A performance comparison of scalar, vector, and concurrent vector computers including supercomputers for modeling transport of reactive contaminants in groundwater

NASA Astrophysics Data System (ADS)

Tripathi, Vijay S.; Yeh, G. T.

1993-06-01

Sophisticated and highly computation-intensive models of transport of reactive contaminants in groundwater have been developed in recent years. Application of such models to real-world contaminant transport problems, e.g., simulation of groundwater transport of 10-15 chemically reactive elements (e.g., toxic metals) and relevant complexes and minerals in two and three dimensions over a distance of several hundred meters, requires high-performance computers including supercomputers. Although not widely recognized as such, the computational complexity and demand of these models compare with well-known computation-intensive applications including weather forecasting and quantum chemical calculations. A survey of the performance of a variety of available hardware, as measured by the run times for a reactive transport model HYDROGEOCHEM, showed that while supercomputers provide the fastest execution times for such problems, relatively low-cost reduced instruction set computer (RISC) based scalar computers provide the best performance-to-price ratio. Because supercomputers like the Cray X-MP are inherently multiuser resources, often the RISC computers also provide much better turnaround times. Furthermore, RISC-based workstations provide the best platforms for "visualization" of groundwater flow and contaminant plumes. The most notable result, however, is that current workstations costing less than $10,000 provide performance within a factor of 5 of a Cray X-MP.

Evaluation of concentrated space solar arrays using computer modeling. [for spacecraft propulsion and power supplies

NASA Technical Reports Server (NTRS)

Rockey, D. E.

1979-01-01

A general approach is developed for predicting the power output of a concentrator enhanced photovoltaic space array. A ray trace routine determines the concentrator intensity arriving at each solar cell. An iterative calculation determines the cell's operating temperature since cell temperature and cell efficiency are functions of one another. The end result of the iterative calculation is that the individual cell's power output is determined as a function of temperature and intensity. Circuit output is predicted by combining the individual cell outputs using the single diode model of a solar cell. Concentrated array characteristics such as uniformity of intensity and operating temperature at various points across the array are examined using computer modeling techniques. An illustrative example is given showing how the output of an array can be enhanced using solar concentration techniques.

Accelerated solution of discrete ordinates approximation to the Boltzmann transport equation via model reduction

DOE PAGES

Tencer, John; Carlberg, Kevin; Larsen, Marvin; ...

2017-06-17

Radiation heat transfer is an important phenomenon in many physical systems of practical interest. When participating media is important, the radiative transfer equation (RTE) must be solved for the radiative intensity as a function of location, time, direction, and wavelength. In many heat-transfer applications, a quasi-steady assumption is valid, thereby removing time dependence. The dependence on wavelength is often treated through a weighted sum of gray gases (WSGG) approach. The discrete ordinates method (DOM) is one of the most common methods for approximating the angular (i.e., directional) dependence. The DOM exactly solves for the radiative intensity for a finite numbermore » of discrete ordinate directions and computes approximations to integrals over the angular space using a quadrature rule; the chosen ordinate directions correspond to the nodes of this quadrature rule. This paper applies a projection-based model-reduction approach to make high-order quadrature computationally feasible for the DOM for purely absorbing applications. First, the proposed approach constructs a reduced basis from (high-fidelity) solutions of the radiative intensity computed at a relatively small number of ordinate directions. Then, the method computes inexpensive approximations of the radiative intensity at the (remaining) quadrature points of a high-order quadrature using a reduced-order model constructed from the reduced basis. Finally, this results in a much more accurate solution than might have been achieved using only the ordinate directions used to compute the reduced basis. One- and three-dimensional test problems highlight the efficiency of the proposed method.« less

Accelerated solution of discrete ordinates approximation to the Boltzmann transport equation via model reduction

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

Tencer, John; Carlberg, Kevin; Larsen, Marvin

Radiation heat transfer is an important phenomenon in many physical systems of practical interest. When participating media is important, the radiative transfer equation (RTE) must be solved for the radiative intensity as a function of location, time, direction, and wavelength. In many heat-transfer applications, a quasi-steady assumption is valid, thereby removing time dependence. The dependence on wavelength is often treated through a weighted sum of gray gases (WSGG) approach. The discrete ordinates method (DOM) is one of the most common methods for approximating the angular (i.e., directional) dependence. The DOM exactly solves for the radiative intensity for a finite numbermore » of discrete ordinate directions and computes approximations to integrals over the angular space using a quadrature rule; the chosen ordinate directions correspond to the nodes of this quadrature rule. This paper applies a projection-based model-reduction approach to make high-order quadrature computationally feasible for the DOM for purely absorbing applications. First, the proposed approach constructs a reduced basis from (high-fidelity) solutions of the radiative intensity computed at a relatively small number of ordinate directions. Then, the method computes inexpensive approximations of the radiative intensity at the (remaining) quadrature points of a high-order quadrature using a reduced-order model constructed from the reduced basis. Finally, this results in a much more accurate solution than might have been achieved using only the ordinate directions used to compute the reduced basis. One- and three-dimensional test problems highlight the efficiency of the proposed method.« less

In Vivo Validation of Numerical Prediction for Turbulence Intensity in an Aortic Coarctation

PubMed Central

Arzani, Amirhossein; Dyverfeldt, Petter; Ebbers, Tino; Shadden, Shawn C.

2013-01-01

This paper compares numerical predictions of turbulence intensity with in vivo measurement. Magnetic resonance imaging (MRI) was carried out on a 60-year-old female with a restenosed aortic coarctation. Time-resolved three-directional phase-contrast (PC) MRI data was acquired to enable turbulence intensity estimation. A contrast-enhanced MR angiography (MRA) and a time-resolved 2D PCMRI measurement were also performed to acquire data needed to perform subsequent image-based computational fluid dynamics (CFD) modeling. A 3D model of the aortic coarctation and surrounding vasculature was constructed from the MRA data, and physiologic boundary conditions were modeled to match 2D PCMRI and pressure pulse measurements. Blood flow velocity data was subsequently obtained by numerical simulation. Turbulent kinetic energy (TKE) was computed from the resulting CFD data. Results indicate relative agreement (error ≈10%) between the in vivo measurements and the CFD predictions of TKE. The discrepancies in modeled vs. measured TKE values were within expectations due to modeling and measurement errors. PMID:22016327

Mathematical algorithm development and parametric studies with the GEOFRAC three-dimensional stochastic model of natural rock fracture systems

NASA Astrophysics Data System (ADS)

Ivanova, Violeta M.; Sousa, Rita; Murrihy, Brian; Einstein, Herbert H.

2014-06-01

This paper presents results from research conducted at MIT during 2010-2012 on modeling of natural rock fracture systems with the GEOFRAC three-dimensional stochastic model. Following a background summary of discrete fracture network models and a brief introduction of GEOFRAC, the paper provides a thorough description of the newly developed mathematical and computer algorithms for fracture intensity, aperture, and intersection representation, which have been implemented in MATLAB. The new methods optimize, in particular, the representation of fracture intensity in terms of cumulative fracture area per unit volume, P32, via the Poisson-Voronoi Tessellation of planes into polygonal fracture shapes. In addition, fracture apertures now can be represented probabilistically or deterministically whereas the newly implemented intersection algorithms allow for computing discrete pathways of interconnected fractures. In conclusion, results from a statistical parametric study, which was conducted with the enhanced GEOFRAC model and the new MATLAB-based Monte Carlo simulation program FRACSIM, demonstrate how fracture intensity, size, and orientations influence fracture connectivity.

A Note on Testing Mediated Effects in Structural Equation Models: Reconciling Past and Current Research on the Performance of the Test of Joint Significance

ERIC Educational Resources Information Center

Valente, Matthew J.; Gonzalez, Oscar; Miocevic, Milica; MacKinnon, David P.

2016-01-01

Methods to assess the significance of mediated effects in education and the social sciences are well studied and fall into two categories: single sample methods and computer-intensive methods. A popular single sample method to detect the significance of the mediated effect is the test of joint significance, and a popular computer-intensive method…

Impact of surface coupling grids on tropical cyclone extremes in high-resolution atmospheric simulations

DOE PAGES

Zarzycki, Colin M.; Reed, Kevin A.; Bacmeister, Julio T.; ...

2016-02-25

This article discusses the sensitivity of tropical cyclone climatology to surface coupling strategy in high-resolution configurations of the Community Earth System Model. Using two supported model setups, we demonstrate that the choice of grid on which the lowest model level wind stress and surface fluxes are computed may lead to differences in cyclone strength in multi-decadal climate simulations, particularly for the most intense cyclones. Using a deterministic framework, we show that when these surface quantities are calculated on an ocean grid that is coarser than the atmosphere, the computed frictional stress is misaligned with wind vectors in individual atmospheric gridmore » cells. This reduces the effective surface drag, and results in more intense cyclones when compared to a model configuration where the ocean and atmosphere are of equivalent resolution. Our results demonstrate that the choice of computation grid for atmosphere–ocean interactions is non-negligible when considering climate extremes at high horizontal resolution, especially when model components are on highly disparate grids.« less

LASER APPLICATIONS AND OTHER TOPICS IN QUANTUM ELECTRONICS: Methods of computational physics in the problem of mathematical interpretation of laser investigations

NASA Astrophysics Data System (ADS)

Brodyn, M. S.; Starkov, V. N.

2007-07-01

It is shown that in laser experiments performed by using an 'imperfect' setup when instrumental distortions are considerable, sufficiently accurate results can be obtained by the modern methods of computational physics. It is found for the first time that a new instrumental function — the 'cap' function — a 'sister' of a Gaussian curve proved to be demanded namely in laser experiments. A new mathematical model of a measurement path and carefully performed computational experiment show that a light beam transmitted through a mesoporous film has actually a narrower intensity distribution than the detected beam, and the amplitude of the real intensity distribution is twice as large as that for measured intensity distributions.

Accelerating Climate and Weather Simulations through Hybrid Computing

NASA Technical Reports Server (NTRS)

Zhou, Shujia; Cruz, Carlos; Duffy, Daniel; Tucker, Robert; Purcell, Mark

2011-01-01

Unconventional multi- and many-core processors (e.g. IBM (R) Cell B.E.(TM) and NVIDIA (R) GPU) have emerged as effective accelerators in trial climate and weather simulations. Yet these climate and weather models typically run on parallel computers with conventional processors (e.g. Intel, AMD, and IBM) using Message Passing Interface. To address challenges involved in efficiently and easily connecting accelerators to parallel computers, we investigated using IBM's Dynamic Application Virtualization (TM) (IBM DAV) software in a prototype hybrid computing system with representative climate and weather model components. The hybrid system comprises two Intel blades and two IBM QS22 Cell B.E. blades, connected with both InfiniBand(R) (IB) and 1-Gigabit Ethernet. The system significantly accelerates a solar radiation model component by offloading compute-intensive calculations to the Cell blades. Systematic tests show that IBM DAV can seamlessly offload compute-intensive calculations from Intel blades to Cell B.E. blades in a scalable, load-balanced manner. However, noticeable communication overhead was observed, mainly due to IP over the IB protocol. Full utilization of IB Sockets Direct Protocol and the lower latency production version of IBM DAV will reduce this overhead.

A tesselation-based model for intensity estimation and laser plasma interactions calculations in three dimensions

NASA Astrophysics Data System (ADS)

Colaïtis, A.; Chapman, T.; Strozzi, D.; Divol, L.; Michel, P.

2018-03-01

A three-dimensional laser propagation model for computation of laser-plasma interactions is presented. It is focused on indirect drive geometries in inertial confinement fusion and formulated for use at large temporal and spatial scales. A modified tesselation-based estimator and a relaxation scheme are used to estimate the intensity distribution in plasma from geometrical optics rays. Comparisons with reference solutions show that this approach is well-suited to reproduce realistic 3D intensity field distributions of beams smoothed by phase plates. It is shown that the method requires a reduced number of rays compared to traditional rigid-scale intensity estimation. Using this field estimator, we have implemented laser refraction, inverse-bremsstrahlung absorption, and steady-state crossed-beam energy transfer with a linear kinetic model in the numerical code Vampire. Probe beam amplification and laser spot shapes are compared with experimental results and pf3d paraxial simulations. These results are promising for the efficient and accurate computation of laser intensity distributions in holhraums, which is of importance for determining the capsule implosion shape and risks of laser-plasma instabilities such as hot electron generation and backscatter in multi-beam configurations.

Sensitivity of the 6300 A twilight airglow to neutral composition

NASA Technical Reports Server (NTRS)

Melendez-Alvira, D. J.; Torr, D. G.; Richards, P. G.; Swift, W. R.; Torr, M. R.; Baldridge, T.; Rassoul, H.

1995-01-01

The field line interhemispheric plasma (FLIP) model is used to study the 6300 A line intensity measured during three morning twilights from the McDonald Observatory in Texas. The Imaging Spectrometric Observatory (ISO) measured the 6300 A intensity during the winter of 1987 and the spring and summer of 1988. The FLIP model reproduces the measured intensity and its variation through the twilight well on each day using neutral densities from the MSIS-86 empirical model. This is in spite of the fact that different component sources dominate the integrated volume emission rate on each of the days analyzed. The sensitivity of the intensity to neutral composition is computed by varying the N2, O2, and O densities in the FLIP model and comparing to the intensity computed with the unmodified MSIS-86 densities. The ion densities change self-consistently. Thus the change in neutral composition also changes the electron density. The F2 peak height is unchanged in the model runs for a given day. The intensity changes near 100 deg SZA are comparable to within 10% when either (O2), (N2), or (O) is changed, regardless of which component source is dominant. There is strong sensitivity to changes in (N2) when dissociative recombination is dominant, virtually no change in the nighttime (SZA greater than or equal to 108 deg) intensity with (O2) doubled, and sensitivity of over 50% to doubling or halving (O) at night. When excitation by conjugate photoelectrons is the dominant nighttime component source, the relative intensity change with (O) doubled or halved is very small. This study shows the strong need for simultaneous measurements of electron density and of emissions proportional to photoelectron fluxes if the 6300 A twilight airglow is to be used to retrieve neutral densities.

Simulating Quantile Models with Applications to Economics and Management

NASA Astrophysics Data System (ADS)

Machado, José A. F.

2010-05-01

The massive increase in the speed of computers over the past forty years changed the way that social scientists, applied economists and statisticians approach their trades and also the very nature of the problems that they could feasibly tackle. The new methods that use intensively computer power go by the names of "computer-intensive" or "simulation". My lecture will start with bird's eye view of the uses of simulation in Economics and Statistics. Then I will turn out to my own research on uses of computer- intensive methods. From a methodological point of view the question I address is how to infer marginal distributions having estimated a conditional quantile process, (Counterfactual Decomposition of Changes in Wage Distributions using Quantile Regression," Journal of Applied Econometrics 20, 2005). Illustrations will be provided of the use of the method to perform counterfactual analysis in several different areas of knowledge.

Frozen lattice and absorptive model for high angle annular dark field scanning transmission electron microscopy: A comparison study in terms of integrated intensity and atomic column position measurement.

