beams are common in the corona. Based on particle-in-cell simulations, we show that both the core-halo feature and kinetic scale turbulence observed in the solar wind can be produced by the nonlinear evolution of electron two-stream instability driven by nanoflare accelerated electron beams. The energy exchange between waves and particles reaches equilibrium in the inner corona and the key featuresmore » of the turbulence and velocity distribution are preserved as the solar wind escapes into interplanetary space along open magnetic field lines. Observational tests of the model and future theoretical work are discussed.« less

High efficiency and broadband acoustic diodes

NASA Astrophysics Data System (ADS)

Fu, Congyi; Wang, Bohan; Zhao, Tianfei; Chen, C. Q.

2018-01-01

Energy transmission efficiency and working bandwidth are the two major factors limiting the application of current acoustic diodes (ADs). This letter presents a design of high efficiency and broadband acoustic diodes composed of a nonlinear frequency converter and a linear wave filter. The converter consists of two masses connected by a bilinear spring with asymmetric tension and compression stiffness. The wave filter is a linear mass-spring lattice (sonic crystal). Both numerical simulation and experiment show that the energy transmission efficiency of the acoustic diode can be improved by as much as two orders of magnitude, reaching about 61%. Moreover, the primary working band width of the AD is about two times of the cut-off frequency of the sonic crystal filter. The cut-off frequency dependent working band of the AD implies that the developed AD can be scaled up or down from macro-scale to micro- and nano-scale.

From Coexpression to Coregulation: An Approach to Inferring Transcriptional Regulation Among Gene Classes from Large-Scale Expression Data

NASA Technical Reports Server (NTRS)

Mjolsness, Eric; Castano, Rebecca; Mann, Tobias; Wold, Barbara

2000-01-01

We provide preliminary evidence that existing algorithms for inferring small-scale gene regulation networks from gene expression data can be adapted to large-scale gene expression data coming from hybridization microarrays. The essential steps are (I) clustering many genes by their expression time-course data into a minimal set of clusters of co-expressed genes, (2) theoretically modeling the various conditions under which the time-courses are measured using a continuous-time analog recurrent neural network for the cluster mean time-courses, (3) fitting such a regulatory model to the cluster mean time courses by simulated annealing with weight decay, and (4) analysing several such fits for commonalities in the circuit parameter sets including the connection matrices. This procedure can be used to assess the adequacy of existing and future gene expression time-course data sets for determining transcriptional regulatory relationships such as coregulation.

Local-Scale Simulations of Nucleate Boiling on Micrometer Featured Surfaces: Preprint

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

Sitaraman, Hariswaran; Moreno, Gilberto; Narumanchi, Sreekant V

2017-08-03

A high-fidelity computational fluid dynamics (CFD)-based model for bubble nucleation of the refrigerant HFE7100 on micrometer-featured surfaces is presented in this work. The single-fluid incompressible Navier-Stokes equations, along with energy transport and natural convection effects are solved on a featured surface resolved grid. An a priori cavity detection method is employed to convert raw profilometer data of a surface into well-defined cavities. The cavity information and surface morphology are represented in the CFD model by geometric mesh deformations. Surface morphology is observed to initiate buoyancy-driven convection in the liquid phase, which in turn results in faster nucleation of cavities. Simulationsmore » pertaining to a generic rough surface show a trend where smaller size cavities nucleate with higher wall superheat. This local-scale model will serve as a self-consistent connection to larger device scale continuum models where local feature representation is not possible.« less

Local-Scale Simulations of Nucleate Boiling on Micrometer-Featured Surfaces

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

Sitaraman, Hariswaran; Moreno, Gilberto; Narumanchi, Sreekant V

2017-07-12

A high-fidelity computational fluid dynamics (CFD)-based model for bubble nucleation of the refrigerant HFE7100 on micrometer-featured surfaces is presented in this work. The single-fluid incompressible Navier-Stokes equations, along with energy transport and natural convection effects are solved on a featured surface resolved grid. An a priori cavity detection method is employed to convert raw profilometer data of a surface into well-defined cavities. The cavity information and surface morphology are represented in the CFD model by geometric mesh deformations. Surface morphology is observed to initiate buoyancy-driven convection in the liquid phase, which in turn results in faster nucleation of cavities. Simulationsmore » pertaining to a generic rough surface show a trend where smaller size cavities nucleate with higher wall superheat. This local-scale model will serve as a self-consistent connection to larger device scale continuum models where local feature representation is not possible.« less

Scale effect on overland flow connectivity at the plot scale

NASA Astrophysics Data System (ADS)

Peñuela, A.; Javaux, M.; Bielders, C. L.

2012-06-01

A major challenge in present-day hydrological sciences is to enhance the performance of existing distributed hydrological models through a better description of subgrid processes, in particular the subgrid connectivity of flow paths. The relative surface connection function (RSC) was proposed by Antoine et al. (2009) as a functional indicator of runoff flow connectivity. For a given area, it expresses the percentage of the surface connected to the outflow boundary (C) as a function of the degree of filling of the depression storage. This function explicitly integrates the flow network at the soil surface and hence provides essential information regarding the flow paths' connectivity. It has been shown that this function could help improve the modeling of the hydrogram at the square meter scale, yet it is unknown how the scale affects the RSC function, and whether and how it can be extrapolated to other scales. The main objective of this research is to study the scale effect on overland flow connectivity (RSC function). For this purpose, digital elevation data of a real field (9 × 3 m) and three synthetic fields (6 × 6 m) with contrasting hydrological responses were used, and the RSC function was calculated at different scales by changing the length (l) or width (w) of the field. Border effects, at different extents depending on the microtopography, were observed for the smaller scales, when decreasing l or w, which resulted in a strong decrease or increase of the maximum depression storage, respectively. There was no scale effect on the RSC function when changing w. On the contrary, a remarkable scale effect was observed in the RSC function when changing l. In general, for a given degree of filling of the depression storage, C decreased as l increased. This change in C was inversely proportional to the change in l. This observation applied only up to approx. 50-70% (depending on the hydrological response of the field) of filling of depression storage, after which no correlation was found between C and l. The results of this study help identify the minimal scale to study overland flow connectivity. At scales larger than the minimal scale, the RSC function showed a great potential to be extrapolated to other scales.

Scale effect on overland flow connectivity at the plot scale

NASA Astrophysics Data System (ADS)

Peñuela, A.; Javaux, M.; Bielders, C. L.

2013-01-01

A major challenge in present-day hydrological sciences is to enhance the performance of existing distributed hydrological models through a better description of subgrid processes, in particular the subgrid connectivity of flow paths. The Relative Surface Connection (RSC) function was proposed by Antoine et al. (2009) as a functional indicator of runoff flow connectivity. For a given area, it expresses the percentage of the surface connected to the outflow boundary (C) as a function of the degree of filling of the depression storage. This function explicitly integrates the flow network at the soil surface and hence provides essential information regarding the flow paths' connectivity. It has been shown that this function could help improve the modeling of the hydrograph at the square meter scale, yet it is unknown how the scale affects the RSC function, and whether and how it can be extrapolated to other scales. The main objective of this research is to study the scale effect on overland flow connectivity (RSC function). For this purpose, digital elevation data of a real field (9 × 3 m) and three synthetic fields (6 × 6 m) with contrasting hydrological responses were used, and the RSC function was calculated at different scales by changing the length (l) or width (w) of the field. To different extents depending on the microtopography, border effects were observed for the smaller scales when decreasing l or w, which resulted in a strong decrease or increase of the maximum depression storage, respectively. There was no scale effect on the RSC function when changing w, but a remarkable scale effect was observed in the RSC function when changing l. In general, for a given degree of filling of the depression storage, C decreased as l increased, the change in C being inversely proportional to the change in l. However, this observation applied only up to approx. 50-70% (depending on the hydrological response of the field) of filling of depression storage, after which no correlation was found between C and l. The results of this study help identify the minimal scale to study overland flow connectivity. At scales larger than the minimal scale, the RSC function showed a great potential to be extrapolated to other scales.

Experimental study on the connection property of full-scale composite member

NASA Astrophysics Data System (ADS)

Panpan, Cao; Qing, Sun

2018-01-01

The excellent properties of composite result in its increasingly application in electric power construction, however there are less experimental studies on full-scale composite member connection property. Full-scale experiments of the connection property between E-glass fiber/epoxy reinforced polymer member and steel casing in practical engineering have been conducted. Based on the axial compression test of the designed specimens, the failure process and failure characteristics were observed, the load-displacement curves and strain distribution of the specimens were obtained. The finite element analysis was used to get the tensile connection strength of the component. The connection property of the components was analyzed to provide basis of the casing connection of GFRP application in practical engineering.

The characterization of a point bar-channel aquifer analogue: from geostatistical simulation to solute transport through hydrofacies connectivity

NASA Astrophysics Data System (ADS)

Dell'Arciprete, Diana; Baratelli, Fulvia; Bersezio, Riccardo; Felletti, Fabrizio; Giudici, Mauro; Vassena, Chiara

2010-05-01

Ground water flow and solute transport are controlled by the geological structure and the corresponding heterogeneity and anisotropy of the hydraulic conductivity (K) field. In alluvial aquifers, a complete interdisciplinary characterization of the reservoir is important for reliable predictions. The reconstruction of the subsurface heterogeneity cannot be limited to honor point (e.g., well stratigraphic logs) data, but should also account for the presence of connected high K hydrofacies, which might form preferential flow paths. To explore these concepts an aquifer analogue, at the scale of the point-bar/channel depositional element of a meandering river, was studied. The analogue, exposed in a gravel pit, belongs to the historical sediments of the terraced meandering valley of the Lambro River (Po plain, Northern Italy). The study has been conducted in five steps. (1) Architectural and sedimentological modelling was based on 31 stratigraphic logs collected along five quarry faces (four in E-W direction and one in N-S direction) and a geophysical survey, whereas the hydrostratigraphical characterization was obtained by permeability analysis of 28 samples. Facies mapping was performed in the field and supported by the analysis of the photo-composition of the quarry faces to obtain the geometry, the hierarchy and the internal architecture of sedimentary bodies. Permeability measurements on undisturbed samples and estimates based on the grain-size distribution were compared with bibliography values and used to merge the facies into four hydrofacies: least permeable (very fine sand and silt-clay respectively from topmost channel-fill, silt/clay plugs, drapes and balls), low permeable (sand from point-bar and channel fill bedforms), medium permeable (sandy gravel e gravelly sand from point bars) and most permeable (lower part of lateral accreted units). (2) For a test volume of 11.4m × 11.4m × 2.85m 50 equiprobable simulations of the hydrofacies distribution have been obtained with SISIM (Sequential indicator simulation) and MPS (Multiple point simulation) on a grid of voxels of 20cm × 20cm × 5cm. Conditioning data have been extracted from the hydrofacies maps of two crossing quarry faces. (3) The connectivity of the four simulated hydrofacies has been quantified with total and intrinsic indicators: the former measures the degree of connection within the entire volume, whereas the latter measures the degree of connection of a facies within itself and is therefore less dependent on the proportion of the facies in the total volume. (4) Finite-difference modeling of groundwater flow has been applied to compute the equivalent hydraulic-conductivity tensor. (5) Numerical experiments of convective transport of non-reactive solutes have been performed, in order to map the preferential flow paths and to compute the dispersion tensor with a Lagrangian approach and the longitudinal dispersion with an Eulerian approach. The results show that a multidisciplinary approach permits to reproduce the heterogeneity of this aquifer analogue, so that the results (strength and weaknesses of different geostatistical simulation methods, relationship of connectivity indicators with flow and transport parameters, etc.) obtained for this case study can be generalized to aquifers characterized by similar geological situations.

Damaris: Addressing performance variability in data management for post-petascale simulations

DOE PAGES

Dorier, Matthieu; Antoniu, Gabriel; Cappello, Franck; ...

2016-10-01

With exascale computing on the horizon, reducing performance variability in data management tasks (storage, visualization, analysis, etc.) is becoming a key challenge in sustaining high performance. Here, this variability significantly impacts the overall application performance at scale and its predictability over time. In this article, we present Damaris, a system that leverages dedicated cores in multicore nodes to offload data management tasks, including I/O, data compression, scheduling of data movements, in situ analysis, and visualization. We evaluate Damaris with the CM1 atmospheric simulation and the Nek5000 computational fluid dynamic simulation on four platforms, including NICS’s Kraken and NCSA’s Blue Waters.more » Our results show that (1) Damaris fully hides the I/O variability as well as all I/O-related costs, thus making simulation performance predictable; (2) it increases the sustained write throughput by a factor of up to 15 compared with standard I/O approaches; (3) it allows almost perfect scalability of the simulation up to over 9,000 cores, as opposed to state-of-the-art approaches that fail to scale; and (4) it enables a seamless connection to the VisIt visualization software to perform in situ analysis and visualization in a way that impacts neither the performance of the simulation nor its variability. In addition, we extended our implementation of Damaris to also support the use of dedicated nodes and conducted a thorough comparison of the two approaches—dedicated cores and dedicated nodes—for I/O tasks with the aforementioned applications.« less

Damaris: Addressing performance variability in data management for post-petascale simulations

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

Dorier, Matthieu; Antoniu, Gabriel; Cappello, Franck

With exascale computing on the horizon, reducing performance variability in data management tasks (storage, visualization, analysis, etc.) is becoming a key challenge in sustaining high performance. Here, this variability significantly impacts the overall application performance at scale and its predictability over time. In this article, we present Damaris, a system that leverages dedicated cores in multicore nodes to offload data management tasks, including I/O, data compression, scheduling of data movements, in situ analysis, and visualization. We evaluate Damaris with the CM1 atmospheric simulation and the Nek5000 computational fluid dynamic simulation on four platforms, including NICS’s Kraken and NCSA’s Blue Waters.more » Our results show that (1) Damaris fully hides the I/O variability as well as all I/O-related costs, thus making simulation performance predictable; (2) it increases the sustained write throughput by a factor of up to 15 compared with standard I/O approaches; (3) it allows almost perfect scalability of the simulation up to over 9,000 cores, as opposed to state-of-the-art approaches that fail to scale; and (4) it enables a seamless connection to the VisIt visualization software to perform in situ analysis and visualization in a way that impacts neither the performance of the simulation nor its variability. In addition, we extended our implementation of Damaris to also support the use of dedicated nodes and conducted a thorough comparison of the two approaches—dedicated cores and dedicated nodes—for I/O tasks with the aforementioned applications.« less

Molecular-dynamics simulations of crosslinking and confinement effects on structure, segmental mobility and mechanics of filled elastomers

NASA Astrophysics Data System (ADS)

Davris, Theodoros; Lyulin, Alexey V.

2016-05-01

The significant drop of the storage modulus under uniaxial deformation (Payne effect) restrains the performance of the elastomer-based composites and the development of possible new applications. In this paper molecular-dynamics (MD) computer simulations using LAMMPS MD package have been performed to study the mechanical properties of a coarse-grained model of this family of nanocomposite materials. Our goal is to provide simulational insights into the viscoelastic properties of filled elastomers, and try to connect the macroscopic mechanics with composite microstructure, the strength of the polymer-filler interactions and the polymer mobility at different scales. To this end we simulate random copolymer films capped between two infinite solid (filler aggregate) walls. We systematically vary the strength of the polymer-substrate adhesion interactions, degree of polymer confinement (film thickness), polymer crosslinking density, and study their influence on the equilibrium and non-equilibrium structure, segmental dynamics, and the mechanical properties of the simulated systems. The glass-transition temperature increases once the mesh size became smaller than the chain radius of gyration; otherwise it remained invariant to mesh-size variations. This increase in the glass-transition temperature was accompanied by a monotonic slowing-down of segmental dynamics on all studied length scales. This observation is attributed to the correspondingly decreased width of the bulk density layer that was obtained in films whose thickness was larger than the end-to-end distance of the bulk polymer chains. To test this hypothesis additional simulations were performed in which the crystalline walls were replaced with amorphous or rough walls.

A non-perturbative exploration of the high energy regime in Nf=3 QCD. ALPHA Collaboration

NASA Astrophysics Data System (ADS)

Dalla Brida, Mattia; Fritzsch, Patrick; Korzec, Tomasz; Ramos, Alberto; Sint, Stefan; Sommer, Rainer

2018-05-01

Using continuum extrapolated lattice data we trace a family of running couplings in three-flavour QCD over a large range of scales from about 4 to 128 GeV. The scale is set by the finite space time volume so that recursive finite size techniques can be applied, and Schrödinger functional (SF) boundary conditions enable direct simulations in the chiral limit. Compared to earlier studies we have improved on both statistical and systematic errors. Using the SF coupling to implicitly define a reference scale 1/L_0≈ 4 GeV through \\bar{g}^2(L_0) =2.012, we quote L_0 Λ ^{N_f=3}_{{\\overline{MS}}} =0.0791(21). This error is dominated by statistics; in particular, the remnant perturbative uncertainty is negligible and very well controlled, by connecting to infinite renormalization scale from different scales 2^n/L_0 for n=0,1,\\ldots ,5. An intermediate step in this connection may involve any member of a one-parameter family of SF couplings. This provides an excellent opportunity for tests of perturbation theory some of which have been published in a letter (ALPHA collaboration, M. Dalla Brida et al. in Phys Rev Lett 117(18):182001, 2016). The results indicate that for our target precision of 3 per cent in L_0 Λ ^{N_f=3}_{{\\overline{MS}}}, a reliable estimate of the truncation error requires non-perturbative data for a sufficiently large range of values of α _s=\\bar{g}^2/(4π ). In the present work we reach this precision by studying scales that vary by a factor 2^5= 32, reaching down to α _s≈ 0.1. We here provide the details of our analysis and an extended discussion.

Multi-scale Pore Imaging Techniques to Characterise Heterogeneity Effects on Flow in Carbonate Rock

NASA Astrophysics Data System (ADS)

Shah, S. M.

2017-12-01

Digital rock analysis and pore-scale studies have become an essential tool in the oil and gas industry to understand and predict the petrophysical and multiphase flow properties for the assessment and exploitation of hydrocarbon reserves. Carbonate reservoirs, accounting for majority of the world's hydrocarbon reserves, are well known for their heterogeneity and multiscale pore characteristics. The pore sizes in carbonate rock can vary over orders of magnitudes, the geometry and topology parameters of pores at different scales have a great impact on flow properties. A pore-scale study is often comprised of two key procedures: 3D pore-scale imaging and numerical modelling techniques. The fundamental problem in pore-scale imaging and modelling is how to represent and model the different range of scales encountered in porous media, from the pore-scale to macroscopic petrophysical and multiphase flow properties. However, due to the restrictions of image size vs. resolution, the desired detail is rarely captured at the relevant length scales using any single imaging technique. Similarly, direct simulations of transport properties in heterogeneous rocks with broad pore size distributions are prohibitively expensive computationally. In this study, we present the advances and review the practical limitation of different imaging techniques varying from core-scale (1mm) using Medical Computed Tomography (CT) to pore-scale (10nm - 50µm) using Micro-CT, Confocal Laser Scanning Microscopy (CLSM) and Focussed Ion Beam (FIB) to characterise the complex pore structure in Ketton carbonate rock. The effect of pore structure and connectivity on the flow properties is investigated using the obtained pore scale images of Ketton carbonate using Pore Network and Lattice-Boltzmann simulation methods in comparison with experimental data. We also shed new light on the existence and size of the Representative Element of Volume (REV) capturing the different scales of heterogeneity from the pore-scale imaging.

Scale effect on overland flow connectivity, at the interill scale

NASA Astrophysics Data System (ADS)

Penuela Fernandez, A.; Bielders, C.; Javaux, M.

2012-04-01

The relative surface connection function (RSC) was proposed by Antoine et al. (2009) as a functional indicator of runoff flow connectivity. For a given area, it expresses the percentage of the surface connected to the outlet (C) as a function of the degree of filling of the depression storage. This function explicitly integrates the flow network at the soil surface and hence provides essential information regarding the flow paths' connectivity. It has been shown that this function could help improve the modeling of the hydrogram at the square meter scale, yet it is unknown how the scale affects the RSC function, and whether and how it can be extrapolated to other scales. The main objective of this research is to study the scale effect on overland flow connectivity (RSC function). For this purpose, digital elevation data of a real field (9 x 3 m) and three synthetic fields (6 x 6 m) with contrasting hydrological responses was used, and the RSC function was calculated at different scales by changing the length (L) or width (l) of the field. Border effects were observed for the smaller scales. In most of cases, for L or l smaller than 750mm, increasing L or l, resulted in a strong increase or decrease of the maximum depression storage, respectively. There was no scale effect on the RSC function when changing l. On the contrary, a remarkable scale effect was observed in the RSC function when changing L. In general, for a given degree of filling of the depression storage, C decreased as L increased. This change in C was inversely proportional to the change in L. This observation applied only up to approx. 50-70% (depending on the hydrological response of the field) of filling of depression storage, after which no correlation was found between C and L. The results of this study help identify the critical scale to study overland flow connectivity. At scales larger than the critical scale, the RSC function showed a great potential to be extrapolated to other scales.

Multi-scale connectivity and graph theory highlight critical areas for conservation under climate change

USGS Publications Warehouse

Dilts, Thomas E.; Weisberg, Peter J.; Leitner, Phillip; Matocq, Marjorie D.; Inman, Richard D.; Nussear, Ken E.; Esque, Todd C.

2016-01-01

Conservation planning and biodiversity management require information on landscape connectivity across a range of spatial scales from individual home ranges to large regions. Reduction in landscape connectivity due changes in land-use or development is expected to act synergistically with alterations to habitat mosaic configuration arising from climate change. We illustrate a multi-scale connectivity framework to aid habitat conservation prioritization in the context of changing land use and climate. Our approach, which builds upon the strengths of multiple landscape connectivity methods including graph theory, circuit theory and least-cost path analysis, is here applied to the conservation planning requirements of the Mohave ground squirrel. The distribution of this California threatened species, as for numerous other desert species, overlaps with the proposed placement of several utility-scale renewable energy developments in the American Southwest. Our approach uses information derived at three spatial scales to forecast potential changes in habitat connectivity under various scenarios of energy development and climate change. By disentangling the potential effects of habitat loss and fragmentation across multiple scales, we identify priority conservation areas for both core habitat and critical corridor or stepping stone habitats. This approach is a first step toward applying graph theory to analyze habitat connectivity for species with continuously-distributed habitat, and should be applicable across a broad range of taxa.

Role of five-fold symmetry in undercooled Al-Cu binary alloys

NASA Astrophysics Data System (ADS)

Pasturel, A.; Jakse, N.

2018-04-01

We investigate the role of five-fold symmetry (FFS) in undercooled Al1-xCux liquids (x = 0.3 and 0.4) using ab initio molecular dynamics simulations. We show that the structure factors and pair-correlation functions display characteristic features which are compatible with the occurrence of FFS and the emergence of a medium range order (MRO) below a temperature TX located close to the liquidus temperature. Then, we demonstrate that the formation of MRO is associated with a strong increase in local FFS-motifs which become more and more connected with decreasing temperature. From the temperature dependence of dynamic properties, we find that TX corresponds also to the onset of dynamic phenomena, like the non-Arrhenius temperature dependence of transport properties and the emergence of dynamical heterogeneities (DHs). Finally, we clearly identify a relationship between the fivefold topology at the medium-range scale (IMRO) and the spatial distribution of DHs using isoconfigurational ensemble simulations. This questions the direct role of the connectivity of five-fold-based motifs found in IMRO in nucleation of the parent crystalline ground states, namely, Al2Cu and Al3Cu2, which also display local ordering with a significant degree of FFS.

Pore-scale modeling of capillary trapping in water-wet porous media: A new cooperative pore-body filling model

NASA Astrophysics Data System (ADS)

Ruspini, L. C.; Farokhpoor, R.; Øren, P. E.

2017-10-01

We present a pore-network model study of capillary trapping in water-wet porous media. The amount and distribution of trapped non-wetting phase is determined by the competition between two trapping mechanisms - snap-off and cooperative pore-body filling. We develop a new model to describe the pore-body filling mechanism in geologically realistic pore-networks. The model accounts for the geometrical characteristics of the pore, the spatial location of the connecting throats and the local fluid topology at the time of the displacement. We validate the model by comparing computed capillary trapping curves with published data for four different water-wet rocks. Computations are performed on pore-networks extracted from micro-CT images and process-based reconstructions of the actual rocks used in the experiments. Compared with commonly used stochastic models, the new model describes more accurately the experimental measurements, especially for well connected porous systems where trapping is controlled by subtleties of the pore structure. The new model successfully predicts relative permeabilities and residual saturation for Bentheimer sandstone using in-situ measured contact angles as input to the simulations. The simulated trapped cluster size distributions are compared with predictions from percolation theory.

Structure-function clustering in multiplex brain networks

NASA Astrophysics Data System (ADS)

Crofts, J. J.; Forrester, M.; O'Dea, R. D.

2016-10-01

A key question in neuroscience is to understand how a rich functional repertoire of brain activity arises within relatively static networks of structurally connected neural populations: elucidating the subtle interactions between evoked “functional connectivity” and the underlying “structural connectivity” has the potential to address this. These structural-functional networks (and neural networks more generally) are more naturally described using a multilayer or multiplex network approach, in favour of standard single-layer network analyses that are more typically applied to such systems. In this letter, we address such issues by exploring important structure-function relations in the Macaque cortical network by modelling it as a duplex network that comprises an anatomical layer, describing the known (macro-scale) network topology of the Macaque monkey, and a functional layer derived from simulated neural activity. We investigate and characterize correlations between structural and functional layers, as system parameters controlling simulated neural activity are varied, by employing recently described multiplex network measures. Moreover, we propose a novel measure of multiplex structure-function clustering which allows us to investigate the emergence of functional connections that are distinct from the underlying cortical structure, and to highlight the dependence of multiplex structure on the neural dynamical regime.

Process connectivity in a naturally prograding river delta

NASA Astrophysics Data System (ADS)

Sendrowski, Alicia; Passalacqua, Paola

2017-03-01

River deltas are lowland systems that can display high hydrological connectivity. This connectivity can be structural (morphological connections), functional (control of fluxes), and process connectivity (information flow from system drivers to sinks). In this work, we quantify hydrological process connectivity in Wax Lake Delta, coastal Louisiana, by analyzing couplings among external drivers (discharge, tides, and wind) and water levels recorded at five islands and one channel over summer 2014. We quantify process connections with information theory, a branch of mathematics concerned with the communication of information. We represent process connections as a network; variables serve as network nodes and couplings as network links describing the strength, direction, and time scale of information flow. Comparing process connections at long (105 days) and short (10 days) time scales, we show that tides exhibit daily synchronization with water level, with decreasing strength from downstream to upstream, and that tides transfer information as tides transition from spring to neap. Discharge synchronizes with water level and the time scale of its information transfer compares well to physical travel times through the system, computed with a hydrodynamic model. Information transfer and physical transport show similar spatial patterns, although information transfer time scales are larger than physical travel times. Wind events associated with water level setup lead to increased process connectivity with highly variable information transfer time scales. We discuss the information theory results in the context of the hydrologic behavior of the delta, the role of vegetation as a connector/disconnector on islands, and the applicability of process networks as tools for delta modeling results.