PubMed

Alania, M; Lobato, I; Van Aert, S

2018-01-01

In this paper, both the frozen lattice (FL) and the absorptive potential (AP) approximation models are compared in terms of the integrated intensity and the precision with which atomic columns can be located from an image acquired using high angle annular dark field (HAADF) scanning transmission electron microscopy (STEM). The comparison is made for atoms of Cu, Ag, and Au. The integrated intensity is computed for both an isolated atomic column and an atomic column inside an FCC structure. The precision has been computed using the so-called Cramér-Rao Lower Bound (CRLB), which provides a theoretical lower bound on the variance with which parameters can be estimated. It is shown that the AP model results into accurate measurements for the integrated intensity only for small detector ranges under relatively low angles and for small thicknesses. In terms of the attainable precision, both methods show similar results indicating picometer range precision under realistic experimental conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Model development for Ulysses and SOHO

NASA Technical Reports Server (NTRS)

Wu, S. T.

1993-01-01

The purpose of this research is to provide scientific expertise in solar physics and in the development and use of magnetohydrodynamic (MHD) models of coronal structures for the computation of Lyman alpha scattered radiation in these structures. The specific objectives will be to run MHD models with new boundary conditions and compute resulting scattered solar Lyman alpha intensities, guided by results from the first series of boundary conditions.

Cyclone Simulation via Action Minimization

NASA Astrophysics Data System (ADS)

Plotkin, D. A.; Weare, J.; Abbot, D. S.

2016-12-01

A postulated impact of climate change is an increase in intensity of tropical cyclones (TCs). This hypothesized effect results from the fact that TCs are powered subsaturated boundary layer air picking up water vapor from the surface ocean as it flows inwards towards the eye. This water vapor serves as the energy input for TCs, which can be idealized as heat engines. The inflowing air has a nearly identical temperature as the surface ocean; therefore, warming of the surface leads to a warmer atmospheric boundary layer. By the Clausius-Clapeyron relationship, warmer boundary layer air can hold more water vapor and thus results in more energetic storms. Changes in TC intensity are difficult to predict due to the presence of fine structures (e.g. convective structures and rainbands) with length scales of less than 1 km, while general circulation models (GCMs) generally have horizontal resolutions of tens of kilometers. The models are therefore unable to capture these features, which are critical to accurately simulating cyclone structure and intensity. Further, strong TCs are rare events, meaning that long multi-decadal simulations are necessary to generate meaningful statistics about intense TC activity. This adds to the computational expense, making it yet more difficult to generate accurate statistics about long-term changes in TC intensity due to global warming via direct simulation. We take an alternative approach, applying action minimization techniques developed in molecular dynamics to the WRF weather/climate model. We construct artificial model trajectories that lead from quiescent (TC-free) states to TC states, then minimize the deviation of these trajectories from true model dynamics. We can thus create Monte Carlo model ensembles that are biased towards cyclogenesis, which reduces computational expense by limiting time spent in non-TC states. This allows for: 1) selective interrogation of model states with TCs; 2) finding the likeliest paths for transitions between TC-free and TC states; and 3) an increase in horizontal resolution due to computational savings achieved by reducing time spent simulating TC-free states. This increase in resolution, coupled with a decrease in simulation time, allows for prediction of the change in TC frequency and intensity distributions resulting from climate change.

Feasibility of employing model-based optimization of pulse amplitude and electrode distance for effective tumor electropermeabilization.

PubMed

Sel, Davorka; Lebar, Alenka Macek; Miklavcic, Damijan

2007-05-01

In electrochemotherapy (ECT) electropermeabilization, parameters (pulse amplitude, electrode setup) need to be customized in order to expose the whole tumor to electric field intensities above permeabilizing threshold to achieve effective ECT. In this paper, we present a model-based optimization approach toward determination of optimal electropermeabilization parameters for effective ECT. The optimization is carried out by minimizing the difference between the permeabilization threshold and electric field intensities computed by finite element model in selected points of tumor. We examined the feasibility of model-based optimization of electropermeabilization parameters on a model geometry generated from computer tomography images, representing brain tissue with tumor. Continuous parameter subject to optimization was pulse amplitude. The distance between electrode pairs was optimized as a discrete parameter. Optimization also considered the pulse generator constraints on voltage and current. During optimization the two constraints were reached preventing the exposure of the entire volume of the tumor to electric field intensities above permeabilizing threshold. However, despite the fact that with the particular needle array holder and pulse generator the entire volume of the tumor was not permeabilized, the maximal extent of permeabilization for the particular case (electrodes, tissue) was determined with the proposed approach. Model-based optimization approach could also be used for electro-gene transfer, where electric field intensities should be distributed between permeabilizing threshold and irreversible threshold-the latter causing tissue necrosis. This can be obtained by adding constraints on maximum electric field intensity in optimization procedure.

Autonomic Closure for Turbulent Flows Using Approximate Bayesian Computation

NASA Astrophysics Data System (ADS)

Doronina, Olga; Christopher, Jason; Hamlington, Peter; Dahm, Werner

2017-11-01

Autonomic closure is a new technique for achieving fully adaptive and physically accurate closure of coarse-grained turbulent flow governing equations, such as those solved in large eddy simulations (LES). Although autonomic closure has been shown in recent a priori tests to more accurately represent unclosed terms than do dynamic versions of traditional LES models, the computational cost of the approach makes it challenging to implement for simulations of practical turbulent flows at realistically high Reynolds numbers. The optimization step used in the approach introduces large matrices that must be inverted and is highly memory intensive. In order to reduce memory requirements, here we propose to use approximate Bayesian computation (ABC) in place of the optimization step, thereby yielding a computationally-efficient implementation of autonomic closure that trades memory-intensive for processor-intensive computations. The latter challenge can be overcome as co-processors such as general purpose graphical processing units become increasingly available on current generation petascale and exascale supercomputers. In this work, we outline the formulation of ABC-enabled autonomic closure and present initial results demonstrating the accuracy and computational cost of the approach.

NEW GIS WATERSHED ANALYSIS TOOLS FOR SOIL CHARACTERIZATION AND EROSION AND SEDIMENTATION MODELING

EPA Science Inventory

A comprehensive procedure for computing soil erosion and sediment delivery metrics has been developed which utilizes a suite of automated scripts and a pair of processing-intensive executable programs operating on a personal computer platform.

The emerging role of cloud computing in molecular modelling.

PubMed

Ebejer, Jean-Paul; Fulle, Simone; Morris, Garrett M; Finn, Paul W

2013-07-01

There is a growing recognition of the importance of cloud computing for large-scale and data-intensive applications. The distinguishing features of cloud computing and their relationship to other distributed computing paradigms are described, as are the strengths and weaknesses of the approach. We review the use made to date of cloud computing for molecular modelling projects and the availability of front ends for molecular modelling applications. Although the use of cloud computing technologies for molecular modelling is still in its infancy, we demonstrate its potential by presenting several case studies. Rapid growth can be expected as more applications become available and costs continue to fall; cloud computing can make a major contribution not just in terms of the availability of on-demand computing power, but could also spur innovation in the development of novel approaches that utilize that capacity in more effective ways. Copyright © 2013 Elsevier Inc. All rights reserved.

Computational Investigation of Soot and Radiation in Turbulent Reacting Flows

NASA Astrophysics Data System (ADS)

Lalit, Harshad

This study delves into computational modeling of soot and infrared radiation for turbulent reacting flows, detailed understanding of both of which is paramount in the design of cleaner engines and pollution control. In the first part of the study, the concept of Stochastic Time and Space Series Analysis (STASS) as a numerical tool to compute time dependent statistics of radiation intensity is introduced for a turbulent premixed flame. In the absence of high fidelity codes for large eddy simulation or direct numerical simulation of turbulent flames, the utility of STASS for radiation imaging of reacting flows to understand the flame structure is assessed by generating images of infrared radiation in spectral bands dominated by radiation from gas phase carbon dioxide and water vapor using an assumed PDF method. The study elucidates the need for time dependent computation of radiation intensity for validation with experiments and the need for accounting for turbulence radiation interactions for correctly predicting radiation intensity and consequently the flame temperature and NOx in a reacting fluid flow. Comparison of single point statistics of infrared radiation intensity with measurements show that STASS can not only predict the flame structure but also estimate the dynamics of thermochemical scalars in the flame with reasonable accuracy. While a time series is used to generate realizations of thermochemical scalars in the first part of the study, in the second part, instantaneous realizations of resolved scale temperature, CO2 and H2O mole fractions and soot volume fractions are extracted from a large eddy simulation (LES) to carry out quantitative imaging of radiation intensity (QIRI) for a turbulent soot generating ethylene diffusion flame. A primary motivation of the study is to establish QIRI as a computational tool for validation of soot models, especially in the absence of conventional flow field and measured scalar data for sooting flames. Realizations of scalars from the LES are used in conjunction with the radiation heat transfer equation and a narrow band radiation model to compute time dependent and time averaged images of infrared radiation intensity in spectral bands corresponding to molecular radiation from gas phase carbon dioxide and soot particles exclusively. While qualitative and quantitative comparisons with measured images in the CO2 radiation band show that the flame structure is correctly computed, images computed in the soot radiation band illustrate that the soot volume fraction is under predicted by the computations. The effect of the soot model and cause of under prediction is investigated further by correcting the soot volume fraction using an empirical state relationship. By comparing default simulations with computations using the state relation, it is shown that while the soot model under-estimates the soot concentration, it correctly computes the intermittency of soot in the flame. The study of sooting flames is extended further by performing a parametric analysis of physical and numerical parameters that affect soot formation and transport in two laboratory scale turbulent sooting flames, one fueled by natural gas and the other by ethylene. The study is focused on investigating the effect of molecular diffusion of species, dilution of fuel with hydrogen gas and the effect of chemical reaction mechanism on the soot concentration in the flame. The effect of species Lewis numbers on soot evolution and transport is investigated by carrying out simulations, first with the default equal diffusivity (ED) assumption and then by incorporating a differential diffusion (DD) model. Computations using the DD model over-estimate the concentration of the soot precursor and soot oxidizer species, leading to inconsistencies in the estimate of the soot concentration. The linear differential diffusion (LDD) model, reported previously to consistently model differential diffusion effects is implemented to correct the over prediction effect of the DD model. It is shown that the effect of species Lewis number on soot evolution is a secondary phenomenon and that soot is primarily transported by advection of the fluid in a turbulent flame. The effect of hydrogen dilution on the soot formation and transport process is also studied. It is noted that the decay of soot volume fraction and flame length with hydrogen addition follows trends observed in laminar sooting flame measurements. While hydrogen enhances mixing shown by the laminar flamelet solutions, the mixing effect does not significantly contribute to differential molecular diffusion effects in the soot nucleation regions downstream of the flame and has a negligible effect on soot transport. The sensitivity of computations of soot volume fraction towards the chemical reaction mechanism is shown. It is concluded that modeling reaction pathways of C3 and C4 species that lead up to Polycyclic Aromatic Hydrocarbon (PAH) molecule formation is paramount for accurate predictions of soot in the flame. (Abstract shortened by ProQuest.).

Py4CAtS - Python tools for line-by-line modelling of infrared atmospheric radiative transfer

NASA Astrophysics Data System (ADS)

Schreier, Franz; García, Sebastián Gimeno

2013-05-01

Py4CAtS — Python scripts for Computational ATmospheric Spectroscopy is a Python re-implementation of the Fortran infrared radiative transfer code GARLIC, where compute-intensive code sections utilize the Numeric/Scientific Python modules for highly optimized array-processing. The individual steps of an infrared or microwave radiative transfer computation are implemented in separate scripts to extract lines of relevant molecules in the spectral range of interest, to compute line-by-line cross sections for given pressure(s) and temperature(s), to combine cross sections to absorption coefficients and optical depths, and to integrate along the line-of-sight to transmission and radiance/intensity. The basic design of the package, numerical and computational aspects relevant for optimization, and a sketch of the typical workflow are presented.

A Fuzzy Computing Model for Identifying Polarity of Chinese Sentiment Words

PubMed Central

Huang, Yongfeng; Wu, Xian; Li, Xing

2015-01-01

With the spurt of online user-generated contents on web, sentiment analysis has become a very active research issue in data mining and natural language processing. As the most important indicator of sentiment, sentiment words which convey positive and negative polarity are quite instrumental for sentiment analysis. However, most of the existing methods for identifying polarity of sentiment words only consider the positive and negative polarity by the Cantor set, and no attention is paid to the fuzziness of the polarity intensity of sentiment words. In order to improve the performance, we propose a fuzzy computing model to identify the polarity of Chinese sentiment words in this paper. There are three major contributions in this paper. Firstly, we propose a method to compute polarity intensity of sentiment morphemes and sentiment words. Secondly, we construct a fuzzy sentiment classifier and propose two different methods to compute the parameter of the fuzzy classifier. Thirdly, we conduct extensive experiments on four sentiment words datasets and three review datasets, and the experimental results indicate that our model performs better than the state-of-the-art methods. PMID:26106409

Mapping species abundance by a spatial zero-inflated Poisson model: a case study in the Wadden Sea, the Netherlands.

PubMed

Lyashevska, Olga; Brus, Dick J; van der Meer, Jaap

2016-01-01

The objective of the study was to provide a general procedure for mapping species abundance when data are zero-inflated and spatially correlated counts. The bivalve species Macoma balthica was observed on a 500×500 m grid in the Dutch part of the Wadden Sea. In total, 66% of the 3451 counts were zeros. A zero-inflated Poisson mixture model was used to relate counts to environmental covariates. Two models were considered, one with relatively fewer covariates (model "small") than the other (model "large"). The models contained two processes: a Bernoulli (species prevalence) and a Poisson (species intensity, when the Bernoulli process predicts presence). The model was used to make predictions for sites where only environmental data are available. Predicted prevalences and intensities show that the model "small" predicts lower mean prevalence and higher mean intensity, than the model "large". Yet, the product of prevalence and intensity, which might be called the unconditional intensity, is very similar. Cross-validation showed that the model "small" performed slightly better, but the difference was small. The proposed methodology might be generally applicable, but is computer intensive.

Hurricane Intensity Forecasts with a Global Mesoscale Model on the NASA Columbia Supercomputer

NASA Technical Reports Server (NTRS)

Shen, Bo-Wen; Tao, Wei-Kuo; Atlas, Robert

2006-01-01

It is known that General Circulation Models (GCMs) have insufficient resolution to accurately simulate hurricane near-eye structure and intensity. The increasing capabilities of high-end computers (e.g., the NASA Columbia Supercomputer) have changed this. In 2004, the finite-volume General Circulation Model at a 1/4 degree resolution, doubling the resolution used by most of operational NWP center at that time, was implemented and run to obtain promising landfall predictions for major hurricanes (e.g., Charley, Frances, Ivan, and Jeanne). In 2005, we have successfully implemented the 1/8 degree version, and demonstrated its performance on intensity forecasts with hurricane Katrina (2005). It is found that the 1/8 degree model is capable of simulating the radius of maximum wind and near-eye wind structure, and thereby promising intensity forecasts. In this study, we will further evaluate the model s performance on intensity forecasts of hurricanes Ivan, Jeanne, Karl in 2004. Suggestions for further model development will be made in the end.