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

Structurally Dynamic Spin Market Networks

NASA Astrophysics Data System (ADS)

Horváth, Denis; Kuscsik, Zoltán

The agent-based model of stock price dynamics on a directed evolving complex network is suggested and studied by direct simulation. The stationary regime is maintained as a result of the balance between the extremal dynamics, adaptivity of strategic variables and reconnection rules. The inherent structure of node agent "brain" is modeled by a recursive neural network with local and global inputs and feedback connections. For specific parametric combination the complex network displays small-world phenomenon combined with scale-free behavior. The identification of a local leader (network hub, agent whose strategies are frequently adapted by its neighbors) is carried out by repeated random walk process through network. The simulations show empirically relevant dynamics of price returns and volatility clustering. The additional emerging aspects of stylized market statistics are Zipfian distributions of fitness.

Observational Signatures of Coronal Heating

NASA Astrophysics Data System (ADS)

Dahlburg, R. B.; Einaudi, G.; Ugarte-Urra, I.; Warren, H. P.; Rappazzo, A. F.; Velli, M.; Taylor, B.

2016-12-01

Recent research on observational signatures of turbulent heating of a coronal loop will be discussed. The evolution of the loop is is studied by means of numericalsimulations of the fully compressible three-dimensionalmagnetohydrodynamic equations using the HYPERION code. HYPERION calculates the full energy cycle involving footpoint convection, magnetic reconnection,nonlinear thermal conduction and optically thin radiation.The footpoints of the loop magnetic field are convected by random photospheric motions. As a consequence the magnetic field in the loop is energized and develops turbulent nonlinear dynamics characterized by the continuous formation and dissipation of field-aligned current sheets: energy is deposited at small scales where heating occurs. Dissipation is non-uniformly distributed so that only a fraction of thecoronal mass and volume gets heated at any time. Temperature and density are highly structured at scales which, in the solar corona, remain observationally unresolved: the plasma of the simulated loop is multi-thermal, where highly dynamical hotter and cooler plasma strands arescattered throughout the loop at sub-observational scales. Typical simulated coronal loops are 50000 km length and have axial magnetic field intensities ranging from 0.01 to 0.04 Tesla.To connect these simulations to observations the computed numberdensities and temperatures are used to synthesize the intensities expected inemission lines typically observed with the Extreme ultraviolet Imaging Spectrometer(EIS) on Hinode. These intensities are then employed to compute differentialemission measure distributions, which are found to be very similar to those derivedfrom observations of solar active regions.

Longitudinal train dynamics: an overview

NASA Astrophysics Data System (ADS)

Wu, Qing; Spiryagin, Maksym; Cole, Colin

2016-12-01

This paper discusses the evolution of longitudinal train dynamics (LTD) simulations, which covers numerical solvers, vehicle connection systems, air brake systems, wagon dumper systems and locomotives, resistance forces and gravitational components, vehicle in-train instabilities, and computing schemes. A number of potential research topics are suggested, such as modelling of friction, polymer, and transition characteristics for vehicle connection simulations, studies of wagon dumping operations, proper modelling of vehicle in-train instabilities, and computing schemes for LTD simulations. Evidence shows that LTD simulations have evolved with computing capabilities. Currently, advanced component models that directly describe the working principles of the operation of air brake systems, vehicle connection systems, and traction systems are available. Parallel computing is a good solution to combine and simulate all these advanced models. Parallel computing can also be used to conduct three-dimensional long train dynamics simulations.

Scaling of peak flows with constant flow velocity in random self-similar networks

USGS Publications Warehouse

Troutman, Brent M.; Mantilla, Ricardo; Gupta, Vijay K.

2011-01-01

A methodology is presented to understand the role of the statistical self-similar topology of real river networks on scaling, or power law, in peak flows for rainfall-runoff events. We created Monte Carlo generated sets of ensembles of 1000 random self-similar networks (RSNs) with geometrically distributed interior and exterior generators having parameters pi and pe, respectively. The parameter values were chosen to replicate the observed topology of real river networks. We calculated flow hydrographs in each of these networks by numerically solving the link-based mass and momentum conservation equation under the assumption of constant flow velocity. From these simulated RSNs and hydrographs, the scaling exponents β and φ characterizing power laws with respect to drainage area, and corresponding to the width functions and flow hydrographs respectively, were estimated. We found that, in general, φ > β, which supports a similar finding first reported for simulations in the river network of the Walnut Gulch basin, Arizona. Theoretical estimation of β and φ in RSNs is a complex open problem. Therefore, using results for a simpler problem associated with the expected width function and expected hydrograph for an ensemble of RSNs, we give heuristic arguments for theoretical derivations of the scaling exponents β(E) and φ(E) that depend on the Horton ratios for stream lengths and areas. These ratios in turn have a known dependence on the parameters of the geometric distributions of RSN generators. Good agreement was found between the analytically conjectured values of β(E) and φ(E) and the values estimated by the simulated ensembles of RSNs and hydrographs. The independence of the scaling exponents φ(E) and φ with respect to the value of flow velocity and runoff intensity implies an interesting connection between unit hydrograph theory and flow dynamics. Our results provide a reference framework to study scaling exponents under more complex scenarios of flow dynamics and runoff generation processes using ensembles of RSNs.

Assessing the Impact of Topography on Groundwater Salinization Due to Storm Surge Inundation

NASA Astrophysics Data System (ADS)

Yu, X.; Yang, J.; Graf, T.; Koneshloo, M.; O'Neal, M. A.; Michael, H. A.

2015-12-01

The sea-level rise and increase in the frequency and intensity of coastal storms due to climate change are likely to exacerbate adverse effects of storm surges on low-lying coastal areas. The landward flow of water during storm surges introduces salt to surficial coastal aquifers and threatens groundwater resources. Coastal topography (e.g. ponds, dunes, canals) likely has a strong impact on overwash and salinization processes, but is generally highly simplified in modeling studies. To understand the topographic impacts on groundwater salinization, we modeled overwash and variable-density groundwater flow and salt transport in 3D using the fully coupled surface and subsurface numerical simulator, HydroGeoSphere. The model simulates the coastal aquifer as an integrated system considering processes such as overland flow, coupled surface and subsurface exchange, variably saturated flow, and variable-density flow. To represent various coastal landscape types, we started with realistic coastal topography from Delaware, USA, and then generated synthetic fields with differing shore-perpendicular connectivity and surface depressions. The groundwater salinization analysis suggested that the topographic connectivity promoting overland flow controls the volume of aquifer that is salinized. In contrast, depression storage of surface water mainly controls the time for infiltrated salt to flush from the aquifer. The results indicate that for a range of synthetic conditions, topography increases the flushing time of salt by 20-300% relative to an equivalent "simple slope" in which topographic variation is absent. Our study suggests that topography have a significant impact on overwash salinization, with important implications for land management at local scales and groundwater vulnerability assessment at regional to global scales.

ntermediate frequency atmospheric disturbances: A dynamical bridge connecting western U.S. extreme precipitation with East Asian cold surges

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

Jiang, Tianyu NMI; Evans, Katherine J; Deng, Yi

In this study, an atmospheric river (AR) detection algorithm is developed to investigate the downstream modulation of the eastern North Pacific ARs by another weather extreme, known as the East Asian cold surge (EACS), in both reanalysis data and high-resolution global model simulations. It is shown that following the peak of an EACS, atmospheric disturbances of intermediate frequency (IF; 10 30 day period) are excited downstream. This leads to the formation of a persistent cyclonic circulation anomaly over the eastern North Pacific that dramatically enhances the AR occurrence probability and the surface precipitation over the western U.S. between 30 Nmore » and 50 N. A diagnosis of the local geopotential height tendency further confirms the essential role of IF disturbances in establishing the observed persistent anomaly. This downstream modulation effect is then examined in the two simulations of the National Center for Atmospheric Research Community Climate System Model version 4 with different horizontal resolutions (T85 and T341) for the same period (1979 2005). The connection between EACS and AR is much better captured by the T341 version of the model, mainly due to a better representation of the scale interaction and the characteristics of IF atmospheric disturbances in the higher-resolution model. The findings here suggest that faithful representations of scale interaction in a global model are critical for modeling and predicting the occurrences of hydrological extremes in the western U.S. and for understanding their potential future changes.« less

Surface-Atmosphere Connections on Titan: A New Window into Terrestrial Hydroclimate

NASA Astrophysics Data System (ADS)

Faulk, Sean

This dissertation investigates the coupling between the large-scale atmospheric circulation and surface processes on Titan, with a particular focus on methane precipitation and its influence on surface geomorphology and hydrology. As the only body in the Solar System with an active hydrologic cycle other than Earth, Titan presents a valuable laboratory for studying principles of hydroclimate on terrestrial planets. Idealized general circulation models (GCMs) are used here to test hypotheses regarding Titan's surface-atmosphere connections. First, an Earth-like GCM simulated over a range of rotation rates is used to evaluate the effect of rotation rate on seasonal monsoon behavior. Slower rotation rates result in poleward migration of summer rain, indicating a large-scale atmospheric control on Titan's observed dichotomy of dry low latitudes and moist high latitudes. Second, a Titan GCM benchmarked against observations is used to analyze the magnitudes and frequencies of extreme methane rainstorms as simulated by the model. Regional patterns in these extreme events correlate well with observed geomorphic features, with the most extreme rainstorms occurring in mid-latitude regions associated with high alluvial fan concentrations. Finally, a planetary surface hydrology scheme is developed and incorporated into a Titan GCM to evaluate the roles of surface flow, subsurface flow, infiltration, and groundmethane evaporation in Titan's climate. The model reproduces Titan's observed surface liquid and cloud distributions, and reaches an equilibrium state with limited interhemispheric transport where atmospheric transport is approximately balanced by subsurface transport. The equilibrium state suggests that Titan's current hemispheric surface liquid asymmetry, favoring methane accumulation in the north, is stable in the modern climate.

Constructing Neuronal Network Models in Massively Parallel Environments.

PubMed

Ippen, Tammo; Eppler, Jochen M; Plesser, Hans E; Diesmann, Markus

2017-01-01

Recent advances in the development of data structures to represent spiking neuron network models enable us to exploit the complete memory of petascale computers for a single brain-scale network simulation. In this work, we investigate how well we can exploit the computing power of such supercomputers for the creation of neuronal networks. Using an established benchmark, we divide the runtime of simulation code into the phase of network construction and the phase during which the dynamical state is advanced in time. We find that on multi-core compute nodes network creation scales well with process-parallel code but exhibits a prohibitively large memory consumption. Thread-parallel network creation, in contrast, exhibits speedup only up to a small number of threads but has little overhead in terms of memory. We further observe that the algorithms creating instances of model neurons and their connections scale well for networks of ten thousand neurons, but do not show the same speedup for networks of millions of neurons. Our work uncovers that the lack of scaling of thread-parallel network creation is due to inadequate memory allocation strategies and demonstrates that thread-optimized memory allocators recover excellent scaling. An analysis of the loop order used for network construction reveals that more complex tests on the locality of operations significantly improve scaling and reduce runtime by allowing construction algorithms to step through large networks more efficiently than in existing code. The combination of these techniques increases performance by an order of magnitude and harnesses the increasingly parallel compute power of the compute nodes in high-performance clusters and supercomputers.

Constructing Neuronal Network Models in Massively Parallel Environments

PubMed Central

Ippen, Tammo; Eppler, Jochen M.; Plesser, Hans E.; Diesmann, Markus

2017-01-01

Recent advances in the development of data structures to represent spiking neuron network models enable us to exploit the complete memory of petascale computers for a single brain-scale network simulation. In this work, we investigate how well we can exploit the computing power of such supercomputers for the creation of neuronal networks. Using an established benchmark, we divide the runtime of simulation code into the phase of network construction and the phase during which the dynamical state is advanced in time. We find that on multi-core compute nodes network creation scales well with process-parallel code but exhibits a prohibitively large memory consumption. Thread-parallel network creation, in contrast, exhibits speedup only up to a small number of threads but has little overhead in terms of memory. We further observe that the algorithms creating instances of model neurons and their connections scale well for networks of ten thousand neurons, but do not show the same speedup for networks of millions of neurons. Our work uncovers that the lack of scaling of thread-parallel network creation is due to inadequate memory allocation strategies and demonstrates that thread-optimized memory allocators recover excellent scaling. An analysis of the loop order used for network construction reveals that more complex tests on the locality of operations significantly improve scaling and reduce runtime by allowing construction algorithms to step through large networks more efficiently than in existing code. The combination of these techniques increases performance by an order of magnitude and harnesses the increasingly parallel compute power of the compute nodes in high-performance clusters and supercomputers. PMID:28559808

A physics-motivated Centroidal Voronoi Particle domain decomposition method

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

Fu, Lin, E-mail: lin.fu@tum.de; Hu, Xiangyu Y., E-mail: xiangyu.hu@tum.de; Adams, Nikolaus A., E-mail: nikolaus.adams@tum.de

2017-04-15

In this paper, we propose a novel domain decomposition method for large-scale simulations in continuum mechanics by merging the concepts of Centroidal Voronoi Tessellation (CVT) and Voronoi Particle dynamics (VP). The CVT is introduced to achieve a high-level compactness of the partitioning subdomains by the Lloyd algorithm which monotonically decreases the CVT energy. The number of computational elements between neighboring partitioning subdomains, which scales the communication effort for parallel simulations, is optimized implicitly as the generated partitioning subdomains are convex and simply connected with small aspect-ratios. Moreover, Voronoi Particle dynamics employing physical analogy with a tailored equation of state ismore » developed, which relaxes the particle system towards the target partition with good load balance. Since the equilibrium is computed by an iterative approach, the partitioning subdomains exhibit locality and the incremental property. Numerical experiments reveal that the proposed Centroidal Voronoi Particle (CVP) based algorithm produces high-quality partitioning with high efficiency, independently of computational-element types. Thus it can be used for a wide range of applications in computational science and engineering.« less

Anatomical connectivity influences both intra- and inter-brain synchronizations.

PubMed

Dumas, Guillaume; Chavez, Mario; Nadel, Jacqueline; Martinerie, Jacques

2012-01-01

Recent development in diffusion spectrum brain imaging combined to functional simulation has the potential to further our understanding of how structure and dynamics are intertwined in the human brain. At the intra-individual scale, neurocomputational models have already started to uncover how the human connectome constrains the coordination of brain activity across distributed brain regions. In parallel, at the inter-individual scale, nascent social neuroscience provides a new dynamical vista of the coupling between two embodied cognitive agents. Using EEG hyperscanning to record simultaneously the brain activities of subjects during their ongoing interaction, we have previously demonstrated that behavioral synchrony correlates with the emergence of inter-brain synchronization. However, the functional meaning of such synchronization remains to be specified. Here, we use a biophysical model to quantify to what extent inter-brain synchronizations are related to the anatomical and functional similarity of the two brains in interaction. Pairs of interacting brains were numerically simulated and compared to real data. Results show a potential dynamical property of the human connectome to facilitate inter-individual synchronizations and thus may partly account for our propensity to generate dynamical couplings with others.

A physics-motivated Centroidal Voronoi Particle domain decomposition method

NASA Astrophysics Data System (ADS)

Fu, Lin; Hu, Xiangyu Y.; Adams, Nikolaus A.

2017-04-01

In this paper, we propose a novel domain decomposition method for large-scale simulations in continuum mechanics by merging the concepts of Centroidal Voronoi Tessellation (CVT) and Voronoi Particle dynamics (VP). The CVT is introduced to achieve a high-level compactness of the partitioning subdomains by the Lloyd algorithm which monotonically decreases the CVT energy. The number of computational elements between neighboring partitioning subdomains, which scales the communication effort for parallel simulations, is optimized implicitly as the generated partitioning subdomains are convex and simply connected with small aspect-ratios. Moreover, Voronoi Particle dynamics employing physical analogy with a tailored equation of state is developed, which relaxes the particle system towards the target partition with good load balance. Since the equilibrium is computed by an iterative approach, the partitioning subdomains exhibit locality and the incremental property. Numerical experiments reveal that the proposed Centroidal Voronoi Particle (CVP) based algorithm produces high-quality partitioning with high efficiency, independently of computational-element types. Thus it can be used for a wide range of applications in computational science and engineering.

SNAVA-A real-time multi-FPGA multi-model spiking neural network simulation architecture.

PubMed

Sripad, Athul; Sanchez, Giovanny; Zapata, Mireya; Pirrone, Vito; Dorta, Taho; Cambria, Salvatore; Marti, Albert; Krishnamourthy, Karthikeyan; Madrenas, Jordi

2018-01-01

Spiking Neural Networks (SNN) for Versatile Applications (SNAVA) simulation platform is a scalable and programmable parallel architecture that supports real-time, large-scale, multi-model SNN computation. This parallel architecture is implemented in modern Field-Programmable Gate Arrays (FPGAs) devices to provide high performance execution and flexibility to support large-scale SNN models. Flexibility is defined in terms of programmability, which allows easy synapse and neuron implementation. This has been achieved by using a special-purpose Processing Elements (PEs) for computing SNNs, and analyzing and customizing the instruction set according to the processing needs to achieve maximum performance with minimum resources. The parallel architecture is interfaced with customized Graphical User Interfaces (GUIs) to configure the SNN's connectivity, to compile the neuron-synapse model and to monitor SNN's activity. Our contribution intends to provide a tool that allows to prototype SNNs faster than on CPU/GPU architectures but significantly cheaper than fabricating a customized neuromorphic chip. This could be potentially valuable to the computational neuroscience and neuromorphic engineering communities. Copyright © 2017 Elsevier Ltd. All rights reserved.

Conformity hinders the evolution of cooperation on scale-free networks

NASA Astrophysics Data System (ADS)

Peña, Jorge; Volken, Henri; Pestelacci, Enea; Tomassini, Marco

2009-07-01

We study the effects of conformity, the tendency of humans to imitate locally common behaviors, in the evolution of cooperation when individuals occupy the vertices of a graph and engage in the one-shot prisoner’s dilemma or the snowdrift game with their neighbors. Two different graphs are studied: rings (one-dimensional lattices with cyclic boundary conditions) and scale-free networks of the Barabási-Albert type. The proposed evolutionary-graph model is studied both by means of Monte Carlo simulations and an extended pair-approximation technique. We find improved levels of cooperation when evolution is carried on rings and individuals imitate according to both the traditional payoff bias and a conformist bias. More importantly, we show that scale-free networks are no longer powerful amplifiers of cooperation when fair amounts of conformity are introduced in the imitation rules of the players. Such weakening of the cooperation-promoting abilities of scale-free networks is the result of a less biased flow of information in scale-free topologies, making hubs more susceptible of being influenced by less-connected neighbors.

Some thoughts on building, evaluating and constraining hydrologic models from catchment to continental scales

NASA Astrophysics Data System (ADS)

Wagener, Thorsten

2017-04-01

We increasingly build and apply hydrologic models that simulate systems beyond the catchment scale. Such models run at regional, national or even continental scales. They therefore offer opportunities for new scientific insights, for example by enabling comparative hydrology or connectivity studies, and for water management, where we might better understand changes to water resources from larger scale activities like agriculture or from hazards such as droughts. However, these models also require us to rethink how we build and evaluate them given that some of the unsolved problems from the catchment scale have not gone away. So what role should such models play in scientific advancement in hydrology? What problems do we still have to resolve before they can fulfill their role? What opportunities for solving these problems are there, but have not yet been utilized? I will provide some thoughts on these issues in the context of the IAHS Panta Rhei initiative and the scientific challenges it has set out for hydrology (Montanari et al., 2013, Hydrological Sciences Journal; McMillan et al., 2016, Hydrological Sciences Journal).

Connecting the failure of K-theory inside and above vegetation canopies and ejection-sweep cycles by a large eddy simulation

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

Banerjee, Tirtha; De Roo, Frederik; Mauder, Matthias

Parameterizations of biosphere-atmosphere interaction processes in climate models and other hydrological applications require characterization of turbulent transport of momentum and scalars between vegetation canopies and the atmosphere, which is often modeled using a turbulent analogy to molecular diffusion processes. However, simple flux-gradient approaches (K-theory) fail for canopy turbulence. One cause is turbulent transport by large coherent eddies at the canopy scale, which can be linked to sweep-ejection events, and bear signatures of non-local organized eddy motions. K-theory, that parameterizes the turbulent flux or stress proportional to the local concentration or velocity gradient, fails to account for these non-local organized motions. The connection to sweep-ejection cycles and the local turbulent flux can be traced back to the turbulence triple momentmore » $$\\overline{C'W'W'}$$. In this work, we use large-eddy simulation to investigate the diagnostic connection between the failure of K-theory and sweep-ejection motions. Analyzed schemes are quadrant analysis (QA) and a complete and incomplete cumulant expansion (CEM and ICEM) method. The latter approaches introduce a turbulence timescale in the modeling. Furthermore, we find that the momentum flux needs a different formulation for the turbulence timescale than the sensible heat flux. In conclusion, accounting for buoyancy in stratified conditions is also deemed to be important in addition to accounting for non-local events to predict the correct momentum or scalar fluxes.« less

Connecting the failure of K-theory inside and above vegetation canopies and ejection-sweep cycles by a large eddy simulation

DOE PAGES

Banerjee, Tirtha; De Roo, Frederik; Mauder, Matthias

2017-10-19

Parameterizations of biosphere-atmosphere interaction processes in climate models and other hydrological applications require characterization of turbulent transport of momentum and scalars between vegetation canopies and the atmosphere, which is often modeled using a turbulent analogy to molecular diffusion processes. However, simple flux-gradient approaches (K-theory) fail for canopy turbulence. One cause is turbulent transport by large coherent eddies at the canopy scale, which can be linked to sweep-ejection events, and bear signatures of non-local organized eddy motions. K-theory, that parameterizes the turbulent flux or stress proportional to the local concentration or velocity gradient, fails to account for these non-local organized motions. The connection to sweep-ejection cycles and the local turbulent flux can be traced back to the turbulence triple momentmore » $$\\overline{C'W'W'}$$. In this work, we use large-eddy simulation to investigate the diagnostic connection between the failure of K-theory and sweep-ejection motions. Analyzed schemes are quadrant analysis (QA) and a complete and incomplete cumulant expansion (CEM and ICEM) method. The latter approaches introduce a turbulence timescale in the modeling. Furthermore, we find that the momentum flux needs a different formulation for the turbulence timescale than the sensible heat flux. In conclusion, accounting for buoyancy in stratified conditions is also deemed to be important in addition to accounting for non-local events to predict the correct momentum or scalar fluxes.« less

Discretized kinetic theory on scale-free networks

NASA Astrophysics Data System (ADS)

Bertotti, Maria Letizia; Modanese, Giovanni

2016-10-01

The network of interpersonal connections is one of the possible heterogeneous factors which affect the income distribution emerging from micro-to-macro economic models. In this paper we equip our model discussed in [1, 2] with a network structure. The model is based on a system of n differential equations of the kinetic discretized-Boltzmann kind. The network structure is incorporated in a probabilistic way, through the introduction of a link density P(α) and of correlation coefficients P(β|α), which give the conditioned probability that an individual with α links is connected to one with β links. We study the properties of the equations and give analytical results concerning the existence, normalization and positivity of the solutions. For a fixed network with P(α) = c/α q , we investigate numerically the dependence of the detailed and marginal equilibrium distributions on the initial conditions and on the exponent q. Our results are compatible with those obtained from the Bouchaud-Mezard model and from agent-based simulations, and provide additional information about the dependence of the individual income on the level of connectivity.

Effects of fear factors in disease propagation

NASA Astrophysics Data System (ADS)

Wang, Yubo; Xiao, Gaoxi; Wong, Limsoon; Fu, Xiuju; Ma, Stefan; Hiang Cheng, Tee

2011-09-01

Upon an outbreak of a dangerous infectious disease, people generally tend to reduce their contacts with others in fear of getting infected. Such typical actions apparently help slow down the spreading of infection. Thanks to today's broad public media coverage, the fear factor may even contribute to preventing an outbreak from happening. We are motivated to study such effects by adopting a complex network approach. First we evaluate the simple case where connections between individuals are randomly removed due to the fear factor. Then we consider a different case where each individual keeps at least a few connections after contact reduction. Such a case is arguably more realistic since people may choose to keep a few social contacts, e.g., with their family members and closest friends, at any cost. Finally, a study is conducted on the case where connection removals are carried out dynamically while the infection is spreading out. Analytical and simulation results show that the fear factor may not easily prevent an epidemic outbreak from happening in scale-free networks. However, it significantly reduces the fraction of the nodes ever getting infected during the outbreak.

Multiscale pore structure and its effect on gas transport in organic-rich shale

NASA Astrophysics Data System (ADS)

Wu, Tianhao; Li, Xiang; Zhao, Junliang; Zhang, Dongxiao

2017-07-01

A systematic investigation of multiscale pore structure in organic-rich shale by means of the combination of various imaging techniques is presented, including the state-of-the-art Helium-Ion-Microscope (HIM). The study achieves insight into the major features at each scale and suggests the affordable techniques for specific objectives from the aspects of resolution, dimension, and cost. The pores, which appear to be isolated, are connected by smaller pores resolved by higher-resolution imaging. This observation provides valuable information, from the microscopic perspective of pore structure, for understanding how gas accumulates and transports from where it is generated. A comprehensive workflow is proposed based on the characteristics acquired from the multiscale pore structure analysis to simulate the gas transport process. The simulations are completed with three levels: the microscopic mechanisms should be taken into consideration at level I; the spatial distribution features of organic matter, inorganic matter, and macropores constitute the major issue at level II; and the microfracture orientation and topological structure are dominant factors at level III. The results of apparent permeability from simulations agree well with the values acquired from experiments. By means of the workflow, the impact of various gas transport mechanisms at different scales can be investigated more individually and precisely than conventional experiments.

Scaling up a CMS tier-3 site with campus resources and a 100 Gb/s network connection: what could go wrong?

NASA Astrophysics Data System (ADS)

Wolf, Matthias; Woodard, Anna; Li, Wenzhao; Hurtado Anampa, Kenyi; Tovar, Benjamin; Brenner, Paul; Lannon, Kevin; Hildreth, Mike; Thain, Douglas

2017-10-01

The University of Notre Dame (ND) CMS group operates a modest-sized Tier-3 site suitable for local, final-stage analysis of CMS data. However, through the ND Center for Research Computing (CRC), Notre Dame researchers have opportunistic access to roughly 25k CPU cores of computing and a 100 Gb/s WAN network link. To understand the limits of what might be possible in this scenario, we undertook to use these resources for a wide range of CMS computing tasks from user analysis through large-scale Monte Carlo production (including both detector simulation and data reconstruction.) We will discuss the challenges inherent in effectively utilizing CRC resources for these tasks and the solutions deployed to overcome them.

A chip-scale, telecommunications-band frequency conversion interface for quantum emitters.

PubMed

Agha, Imad; Ates, Serkan; Davanço, Marcelo; Srinivasan, Kartik

2013-09-09

We describe a chip-scale, telecommunications-band frequency conversion interface designed for low-noise operation at wavelengths desirable for common single photon emitters. Four-wave-mixing Bragg scattering in silicon nitride waveguides is used to demonstrate frequency upconversion and downconversion between the 980 nm and 1550 nm wavelength regions, with signal-to-background levels > 10 and conversion efficiency of ≈ -60 dB at low continuous wave input pump powers (< 50 mW). Finite element simulations and the split-step Fourier method indicate that increased input powers of ≈ 10 W (produced by amplified nanosecond pulses, for example) will result in a conversion efficiency > 25 % in existing geometries. Finally, we present waveguide designs that can be used to connect shorter wavelength (637 nm to 852 nm) quantum emitters with 1550 nm.