Multiscale Simulations of Reactive Transport

NASA Astrophysics Data System (ADS)

Tartakovsky, D. M.; Bakarji, J.

2014-12-01

Discrete, particle-based simulations offer distinct advantages when modeling solute transport and chemical reactions. For example, Brownian motion is often used to model diffusion in complex pore networks, and Gillespie-type algorithms allow one to handle multicomponent chemical reactions with uncertain reaction pathways. Yet such models can be computationally more intensive than their continuum-scale counterparts, e.g., advection-dispersion-reaction equations. Combining the discrete and continuum models has a potential to resolve the quantity of interest with a required degree of physicochemical granularity at acceptable computational cost. We present computational examples of such "hybrid models" and discuss the challenges associated with coupling these two levels of description.

Decision making and preferences for acoustic signals in choice situations by female crickets.

PubMed

Gabel, Eileen; Kuntze, Janine; Hennig, R Matthias

2015-08-01

Multiple attributes usually have to be assessed when choosing a mate. Efficient choice of the best mate is complicated if the available cues are not positively correlated, as is often the case during acoustic communication. Because of varying distances of signalers, a female may be confronted with signals of diverse quality at different intensities. Here, we examined how available cues are weighted for a decision by female crickets. Two songs with different temporal patterns and/or sound intensities were presented in a choice paradigm and compared with female responses from a no-choice test. When both patterns were presented at equal intensity, preference functions became wider in choice situations compared with a no-choice paradigm. When the stimuli in two-choice tests were presented at different intensities, this effect was counteracted as preference functions became narrower compared with choice tests using stimuli of equal intensity. The weighting of intensity differences depended on pattern quality and was therefore non-linear. A simple computational model based on pattern and intensity cues reliably predicted female decisions. A comparison of processing schemes suggested that the computations for pattern recognition and directionality are performed in a network with parallel topology. However, the computational flow of information corresponded to serial processing. © 2015. Published by The Company of Biologists Ltd.

METCAN: The metal matrix composite analyzer

NASA Technical Reports Server (NTRS)

Hopkins, Dale A.; Murthy, Pappu L. N.

1988-01-01

Metal matrix composites (MMC) are the subject of intensive study and are receiving serious consideration for critical structural applications in advanced aerospace systems. MMC structural analysis and design methodologies are studied. Predicting the mechanical and thermal behavior and the structural response of components fabricated from MMC requires the use of a variety of mathematical models. These models relate stresses to applied forces, stress intensities at the tips of cracks to nominal stresses, buckling resistance to applied force, or vibration response to excitation forces. The extensive research in computational mechanics methods for predicting the nonlinear behavior of MMC are described. This research has culminated in the development of the METCAN (METal Matrix Composite ANalyzer) computer code.

A computational study for investigating acoustic streaming and tissue heating during high intensity focused ultrasound through blood vessel with an obstacle

NASA Astrophysics Data System (ADS)

Parvin, Salma; Sultana, Aysha

2017-06-01

The influence of High Intensity Focused Ultrasound (HIFU) on the obstacle through blood vessel is studied numerically. A three-dimensional acoustics-thermal-fluid coupling model is employed to compute the temperature field around the obstacle through blood vessel. The model construction is based on the linear Westervelt and conjugate heat transfer equations for the obstacle through blood vessel. The system of equations is solved using Finite Element Method (FEM). We found from this three-dimensional numerical study that the rate of heat transfer is increasing from the obstacle and both the convective cooling and acoustic streaming can considerably change the temperature field.

The effect of El Chichon on the intensity and polarization of skylight at Mauna Loa

NASA Technical Reports Server (NTRS)

King, M. D.; Fraser, R. S.

1983-01-01

An empirical model of the stratospheric aerosol over Mauna Loa Observatory (MLO) has been developed, in order to study the effect of aerosol particles from the eruption of the El Chichon volcano on the intensity and degree of skylight polarization. The modeling computations were based on measurements of monthly mean optical thickness for July 1982, together with lidar measurements of the vertical distribution of aerosols. On the basis of the theoretical computations, it is shown that the number and location of polarization neutral points, and the location and magnitude of the peak polarization were both functions of the relatively narrow distribution of aerosol particle size near 0.4 microns.

MRPack: Multi-Algorithm Execution Using Compute-Intensive Approach in MapReduce

PubMed Central

2015-01-01

Large quantities of data have been generated from multiple sources at exponential rates in the last few years. These data are generated at high velocity as real time and streaming data in variety of formats. These characteristics give rise to challenges in its modeling, computation, and processing. Hadoop MapReduce (MR) is a well known data-intensive distributed processing framework using the distributed file system (DFS) for Big Data. Current implementations of MR only support execution of a single algorithm in the entire Hadoop cluster. In this paper, we propose MapReducePack (MRPack), a variation of MR that supports execution of a set of related algorithms in a single MR job. We exploit the computational capability of a cluster by increasing the compute-intensiveness of MapReduce while maintaining its data-intensive approach. It uses the available computing resources by dynamically managing the task assignment and intermediate data. Intermediate data from multiple algorithms are managed using multi-key and skew mitigation strategies. The performance study of the proposed system shows that it is time, I/O, and memory efficient compared to the default MapReduce. The proposed approach reduces the execution time by 200% with an approximate 50% decrease in I/O cost. Complexity and qualitative results analysis shows significant performance improvement. PMID:26305223

MRPack: Multi-Algorithm Execution Using Compute-Intensive Approach in MapReduce.

PubMed

Idris, Muhammad; Hussain, Shujaat; Siddiqi, Muhammad Hameed; Hassan, Waseem; Syed Muhammad Bilal, Hafiz; Lee, Sungyoung

2015-01-01

Large quantities of data have been generated from multiple sources at exponential rates in the last few years. These data are generated at high velocity as real time and streaming data in variety of formats. These characteristics give rise to challenges in its modeling, computation, and processing. Hadoop MapReduce (MR) is a well known data-intensive distributed processing framework using the distributed file system (DFS) for Big Data. Current implementations of MR only support execution of a single algorithm in the entire Hadoop cluster. In this paper, we propose MapReducePack (MRPack), a variation of MR that supports execution of a set of related algorithms in a single MR job. We exploit the computational capability of a cluster by increasing the compute-intensiveness of MapReduce while maintaining its data-intensive approach. It uses the available computing resources by dynamically managing the task assignment and intermediate data. Intermediate data from multiple algorithms are managed using multi-key and skew mitigation strategies. The performance study of the proposed system shows that it is time, I/O, and memory efficient compared to the default MapReduce. The proposed approach reduces the execution time by 200% with an approximate 50% decrease in I/O cost. Complexity and qualitative results analysis shows significant performance improvement.

Salient regions detection using convolutional neural networks and color volume

NASA Astrophysics Data System (ADS)

Liu, Guang-Hai; Hou, Yingkun

2018-03-01

Convolutional neural network is an important technique in machine learning, pattern recognition and image processing. In order to reduce the computational burden and extend the classical LeNet-5 model to the field of saliency detection, we propose a simple and novel computing model based on LeNet-5 network. In the proposed model, hue, saturation and intensity are utilized to extract depth cues, and then we integrate depth cues and color volume to saliency detection following the basic structure of the feature integration theory. Experimental results show that the proposed computing model outperforms some existing state-of-the-art methods on MSRA1000 and ECSSD datasets.

Space-filling designs for computer experiments: A review

DOE PAGES

Joseph, V. Roshan

2016-01-29

Improving the quality of a product/process using a computer simulator is a much less expensive option than the real physical testing. However, simulation using computationally intensive computer models can be time consuming and therefore, directly doing the optimization on the computer simulator can be infeasible. Experimental design and statistical modeling techniques can be used for overcoming this problem. This article reviews experimental designs known as space-filling designs that are suitable for computer simulations. In the review, a special emphasis is given for a recently developed space-filling design called maximum projection design. Furthermore, its advantages are illustrated using a simulation conductedmore » for optimizing a milling process.« less

Space-filling designs for computer experiments: A review

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

Joseph, V. Roshan

Improving the quality of a product/process using a computer simulator is a much less expensive option than the real physical testing. However, simulation using computationally intensive computer models can be time consuming and therefore, directly doing the optimization on the computer simulator can be infeasible. Experimental design and statistical modeling techniques can be used for overcoming this problem. This article reviews experimental designs known as space-filling designs that are suitable for computer simulations. In the review, a special emphasis is given for a recently developed space-filling design called maximum projection design. Furthermore, its advantages are illustrated using a simulation conductedmore » for optimizing a milling process.« less

Accelerating Dust Storm Simulation by Balancing Task Allocation in Parallel Computing Environment

NASA Astrophysics Data System (ADS)

Gui, Z.; Yang, C.; XIA, J.; Huang, Q.; YU, M.

2013-12-01

Dust storm has serious negative impacts on environment, human health, and assets. The continuing global climate change has increased the frequency and intensity of dust storm in the past decades. To better understand and predict the distribution, intensity and structure of dust storm, a series of dust storm models have been developed, such as Dust Regional Atmospheric Model (DREAM), the NMM meteorological module (NMM-dust) and Chinese Unified Atmospheric Chemistry Environment for Dust (CUACE/Dust). The developments and applications of these models have contributed significantly to both scientific research and our daily life. However, dust storm simulation is a data and computing intensive process. Normally, a simulation for a single dust storm event may take several days or hours to run. It seriously impacts the timeliness of prediction and potential applications. To speed up the process, high performance computing is widely adopted. By partitioning a large study area into small subdomains according to their geographic location and executing them on different computing nodes in a parallel fashion, the computing performance can be significantly improved. Since spatiotemporal correlations exist in the geophysical process of dust storm simulation, each subdomain allocated to a node need to communicate with other geographically adjacent subdomains to exchange data. Inappropriate allocations may introduce imbalance task loads and unnecessary communications among computing nodes. Therefore, task allocation method is the key factor, which may impact the feasibility of the paralleling. The allocation algorithm needs to carefully leverage the computing cost and communication cost for each computing node to minimize total execution time and reduce overall communication cost for the entire system. This presentation introduces two algorithms for such allocation and compares them with evenly distributed allocation method. Specifically, 1) In order to get optimized solutions, a quadratic programming based modeling method is proposed. This algorithm performs well with small amount of computing tasks. However, its efficiency decreases significantly as the subdomain number and computing node number increase. 2) To compensate performance decreasing for large scale tasks, a K-Means clustering based algorithm is introduced. Instead of dedicating to get optimized solutions, this method can get relatively good feasible solutions within acceptable time. However, it may introduce imbalance communication for nodes or node-isolated subdomains. This research shows both two algorithms have their own strength and weakness for task allocation. A combination of the two algorithms is under study to obtain a better performance. Keywords: Scheduling; Parallel Computing; Load Balance; Optimization; Cost Model

Approximate Bayesian Computation in the estimation of the parameters of the Forbush decrease model

NASA Astrophysics Data System (ADS)

Wawrzynczak, A.; Kopka, P.

2017-12-01

Realistic modeling of the complicated phenomena as Forbush decrease of the galactic cosmic ray intensity is a quite challenging task. One aspect is a numerical solution of the Fokker-Planck equation in five-dimensional space (three spatial variables, the time and particles energy). The second difficulty arises from a lack of detailed knowledge about the spatial and time profiles of the parameters responsible for the creation of the Forbush decrease. Among these parameters, the central role plays a diffusion coefficient. Assessment of the correctness of the proposed model can be done only by comparison of the model output with the experimental observations of the galactic cosmic ray intensity. We apply the Approximate Bayesian Computation (ABC) methodology to match the Forbush decrease model to experimental data. The ABC method is becoming increasing exploited for dynamic complex problems in which the likelihood function is costly to compute. The main idea of all ABC methods is to accept samples as an approximate posterior draw if its associated modeled data are close enough to the observed one. In this paper, we present application of the Sequential Monte Carlo Approximate Bayesian Computation algorithm scanning the space of the diffusion coefficient parameters. The proposed algorithm is adopted to create the model of the Forbush decrease observed by the neutron monitors at the Earth in March 2002. The model of the Forbush decrease is based on the stochastic approach to the solution of the Fokker-Planck equation.

Stress Intensity Factors for Cracking Metal Structures under Rapid Thermal Loading. Volume 2. Theoretical Background

DTIC Science & Technology

1989-08-01

thermal pulse loadings. The work couples a Green’s function integration technique for transient thermal stresses with the well-known influence ... function approach for calculating stress intensity factors. A total of seven most commonly used crack models were investigated in this study. A computer

Comment on the paper ;NDSD-1000: High-resolution, high-temperature nitrogen dioxide spectroscopic Databank; by A.A. Lukashevskaya, N.N. Lavrentieva, A.C. Dudaryonok, V.I. Perevalov, J Quant Spectrosc Radiat Transfer 2016;184:205-17

NASA Astrophysics Data System (ADS)

Perrin, A.; Ndao, M.; Manceron, L.

2017-10-01

A recent paper [1] presents a high-resolution, high-temperature version of the Nitrogen Dioxide Spectroscopic Databank called NDSD-1000. The NDSD-1000 database contains line parameters (positions, intensities, self- and air-broadening coefficients, exponents of the temperature dependence of self- and air-broadening coefficients) for numerous cold and hot bands of the 14N16O2 isotopomer of nitrogen dioxide. The parameters used for the line positions and intensities calculation were generated through a global modeling of experimental data collected in the literature within the framework of the method of effective operators. However, the form of the effective dipole moment operator used to compute the NO2 line intensities in the NDSD-1000 database differs from the classical one used for line intensities calculation in the NO2 infrared literature [12]. Using Fourier transform spectra recorded at high resolution in the 6.3 μm region, it is shown here, that the NDSD-1000 formulation is incorrect since the computed intensities do not account properly for the (Int(+)/Int(-)) intensity ratio between the (+) (J = N+ 1/2) and (-) (J = N-1/2) electron - spin rotation subcomponents of the computed vibration rotation transitions. On the other hand, in the HITRAN or GEISA spectroscopic databases, the NO2 line intensities were computed using the classical theoretical approach, and it is shown here that these data lead to a significant better agreement between the observed and calculated spectra.

Accurate optimization of amino acid form factors for computing small-angle X-ray scattering intensity of atomistic protein structures

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

Tong, Dudu; Yang, Sichun; Lu, Lanyuan

2016-06-20

Structure modellingviasmall-angle X-ray scattering (SAXS) data generally requires intensive computations of scattering intensity from any given biomolecular structure, where the accurate evaluation of SAXS profiles using coarse-grained (CG) methods is vital to improve computational efficiency. To date, most CG SAXS computing methods have been based on a single-bead-per-residue approximation but have neglected structural correlations between amino acids. To improve the accuracy of scattering calculations, accurate CG form factors of amino acids are now derived using a rigorous optimization strategy, termed electron-density matching (EDM), to best fit electron-density distributions of protein structures. This EDM method is compared with and tested againstmore » other CG SAXS computing methods, and the resulting CG SAXS profiles from EDM agree better with all-atom theoretical SAXS data. By including the protein hydration shell represented by explicit CG water molecules and the correction of protein excluded volume, the developed CG form factors also reproduce the selected experimental SAXS profiles with very small deviations. Taken together, these EDM-derived CG form factors present an accurate and efficient computational approach for SAXS computing, especially when higher molecular details (represented by theqrange of the SAXS data) become necessary for effective structure modelling.« less

Advanced Technology for Portable Personal Visualization

DTIC Science & Technology

1991-03-01

walking. The building model is created using AutoCAD. Realism is enhanced by calculating a radiosity solution for the lighting model. This has an added...lighting, color combinations and decor. Due to the computationally intensive nature of the radiosity solution, modeling changes cannot be made on-line

Mimicking Natural Laminar to Turbulent Flow Transition: A Systematic CFD Study Using PAB3D

NASA Technical Reports Server (NTRS)

Pao, S. Paul; Abdol-Hamid, Khaled S.