The Early Growth of the First Black Holes

NASA Astrophysics Data System (ADS)

Johnson, Jarrett L.; Haardt, Francesco

2016-03-01

With detections of quasars powered by increasingly massive black holes at increasingly early times in cosmic history over the past decade, there has been correspondingly rapid progress made on the theory of early black hole formation and growth. Here, we review the emerging picture of how the first massive black holes formed from the primordial gas and then grew to supermassive scales. We discuss the initial conditions for the formation of the progenitors of these seed black holes, the factors dictating the initial masses with which they form, and their initial stages of growth via accretion, which may occur at super-Eddington rates. Finally, we briefly discuss how these results connect to large-scale simulations of the growth of supermassive black holes in the first billion years after the Big Bang.

Structural and functional connectivity as a driver of hillslope erosion following disturbance

USDA-ARS?s Scientific Manuscript database

Hydrologic response to rainfall input on fragmented or burnt hillslopes is strongly influenced by the ensuing connectivity of runoff and erosion processes. Yet, cross-scale process connectivity is seldom evaluated in field studies due scale limitations in experimental design. This study quantified...

Studies of stimulus parameters for seizure disruption using neural network simulations.

PubMed

Anderson, William S; Kudela, Pawel; Cho, Jounhong; Bergey, Gregory K; Franaszczuk, Piotr J

2007-08-01

A large scale neural network simulation with realistic cortical architecture has been undertaken to investigate the effects of external electrical stimulation on the propagation and evolution of ongoing seizure activity. This is an effort to explore the parameter space of stimulation variables to uncover promising avenues of research for this therapeutic modality. The model consists of an approximately 800 mum x 800 mum region of simulated cortex, and includes seven neuron classes organized by cortical layer, inhibitory or excitatory properties, and electrophysiological characteristics. The cell dynamics are governed by a modified version of the Hodgkin-Huxley equations in single compartment format. Axonal connections are patterned after histological data and published models of local cortical wiring. Stimulation induced action potentials take place at the axon initial segments, according to threshold requirements on the applied electric field distribution. Stimulation induced action potentials in horizontal axonal branches are also separately simulated. The calculations are performed on a 16 node distributed 32-bit processor system. Clear differences in seizure evolution are presented for stimulated versus the undisturbed rhythmic activity. Data is provided for frequency dependent stimulation effects demonstrating a plateau effect of stimulation efficacy as the applied frequency is increased from 60 to 200 Hz. Timing of the stimulation with respect to the underlying rhythmic activity demonstrates a phase dependent sensitivity. Electrode height and position effects are also presented. Using a dipole stimulation electrode arrangement, clear orientation effects of the dipole with respect to the model connectivity is also demonstrated. A sensitivity analysis of these results as a function of the stimulation threshold is also provided.

The Virtual Brain: a simulator of primate brain network dynamics.

PubMed

Sanz Leon, Paula; Knock, Stuart A; Woodman, M Marmaduke; Domide, Lia; Mersmann, Jochen; McIntosh, Anthony R; Jirsa, Viktor

2013-01-01

We present The Virtual Brain (TVB), a neuroinformatics platform for full brain network simulations using biologically realistic connectivity. This simulation environment enables the model-based inference of neurophysiological mechanisms across different brain scales that underlie the generation of macroscopic neuroimaging signals including functional MRI (fMRI), EEG and MEG. Researchers from different backgrounds can benefit from an integrative software platform including a supporting framework for data management (generation, organization, storage, integration and sharing) and a simulation core written in Python. TVB allows the reproduction and evaluation of personalized configurations of the brain by using individual subject data. This personalization facilitates an exploration of the consequences of pathological changes in the system, permitting to investigate potential ways to counteract such unfavorable processes. The architecture of TVB supports interaction with MATLAB packages, for example, the well known Brain Connectivity Toolbox. TVB can be used in a client-server configuration, such that it can be remotely accessed through the Internet thanks to its web-based HTML5, JS, and WebGL graphical user interface. TVB is also accessible as a standalone cross-platform Python library and application, and users can interact with the scientific core through the scripting interface IDLE, enabling easy modeling, development and debugging of the scientific kernel. This second interface makes TVB extensible by combining it with other libraries and modules developed by the Python scientific community. In this article, we describe the theoretical background and foundations that led to the development of TVB, the architecture and features of its major software components as well as potential neuroscience applications.

The Virtual Brain: a simulator of primate brain network dynamics

PubMed Central

Sanz Leon, Paula; Knock, Stuart A.; Woodman, M. Marmaduke; Domide, Lia; Mersmann, Jochen; McIntosh, Anthony R.; Jirsa, Viktor

2013-01-01

We present The Virtual Brain (TVB), a neuroinformatics platform for full brain network simulations using biologically realistic connectivity. This simulation environment enables the model-based inference of neurophysiological mechanisms across different brain scales that underlie the generation of macroscopic neuroimaging signals including functional MRI (fMRI), EEG and MEG. Researchers from different backgrounds can benefit from an integrative software platform including a supporting framework for data management (generation, organization, storage, integration and sharing) and a simulation core written in Python. TVB allows the reproduction and evaluation of personalized configurations of the brain by using individual subject data. This personalization facilitates an exploration of the consequences of pathological changes in the system, permitting to investigate potential ways to counteract such unfavorable processes. The architecture of TVB supports interaction with MATLAB packages, for example, the well known Brain Connectivity Toolbox. TVB can be used in a client-server configuration, such that it can be remotely accessed through the Internet thanks to its web-based HTML5, JS, and WebGL graphical user interface. TVB is also accessible as a standalone cross-platform Python library and application, and users can interact with the scientific core through the scripting interface IDLE, enabling easy modeling, development and debugging of the scientific kernel. This second interface makes TVB extensible by combining it with other libraries and modules developed by the Python scientific community. In this article, we describe the theoretical background and foundations that led to the development of TVB, the architecture and features of its major software components as well as potential neuroscience applications. PMID:23781198

Percolation connectivity, pore size, and gas apparent permeability: Network simulations and comparison to experimental data

NASA Astrophysics Data System (ADS)

Li, M.; Tang, Y. B.; Bernabé, Y.; Zhao, J. Z.; Li, X. F.; Li, T.

2017-07-01

We modeled single-phase gas flow through porous media using percolation networks. Gas permeability is different from liquid permeability. The latter is only related to the geometry and topology of the pore space, while the former depends on the specific gas considered and varies with gas pressure. As gas pressure decreases, four flow regimes can be distinguished as viscous flow, slip flow, transition flow, and free molecular diffusion. Here we use a published conductance model presumably capable of predicting the flow rate of an arbitrary gas through a cylindrical pipe in the four regimes. We incorporated this model into pipe network simulations. We considered 3-D simple cubic, body-centered cubic, and face-centered cubic lattices, in which we varied the pipe radius distribution and the bond coordination number. Gas flow was simulated at different gas pressures. The simulation results showed that the gas apparent permeability kapp obeys an identical scaling law in all three lattices, kapp (z-zc)β, where the exponent β depends on the width of the pipe radius distribution, z is the mean coordination number, and zc its critical value at the percolation threshold. Surprisingly, (z-zc) had a very weak effect on the ratio of the apparent gas permeability to the absolute liquid permeability, kapp/kabs, suggesting that the Klinkenberg gas slippage correction factor is nearly independent of connectivity. We constructed models of kapp and kapp/kabs based on the observed power law and tested them by comparison with published experimental data on glass beads and other materials.

Molecular Dynamics Modeling of Carbon Nanotube Composite Fracture Using ReaxFF

NASA Technical Reports Server (NTRS)

Jensen, Benjamin D.; Wise, Kristopher E.; Odegard, Gregory M.

2016-01-01

Carbon nanotube (CNT) fiber reinforced composites with specific tensile strengths and moduli approaching those of aerospace grade carbon fiber composites have recently been reported. This achievement was enabled by the emerging availability of high N/tex yarns in kilometer-scale quantities. While the production of this yarn is an impressive advance, its strength is still much lower than that of the individual CNTs comprising the yarn. Closing this gap requires understanding load transfer between CNTs at the nanometer dimensional scale. This work uses reactive molecular dynamics simulations to gain an understanding at the nanometer scale of the key factors that determine CNT nanocomposite mechanical performance, and to place more realistic upper bounds on the target properties. While molecular dynamics simulations using conventional force fields can predict elastic properties, the ReaxFF reactive forcefield can also model fracture behavior because of its ability to accurately describe bond breaking and formation during a simulation. The upper and lower bounds of CNT composite properties are investigated by comparing systems composed of CNTs continuously connected across the periodic boundary with systems composed of finite length CNTs. These lengths, effectively infinite for the continuous tubes and an aspect ratio of 13 for the finite length case, result from practical limitations on the number of atoms that can be included in a simulation. Experimentally measured aspect ratios are typically on the order of 100,000, so the calculated results should represent upper and lower limits on experimental mechanical properties. Finally, the effect of various degrees of covalent crosslinking between the CNTs and amorphous carbon matrix is considered to identify the amount of CNT-matrix covalent bonding that maximizes overall composite properties.

Integrated tokamak modeling: when physics informs engineering and research planning

NASA Astrophysics Data System (ADS)

Poli, Francesca

2017-10-01

Simulations that integrate virtually all the relevant engineering and physics aspects of a real tokamak experiment are a power tool for experimental interpretation, model validation and planning for both present and future devices. This tutorial will guide through the building blocks of an ``integrated'' tokamak simulation, such as magnetic flux diffusion, thermal, momentum and particle transport, external heating and current drive sources, wall particle sources and sinks. Emphasis is given to the connection and interplay between external actuators and plasma response, between the slow time scales of the current diffusion and the fast time scales of transport, and how reduced and high-fidelity models can contribute to simulate a whole device. To illustrate the potential and limitations of integrated tokamak modeling for discharge prediction, a helium plasma scenario for the ITER pre-nuclear phase is taken as an example. This scenario presents challenges because it requires core-edge integration and advanced models for interaction between waves and fast-ions, which are subject to a limited experimental database for validation and guidance. Starting from a scenario obtained by re-scaling parameters from the demonstration inductive ``ITER baseline'', it is shown how self-consistent simulations that encompass both core and edge plasma regions, as well as high-fidelity heating and current drive source models are needed to set constraints on the density, magnetic field and heating scheme. This tutorial aims at demonstrating how integrated modeling, when used with adequate level of criticism, can not only support design of operational scenarios, but also help to asses the limitations and gaps in the available models, thus indicating where improved modeling tools are required and how present experiments can help their validation and inform research planning. Work supported by DOE under DE-AC02-09CH1146.

Performance characteristics of a nanoscale double-gate reconfigurable array

NASA Astrophysics Data System (ADS)

Beckett, Paul

2008-12-01

The double gate transistor is a promising device applicable to deep sub-micron design due to its inherent resistance to short-channel effects and superior subthreshold performance. Using both TCAD and SPICE circuit simulation, it is shown that the characteristics of fully depleted dual-gate thin-body Schottky barrier silicon transistors will not only uncouple the conflicting requirements of high performance and low standby power in digital logic, but will also allow the development of a locally-connected reconfigurable computing mesh. The magnitude of the threshold shift effect will scale with device dimensions and will remain compatible with oxide reliability constraints. A field-programmable architecture based on the double gate transistor is described in which the operating point of the circuit is biased via one gate while the other gate is used to form the logic array, such that complex heterogeneous computing functions may be developed from this homogeneous, mesh-connected organization.

Implementation of fuzzy-sliding mode based control of a grid connected photovoltaic system.

PubMed

Menadi, Abdelkrim; Abdeddaim, Sabrina; Ghamri, Ahmed; Betka, Achour

2015-09-01

The present work describes an optimal operation of a small scale photovoltaic system connected to a micro-grid, based on both sliding mode and fuzzy logic control. Real time implementation is done through a dSPACE 1104 single board, controlling a boost chopper on the PV array side and a voltage source inverter (VSI) on the grid side. The sliding mode controller tracks permanently the maximum power of the PV array regardless of atmospheric condition variations, while The fuzzy logic controller (FLC) regulates the DC-link voltage, and ensures via current control of the VSI a quasi-total transit of the extracted PV power to the grid under a unity power factor operation. Simulation results, carried out via Matlab-Simulink package were approved through experiment, showing the effectiveness of the proposed control techniques. Copyright © 2015. Published by Elsevier Ltd.

Micromechanical torsional digital-to-analog converter for open-loop angular positioning applications

NASA Astrophysics Data System (ADS)

Zhou, Guangya; Tay, Francis E. H.; Chau, Fook Siong; Zhao, Yi; Logeeswaran, VJ

2004-05-01

This paper reports a novel micromechanical torsional digital-to-analog converter (MTDAC), operated in open-loop with digitally controlled precise multi-level tilt angles. The MTDAC mechanism presented is analogous to that of an electrical binary-weighted-input digital-to-analog converter (DAC). It consists of a rigid tunable platform, an array of torsional microactuators, each operating in a two-state (on/off) mode, and a set of connection beams with binary-weighted torsional stiffnesses that connect the actuators to the platform. The feasibility of the proposed MTDAC mechanism was verified numerically by finite element simulations and experimentally with a commercial optical phase-shifting interferometric system. A prototype 2-bit MTDAC was implemented using the poly-MUMPS process achieving a full-scale output tilt angle of 1.92° with a rotation step of 0.64°. This mechanism can be configured for many promising applications, particularly in beam steering-based OXC switches.

On Estimation of Contamination from Hydrogen Cyanide in Carbon Monoxide Line-intensity Mapping

NASA Astrophysics Data System (ADS)

Chung, Dongwoo T.; Li, Tony Y.; Viero, Marco P.; Church, Sarah E.; Wechsler, Risa H.

2017-09-01

Line-intensity mapping surveys probe large-scale structure through spatial variations in molecular line emission from a population of unresolved cosmological sources. Future such surveys of carbon monoxide line emission, specifically the CO(1-0) line, face potential contamination from a disjointed population of sources emitting in a hydrogen cyanide emission line, HCN(1-0). This paper explores the potential range of the strength of HCN emission and its effect on the CO auto power spectrum, using simulations with an empirical model of the CO/HCN-halo connection. We find that effects on the observed CO power spectrum depend on modeling assumptions but are very small for our fiducial model, which is based on current understanding of the galaxy-halo connection. Given the fiducial model, we expect the bias in overall CO detection significance due to HCN to be less than 1%.

Shear failure of granular materials

NASA Astrophysics Data System (ADS)

Degiuli, Eric; Balmforth, Neil; McElwaine, Jim; Schoof, Christian; Hewitt, Ian

2012-02-01

Connecting the macroscopic behavior of granular materials with the microstructure remains a great challenge. Recent work connects these scales with a discrete calculus [1]. In this work we generalize this formalism from monodisperse packings of disks to 2D assemblies of arbitrarily shaped grains. In particular, we derive Airy's expression for a symmetric, divergence-free stress tensor. Using these tools, we derive, from first-principles and in a mean-field approximation, the entropy of frictional force configurations in the Force Network Ensemble. As a macroscopic consequence of the Coulomb friction condition at contacts, we predict shear failure at a critical shear stress, in accordance with the Mohr-Coulomb failure condition well known in engineering. Results are compared with numerical simulations, and the dependence on the microscopic geometric configuration is discussed. [4pt] [1] E. DeGiuli & J. McElwaine, PRE 2011. doi: 10.1103/PhysRevE.84.041310

Computation of water hammer protection of modernized pumping station

NASA Astrophysics Data System (ADS)

Himr, Daniel

2014-03-01

Pumping station supplies water for irrigation. Maximal capacity 2 × 1.2m3·s-1 became insufficient, thus it was upgraded to 2 × 2m3·s-1. Paper is focused on design of protection against water hammer in case of sudden pumps trip. Numerical simulation of the most dangerous case (when pumps are giving the maximal flow rate) showed that existing air vessels were not able to protect the system and it would be necessary to add new vessels. Special care was paid to influence of their connection to the main pipeline, because the resistance of the connection has a significant impact on the scale of pressure pulsations. Finally, the pump trip was performed to verify if the system worked correctly. The test showed that pressure pulsations are lower (better) than computation predicted. This discrepancy was further analysed.

On Estimation of Contamination from Hydrogen Cyanide in Carbon Monoxide Line-intensity Mapping

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

Chung, Dongwoo T.; Li, Tony Y.; Viero, Marco P.

Line-intensity mapping surveys probe large-scale structure through spatial variations in molecular line emission from a population of unresolved cosmological sources. Future such surveys of carbon monoxide line emission, specifically the CO(1-0) line, face potential contamination from a disjointed population of sources emitting in a hydrogen cyanide emission line, HCN(1-0). This paper explores the potential range of the strength of HCN emission and its effect on the CO auto power spectrum, using simulations with an empirical model of the CO/HCN–halo connection. We find that effects on the observed CO power spectrum depend on modeling assumptions but are very small for ourmore » fiducial model, which is based on current understanding of the galaxy–halo connection. Given the fiducial model, we expect the bias in overall CO detection significance due to HCN to be less than 1%.« less

On Estimation of Contamination from Hydrogen Cyanide in Carbon Monoxide Line-intensity Mapping

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

Chung, Dongwoo T.; Li, Tony Y.; Viero, Marco P.

Here, line-intensity mapping surveys probe large-scale structure through spatial variations in molecular line emission from a population of unresolved cosmological sources. Future such surveys of carbon monoxide line emission, specifically the CO(1-0) line, face potential contamination from a disjointed population of sources emitting in a hydrogen cyanide emission line, HCN(1-0). This paper explores the potential range of the strength of HCN emission and its effect on the CO auto power spectrum, using simulations with an empirical model of the CO/HCN–halo connection. We find that effects on the observed CO power spectrum depend on modeling assumptions but are very small formore » our fiducial model, which is based on current understanding of the galaxy–halo connection. Given the fiducial model, we expect the bias in overall CO detection significance due to HCN to be less than 1%.« less

On Estimation of Contamination from Hydrogen Cyanide in Carbon Monoxide Line-intensity Mapping

DOE PAGES

Chung, Dongwoo T.; Li, Tony Y.; Viero, Marco P.; ...

2017-08-31

Here, line-intensity mapping surveys probe large-scale structure through spatial variations in molecular line emission from a population of unresolved cosmological sources. Future such surveys of carbon monoxide line emission, specifically the CO(1-0) line, face potential contamination from a disjointed population of sources emitting in a hydrogen cyanide emission line, HCN(1-0). This paper explores the potential range of the strength of HCN emission and its effect on the CO auto power spectrum, using simulations with an empirical model of the CO/HCN–halo connection. We find that effects on the observed CO power spectrum depend on modeling assumptions but are very small formore » our fiducial model, which is based on current understanding of the galaxy–halo connection. Given the fiducial model, we expect the bias in overall CO detection significance due to HCN to be less than 1%.« less

High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6

NASA Astrophysics Data System (ADS)

Haarsma, Reindert J.; Roberts, Malcolm J.; Vidale, Pier Luigi; Senior, Catherine A.; Bellucci, Alessio; Bao, Qing; Chang, Ping; Corti, Susanna; Fučkar, Neven S.; Guemas, Virginie; von Hardenberg, Jost; Hazeleger, Wilco; Kodama, Chihiro; Koenigk, Torben; Leung, L. Ruby; Lu, Jian; Luo, Jing-Jia; Mao, Jiafu; Mizielinski, Matthew S.; Mizuta, Ryo; Nobre, Paulo; Satoh, Masaki; Scoccimarro, Enrico; Semmler, Tido; Small, Justin; von Storch, Jin-Song

2016-11-01

Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest both the possibility of significant changes in large-scale aspects of circulation as well as improvements in small-scale processes and extremes. However, such high-resolution global simulations at climate timescales, with resolutions of at least 50 km in the atmosphere and 0.25° in the ocean, have been performed at relatively few research centres and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other model intercomparison projects (MIPs). Increases in high-performance computing (HPC) resources, as well as the revised experimental design for CMIP6, now enable a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability. The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal-resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950-2050, with the possibility of extending to 2100, together with some additional targeted experiments. This paper describes the experimental set-up of HighResMIP, the analysis plan, the connection with the other CMIP6 endorsed MIPs, as well as the DECK and CMIP6 historical simulations. HighResMIP thereby focuses on one of the CMIP6 broad questions, "what are the origins and consequences of systematic model biases?", but we also discuss how it addresses the World Climate Research Program (WCRP) grand challenges.

Acoustic mode coupling induced by shallow water nonlinear internal waves: sensitivity to environmental conditions and space-time scales of internal waves.

PubMed

Colosi, John A

2008-09-01

While many results have been intuited from numerical simulation studies, the precise connections between shallow-water acoustic variability and the space-time scales of nonlinear internal waves (NLIWs) as well as the background environmental conditions have not been clearly established analytically. Two-dimensional coupled mode propagation through NLIWs is examined using a perturbation series solution in which each order n is associated with nth-order multiple scattering. Importantly, the perturbation solution gives resonance conditions that pick out specific NLIW scales that cause coupling, and seabed attenuation is demonstrated to broaden these resonances, fundamentally changing the coupling behavior at low frequency. Sound-speed inhomogeneities caused by internal solitary waves (ISWs) are primarily considered and the dependence of mode coupling on ISW amplitude, range width, depth structure, location relative to the source, and packet characteristics are delineated as a function of acoustic frequency. In addition, it is seen that significant energy transfer to modes with initially low or zero energy involves at least a second order scattering process. Under moderate scattering conditions, comparisons of first order, single scattering theoretical predictions to direct numerical simulation demonstrate the accuracy of the approach for acoustic frequencies upto 400 Hz and for single as well as multiple ISW wave packets.

Cortical circuitry implementing graphical models.

PubMed

Litvak, Shai; Ullman, Shimon

2009-11-01

In this letter, we develop and simulate a large-scale network of spiking neurons that approximates the inference computations performed by graphical models. Unlike previous related schemes, which used sum and product operations in either the log or linear domains, the current model uses an inference scheme based on the sum and maximization operations in the log domain. Simulations show that using these operations, a large-scale circuit, which combines populations of spiking neurons as basic building blocks, is capable of finding close approximations to the full mathematical computations performed by graphical models within a few hundred milliseconds. The circuit is general in the sense that it can be wired for any graph structure, it supports multistate variables, and it uses standard leaky integrate-and-fire neuronal units. Following previous work, which proposed relations between graphical models and the large-scale cortical anatomy, we focus on the cortical microcircuitry and propose how anatomical and physiological aspects of the local circuitry may map onto elements of the graphical model implementation. We discuss in particular the roles of three major types of inhibitory neurons (small fast-spiking basket cells, large layer 2/3 basket cells, and double-bouquet neurons), subpopulations of strongly interconnected neurons with their unique connectivity patterns in different cortical layers, and the possible role of minicolumns in the realization of the population-based maximum operation.

Fractal analysis of the dark matter and gas distributions in the Mare-Nostrum universe

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

Gaite, José, E-mail: jose.gaite@upm.es

2010-03-01

We develop a method of multifractal analysis of N-body cosmological simulations that improves on the customary counts-in-cells method by taking special care of the effects of discreteness and large scale homogeneity. The analysis of the Mare-Nostrum simulation with our method provides strong evidence of self-similar multifractal distributions of dark matter and gas, with a halo mass function that is of Press-Schechter type but has a power-law exponent -2, as corresponds to a multifractal. Furthermore, our analysis shows that the dark matter and gas distributions are indistinguishable as multifractals. To determine if there is any gas biasing, we calculate the cross-correlationmore » coefficient, with negative but inconclusive results. Hence, we develop an effective Bayesian analysis connected with information theory, which clearly demonstrates that the gas is biased in a long range of scales, up to the scale of homogeneity. However, entropic measures related to the Bayesian analysis show that this gas bias is small (in a precise sense) and is such that the fractal singularities of both distributions coincide and are identical. We conclude that this common multifractal cosmic web structure is determined by the dynamics and is independent of the initial conditions.« less

Functional connectivity change as shared signal dynamics

PubMed Central

Cole, Michael W.; Yang, Genevieve J.; Murray, John D.; Repovš, Grega; Anticevic, Alan

2015-01-01

Background An increasing number of neuroscientific studies gain insights by focusing on differences in functional connectivity – between groups, individuals, temporal windows, or task conditions. We found using simulations that additional insights into such differences can be gained by forgoing variance normalization, a procedure used by most functional connectivity measures. Simulations indicated that these functional connectivity measures are sensitive to increases in independent fluctuations (unshared signal) in time series, consistently reducing functional connectivity estimates (e.g., correlations) even though such changes are unrelated to corresponding fluctuations (shared signal) between those time series. This is inconsistent with the common notion of functional connectivity as the amount of inter-region interaction. New Method Simulations revealed that a version of correlation without variance normalization – covariance – was able to isolate differences in shared signal, increasing interpretability of observed functional connectivity change. Simulations also revealed cases problematic for non-normalized methods, leading to a “covariance conjunction” method combining the benefits of both normalized and non-normalized approaches. Results We found that covariance and covariance conjunction methods can detect functional connectivity changes across a variety of tasks and rest in both clinical and non-clinical functional MRI datasets. Comparison with Existing Method(s) We verified using a variety of tasks and rest in both clinical and non-clinical functional MRI datasets that it matters in practice whether correlation, covariance, or covariance conjunction methods are used. Conclusions These results demonstrate the practical and theoretical utility of isolating changes in shared signal, improving the ability to interpret observed functional connectivity change. PMID:26642966

Generate the scale-free brain music from BOLD signals

PubMed Central

Lu, Jing; Guo, Sijia; Chen, Mingming; Wang, Weixia; Yang, Hua; Guo, Daqing; Yao, Dezhong

2018-01-01

Abstract Many methods have been developed to translate a human electroencephalogram (EEG) into music. In addition to EEG, functional magnetic resonance imaging (fMRI) is another method used to study the brain and can reflect physiological processes. In 2012, we established a method to use simultaneously recorded fMRI and EEG signals to produce EEG-fMRI music, which represents a step toward scale-free brain music. In this study, we used a neural mass model, the Jansen–Rit model, to simulate activity in several cortical brain regions. The interactions between different brain regions were represented by the average normalized diffusion tensor imaging (DTI) structural connectivity with a coupling coefficient that modulated the coupling strength. Seventy-eight brain regions were adopted from the Automated Anatomical Labeling (AAL) template. Furthermore, we used the Balloon–Windkessel hemodynamic model to transform neural activity into a blood-oxygen-level dependent (BOLD) signal. Because the fMRI BOLD signal changes slowly, we used a sampling rate of 250 Hz to produce the temporal series for music generation. Then, the BOLD music was generated for each region using these simulated BOLD signals. Because the BOLD signal is scale free, these music pieces were also scale free, which is similar to classic music. Here, to simulate the case of an epileptic patient, we changed the parameter that determined the amplitude of the excitatory postsynaptic potential (EPSP) in the neural mass model. Finally, we obtained BOLD music for healthy and epileptic patients. The differences in levels of arousal between the 2 pieces of music may provide a potential tool for discriminating the different populations if the differences can be confirmed by more real data. PMID:29480872

Generate the scale-free brain music from BOLD signals.