2005-01-01

For applied aerodynamic computations using a general purpose Navier-Stokes code, the common practice of treating laminar to turbulent flow transition over a non-slip surface is somewhat arbitrary by either treating the entire flow as turbulent or forcing the flow to undergo transition at given trip locations in the computational domain. In this study, the possibility of using the PAB3D code, standard k-epsilon turbulence model, and the Girimaji explicit algebraic stresses model to mimic natural laminar to turbulent flow transition was explored. The sensitivity of flow transition with respect to two limiters in the standard k-epsilon turbulence model was examined using a flat plate and a 6:1 aspect ratio prolate spheroid for our computations. For the flat plate, a systematic dependence of transition Reynolds number on background turbulence intensity was found. For the prolate spheroid, the transition patterns in the three-dimensional boundary layer at different flow conditions were sensitive to the free stream turbulence viscosity limit, the reference Reynolds number and the angle of attack, but not to background turbulence intensity below a certain threshold value. The computed results showed encouraging agreements with the experimental measurements at the corresponding geometry and flow conditions.

MapReduce Based Parallel Neural Networks in Enabling Large Scale Machine Learning

PubMed Central

Yang, Jie; Huang, Yuan; Xu, Lixiong; Li, Siguang; Qi, Man

2015-01-01

Artificial neural networks (ANNs) have been widely used in pattern recognition and classification applications. However, ANNs are notably slow in computation especially when the size of data is large. Nowadays, big data has received a momentum from both industry and academia. To fulfill the potentials of ANNs for big data applications, the computation process must be speeded up. For this purpose, this paper parallelizes neural networks based on MapReduce, which has become a major computing model to facilitate data intensive applications. Three data intensive scenarios are considered in the parallelization process in terms of the volume of classification data, the size of the training data, and the number of neurons in the neural network. The performance of the parallelized neural networks is evaluated in an experimental MapReduce computer cluster from the aspects of accuracy in classification and efficiency in computation. PMID:26681933

MapReduce Based Parallel Neural Networks in Enabling Large Scale Machine Learning.

PubMed

Liu, Yang; Yang, Jie; Huang, Yuan; Xu, Lixiong; Li, Siguang; Qi, Man

2015-01-01

Artificial neural networks (ANNs) have been widely used in pattern recognition and classification applications. However, ANNs are notably slow in computation especially when the size of data is large. Nowadays, big data has received a momentum from both industry and academia. To fulfill the potentials of ANNs for big data applications, the computation process must be speeded up. For this purpose, this paper parallelizes neural networks based on MapReduce, which has become a major computing model to facilitate data intensive applications. Three data intensive scenarios are considered in the parallelization process in terms of the volume of classification data, the size of the training data, and the number of neurons in the neural network. The performance of the parallelized neural networks is evaluated in an experimental MapReduce computer cluster from the aspects of accuracy in classification and efficiency in computation.

Modeling the probability distribution of peak discharge for infiltrating hillslopes

NASA Astrophysics Data System (ADS)

Baiamonte, Giorgio; Singh, Vijay P.

2017-07-01

Hillslope response plays a fundamental role in the prediction of peak discharge at the basin outlet. The peak discharge for the critical duration of rainfall and its probability distribution are needed for designing urban infrastructure facilities. This study derives the probability distribution, denoted as GABS model, by coupling three models: (1) the Green-Ampt model for computing infiltration, (2) the kinematic wave model for computing discharge hydrograph from the hillslope, and (3) the intensity-duration-frequency (IDF) model for computing design rainfall intensity. The Hortonian mechanism for runoff generation is employed for computing the surface runoff hydrograph. Since the antecedent soil moisture condition (ASMC) significantly affects the rate of infiltration, its effect on the probability distribution of peak discharge is investigated. Application to a watershed in Sicily, Italy, shows that with the increase of probability, the expected effect of ASMC to increase the maximum discharge diminishes. Only for low values of probability, the critical duration of rainfall is influenced by ASMC, whereas its effect on the peak discharge seems to be less for any probability. For a set of parameters, the derived probability distribution of peak discharge seems to be fitted by the gamma distribution well. Finally, an application to a small watershed, with the aim to test the possibility to arrange in advance the rational runoff coefficient tables to be used for the rational method, and a comparison between peak discharges obtained by the GABS model with those measured in an experimental flume for a loamy-sand soil were carried out.

Hot prominence detected in the core of a coronal mass ejection. II. Analysis of the C III line detected by SOHO/UVCS

NASA Astrophysics Data System (ADS)

Jejčič, S.; Susino, R.; Heinzel, P.; Dzifčáková, E.; Bemporad, A.; Anzer, U.

2017-11-01

Context. We study the physics of erupting prominences in the core of coronal mass ejections (CMEs) and present a continuation of a previous analysis. Aims: We determine the kinetic temperature and microturbulent velocity of an erupting prominence embedded in the core of a CME that occurred on August 2, 2000 using the Ultraviolet Coronagraph and Spectrometer observations (UVCS) on board the Solar and Heliospheric Observatory (SOHO) simultaneously in the hydrogen Lα and C III lines. We develop the non-LTE (departures from the local thermodynamic equilibrium - LTE) spectral diagnostics based on Lα and Lβ measured integrated intensities to derive other physical quantities of the hot erupting prominence. Based on this, we synthesize the C III line intensity to compare it with observations. Methods: Our method is based on non-LTE modeling of eruptive prominences. We used a general non-LTE radiative-transfer code only for optically thin prominence points because optically thick points do not allow the direct determination of the kinetic temperature and microturbulence from the line profiles. The input parameters of the code were the kinetic temperature and microturbulent velocity derived from the Lα and C III line widths, as well as the integrated intensity of the Lα and Lβ lines. The code runs in three loops to compute the radial flow velocity, electron density, and effective thickness as the best fit to the Lα and Lβ integrated intensities within the accuracy defined by the absolute radiometric calibration of UVCS data. Results: We analyzed 39 observational points along the whole erupting prominence because for these points we found a solution for the kinetic temperature and microturbulent velocity. For these points we ran the non-LTE code to determine best-fit models. All models with τ0(Lα) ≤ 0.3 and τ0(C III) ≤ 0.3 were analyzed further, for which we computed the integrated intensity of the C III line using a two-level atom. The best agreement between computed and observed integrated intensity led to 30 optically thin points along the prominence. The results are presented as histograms of the kinetic temperature, microturbulent velocity, effective thickness, radial flow velocity, electron density, and gas pressure. We also show the relation between the microturbulence and kinetic temperature together with a scatter plot of computed versus observed C III integrated intensities and the ratio of the computed to observed C III integrated intensities versus kinetic temperature. Conclusions: The erupting prominence embedded in the CME is relatively hot with a low electron density, a wide range of effective thicknesses, a rather narrow range of radial flow velocities, and a microturbulence of about 25 km s-1. This analysis shows a disagreement between observed and synthetic intensities of the C III line, the reason for which most probably is that photoionization is neglected in calculations of the ionization equilibrium. Alternatively, the disagreement might be due to non-equilibrium processes.

On a 3-D singularity element for computation of combined mode stress intensities

NASA Technical Reports Server (NTRS)

Atluri, S. N.; Kathiresan, K.

1976-01-01

A special three-dimensional singularity element is developed for the computation of combined modes 1, 2, and 3 stress intensity factors, which vary along an arbitrarily curved crack front in three dimensional linear elastic fracture problems. The finite element method is based on a displacement-hybrid finite element model, based on a modified variational principle of potential energy, with arbitrary element interior displacements, interelement boundary displacements, and element boundary tractions as variables. The special crack-front element used in this analysis contains the square root singularity in strains and stresses, where the stress-intensity factors K(1), K(2), and K(3) are quadratically variable along the crack front and are solved directly along with the unknown nodal displacements.

Computational physics of the mind

NASA Astrophysics Data System (ADS)

Duch, Włodzisław

1996-08-01

In the XIX century and earlier physicists such as Newton, Mayer, Hooke, Helmholtz and Mach were actively engaged in the research on psychophysics, trying to relate psychological sensations to intensities of physical stimuli. Computational physics allows to simulate complex neural processes giving a chance to answer not only the original psychophysical questions but also to create models of the mind. In this paper several approaches relevant to modeling of the mind are outlined. Since direct modeling of the brain functions is rather limited due to the complexity of such models a number of approximations is introduced. The path from the brain, or computational neurosciences, to the mind, or cognitive sciences, is sketched, with emphasis on higher cognitive functions such as memory and consciousness. No fundamental problems in understanding of the mind seem to arise. From a computational point of view realistic models require massively parallel architectures.

The anomalous demagnetization behaviour of chondritic meteorites

NASA Astrophysics Data System (ADS)

Morden, S. J.

1992-06-01

Alternating field (AF) demagnetization of chondritic samples often shows anomalous results such as large directional and intensity changes; 'saw-tooth' intensity vs. demagnetizing field curves are also prevalent. An attempt to explain this behaviour is presented, using a computer model in which individual 'mineral grains' can be 'magnetized' in a variety of different ways. A simulated demagnetization can then be carried out to examine the results. It was found that the experimental behaviour of chondrites can be successfully mimicked by loading the computer model with a series of randomly orientated and sized vectors. The parameters of the model can be changed to reflect different trends seen in experimental data. Many published results can be modelled using this method. A known magnetic mineralogy can be modelled, and an unknown mineralogy deduced from AF demagnetization curves. Only by comparing data from mutually orientated samples can true stable regions for palaeointensity measurements be identified, calling into question some previous estimates of field strength from meteorites.

Computer Modeling of High-Intensity Cs-Sputter Ion Sources

NASA Astrophysics Data System (ADS)

Brown, T. A.; Roberts, M. L.; Southon, J. R.

The grid-point mesh program NEDLab has been used to computer model the interior of the high-intensity Cs-sputter source used in routine operations at the Center for Accelerator Mass Spectrometry (CAMS), with the goal of improving negative ion output. NEDLab has several features that are important to realistic modeling of such sources. First, space-charge effects are incorporated in the calculations through an automated ion-trajectories/Poissonelectric-fields successive-iteration process. Second, space charge distributions can be averaged over successive iterations to suppress model instabilities. Third, space charge constraints on ion emission from surfaces can be incorporate under Child's Law based algorithms. Fourth, the energy of ions emitted from a surface can be randomly chosen from within a thermal energy distribution. And finally, ions can be emitted from a surface at randomized angles The results of our modeling effort indicate that significant modification of the interior geometry of the source will double Cs+ ion production from our spherical ionizer and produce a significant increase in negative ion output from the source.

Communication and well-being outcomes of a hybrid service delivery model of intensive impairment-based treatment for aphasia in the hospital setting: a pilot study.

PubMed

Wenke, Rachel; Cardell, Elizabeth; Lawrie, Melissa; Gunning, Dana

2018-06-01

This pilot study aimed to evaluate the effects of an intensive hybrid service delivery model (i.e., combining face-to-face individual, computer and group therapy) on communication and well-being for people with aphasia (PWA) in the hospital setting. The study explored two different intensities of the hybrid model, 4 h/week (Hybrid-4) and 8 h/week (Hybrid-8) both for 8 weeks. Participants ranging from 1 month to 5 years post-onset were allocated using matched-pair randomisation to receive either Hybrid-4 (n = 5) or Hybrid-8 (n = 4) and assessed using a comprehensive language battery by a blinded assessor, as well as selected activity, participation and well-being measures before, immediately after and 4-week post-treatment. All participants in Hybrid-4 and three out of four participants in Hybrid-8 demonstrated clinically significant improvement to measures of language impairment immediately post-treatment, with the majority also demonstrating maintenance effects 4-week post-treatment. Clinically significant improvements to activity, participation and well-being measures were also observed across participants in both groups. Findings support the potential benefit of employing an intensive hybrid service model and suggest that both 4 and 8 h per week of impairment-based treatment for 8 weeks may result in improvements in communication and well-being for some PWA across different stages of recovery. Implications for rehabilitation The present findings help bridge the gap between what evidence suggests is effective intensity of rehabilitation for aphasia and what can be practically delivered in real-world hospital settings. Findings support the potential clinical value of employing a hybrid service model (using computer, group and individual therapy) to deliver intensive rehabilitation to people with aphasia in the hospital setting, and suggest that clinically significant improvements to communication and well-being can result when the model is delivered at either 4 or 8 h per week. The current study highlights that people with aphasia in the early stages of aphasia recovery can potentially benefit from intensive impairment-based hybrid models of intervention.

The intensity dependence of lesion position shift during focused ultrasound surgery.

PubMed

Meaney, P M; Cahill, M D; ter Haar, G R

2000-03-01

Knowledge of the spatial distribution of intensity loss from an ultrasonic beam is critical for predicting lesion formation in focused ultrasound (US) surgery (FUS). To date, most models have used linear propagation models to predict intensity profiles required to compute the temporally varying temperature distributions used to compute thermal dose contours. These are used to predict the extent of thermal damage. However, these simulations fail to describe adequately the abnormal lesion formation behaviour observed during ex vivo experiments in cases for which the transducer drive levels are varied over a wide range. In such experiments, the extent of thermal damage has been observed to move significantly closer to the transducer with increased transducer drive levels than would be predicted using linear-propagation models. The first set of simulations described herein use the KZK (Khokhlov-Zabolotskaya-Kuznetsov) nonlinear propagation model with the parabolic approximation for highly focused US waves to demonstrate that both the peak intensity and the lesion positions do, indeed, move closer to the transducer. This illustrates that, for accurate modelling of heating during FUS, nonlinear effects should be considered. Additionally, a first order approximation has been employed that attempts to account for the abnormal heat deposition distributions that accompany high transducer drive level FUS exposures where cavitation and boiling may be present. The results of these simulations are presented. It is suggested that this type of approach may be a useful tool in understanding thermal damage mechanisms.