PubMed

Lu, Jing; Guo, Sijia; Chen, Mingming; Wang, Weixia; Yang, Hua; Guo, Daqing; Yao, Dezhong

2018-01-01

Many methods have been developed to translate a human electroencephalogram (EEG) into music. In addition to EEG, functional magnetic resonance imaging (fMRI) is another method used to study the brain and can reflect physiological processes. In 2012, we established a method to use simultaneously recorded fMRI and EEG signals to produce EEG-fMRI music, which represents a step toward scale-free brain music. In this study, we used a neural mass model, the Jansen-Rit model, to simulate activity in several cortical brain regions. The interactions between different brain regions were represented by the average normalized diffusion tensor imaging (DTI) structural connectivity with a coupling coefficient that modulated the coupling strength. Seventy-eight brain regions were adopted from the Automated Anatomical Labeling (AAL) template. Furthermore, we used the Balloon-Windkessel hemodynamic model to transform neural activity into a blood-oxygen-level dependent (BOLD) signal. Because the fMRI BOLD signal changes slowly, we used a sampling rate of 250 Hz to produce the temporal series for music generation. Then, the BOLD music was generated for each region using these simulated BOLD signals. Because the BOLD signal is scale free, these music pieces were also scale free, which is similar to classic music. Here, to simulate the case of an epileptic patient, we changed the parameter that determined the amplitude of the excitatory postsynaptic potential (EPSP) in the neural mass model. Finally, we obtained BOLD music for healthy and epileptic patients. The differences in levels of arousal between the 2 pieces of music may provide a potential tool for discriminating the different populations if the differences can be confirmed by more real data. Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.

HIV competition dynamics over sexual networks: first comer advantage conserves founder effects.

PubMed

Ferdinandy, Bence; Mones, Enys; Vicsek, Tamás; Müller, Viktor

2015-02-01

Outside Africa, the global phylogeography of HIV is characterized by compartmentalized local epidemics that are typically dominated by a single subtype, which indicates strong founder effects. We hypothesized that the competition of viral strains at the epidemic level may involve an advantage of the resident strain that was the first to colonize a population. Such an effect would slow down the invasion of new strains, and thus also the diversification of the epidemic. We developed a stochastic modelling framework to simulate HIV epidemics over dynamic contact networks. We simulated epidemics in which the second strain was introduced into a population where the first strain had established a steady-state epidemic, and assessed whether, and on what time scale, the second strain was able to spread in the population. Simulations were parameterized based on empirical data; we tested scenarios with varying levels of overall prevalence. The spread of the second strain occurred on a much slower time scale compared with the initial expansion of the first strain. With strains of equal transmission efficiency, the second strain was unable to invade on a time scale relevant for the history of the HIV pandemic. To become dominant over a time scale of decades, the second strain needed considerable (>25%) advantage in transmission efficiency over the resident strain. The inhibition effect was weaker if the second strain was introduced while the first strain was still in its growth phase. We also tested how possible mechanisms of interference (inhibition of superinfection, depletion of highly connected hubs in the network, one-time acute peak of infectiousness) contribute to the inhibition effect. Our simulations confirmed a strong first comer advantage in the competition dynamics of HIV at the population level, which may explain the global phylogeography of the virus and may influence the future evolution of the pandemic.

EVALUATION OF THE ABILITY OF CHLORINE TO INACTIVATE SELECTED ORGANISMS FROM THE BIOFILM OF A DRINKING WATER DISTRIBUTION SYSTEM SIMULATOR FOLLOWING A LONG-TERM WASTEWATER CROSS-CONNECTION

EPA Science Inventory

The drinking water distribution system simulator (DSS) from the U.S. EPA was operated with a direct cross-connection of 0.3% wastewater to system volume per day for 70 d. During the cross-connection, tap water, wastewater, and system discharge water were monitored to ensure that ...

Responses to climate change in hot desert ecosystems: connecting local to global scales

USDA-ARS?s Scientific Manuscript database

The consequences of connectivity in resources, propagules, and information to the interplay between drivers and responses across scales can result in ecological dynamics that are not easily predicted based on local drivers. Three major classes of connectivity events link local ecological dynamics wi...

A multiscale simulation technique for molecular electronics: design of a directed self-assembled molecular n-bit shift register memory device.

PubMed

Lambropoulos, Nicholas A; Reimers, Jeffrey R; Crossley, Maxwell J; Hush, Noel S; Silverbrook, Kia

2013-12-20

A general method useful in molecular electronics design is developed that integrates modelling on the nano-scale (using quantum-chemical software) and on the micro-scale (using finite-element methods). It is applied to the design of an n-bit shift register memory that could conceivably be built using accessible technologies. To achieve this, the entire complex structure of the device would be built to atomic precision using feedback-controlled lithography to provide atomic-level control of silicon devices, controlled wet-chemical synthesis of molecular insulating pillars above the silicon, and controlled wet-chemical self-assembly of modular molecular devices to these pillars that connect to external metal electrodes (leads). The shift register consists of n connected cells that read data from an input electrode, pass it sequentially between the cells under the control of two external clock electrodes, and deliver it finally to an output device. The proposed cells are trimeric oligoporphyrin units whose internal states are manipulated to provide functionality, covalently connected to other cells via dipeptide linkages. Signals from the clock electrodes are conveyed by oligoporphyrin molecular wires, and μ-oxo porphyrin insulating columns are used as the supporting pillars. The developed multiscale modelling technique is applied to determine the characteristics of this molecular device, with in particular utilization of the inverted region for molecular electron-transfer processes shown to facilitate latching and control using exceptionally low energy costs per logic operation compared to standard CMOS shift register technology.

The ecological connectivity of whale shark aggregations in the Indian Ocean: a photo-identification approach.

PubMed

Andrzejaczek, Samantha; Meeuwig, Jessica; Rowat, David; Pierce, Simon; Davies, Tim; Fisher, Rebecca; Meekan, Mark

2016-11-01

Genetic and modelling studies suggest that seasonal aggregations of whale sharks ( Rhincodon typus ) at coastal sites in the tropics may be linked by migration. Here, we used photo-identification (photo-ID) data collected by both citizen scientists and researchers to assess the connectedness of five whale shark aggregation sites across the entire Indian Ocean at timescales of up to a decade. We used the semi-automated program I 3 S (Individual Interactive Identification System) to compare photographs of the unique natural marking patterns of individual whale sharks collected from aggregations at Mozambique, the Seychelles, the Maldives, Christmas Island (Australia) and Ningaloo Reef (Australia). From a total of 6519 photos, we found no evidence of connectivity of whale shark aggregations at ocean-basin scales within the time frame of the study and evidence for only limited connectivity at regional (hundreds to thousands of kilometres) scales. A male whale shark photographed in January 2010 at Mozambique was resighted eight months later in the Seychelles and was the only one of 1724 individuals in the database to be photographed at more than one site. On average, 35% of individuals were resighted at the same site in more than one year. A Monte Carlo simulation study showed that the power of this photo-ID approach to document patterns of emigration and immigration was strongly dependent on both the number of individuals identified in aggregations and the size of resident populations.

Stochastic analysis of epidemics on adaptive time varying networks

NASA Astrophysics Data System (ADS)

Kotnis, Bhushan; Kuri, Joy

2013-06-01

Many studies investigating the effect of human social connectivity structures (networks) and human behavioral adaptations on the spread of infectious diseases have assumed either a static connectivity structure or a network which adapts itself in response to the epidemic (adaptive networks). However, human social connections are inherently dynamic or time varying. Furthermore, the spread of many infectious diseases occur on a time scale comparable to the time scale of the evolving network structure. Here we aim to quantify the effect of human behavioral adaptations on the spread of asymptomatic infectious diseases on time varying networks. We perform a full stochastic analysis using a continuous time Markov chain approach for calculating the outbreak probability, mean epidemic duration, epidemic reemergence probability, etc. Additionally, we use mean-field theory for calculating epidemic thresholds. Theoretical predictions are verified using extensive simulations. Our studies have uncovered the existence of an “adaptive threshold,” i.e., when the ratio of susceptibility (or infectivity) rate to recovery rate is below the threshold value, adaptive behavior can prevent the epidemic. However, if it is above the threshold, no amount of behavioral adaptations can prevent the epidemic. Our analyses suggest that the interaction patterns of the infected population play a major role in sustaining the epidemic. Our results have implications on epidemic containment policies, as awareness campaigns and human behavioral responses can be effective only if the interaction levels of the infected populace are kept in check.

The ecological connectivity of whale shark aggregations in the Indian Ocean: a photo-identification approach

PubMed Central

Meeuwig, Jessica; Rowat, David; Pierce, Simon; Davies, Tim; Fisher, Rebecca; Meekan, Mark

2016-01-01

Genetic and modelling studies suggest that seasonal aggregations of whale sharks (Rhincodon typus) at coastal sites in the tropics may be linked by migration. Here, we used photo-identification (photo-ID) data collected by both citizen scientists and researchers to assess the connectedness of five whale shark aggregation sites across the entire Indian Ocean at timescales of up to a decade. We used the semi-automated program I3S (Individual Interactive Identification System) to compare photographs of the unique natural marking patterns of individual whale sharks collected from aggregations at Mozambique, the Seychelles, the Maldives, Christmas Island (Australia) and Ningaloo Reef (Australia). From a total of 6519 photos, we found no evidence of connectivity of whale shark aggregations at ocean-basin scales within the time frame of the study and evidence for only limited connectivity at regional (hundreds to thousands of kilometres) scales. A male whale shark photographed in January 2010 at Mozambique was resighted eight months later in the Seychelles and was the only one of 1724 individuals in the database to be photographed at more than one site. On average, 35% of individuals were resighted at the same site in more than one year. A Monte Carlo simulation study showed that the power of this photo-ID approach to document patterns of emigration and immigration was strongly dependent on both the number of individuals identified in aggregations and the size of resident populations. PMID:28018629

A multiscale simulation technique for molecular electronics: design of a directed self-assembled molecular n-bit shift register memory device

NASA Astrophysics Data System (ADS)

Lambropoulos, Nicholas A.; Reimers, Jeffrey R.; Crossley, Maxwell J.; Hush, Noel S.; Silverbrook, Kia

2013-12-01

A general method useful in molecular electronics design is developed that integrates modelling on the nano-scale (using quantum-chemical software) and on the micro-scale (using finite-element methods). It is applied to the design of an n-bit shift register memory that could conceivably be built using accessible technologies. To achieve this, the entire complex structure of the device would be built to atomic precision using feedback-controlled lithography to provide atomic-level control of silicon devices, controlled wet-chemical synthesis of molecular insulating pillars above the silicon, and controlled wet-chemical self-assembly of modular molecular devices to these pillars that connect to external metal electrodes (leads). The shift register consists of n connected cells that read data from an input electrode, pass it sequentially between the cells under the control of two external clock electrodes, and deliver it finally to an output device. The proposed cells are trimeric oligoporphyrin units whose internal states are manipulated to provide functionality, covalently connected to other cells via dipeptide linkages. Signals from the clock electrodes are conveyed by oligoporphyrin molecular wires, and μ-oxo porphyrin insulating columns are used as the supporting pillars. The developed multiscale modelling technique is applied to determine the characteristics of this molecular device, with in particular utilization of the inverted region for molecular electron-transfer processes shown to facilitate latching and control using exceptionally low energy costs per logic operation compared to standard CMOS shift register technology.

Time tracking and interaction of energy-eddies at different scales

NASA Astrophysics Data System (ADS)

Cardesa, Jose I.; Vela-Martin, Alberto; Jimenez, Javier

2016-11-01

We study the energy cascade through coherent structures obtained in time-resolved simulations of incompressible, statistically steady isotropic turbulence. The structures are defined as geometrically connected regions of the flow with high kinetic energy. We compute the latter by band-pass filtering the velocity field around a scale r. We analyse the dynamics of structures extracted with different r, which are a proxy for eddies containing energy at those r. We find that the size of these "energy-eddies" scales with r, while their lifetime scales with the local eddy-turnover r 2 / 3ɛ - 1 / 3 , where ɛ is the energy dissipation averaged over all space and time. Furthermore, a statistical analysis over the lives of the eddies shows a slight predominance of the splitting over the merging process. When we isolate the eddies which do not interact with other eddies of the same scale, we observe a parent-child dependence by which, on average, structures are born at scale r during the decaying part of the life of a structure at scale r' > r . The energy-eddy at r' lives in the same region of space as that at r. Finally, we investigate how interactions between eddies at the same scale are echoed across other scales. Funded by the ERC project Coturb.

Simulating the heterogeneity in braided channel belt deposits: 2. Examples of results and comparison to natural deposits

NASA Astrophysics Data System (ADS)

Guin, Arijit; Ramanathan, Ramya; Ritzi, Robert W.; Dominic, David F.; Lunt, Ian A.; Scheibe, Timothy D.; Freedman, Vicky L.

2010-04-01

In part 1 of this paper (Ramanathan et al., 2010b) we presented a methodology and a code for modeling the hierarchical sedimentary architecture in braided channel belt deposits. Here in part 2, the code was used to create a digital model of this architecture and the corresponding spatial distribution of permeability. The simulated architecture was compared to the real stratal architecture observed in an abandoned channel belt. The comparisons included assessments of similarity which were both qualitative and quantitative. The qualitative comparisons show that the geometries of unit types within the synthetic deposits are generally consistent with field observations. The unit types in the synthetic deposits would generally be recognized as representing their counterparts in nature, including cross stratasets, lobate and scroll bar deposits, and channel fills. Furthermore, the synthetic deposits have a hierarchical spatial relationship among these units consistent with observations from field exposures and geophysical images. In quantitative comparisons the proportions and the length, width, and height of unit types at different scales, across all levels of the stratal hierarchy, compare well between the synthetic and the natural deposits. A number of important attributes of the synthetic channel belt deposits are shown to be influenced by more than one level within the hierarchy of stratal architecture. First, the high-permeability open-framework gravels connected across all levels and thus formed preferential flow pathways; open-framework gravels are known to form preferential flow pathways in natural channel belt deposits. The nature of a connected cluster changed across different levels of the stratal hierarchy, and as a result of the geologic structure, the connectivity occurs at proportions of open-framework gravels below the theoretical percolation threshold for random infinite media. Second, when the channel belt model was populated with permeability distributions by lowest-level unit type, the composite permeability semivariogram contained structures that were identifiable at more than one scale, and each of these structures could be directly linked to unit types of different scales existing at different levels within the hierarchy of strata. These collective results are encouraging with respect to our goal that this model be relevant for testing ideas in future research on flow and transport in aquifers and reservoirs with multiscale heterogeneity.