DDDAMS-based Urban Surveillance and Crowd Control via UAVs and UGVs

DTIC Science & Technology

2015-12-04

for crowd dynamics modeling by incorporating multi-resolution data, where a grid-based method is used to model crowd motion with UAVs’ low -resolution...information and more computational intensive (and time-consuming). Given that the deployment of fidelity selection results in simulation faces computational... low fidelity information FOV y (A) DR x (A) DR y (A) Not detected high fidelity information Table 1: Parameters for UAV and UGV for their detection

Architecture and Programming Models for High Performance Intensive Computation

DTIC Science & Technology

2016-06-29

Applications Systems and Large-Scale-Big-Data & Large-Scale-Big-Computing (DDDAS- LS ). ICCS 2015, June 2015. Reykjavk, Ice- land. 2. Bo YT, Wang P, Guo ZL...The Mahali project,” Communications Magazine , vol. 52, pp. 111–133, Aug 2014. 14 DISTRIBUTION A: Distribution approved for public release. Response ID

Active Subspace Methods for Data-Intensive Inverse Problems

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

Wang, Qiqi

2017-04-27

The project has developed theory and computational tools to exploit active subspaces to reduce the dimension in statistical calibration problems. This dimension reduction enables MCMC methods to calibrate otherwise intractable models. The same theoretical and computational tools can also reduce the measurement dimension for calibration problems that use large stores of data.

Thermal Convection on an Irradiated Target

NASA Astrophysics Data System (ADS)

Mehmedagic, Igbal; Thangam, Siva

2016-11-01

The present work involves the computational modeling of metallic targets subject to steady and high intensity heat flux. The ablation and associated fluid dynamics when metallic surfaces are exposed to high intensity laser fluence at normal atmospheric conditions is modelled. The incident energy from the laser is partly absorbed and partly reflected by the surface during ablation and subsequent vaporization of the melt. Computational findings based on effective representation and prediction of the heat transfer, melting and vaporization of the targeting material as well as plume formation and expansion are presented and discussed in the context of various ablation mechanisms, variable thermo-physical and optical properties, plume expansion and surface geometry. The energy distribution during the process between the bulk and vapor phase strongly depends on optical and thermodynamic properties of the irradiated material, radiation wavelength, and laser intensity. The relevance of the findings to various manufacturing processes as well as for the development of protective shields is discussed. Funded in part by U. S. Army ARDEC, Picatinny Arsenal, NJ.

Reverse time migration by Krylov subspace reduced order modeling

NASA Astrophysics Data System (ADS)

Basir, Hadi Mahdavi; Javaherian, Abdolrahim; Shomali, Zaher Hossein; Firouz-Abadi, Roohollah Dehghani; Gholamy, Shaban Ali

2018-04-01

Imaging is a key step in seismic data processing. To date, a myriad of advanced pre-stack depth migration approaches have been developed; however, reverse time migration (RTM) is still considered as the high-end imaging algorithm. The main limitations associated with the performance cost of reverse time migration are the intensive computation of the forward and backward simulations, time consumption, and memory allocation related to imaging condition. Based on the reduced order modeling, we proposed an algorithm, which can be adapted to all the aforementioned factors. Our proposed method benefit from Krylov subspaces method to compute certain mode shapes of the velocity model computed by as an orthogonal base of reduced order modeling. Reverse time migration by reduced order modeling is helpful concerning the highly parallel computation and strongly reduces the memory requirement of reverse time migration. The synthetic model results showed that suggested method can decrease the computational costs of reverse time migration by several orders of magnitudes, compared with reverse time migration by finite element method.

The Virtual Earthquake and Seismology Research Community e-science environment in Europe (VERCE) FP7-INFRA-2011-2 project

NASA Astrophysics Data System (ADS)

Vilotte, J.-P.; Atkinson, M.; Michelini, A.; Igel, H.; van Eck, T.

2012-04-01

Increasingly dense seismic and geodetic networks are continuously transmitting a growing wealth of data from around the world. The multi-use of these data leaded the seismological community to pioneer globally distributed open-access data infrastructures, standard services and formats, e.g., the Federation of Digital Seismic Networks (FDSN) and the European Integrated Data Archives (EIDA). Our ability to acquire observational data outpaces our ability to manage, analyze and model them. Research in seismology is today facing a fundamental paradigm shift. Enabling advanced data-intensive analysis and modeling applications challenges conventional storage, computation and communication models and requires a new holistic approach. It is instrumental to exploit the cornucopia of data, and to guarantee optimal operation and design of the high-cost monitoring facilities. The strategy of VERCE is driven by the needs of the seismological data-intensive applications in data analysis and modeling. It aims to provide a comprehensive architecture and framework adapted to the scale and the diversity of those applications, and integrating the data infrastructures with Grid, Cloud and HPC infrastructures. It will allow prototyping solutions for new use cases as they emerge within the European Plate Observatory Systems (EPOS), the ESFRI initiative of the solid Earth community. Computational seismology, and information management, is increasingly revolving around massive amounts of data that stem from: (1) the flood of data from the observational systems; (2) the flood of data from large-scale simulations and inversions; (3) the ability to economically store petabytes of data online; (4) the evolving Internet and Data-aware computing capabilities. As data-intensive applications are rapidly increasing in scale and complexity, they require additional services-oriented architectures offering a virtualization-based flexibility for complex and re-usable workflows. Scientific information management poses computer science challenges: acquisition, organization, query and visualization tasks scale almost linearly with the data volumes. Commonly used FTP-GREP metaphor allows today to scan gigabyte-sized datasets but will not work for scanning terabyte-sized continuous waveform datasets. New data analysis and modeling methods, exploiting the signal coherence within dense network arrays, are nonlinear. Pair-algorithms on N points scale as N2. Wave form inversion and stochastic simulations raise computing and data handling challenges These applications are unfeasible for tera-scale datasets without new parallel algorithms that use near-linear processing, storage and bandwidth, and that can exploit new computing paradigms enabled by the intersection of several technologies (HPC, parallel scalable database crawler, data-aware HPC). This issues will be discussed based on a number of core pilot data-intensive applications and use cases retained in VERCE. This core applications are related to: (1) data processing and data analysis methods based on correlation techniques; (2) cpu-intensive applications such as large-scale simulation of synthetic waveforms in complex earth systems, and full waveform inversion and tomography. We shall analyze their workflow and data flow, and their requirements for a new service-oriented architecture and a data-aware platform with services and tools. Finally, we will outline the importance of a new collaborative environment between seismology and computer science, together with the need for the emergence and the recognition of 'research technologists' mastering the evolving data-aware technologies and the data-intensive research goals in seismology.

A Stratified Acoustic Model Accounting for Phase Shifts for Underwater Acoustic Networks

PubMed Central

Wang, Ping; Zhang, Lin; Li, Victor O. K.

2013-01-01

Accurate acoustic channel models are critical for the study of underwater acoustic networks. Existing models include physics-based models and empirical approximation models. The former enjoy good accuracy, but incur heavy computational load, rendering them impractical in large networks. On the other hand, the latter are computationally inexpensive but inaccurate since they do not account for the complex effects of boundary reflection losses, the multi-path phenomenon and ray bending in the stratified ocean medium. In this paper, we propose a Stratified Acoustic Model (SAM) based on frequency-independent geometrical ray tracing, accounting for each ray's phase shift during the propagation. It is a feasible channel model for large scale underwater acoustic network simulation, allowing us to predict the transmission loss with much lower computational complexity than the traditional physics-based models. The accuracy of the model is validated via comparisons with the experimental measurements in two different oceans. Satisfactory agreements with the measurements and with other computationally intensive classical physics-based models are demonstrated. PMID:23669708

A stratified acoustic model accounting for phase shifts for underwater acoustic networks.

PubMed

Wang, Ping; Zhang, Lin; Li, Victor O K

2013-05-13

Accurate acoustic channel models are critical for the study of underwater acoustic networks. Existing models include physics-based models and empirical approximation models. The former enjoy good accuracy, but incur heavy computational load, rendering them impractical in large networks. On the other hand, the latter are computationally inexpensive but inaccurate since they do not account for the complex effects of boundary reflection losses, the multi-path phenomenon and ray bending in the stratified ocean medium. In this paper, we propose a Stratified Acoustic Model (SAM) based on frequency-independent geometrical ray tracing, accounting for each ray's phase shift during the propagation. It is a feasible channel model for large scale underwater acoustic network simulation, allowing us to predict the transmission loss with much lower computational complexity than the traditional physics-based models. The accuracy of the model is validated via comparisons with the experimental measurements in two different oceans. Satisfactory agreements with the measurements and with other computationally intensive classical physics-based models are demonstrated.

Developing Subdomain Allocation Algorithms Based on Spatial and Communicational Constraints to Accelerate Dust Storm Simulation

PubMed Central

Gui, Zhipeng; Yu, Manzhu; Yang, Chaowei; Jiang, Yunfeng; Chen, Songqing; Xia, Jizhe; Huang, Qunying; Liu, Kai; Li, Zhenlong; Hassan, Mohammed Anowarul; Jin, Baoxuan

2016-01-01

Dust storm has serious disastrous impacts on environment, human health, and assets. The developments and applications of dust storm models have contributed significantly to better understand and predict the distribution, intensity and structure of dust storms. However, dust storm simulation is a data and computing intensive process. To improve the computing performance, high performance computing has been widely adopted by dividing the entire study area into multiple subdomains and allocating each subdomain on different computing nodes in a parallel fashion. Inappropriate allocation may introduce imbalanced task loads and unnecessary communications among computing nodes. Therefore, allocation is a key factor that may impact the efficiency of parallel process. An allocation algorithm is expected to consider the computing cost and communication cost for each computing node to minimize total execution time and reduce overall communication cost for the entire simulation. This research introduces three algorithms to optimize the allocation by considering the spatial and communicational constraints: 1) an Integer Linear Programming (ILP) based algorithm from combinational optimization perspective; 2) a K-Means and Kernighan-Lin combined heuristic algorithm (K&K) integrating geometric and coordinate-free methods by merging local and global partitioning; 3) an automatic seeded region growing based geometric and local partitioning algorithm (ASRG). The performance and effectiveness of the three algorithms are compared based on different factors. Further, we adopt the K&K algorithm as the demonstrated algorithm for the experiment of dust model simulation with the non-hydrostatic mesoscale model (NMM-dust) and compared the performance with the MPI default sequential allocation. The results demonstrate that K&K method significantly improves the simulation performance with better subdomain allocation. This method can also be adopted for other relevant atmospheric and numerical modeling. PMID:27044039

Simulation Based Exploration of Critical Zone Dynamics in Intensively Managed Landscapes

NASA Astrophysics Data System (ADS)

Kumar, P.

2017-12-01

The advent of high-resolution measurements of topographic and (vertical) vegetation features using areal LiDAR are enabling us to resolve micro-scale ( 1m) landscape structural characteristics over large areas. Availability of hyperspectral measurements is further augmenting these LiDAR data by enabling the biogeochemical characterization of vegetation and soils at unprecedented spatial resolutions ( 1-10m). Such data have opened up novel opportunities for modeling Critical Zone processes and exploring questions that were not possible before. We show how an integrated 3-D model at 1m grid resolution can enable us to resolve micro-topographic and ecological dynamics and their control on hydrologic and biogeochemical processes over large areas. We address the computational challenge of such detailed modeling by exploiting hybrid CPU and GPU computing technologies. We show results of moisture, biogeochemical, and vegetation dynamics from studies in the Critical Zone Observatory for Intensively managed Landscapes (IMLCZO) in the Midwestern United States.

Advancing Cyberinfrastructure to support high resolution water resources modeling

NASA Astrophysics Data System (ADS)

Tarboton, D. G.; Ogden, F. L.; Jones, N.; Horsburgh, J. S.

2012-12-01

Addressing the problem of how the availability and quality of water resources at large scales are sensitive to climate variability, watershed alterations and management activities requires computational resources that combine data from multiple sources and support integrated modeling. Related cyberinfrastructure challenges include: 1) how can we best structure data and computer models to address this scientific problem through the use of high-performance and data-intensive computing, and 2) how can we do this in a way that discipline scientists without extensive computational and algorithmic knowledge and experience can take advantage of advances in cyberinfrastructure? This presentation will describe a new system called CI-WATER that is being developed to address these challenges and advance high resolution water resources modeling in the Western U.S. We are building on existing tools that enable collaboration to develop model and data interfaces that link integrated system models running within an HPC environment to multiple data sources. Our goal is to enhance the use of computational simulation and data-intensive modeling to better understand water resources. Addressing water resource problems in the Western U.S. requires simulation of natural and engineered systems, as well as representation of legal (water rights) and institutional constraints alongside the representation of physical processes. We are establishing data services to represent the engineered infrastructure and legal and institutional systems in a way that they can be used with high resolution multi-physics watershed modeling at high spatial resolution. These services will enable incorporation of location-specific information on water management infrastructure and systems into the assessment of regional water availability in the face of growing demands, uncertain future meteorological forcings, and existing prior-appropriations water rights. This presentation will discuss the informatics challenges involved with data management and easy-to-use access to high performance computing being tackled in this project.

Regional scale landslide risk assessment with a dynamic physical model - development, application and uncertainty analysis

NASA Astrophysics Data System (ADS)

Luna, Byron Quan; Vidar Vangelsten, Bjørn; Liu, Zhongqiang; Eidsvig, Unni; Nadim, Farrokh

2013-04-01

Landslide risk must be assessed at the appropriate scale in order to allow effective risk management. At the moment, few deterministic models exist that can do all the computations required for a complete landslide risk assessment at a regional scale. This arises from the difficulty to precisely define the location and volume of the released mass and from the inability of the models to compute the displacement with a large amount of individual initiation areas (computationally exhaustive). This paper presents a medium-scale, dynamic physical model for rapid mass movements in mountainous and volcanic areas. The deterministic nature of the approach makes it possible to apply it to other sites since it considers the frictional equilibrium conditions for the initiation process, the rheological resistance of the displaced flow for the run-out process and fragility curve that links intensity to economic loss for each building. The model takes into account the triggering effect of an earthquake, intense rainfall and a combination of both (spatial and temporal). The run-out module of the model considers the flow as a 2-D continuum medium solving the equations of mass balance and momentum conservation. The model is embedded in an open source environment geographical information system (GIS), it is computationally efficient and it is transparent (understandable and comprehensible) for the end-user. The model was applied to a virtual region, assessing landslide hazard, vulnerability and risk. A Monte Carlo simulation scheme was applied to quantify, propagate and communicate the effects of uncertainty in input parameters on the final results. In this technique, the input distributions are recreated through sampling and the failure criteria are calculated for each stochastic realisation of the site properties. The model is able to identify the released volumes of the critical slopes and the areas threatened by the run-out intensity. The obtained final outcome is the estimation of individual building damage and total economic risk. The research leading to these results has received funding from the European Community's Seventh Framework Programme [FP7/2007-2013] under grant agreement No 265138 New Multi-HAzard and MulTi-RIsK Assessment MethodS for Europe (MATRIX).

Theoretical study of interactions of BSA protein in a NaCl aqueous solution

NASA Astrophysics Data System (ADS)

Pellicane, Giuseppe; Cavero, Miguel

2013-03-01

Bovine Serum Albumine (BSA) aqueous solutions in the presence of NaCl are investigated for different protein concentrations and low to intermediate ionic strengths. Protein interactions are modeled via a charge-screened colloidal model, in which the range of the potential is determined by the Debye-Hückel constant. We use Monte Carlo computer simulations to calculate the structure factor, and assume an oblate ellipsoidal form factor for BSA. The theoretical scattered intensities are found in good agreement with the experimental small angle X-ray scattering intensities available in the literature. The performance of well-known integral equation closures to the Ornstein-Zernike equation, namely the mean spherical approximation, the Percus-Yevick, and the hypernetted chain equations, is also assessed with respect to computer simulation.

Analytical modeling and feasibility study of a multi-GPU cloud-based server (MGCS) framework for non-voxel-based dose calculations.

PubMed

Neylon, J; Min, Y; Kupelian, P; Low, D A; Santhanam, A

2017-04-01

In this paper, a multi-GPU cloud-based server (MGCS) framework is presented for dose calculations, exploring the feasibility of remote computing power for parallelization and acceleration of computationally and time intensive radiotherapy tasks in moving toward online adaptive therapies. An analytical model was developed to estimate theoretical MGCS performance acceleration and intelligently determine workload distribution. Numerical studies were performed with a computing setup of 14 GPUs distributed over 4 servers interconnected by a 1 Gigabits per second (Gbps) network. Inter-process communication methods were optimized to facilitate resource distribution and minimize data transfers over the server interconnect. The analytically predicted computation time predicted matched experimentally observations within 1-5 %. MGCS performance approached a theoretical limit of acceleration proportional to the number of GPUs utilized when computational tasks far outweighed memory operations. The MGCS implementation reproduced ground-truth dose computations with negligible differences, by distributing the work among several processes and implemented optimization strategies. The results showed that a cloud-based computation engine was a feasible solution for enabling clinics to make use of fast dose calculations for advanced treatment planning and adaptive radiotherapy. The cloud-based system was able to exceed the performance of a local machine even for optimized calculations, and provided significant acceleration for computationally intensive tasks. Such a framework can provide access to advanced technology and computational methods to many clinics, providing an avenue for standardization across institutions without the requirements of purchasing, maintaining, and continually updating hardware.

Robust incremental compensation of the light attenuation with depth in 3D fluorescence microscopy.

PubMed

Kervrann, C; Legland, D; Pardini, L

2004-06-01

Summary Fluorescent signal intensities from confocal laser scanning microscopes (CLSM) suffer from several distortions inherent to the method. Namely, layers which lie deeper within the specimen are relatively dark due to absorption and scattering of both excitation and fluorescent light, photobleaching and/or other factors. Because of these effects, a quantitative analysis of images is not always possible without correction. Under certain assumptions, the decay of intensities can be estimated and used for a partial depth intensity correction. In this paper we propose an original robust incremental method for compensating the attenuation of intensity signals. Most previous correction methods are more or less empirical and based on fitting a decreasing parametric function to the section mean intensity curve computed by summing all pixel values in each section. The fitted curve is then used for the calculation of correction factors for each section and a new compensated sections series is computed. However, these methods do not perfectly correct the images. Hence, the algorithm we propose for the automatic correction of intensities relies on robust estimation, which automatically ignores pixels where measurements deviate from the decay model. It is based on techniques adopted from the computer vision literature for image motion estimation. The resulting algorithm is used to correct volumes acquired in CLSM. An implementation of such a restoration filter is discussed and examples of successful restorations are given.

Time-Dependent Modeling of Underwater Explosions by Convolving Similitude Source with Bandlimited Impulse from the CASS/GRAB Model

DTIC Science & Technology

2015-06-30

401) 832-8689 Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std. Z39-18 i TABLE OF CONTENTS Section Page LIST OF ILLUSTRATIONS...calculated with a high degree of accuracy—leading to intensive computational calculations and long computational times when dealing with range-depth fields...be obtained using similitude analysis; it allows the comparison of differing explosive weights and provides the means to scale the pressure, energy

A Probability Model of Decompression Sickness at 4.3 Psia after Exercise Prebreathe

NASA Technical Reports Server (NTRS)

Conkin, Johnny; Gernhardt, Michael L.; Powell, Michael R.; Pollock, Neal

2004-01-01

Exercise PB can reduce the risk of decompression sickness on ascent to 4.3 psia when performed at the proper intensity and duration. Data are from seven tests. PB times ranged from 90 to 150 min. High intensity, short duration dual-cycle ergometry was done during the PB. This was done alone, or combined with intermittent low intensity exercise or periods of rest for the remaining PB. Nonambulating men and women performed light exercise from a semi-recumbent position at 4.3 psia for four hrs. The Research Model with age tested the probability that DCS increases with advancing age. The NASA Model with gender hypothesized that the probability of DCS increases if gender is female. Accounting for exercise and rest during PB with a variable half-time compartment for computed tissue N2 pressure advances our probability modeling of hypobaric DCS. Both models show that a small increase in exercise intensity during PB reduces the risk of DCS, and a larger increase in exercise intensity dramatically reduces risk. These models support the hypothesis that aerobic fitness is an important consideration for the risk of hypobaric DCS when exercise is performed during the PB.

Multiscale hidden Markov models for photon-limited imaging

NASA Astrophysics Data System (ADS)

Nowak, Robert D.

1999-06-01

Photon-limited image analysis is often hindered by low signal-to-noise ratios. A novel Bayesian multiscale modeling and analysis method is developed in this paper to assist in these challenging situations. In addition to providing a very natural and useful framework for modeling an d processing images, Bayesian multiscale analysis is often much less computationally demanding compared to classical Markov random field models. This paper focuses on a probabilistic graph model called the multiscale hidden Markov model (MHMM), which captures the key inter-scale dependencies present in natural image intensities. The MHMM framework presented here is specifically designed for photon-limited imagin applications involving Poisson statistics, and applications to image intensity analysis are examined.

Computer Modeling of the Structure and Spectra of Fluorescent Proteins

PubMed Central

Grigorenko, B.L.; Savitsky, A.P.

2009-01-01

Fluorescent proteins from the family of green fluorescent proteins are intensively used as biomarkers in living systems. The chromophore group based on the hydroxybenzylidene-imidazoline molecule, which is formed in nature from three amino-acid residues inside the protein globule and well shielded from external media, is responsible for light absorption and fluorescence. Along with the intense experimental studies of the properties of fluorescent proteins and their chromophores by biochemical, X-ray, and spectroscopic tools, in recent years, computer modeling has been used to characterize their properties and spectra. We present in this review the most interesting results of the molecular modeling of the structural parameters and optical and vibrational spectra of the chromophorecontaining domains of fluorescent proteins by methods of quantum chemistry, molecular dynamics, and combined quantum-mechanical-molecular-mechanical approaches. The main emphasis is on the correlation of theoretical and experimental data and on the predictive power of modeling, which may be useful for creating new, efficient biomarkers. PMID:22649601

Acoustic intensity calculations for axisymmetrically modeled fluid regions

NASA Technical Reports Server (NTRS)

Hambric, Stephen A.; Everstine, Gordon C.

1992-01-01

An algorithm for calculating acoustic intensities from a time harmonic pressure field in an axisymmetric fluid region is presented. Acoustic pressures are computed in a mesh of NASTRAN triangular finite elements of revolution (TRIAAX) using an analogy between the scalar wave equation and elasticity equations. Acoustic intensities are then calculated from pressures and pressure derivatives taken over the mesh of TRIAAX elements. Intensities are displayed as vectors indicating the directions and magnitudes of energy flow at all mesh points in the acoustic field. A prolate spheroidal shell is modeled with axisymmetric shell elements (CONEAX) and submerged in a fluid region of TRIAAX elements. The model is analyzed to illustrate the acoustic intensity method and the usefulness of energy flow paths in the understanding of the response of fluid-structure interaction problems. The structural-acoustic analogy used is summarized for completeness. This study uncovered a NASTRAN limitation involving numerical precision issues in the CONEAX stiffness calculation causing large errors in the system matrices for nearly cylindrical cones.

Modeling the Proton Radiation Belt With Van Allen Probes Relativistic Electron-Proton Telescope Data

NASA Technical Reports Server (NTRS)

Kanekal, S. G.; Li, X.; Baker, D. N.; Selesnick, R. S.; Hoxie, V. C.

2018-01-01

An empirical model of the proton radiation belt is constructed from data taken during 2013-2017 by the Relativistic Electron-Proton Telescopes on the Van Allen Probes satellites. The model intensity is a function of time, kinetic energy in the range 18-600 megaelectronvolts, equatorial pitch angle, and L shell of proton guiding centers. Data are selected, on the basis of energy deposits in each of the nine silicon detectors, to reduce background caused by hard proton energy spectra at low L. Instrument response functions are computed by Monte Carlo integration, using simulated proton paths through a simplified structural model, to account for energy loss in shielding material for protons outside the nominal field of view. Overlap of energy channels, their wide angular response, and changing satellite orientation require the model dependencies on all three independent variables be determined simultaneously. This is done by least squares minimization with a customized steepest descent algorithm. Model uncertainty accounts for statistical data error and systematic error in the simulated instrument response. A proton energy spectrum is also computed from data taken during the 8 January 2014 solar event, to illustrate methods for the simpler case of an isotropic and homogeneous model distribution. Radiation belt and solar proton results are compared to intensities computed with a simplified, on-axis response that can provide a good approximation under limited circumstances.

Modeling the Proton Radiation Belt With Van Allen Probes Relativistic Electron-Proton Telescope Data

NASA Astrophysics Data System (ADS)

Selesnick, R. S.; Baker, D. N.; Kanekal, S. G.; Hoxie, V. C.; Li, X.

2018-01-01

An empirical model of the proton radiation belt is constructed from data taken during 2013-2017 by the Relativistic Electron-Proton Telescopes on the Van Allen Probes satellites. The model intensity is a function of time, kinetic energy in the range 18-600 MeV, equatorial pitch angle, and L shell of proton guiding centers. Data are selected, on the basis of energy deposits in each of the nine silicon detectors, to reduce background caused by hard proton energy spectra at low L. Instrument response functions are computed by Monte Carlo integration, using simulated proton paths through a simplified structural model, to account for energy loss in shielding material for protons outside the nominal field of view. Overlap of energy channels, their wide angular response, and changing satellite orientation require the model dependencies on all three independent variables be determined simultaneously. This is done by least squares minimization with a customized steepest descent algorithm. Model uncertainty accounts for statistical data error and systematic error in the simulated instrument response. A proton energy spectrum is also computed from data taken during the 8 January 2014 solar event, to illustrate methods for the simpler case of an isotropic and homogeneous model distribution. Radiation belt and solar proton results are compared to intensities computed with a simplified, on-axis response that can provide a good approximation under limited circumstances.

The Adoption of Grid Computing Technology by Organizations: A Quantitative Study Using Technology Acceptance Model

ERIC Educational Resources Information Center

Udoh, Emmanuel E.

2010-01-01

Advances in grid technology have enabled some organizations to harness enormous computational power on demand. However, the prediction of widespread adoption of the grid technology has not materialized despite the obvious grid advantages. This situation has encouraged intense efforts to close the research gap in the grid adoption process. In this…

Kinetic Modeling of Next-Generation High-Energy, High-Intensity Laser-Ion Accelerators

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

Albright, Brian James; Yin, Lin; Stark, David James

One of the long-standing problems in the community is the question of how we can model “next-generation” laser-ion acceleration in a computationally tractable way. A new particle tracking capability in the LANL VPIC kinetic plasma modeling code has enabled us to solve this long-standing problem

Final Report on Institutional Computing Project s15_hilaserion, “Kinetic Modeling of Next-Generation High-Energy, High-Intensity Laser-Ion Accelerators as an Enabling Capability”

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

Albright, Brian James; Yin, Lin; Stark, David James

This proposal sought of order 1M core-hours of Institutional Computing time intended to enable computing by a new LANL Postdoc (David Stark) working under LDRD ER project 20160472ER (PI: Lin Yin) on laser-ion acceleration. The project was “off-cycle,” initiating in June of 2016 with a postdoc hire.

Computational Modeling of Ablation on an Irradiated Target

NASA Astrophysics Data System (ADS)

Mehmedagic, Igbal; Thangam, Siva

2017-11-01

Computational modeling of pulsed nanosecond laser interaction with an irradiated metallic target is presented. The model formulation involves ablation of the metallic target irradiated by pulsed high intensity laser at normal atmospheric conditions. Computational findings based on effective representation and prediction of the heat transfer, melting and vaporization of the targeting material as well as plume formation and expansion are presented along with its relevance for the development of protective shields. In this context, the available results for a representative irradiation from 1064 nm laser pulse is used to analyze various ablation mechanisms, variable thermo-physical and optical properties, plume expansion and surface geometry. Funded in part by U. S. Army ARDEC, Picatinny Arsenal, NJ.

On the possibility of non-invasive multilayer temperature estimation using soft-computing methods.

PubMed

Teixeira, C A; Pereira, W C A; Ruano, A E; Ruano, M Graça

2010-01-01

This work reports original results on the possibility of non-invasive temperature estimation (NITE) in a multilayered phantom by applying soft-computing methods. The existence of reliable non-invasive temperature estimator models would improve the security and efficacy of thermal therapies. These points would lead to a broader acceptance of this kind of therapies. Several approaches based on medical imaging technologies were proposed, magnetic resonance imaging (MRI) being appointed as the only one to achieve the acceptable temperature resolutions for hyperthermia purposes. However, MRI intrinsic characteristics (e.g., high instrumentation cost) lead us to use backscattered ultrasound (BSU). Among the different BSU features, temporal echo-shifts have received a major attention. These shifts are due to changes of speed-of-sound and expansion of the medium. The originality of this work involves two aspects: the estimator model itself is original (based on soft-computing methods) and the application to temperature estimation in a three-layer phantom is also not reported in literature. In this work a three-layer (non-homogeneous) phantom was developed. The two external layers were composed of (in % of weight): 86.5% degassed water, 11% glycerin and 2.5% agar-agar. The intermediate layer was obtained by adding graphite powder in the amount of 2% of the water weight to the above composition. The phantom was developed to have attenuation and speed-of-sound similar to in vivo muscle, according to the literature. BSU signals were collected and cumulative temporal echo-shifts computed. These shifts and the past temperature values were then considered as possible estimators inputs. A soft-computing methodology was applied to look for appropriate multilayered temperature estimators. The methodology involves radial-basis functions neural networks (RBFNN) with structure optimized by the multi-objective genetic algorithm (MOGA). In this work 40 operating conditions were considered, i.e. five 5-mm spaced spatial points and eight therapeutic intensities (I(SATA)): 0.3, 0.5, 0.7, 1.0, 1.3, 1.5, 1.7 and 2.0W/cm(2). Models were trained and selected to estimate temperature at only four intensities, then during the validation phase, the best-fitted models were analyzed in data collected at the eight intensities. This procedure leads to a more realistic evaluation of the generalisation level of the best-obtained structures. At the end of the identification phase, 82 (preferable) estimator models were achieved. The majority of them present an average maximum absolute error (MAE) inferior to 0.5 degrees C. The best-fitted estimator presents a MAE of only 0.4 degrees C for both the 40 operating conditions. This means that the gold-standard maximum error (0.5 degrees C) pointed for hyperthermia was fulfilled independently of the intensity and spatial position considered, showing the improved generalisation capacity of the identified estimator models. As the majority of the preferable estimator models, the best one presents 6 inputs and 11 neurons. In addition to the appropriate error performance, the estimator models present also a reduced computational complexity and then the possibility to be applied in real-time. A non-invasive temperature estimation model, based on soft-computing technique, was proposed for a three-layered phantom. The best-achieved estimator models presented an appropriate error performance regardless of the spatial point considered (inside or at the interface of the layers) and of the intensity applied. Other methodologies published so far, estimate temperature only in homogeneous media. The main drawback of the proposed methodology is the necessity of a-priory knowledge of the temperature behavior. Data used for training and optimisation should be representative, i.e., they should cover all possible physical situations of the estimation environment.