Porosity and permeability determination of organic-rich Posidonia shales based on 3-D analyses by FIB-SEM microscopy

NASA Astrophysics Data System (ADS)

Grathoff, Georg H.; Peltz, Markus; Enzmann, Frieder; Kaufhold, Stephan

2016-07-01

The goal of this study is to better understand the porosity and permeability in shales to improve modelling fluid and gas flow related to shale diagenesis. Two samples (WIC and HAD) were investigated, both mid-Jurassic organic-rich Posidonia shales from Hils area, central Germany of different maturity (WIC R0 0.53 % and HAD R0 1.45 %). The method for image collection was focused ion beam (FIB) microscopy coupled with scanning electron microscopy (SEM). For image and data analysis Avizo and GeoDict was used. Porosity was calculated from segmented 3-D FIB based images and permeability was simulated by a Navier Stokes-Brinkman solver in the segmented images. Results show that the quantity and distribution of pore clusters and pores (≥ 40 nm) are similar. The largest pores are located within carbonates and clay minerals, whereas the smallest pores are within the matured organic matter. Orientation of the pores calculated as pore paths showed minor directional differences between the samples. Both samples have no continuous connectivity of pore clusters along the axes in the x, y, and z direction on the scale of 10 to 20 of micrometer, but do show connectivity on the micrometer scale. The volume of organic matter in the studied volume is representative of the total organic carbon (TOC) in the samples. Organic matter does show axis connectivity in the x, y, and z directions. With increasing maturity the porosity in organic matter increases from close to 0 to more than 5 %. These pores are small and in the large organic particles have little connection to the mineral matrix. Continuous pore size distributions are compared with mercury intrusion porosimetry (MIP) data. Differences between both methods are caused by resolution limits of the FIB-SEM and by the development of small pores during the maturation of the organic matter. Calculations show no permeability when only considering visible pores due to the lack of axis connectivity. Adding the organic matter with a background permeability of 1 × 10-21 m2 to the calculations, the total permeability increased by up to 1 order of magnitude for the low mature and decreases slightly for the overmature sample from the gas window. Anisotropy of permeability was observed. Permeability coefficients increase by 1 order of magnitude if simulations are performed parallel to the bedding. Our results compare well with experimental data from the literature suggesting that upscaling may be possible in the future as soon as maturity dependent organic matter permeability coefficients can be determined.

Interplay between Functional Connectivity and Scale-Free Dynamics in Intrinsic fMRI Networks

PubMed Central

Ciuciu, Philippe; Abry, Patrice; He, Biyu J.

2014-01-01

Studies employing functional connectivity-type analyses have established that spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signals are organized within large-scale brain networks. Meanwhile, fMRI signals have been shown to exhibit 1/f-type power spectra – a hallmark of scale-free dynamics. We studied the interplay between functional connectivity and scale-free dynamics in fMRI signals, utilizing the fractal connectivity framework – a multivariate extension of the univariate fractional Gaussian noise model, which relies on a wavelet formulation for robust parameter estimation. We applied this framework to fMRI data acquired from healthy young adults at rest and performing a visual detection task. First, we found that scale-invariance existed beyond univariate dynamics, being present also in bivariate cross-temporal dynamics. Second, we observed that frequencies within the scale-free range do not contribute evenly to inter-regional connectivity, with a systematically stronger contribution of the lowest frequencies, both at rest and during task. Third, in addition to a decrease of the Hurst exponent and inter-regional correlations, task performance modified cross-temporal dynamics, inducing a larger contribution of the highest frequencies within the scale-free range to global correlation. Lastly, we found that across individuals, a weaker task modulation of the frequency contribution to inter-regional connectivity was associated with better task performance manifesting as shorter and less variable reaction times. These findings bring together two related fields that have hitherto been studied separately – resting-state networks and scale-free dynamics, and show that scale-free dynamics of human brain activity manifest in cross-regional interactions as well. PMID:24675649

Evolving soils and hydrologic connectivity in semiarid hillslopes

NASA Astrophysics Data System (ADS)

Saco, Patricia M.

2015-04-01

Soil moisture availability is essential for the stability and resilience of semiarid ecosystems. In these ecosystems the amount of soil moisture available for vegetation growth and survival is intrinsically related to the way water is redistributed, that is from source to sink areas, and therefore prescribed by the hydrologic connectivity of the landscape. Recent studies have shown that hydrologic connectivity is highly dynamic and linked to the coevolution of geomorphic, soil and vegetation structures at a variety of spatial and temporal scales. This study investigates the effect of evolving soil depths on hydrologic connectivity using a modelling framework. The focus is on Australian semiarid hillslopes with patterned vegetation that result from coevolving landforms, soils, water redistribution, and vegetation patterns. We present and analyse results from simulations using a coupled landform evolution-dynamic vegetation model, which includes a soil depth evolution module and accounts for soil production and sediment erosion and deposition processes. We analyse the effect of soils depths on surface connectivity for a range of biotic (plant functional type strategies) and abiotic (slope and erodibility) conditions. The analysis shows that different plant functional types, through their varying facilitation strategies, have a profound effect on soils depths and therefore affect hydrologic connectivity and soil moisture patterns. This interplay becomes particularly important for systems that coevolve to have very shallow soils. In this case soil depth becomes the key factor prescribing surface connectivity and available soil moisture for plants, which affect the recovery of the system after disturbance. Conditions for the existence of threshold behaviour for which small perturbations can trigger a sudden increase in hydrologic connectivity, reduced soil moisture availability and decrease in productivity leading to degraded states are investigated. Critical implications for effective restoration efforts are discussed.

Adaptive control of structural balance for complex dynamical networks based on dynamic coupling of nodes

NASA Astrophysics Data System (ADS)

Gao, Zilin; Wang, Yinhe; Zhang, Lili

2018-02-01

In the existing research results of the complex dynamical networks controlled, the controllers are mainly used to guarantee the synchronization or stabilization of the nodes’ state, and the terms coupled with connection relationships may affect the behaviors of nodes, this obviously ignores the dynamic common behavior of the connection relationships between the nodes. In fact, from the point of view of large-scale system, a complex dynamical network can be regarded to be composed of two time-varying dynamic subsystems, which can be called the nodes subsystem and the connection relationships subsystem, respectively. Similar to the synchronization or stabilization of the nodes subsystem, some characteristic phenomena can be also emerged in the connection relationships subsystem. For example, the structural balance in the social networks and the synaptic facilitation in the biological neural networks. This paper focuses on the structural balance in dynamic complex networks. Generally speaking, the state of the connection relationships subsystem is difficult to be measured accurately in practical applications, and thus it is not easy to implant the controller directly into the connection relationships subsystem. It is noted that the nodes subsystem and the relationships subsystem are mutually coupled, which implies that the state of the connection relationships subsystem can be affected by the controllable state of nodes subsystem. Inspired by this observation, by using the structural balance theory of triad, the controller with the parameter adaptive law is proposed for the nodes subsystem in this paper, which may ensure the connection relationship matrix to approximate a given structural balance matrix in the sense of the uniformly ultimately bounded (UUB). That is, the structural balance may be obtained by employing the controlling state of the nodes subsystem. Finally, the simulations are used to show the validity of the method in this paper.

Understanding Prairie Fen Hydrology - a Hierarchical Multi-Scale Groundwater Modeling Approach

NASA Astrophysics Data System (ADS)

Sampath, P.; Liao, H.; Abbas, H.; Ma, L.; Li, S.

2012-12-01

Prairie fens provide critical habitat to more than 50 rare species and significantly contribute to the biodiversity of the upper Great Lakes region. The sustainability of these globally unique ecosystems, however, requires that they be fed by a steady supply of pristine, calcareous groundwater. Understanding the hydrology that supports the existence of such fens is essential in preserving these valuable habitats. This research uses process-based multi-scale groundwater modeling for this purpose. Two fen-sites, MacCready Fen and Ives Road Fen, in Southern Michigan were systematically studied. A hierarchy of nested steady-state models was built for each fen-site to capture the system's dynamics at spatial scales ranging from the regional groundwater-shed to the local fens. The models utilize high-resolution Digital Elevation Models (DEM), National Hydrologic Datasets (NHD), a recently-assembled water-well database, and results from a state-wide groundwater mapping project to represent the complex hydro-geological and stress framework. The modeling system simulates both shallow glacial and deep bedrock aquifers as well as the interaction between surface water and groundwater. Aquifer heterogeneities were explicitly simulated with multi-scale transition probability geo-statistics. A two-way hydraulic head feedback mechanism was set up between the nested models, such that the parent models provided boundary conditions to the child models, and in turn the child models provided local information to the parent models. A hierarchical mass budget analysis was performed to estimate the seepage fluxes at the surface water/groundwater interfaces and to assess the relative importance of the processes at multiple scales that contribute water to the fens. The models were calibrated using observed base-flows at stream gauging stations and/or static water levels at wells. Three-dimensional particle tracking was used to predict the sources of water to the fens. We observed from the multi-scale simulations that the water system that supports the fens is a much larger, more connected, and more complex one than expected. The water in the fen can be traced back to a network of sources, including lakes and wetlands at different elevations, which are connected to a regional mound through a "cascade delivery mechanism". This "master recharge area" is the ultimate source of water not only to the fens in its vicinity, but also for many major rivers and aquifers. The implication of this finding is that prairie fens must be managed as part of a much larger, multi-scale groundwater system and we must consider protection of the shorter and long-term water sources. This will require a fundamental reassessment of our current approach to fen conservation, which is primarily based on protection of individual fens and their immediate surroundings. Clearly, in the future we must plan for conservation of the broad recharge areas and the multiple fen complexes they support.

Modeling Rainfall-Runoff Dynamics in Tropical, Urban Socio-Hydrological Systems: Green Infrastructure and Variable Precipitation Interception

NASA Astrophysics Data System (ADS)

Nytch, C. J.; Meléndez-Ackerman, E. J.

2014-12-01

There is a pressing need to generate spatially-explicit models of rainfall-runoff dynamics in the urban humid tropics that can characterize flow pathways and flood magnitudes in response to erratic precipitation events. To effectively simulate stormwater runoff processes at multiple scales, complex spatio-temporal parameters such as rainfall, evapotranspiration, and antecedent soil moisture conditions must be accurately represented, in addition to uniquely urban factors including stormwater conveyance structures and connectivity between green and gray infrastructure elements. In heavily urbanized San Juan, Puerto Rico, stream flashiness and frequent flooding are major issues, yet still lacking is a hydrological analysis that models the generation and movement of fluvial and pluvial stormwater through the watershed. Our research employs a novel and multifaceted approach to dealing with this problem that integrates 1) field-based rainfall interception and infiltration methodologies to quantify the hydrologic functions of natural and built infrastructure in San Juan; 2) remote sensing analysis to produce a fine-scale typology of green and gray cover types in the city and determine patterns of spatial distribution and connectivity; 3) assessment of precipitation and streamflow variability at local and basin-wide scales using satellite and radar precipitation estimates in concert with rainfall and stream gauge point data and participatory flood mapping; 4) simulation of historical, present-day, and future stormwater runoff scenarios with a fully distributed hydrologic model that couples diverse components of urban socio-hydrological systems from formal and informal knowledge sources; and 5) bias and uncertainty analysis of parameters and model structure within a Bayesian hierarchical framework. Preliminary results from the rainfall interception study suggest that canopy structure and leaf area index of different tree species contribute to variable throughfall and stemflow responses. Additional investigations are pending. The findings from this work will help inform urban planning and design, and build adaptive capacity to reduce flood vulnerability in the context of a changing climate.

Risk assessment of flood disaster and forewarning model at different spatial-temporal scales

NASA Astrophysics Data System (ADS)

Zhao, Jun; Jin, Juliang; Xu, Jinchao; Guo, Qizhong; Hang, Qingfeng; Chen, Yaqian

2018-05-01

Aiming at reducing losses from flood disaster, risk assessment of flood disaster and forewarning model is studied. The model is built upon risk indices in flood disaster system, proceeding from the whole structure and its parts at different spatial-temporal scales. In this study, on the one hand, it mainly establishes the long-term forewarning model for the surface area with three levels of prediction, evaluation, and forewarning. The method of structure-adaptive back-propagation neural network on peak identification is used to simulate indices in prediction sub-model. Set pair analysis is employed to calculate the connection degrees of a single index, comprehensive index, and systematic risk through the multivariate connection number, and the comprehensive assessment is made by assessment matrixes in evaluation sub-model. The comparison judging method is adopted to divide warning degree of flood disaster on risk assessment comprehensive index with forewarning standards in forewarning sub-model and then the long-term local conditions for proposing planning schemes. On the other hand, it mainly sets up the real-time forewarning model for the spot, which introduces the real-time correction technique of Kalman filter based on hydrological model with forewarning index, and then the real-time local conditions for presenting an emergency plan. This study takes Tunxi area, Huangshan City of China, as an example. After risk assessment and forewarning model establishment and application for flood disaster at different spatial-temporal scales between the actual and simulated data from 1989 to 2008, forewarning results show that the development trend for flood disaster risk remains a decline on the whole from 2009 to 2013, despite the rise in 2011. At the macroscopic level, project and non-project measures are advanced, while at the microcosmic level, the time, place, and method are listed. It suggests that the proposed model is feasible with theory and application, thus offering a way for assessing and forewarning flood disaster risk.