Effect of molecular anisotropy on the intensity and degree of polarization of light scattered from model atmospheres

NASA Technical Reports Server (NTRS)

Bahethi, O. P.; Fraser, R. S.

1975-01-01

Computations of the intensity, flux, degree of polarization, and the positions of neutral points are presented for models of the terrestrial gaseous and hazy atmospheres by incorporating the molecular anisotropy due to air in the Rayleigh scattering optical thickness and phase matrix. Molecular anisotropy causes significant changes in the intensity, flux and the degree of polarization of the scattered light. The positions of neutral points do not change significantly. When the Rayleigh scattering optical thickness is kept constant and the molecular anisotropy factor is included only in the Rayleigh phase matrix, the flux does not change and the intensity and positions of neutron points change by a small amount. The changes in the degree of polarization are still significant.

Evaluating the Psychometric Characteristics of Generated Multiple-Choice Test Items

ERIC Educational Resources Information Center

Gierl, Mark J.; Lai, Hollis; Pugh, Debra; Touchie, Claire; Boulais, André-Philippe; De Champlain, André

2016-01-01

Item development is a time- and resource-intensive process. Automatic item generation integrates cognitive modeling with computer technology to systematically generate test items. To date, however, items generated using cognitive modeling procedures have received limited use in operational testing situations. As a result, the psychometric…

Predicting adenocarcinoma recurrence using computational texture models of nodule components in lung CT

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

Depeursinge, Adrien, E-mail: adrien.depeursinge@hevs.ch; Yanagawa, Masahiro; Leung, Ann N.

Purpose: To investigate the importance of presurgical computed tomography (CT) intensity and texture information from ground-glass opacities (GGO) and solid nodule components for the prediction of adenocarcinoma recurrence. Methods: For this study, 101 patients with surgically resected stage I adenocarcinoma were selected. During the follow-up period, 17 patients had disease recurrence with six associated cancer-related deaths. GGO and solid tumor components were delineated on presurgical CT scans by a radiologist. Computational texture models of GGO and solid regions were built using linear combinations of steerable Riesz wavelets learned with linear support vector machines (SVMs). Unlike other traditional texture attributes, themore » proposed texture models are designed to encode local image scales and directions that are specific to GGO and solid tissue. The responses of the locally steered models were used as texture attributes and compared to the responses of unaligned Riesz wavelets. The texture attributes were combined with CT intensities to predict tumor recurrence and patient hazard according to disease-free survival (DFS) time. Two families of predictive models were compared: LASSO and SVMs, and their survival counterparts: Cox-LASSO and survival SVMs. Results: The best-performing predictive model of patient hazard was associated with a concordance index (C-index) of 0.81 ± 0.02 and was based on the combination of the steered models and CT intensities with survival SVMs. The same feature group and the LASSO model yielded the highest area under the receiver operating characteristic curve (AUC) of 0.8 ± 0.01 for predicting tumor recurrence, although no statistically significant difference was found when compared to using intensity features solely. For all models, the performance was found to be significantly higher when image attributes were based on the solid components solely versus using the entire tumors (p < 3.08 × 10{sup −5}). Conclusions: This study constitutes a novel perspective on how to interpret imaging information from CT examinations by suggesting that most of the information related to adenocarcinoma aggressiveness is related to the intensity and morphological properties of solid components of the tumor. The prediction of adenocarcinoma relapse was found to have low specificity but very high sensitivity. Our results could be useful in clinical practice to identify patients for which no recurrence is expected with a very high confidence using a presurgical CT scan only. It also provided an accurate estimation of the risk of recurrence after a given duration t from surgical resection (i.e., C-index = 0.81 ± 0.02)« less

Scalable Parameter Estimation for Genome-Scale Biochemical Reaction Networks

PubMed Central

Kaltenbacher, Barbara; Hasenauer, Jan

2017-01-01

Mechanistic mathematical modeling of biochemical reaction networks using ordinary differential equation (ODE) models has improved our understanding of small- and medium-scale biological processes. While the same should in principle hold for large- and genome-scale processes, the computational methods for the analysis of ODE models which describe hundreds or thousands of biochemical species and reactions are missing so far. While individual simulations are feasible, the inference of the model parameters from experimental data is computationally too intensive. In this manuscript, we evaluate adjoint sensitivity analysis for parameter estimation in large scale biochemical reaction networks. We present the approach for time-discrete measurement and compare it to state-of-the-art methods used in systems and computational biology. Our comparison reveals a significantly improved computational efficiency and a superior scalability of adjoint sensitivity analysis. The computational complexity is effectively independent of the number of parameters, enabling the analysis of large- and genome-scale models. Our study of a comprehensive kinetic model of ErbB signaling shows that parameter estimation using adjoint sensitivity analysis requires a fraction of the computation time of established methods. The proposed method will facilitate mechanistic modeling of genome-scale cellular processes, as required in the age of omics. PMID:28114351

A general-purpose computer program for studying ultrasonic beam patterns generated with acoustic lenses

NASA Technical Reports Server (NTRS)

Roberti, Dino; Ludwig, Reinhold; Looft, Fred J.

1988-01-01

A 3-D computer model of a piston radiator with lenses for focusing and defocusing is presented. To achieve high-resolution imaging, the frequency of the transmitted and received ultrasound must be as high as 10 MHz. Current ultrasonic transducers produce an extremely narrow beam at these high frequencies and thus are not appropriate for imaging schemes such as synthetic-aperture focus techniques (SAFT). Consequently, a numerical analysis program has been developed to determine field intensity patterns that are radiated from ultrasonic transducers with lenses. Lens shapes are described and the field intensities are numerically predicted and compared with experimental results.

THE EFFECT OF A DYNAMIC INNER HELIOSHEATH THICKNESS ON COSMIC-RAY MODULATION

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

Manuel, R.; Ferreira, S. E. S.; Potgieter, M. S., E-mail: rexmanuel@live.com

2015-02-01

The time-dependent modulation of galactic cosmic rays in the heliosphere is studied over different polarity cycles by computing 2.5 GV proton intensities using a two-dimensional, time-dependent modulation model. By incorporating recent theoretical advances in the relevant transport parameters in the model, we showed in previous work that this approach gave realistic computed intensities over a solar cycle. New in this work is that a time dependence of the solar wind termination shock (TS) position is implemented in our model to study the effect of a dynamic inner heliosheath thickness (the region between the TS and heliopause) on the solar modulationmore » of galactic cosmic rays. The study reveals that changes in the inner heliosheath thickness, arising from a time-dependent shock position, does affect cosmic-ray intensities everywhere in the heliosphere over a solar cycle, with the smallest effect in the innermost heliosphere. A time-dependent TS position causes a phase difference between the solar activity periods and the corresponding intensity periods. The maximum intensities in response to a solar minimum activity period are found to be dependent on the time-dependent TS profile. It is found that changing the width of the inner heliosheath with time over a solar cycle can shift the time of when the maximum or minimum cosmic-ray intensities occur at various distances throughout the heliosphere, but more significantly in the outer heliosphere. The time-dependent extent of the inner heliosheath, as affected by solar activity conditions, is thus an additional time-dependent factor to be considered in the long-term modulation of cosmic rays.« less

Realistic Modeling of Interaction of Quiet-Sun Magnetic Fields with the Chromosphere

NASA Technical Reports Server (NTRS)

Kitiashvili, I. N.; Kosovichev, A. G.; Mansour, N. N.; Wray, A. A.

2017-01-01

High­-resolution observations and 3D MHD simulations reveal intense interaction between the convection zone dynamics and the solar atmosphere on subarcsecond scales. To investigate processes of the dynamical coupling and energy exchange between the subsurface layers and the chromosphere we perform 3D radiative MHD modeling for a computational domain that includes the upper convection zone and the chromosphere, and investigate the structure and dynamics for different intensity of the photospheric magnetic flux. For comparison with observations, the simulation models have been used to calculate synthetic Stokes profiles of various spectral lines. The results show intense energy exchange through small­-scale magnetized vortex tubes rooted below the photosphere, which provide extra heating of the chromosphere, initiate shock waves, and small­-scale eruptions.

Use of information and communication technology (ICT) and perceived health in adolescence: the role of sleeping habits and waking-time tiredness.

PubMed

Punamäki, Raija-Leena; Wallenius, Marjut; Nygård, Clase-Håkan; Saarni, Lea; Rimpelä, Arja

2007-08-01

The first aim for this paper was to examine gender and age differences in the intensity of usage of information and communication technology (ICT: computer for digital playing, writing and e-mailing and communication, and Internet surfing, and mobile phone). Second, we modelled the possible mediating role of sleeping habits and waking-time tiredness in the association between ICT usage and perceived health (health complaints, musculoskeletal symptoms, health status). The participants were 7292 Finns aged 12, 14, 16 and 18 years responding to a postal enquiry (response rate 70%). The results showed that boys played digital games and used Internet more often than girls, whose mobile phone usage was more intensive. Structural equation model analyses substantiated the mediating hypothesis: intensive ICT-usage was associated with poor perceived health particularly or only when it negatively affected sleeping habits, which in turn was associated with increased waking-time tiredness. The associations were gender-specific especially among older adolescents (16- and 18-year olds). Intensive computer usage forms a risk for boys', and intensive mobile phone usage for girls' perceived health through the mediating links. Girls were vulnerable to the negative consequences of intensive mobile phone usage, as it associated with perceived health complaints and musculoskeletal symptoms both directly and through deteriorated sleep and increased waking-time tiredness. The results of gender-specific ICT usage and vulnerability are discussed as reflecting gendered psychophysiological, psychological and social developmental demands.

Development of a voltage-dependent current noise algorithm for conductance-based stochastic modelling of auditory nerve fibres.

PubMed

Badenhorst, Werner; Hanekom, Tania; Hanekom, Johan J

2016-12-01

This study presents the development of an alternative noise current term and novel voltage-dependent current noise algorithm for conductance-based stochastic auditory nerve fibre (ANF) models. ANFs are known to have significant variance in threshold stimulus which affects temporal characteristics such as latency. This variance is primarily caused by the stochastic behaviour or microscopic fluctuations of the node of Ranvier's voltage-dependent sodium channels of which the intensity is a function of membrane voltage. Though easy to implement and low in computational cost, existing current noise models have two deficiencies: it is independent of membrane voltage, and it is unable to inherently determine the noise intensity required to produce in vivo measured discharge probability functions. The proposed algorithm overcomes these deficiencies while maintaining its low computational cost and ease of implementation compared to other conductance and Markovian-based stochastic models. The algorithm is applied to a Hodgkin-Huxley-based compartmental cat ANF model and validated via comparison of the threshold probability and latency distributions to measured cat ANF data. Simulation results show the algorithm's adherence to in vivo stochastic fibre characteristics such as an exponential relationship between the membrane noise and transmembrane voltage, a negative linear relationship between the log of the relative spread of the discharge probability and the log of the fibre diameter and a decrease in latency with an increase in stimulus intensity.

Specialized computer architectures for computational aerodynamics

NASA Technical Reports Server (NTRS)

Stevenson, D. K.

1978-01-01

In recent years, computational fluid dynamics has made significant progress in modelling aerodynamic phenomena. Currently, one of the major barriers to future development lies in the compute-intensive nature of the numerical formulations and the relative high cost of performing these computations on commercially available general purpose computers, a cost high with respect to dollar expenditure and/or elapsed time. Today's computing technology will support a program designed to create specialized computing facilities to be dedicated to the important problems of computational aerodynamics. One of the still unresolved questions is the organization of the computing components in such a facility. The characteristics of fluid dynamic problems which will have significant impact on the choice of computer architecture for a specialized facility are reviewed.

A Planar Quasi-Static Constraint Mode Tire Model

DTIC Science & Technology

2015-07-10

strikes a balance between simple tire models that lack the fidelity to make accurate chassis load predictions and computationally intensive models that...strikes a balance between heuristic tire models (such as a linear point-follower) that lack the fidelity to make accurate chassis load predictions...UNCLASSIFIED: Distribution Statement A. Cleared for public release A PLANAR QUASI-STATIC CONSTRAINT MODE TIRE MODEL Rui Maa John B. Ferris

Cognitive Tools for Assessment and Learning in a High Information Flow Environment.

ERIC Educational Resources Information Center

Lajoie, Susanne P.; Azevedo, Roger; Fleiszer, David M.

1998-01-01

Describes the development of a simulation-based intelligent tutoring system for nurses working in a surgical intensive care unit. Highlights include situative learning theories and models of instruction, modeling expertise, complex decision making, linking theories of learning to the design of computer-based learning environments, cognitive task…

Adaptive Control Of Remote Manipulator

NASA Technical Reports Server (NTRS)

Seraji, Homayoun

1989-01-01

Robotic control system causes remote manipulator to follow closely reference trajectory in Cartesian reference frame in work space, without resort to computationally intensive mathematical model of robot dynamics and without knowledge of robot and load parameters. System, derived from linear multivariable theory, uses relatively simple feedforward and feedback controllers with model-reference adaptive control.

Characteristic of laser diode beam propagation through a collimating lens.

PubMed

Xu, Qiang; Han, Yiping; Cui, Zhiwei

2010-01-20

A mathematical model of a laser diode beam propagating through a collimating lens is presented. Wave propagation beyond the paraxial approximation is studied. The phase delay of the laser diode wave in passing through the lens is analyzed in detail. The propagation optical field after the lens is obtained from the diffraction integral by the stationary phase method. The model is employed to predict the light intensity at various beam cross sections, and the computed intensity distributions are in a good agreement with the corresponding measurements.

Framework Resources Multiply Computing Power

NASA Technical Reports Server (NTRS)

2010-01-01

As an early proponent of grid computing, Ames Research Center awarded Small Business Innovation Research (SBIR) funding to 3DGeo Development Inc., of Santa Clara, California, (now FusionGeo Inc., of The Woodlands, Texas) to demonstrate a virtual computer environment that linked geographically dispersed computer systems over the Internet to help solve large computational problems. By adding to an existing product, FusionGeo enabled access to resources for calculation- or data-intensive applications whenever and wherever they were needed. Commercially available as Accelerated Imaging and Modeling, the product is used by oil companies and seismic service companies, which require large processing and data storage capacities.

On the Modeling and Management of Cloud Data Analytics

NASA Astrophysics Data System (ADS)

Castillo, Claris; Tantawi, Asser; Steinder, Malgorzata; Pacifici, Giovanni

A new era is dawning where vast amount of data is subjected to intensive analysis in a cloud computing environment. Over the years, data about a myriad of things, ranging from user clicks to galaxies, have been accumulated, and continue to be collected, on storage media. The increasing availability of such data, along with the abundant supply of compute power and the urge to create useful knowledge, gave rise to a new data analytics paradigm in which data is subjected to intensive analysis, and additional data is created in the process. Meanwhile, a new cloud computing environment has emerged where seemingly limitless compute and storage resources are being provided to host computation and data for multiple users through virtualization technologies. Such a cloud environment is becoming the home for data analytics. Consequently, providing good performance at run-time to data analytics workload is an important issue for cloud management. In this paper, we provide an overview of the data analytics and cloud environment landscapes, and investigate the performance management issues related to running data analytics in the cloud. In particular, we focus on topics such as workload characterization, profiling analytics applications and their pattern of data usage, cloud resource allocation, placement of computation and data and their dynamic migration in the cloud, and performance prediction. In solving such management problems one relies on various run-time analytic models. We discuss approaches for modeling and optimizing the dynamic data analytics workload in the cloud environment. All along, we use the Map-Reduce paradigm as an illustration of data analytics.

Modern Computational Techniques for the HMMER Sequence Analysis

PubMed Central

2013-01-01

This paper focuses on the latest research and critical reviews on modern computing architectures, software and hardware accelerated algorithms for bioinformatics data analysis with an emphasis on one of the most important sequence analysis applications—hidden Markov models (HMM). We show the detailed performance comparison of sequence analysis tools on various computing platforms recently developed in the bioinformatics society. The characteristics of the sequence analysis, such as data and compute-intensive natures, make it very attractive to optimize and parallelize by using both traditional software approach and innovated hardware acceleration technologies. PMID:25937944

Computational approaches to computational aero-acoustics

NASA Technical Reports Server (NTRS)

Hardin, Jay C.

1996-01-01

The various techniques by which the goal of computational aeroacoustics (the calculation and noise prediction of a fluctuating fluid flow) may be achieved are reviewed. The governing equations for compressible fluid flow are presented. The direct numerical simulation approach is shown to be computationally intensive for high Reynolds number viscous flows. Therefore, other approaches, such as the acoustic analogy, vortex models and various perturbation techniques that aim to break the analysis into a viscous part and an acoustic part are presented. The choice of the approach is shown to be problem dependent.

Tutorial: Asteroseismic Stellar Modelling with AIMS

NASA Astrophysics Data System (ADS)

Lund, Mikkel N.; Reese, Daniel R.

The goal of aims (Asteroseismic Inference on a Massive Scale) is to estimate stellar parameters and credible intervals/error bars in a Bayesian manner from a set of asteroseismic frequency data and so-called classical constraints. To achieve reliable parameter estimates and computational efficiency, it searches through a grid of pre-computed models using an MCMC algorithm—interpolation within the grid of models is performed by first tessellating the grid using a Delaunay triangulation and then doing a linear barycentric interpolation on matching simplexes. Inputs for the modelling consist of individual frequencies from peak-bagging, which can be complemented with classical spectroscopic constraints. aims is mostly written in Python with a modular structure to facilitate contributions from the community. Only a few computationally intensive parts have been rewritten in Fortran in order to speed up calculations.

Dynamic visual attention: motion direction versus motion magnitude

NASA Astrophysics Data System (ADS)

Bur, A.; Wurtz, P.; Müri, R. M.; Hügli, H.

2008-02-01

Defined as an attentive process in the context of visual sequences, dynamic visual attention refers to the selection of the most informative parts of video sequence. This paper investigates the contribution of motion in dynamic visual attention, and specifically compares computer models designed with the motion component expressed either as the speed magnitude or as the speed vector. Several computer models, including static features (color, intensity and orientation) and motion features (magnitude and vector) are considered. Qualitative and quantitative evaluations are performed by comparing the computer model output with human saliency maps obtained experimentally from eye movement recordings. The model suitability is evaluated in various situations (synthetic and real sequences, acquired with fixed and moving camera perspective), showing advantages and inconveniences of each method as well as preferred domain of application.

A Computational Framework for Realistic Retina Modeling.

PubMed

Martínez-Cañada, Pablo; Morillas, Christian; Pino, Begoña; Ros, Eduardo; Pelayo, Francisco

2016-11-01

Computational simulations of the retina have led to valuable insights about the biophysics of its neuronal activity and processing principles. A great number of retina models have been proposed to reproduce the behavioral diversity of the different visual processing pathways. While many of these models share common computational stages, previous efforts have been more focused on fitting specific retina functions rather than generalizing them beyond a particular model. Here, we define a set of computational retinal microcircuits that can be used as basic building blocks for the modeling of different retina mechanisms. To validate the hypothesis that similar processing structures may be repeatedly found in different retina functions, we implemented a series of retina models simply by combining these computational retinal microcircuits. Accuracy of the retina models for capturing neural behavior was assessed by fitting published electrophysiological recordings that characterize some of the best-known phenomena observed in the retina: adaptation to the mean light intensity and temporal contrast, and differential motion sensitivity. The retinal microcircuits are part of a new software platform for efficient computational retina modeling from single-cell to large-scale levels. It includes an interface with spiking neural networks that allows simulation of the spiking response of ganglion cells and integration with models of higher visual areas.

Hue-saturation-density (HSD) model for stain recognition in digital images from transmitted light microscopy.

PubMed

van Der Laak, J A; Pahlplatz, M M; Hanselaar, A G; de Wilde, P C

2000-04-01

Transmitted light microscopy is used in pathology to examine stained tissues. Digital image analysis is gaining importance as a means to quantify alterations in tissues. A prerequisite for accurate and reproducible quantification is the possibility to recognise stains in a standardised manner, independently of variations in the staining density. The usefulness of three colour models was studied using data from computer simulations and experimental data from an immuno-doublestained tissue section. Direct use of the three intensities obtained by a colour camera results in the red-green-blue (RGB) model. By decoupling the intensity from the RGB data, the hue-saturation-intensity (HSI) model is obtained. However, the major part of the variation in perceived intensities in transmitted light microscopy is caused by variations in staining density. Therefore, the hue-saturation-density (HSD) transform was defined as the RGB to HSI transform, applied to optical density values rather than intensities for the individual RGB channels. In the RGB model, the mixture of chromatic and intensity information hampers standardisation of stain recognition. In the HSI model, mixtures of stains that could be distinguished from other stains in the RGB model could not be separated. The HSD model enabled all possible distinctions in a two-dimensional, standardised data space. In the RGB model, standardised recognition is only possible by using complex and time-consuming algorithms. The HSI model is not suitable for stain recognition in transmitted light microscopy. The newly derived HSD model was found superior to the existing models for this purpose. Copyright 2000 Wiley-Liss, Inc.

Functional dissociation of stimulus intensity encoding and predictive coding of pain in the insula

PubMed Central

Geuter, Stephan; Boll, Sabrina; Eippert, Falk; Büchel, Christian

2017-01-01

The computational principles by which the brain creates a painful experience from nociception are still unknown. Classic theories suggest that cortical regions either reflect stimulus intensity or additive effects of intensity and expectations, respectively. By contrast, predictive coding theories provide a unified framework explaining how perception is shaped by the integration of beliefs about the world with mismatches resulting from the comparison of these beliefs against sensory input. Using functional magnetic resonance imaging during a probabilistic heat pain paradigm, we investigated which computations underlie pain perception. Skin conductance, pupil dilation, and anterior insula responses to cued pain stimuli strictly followed the response patterns hypothesized by the predictive coding model, whereas posterior insula encoded stimulus intensity. This novel functional dissociation of pain processing within the insula together with previously observed alterations in chronic pain offer a novel interpretation of aberrant pain processing as disturbed weighting of predictions and prediction errors. DOI: http://dx.doi.org/10.7554/eLife.24770.001 PMID:28524817

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

Nikolic, R J

This month's issue has the following articles: (1) Dawn of a New Era of Scientific Discovery - Commentary by Edward I. Moses; (2) At the Frontiers of Fundamental Science Research - Collaborators from national laboratories, universities, and international organizations are using the National Ignition Facility to probe key fundamental science questions; (3) Livermore Responds to Crisis in Post-Earthquake Japan - More than 70 Laboratory scientists provided round-the-clock expertise in radionuclide analysis and atmospheric dispersion modeling as part of the nation's support to Japan following the March 2011 earthquake and nuclear accident; (4) A Comprehensive Resource for Modeling, Simulation, and Experimentsmore » - A new Web-based resource called MIDAS is a central repository for material properties, experimental data, and computer models; and (5) Finding Data Needles in Gigabit Haystacks - Livermore computer scientists have developed a novel computer architecture based on 'persistent' memory to ease data-intensive computations.« less

Parent-child attitude congruence on type and intensity of physical activity: testing multiple mediators of sedentary behavior in older children.

PubMed

Anderson, Cheryl B; Hughes, Sheryl O; Fuemmeler, Bernard F

2009-07-01

This study examined parent-child attitudes on value of specific types and intensities of physical activity, which may explain gender differences in child activity, and evaluated physical activity as a mechanism to reduce time spent in sedentary behaviors. A community sample of 681 parents and 433 children (mean age 9.9 years) reported attitudes on importance of vigorous and moderate intensity team and individually performed sports/activities, as well as household chores. Separate structural models (LISREL 8.7) for girls and boys tested whether parental attitudes were related to child TV and computer via child attitudes, sport team participation, and physical activity, controlling for demographic factors. Child 7-day physical activity, sport teams, weekly TV, computer. Parent-child attitude congruence was more prevalent among boys, and attitudes varied by ethnicity, parent education, and number of children. Positive parent-child attitudes for vigorous team sports were related to increased team participation and physical activity, as well as reduced TV and computer in boys and girls. Value of moderate intensity household chores, such as cleaning house and doing laundry, was related to decreased team participation and increased TV in boys. Only organized team sports, not general physical activity, was related to reduced TV and computer. Results support parents' role in socializing children's achievement task values, affecting child activity by transferring specific attitudes. Value of vigorous intensity sports provided the most benefits to activity and reduction of sedentary behavior, while valuing household chores had unexpected negative effects.

Cone-beam x-ray luminescence computed tomography based on x-ray absorption dosage

NASA Astrophysics Data System (ADS)

Liu, Tianshuai; Rong, Junyan; Gao, Peng; Zhang, Wenli; Liu, Wenlei; Zhang, Yuanke; Lu, Hongbing

2018-02-01

With the advances of x-ray excitable nanophosphors, x-ray luminescence computed tomography (XLCT) has become a promising hybrid imaging modality. In particular, a cone-beam XLCT (CB-XLCT) system has demonstrated its potential in in vivo imaging with the advantage of fast imaging speed over other XLCT systems. Currently, the imaging models of most XLCT systems assume that nanophosphors emit light based on the intensity distribution of x-ray within the object, not completely reflecting the nature of the x-ray excitation process. To improve the imaging quality of CB-XLCT, an imaging model that adopts an excitation model of nanophosphors based on x-ray absorption dosage is proposed in this study. To solve the ill-posed inverse problem, a reconstruction algorithm that combines the adaptive Tikhonov regularization method with the imaging model is implemented for CB-XLCT reconstruction. Numerical simulations and phantom experiments indicate that compared with the traditional forward model based on x-ray intensity, the proposed dose-based model could improve the image quality of CB-XLCT significantly in terms of target shape, localization accuracy, and image contrast. In addition, the proposed model behaves better in distinguishing closer targets, demonstrating its advantage in improving spatial resolution.

A Model-based Framework for Risk Assessment in Human-Computer Controlled Systems

NASA Technical Reports Server (NTRS)

Hatanaka, Iwao

2000-01-01

The rapid growth of computer technology and innovation has played a significant role in the rise of computer automation of human tasks in modem production systems across all industries. Although the rationale for automation has been to eliminate "human error" or to relieve humans from manual repetitive tasks, various computer-related hazards and accidents have emerged as a direct result of increased system complexity attributed to computer automation. The risk assessment techniques utilized for electromechanical systems are not suitable for today's software-intensive systems or complex human-computer controlled systems. This thesis will propose a new systemic model-based framework for analyzing risk in safety-critical systems where both computers and humans are controlling safety-critical functions. A new systems accident model will be developed based upon modem systems theory and human cognitive processes to better characterize system accidents, the role of human operators, and the influence of software in its direct control of significant system functions. Better risk assessments will then be achievable through the application of this new framework to complex human-computer controlled systems.

Accelerated Adaptive MGS Phase Retrieval

NASA Technical Reports Server (NTRS)

Lam, Raymond K.; Ohara, Catherine M.; Green, Joseph J.; Bikkannavar, Siddarayappa A.; Basinger, Scott A.; Redding, David C.; Shi, Fang

2011-01-01

The Modified Gerchberg-Saxton (MGS) algorithm is an image-based wavefront-sensing method that can turn any science instrument focal plane into a wavefront sensor. MGS characterizes optical systems by estimating the wavefront errors in the exit pupil using only intensity images of a star or other point source of light. This innovative implementation of MGS significantly accelerates the MGS phase retrieval algorithm by using stream-processing hardware on conventional graphics cards. Stream processing is a relatively new, yet powerful, paradigm to allow parallel processing of certain applications that apply single instructions to multiple data (SIMD). These stream processors are designed specifically to support large-scale parallel computing on a single graphics chip. Computationally intensive algorithms, such as the Fast Fourier Transform (FFT), are particularly well suited for this computing environment. This high-speed version of MGS exploits commercially available hardware to accomplish the same objective in a fraction of the original time. The exploit involves performing matrix calculations in nVidia graphic cards. The graphical processor unit (GPU) is hardware that is specialized for computationally intensive, highly parallel computation. From the software perspective, a parallel programming model is used, called CUDA, to transparently scale multicore parallelism in hardware. This technology gives computationally intensive applications access to the processing power of the nVidia GPUs through a C/C++ programming interface. The AAMGS (Accelerated Adaptive MGS) software takes advantage of these advanced technologies, to accelerate the optical phase error characterization. With a single PC that contains four nVidia GTX-280 graphic cards, the new implementation can process four images simultaneously to produce a JWST (James Webb Space Telescope) wavefront measurement 60 times faster than the previous code.

Computing Science and Statistics: Proceedings of the Symposium on the Interface: Computationally Intensive Methods in Statistics (20th) Held in Fairfax, Virginia on April 20-23, 1988

DTIC Science & Technology

1989-03-15

essence of the idea ycessible mtho forunrtandig eth- Tis tand thP ra) rm guh ide propet oaes nd d of e aessie meh bsd fooesadng asymptoti- isthe for s...network? This of Such empirical parametric model fitting is of course depends heavily on the class of net- course the essence of much of applied...smaller problems is the essence of graphical modeling. A model hy- attributes. Let e be the discrete joint outcome space for those N pergraph, g

QPROT: Statistical method for testing differential expression using protein-level intensity data in label-free quantitative proteomics.

PubMed

Choi, Hyungwon; Kim, Sinae; Fermin, Damian; Tsou, Chih-Chiang; Nesvizhskii, Alexey I

2015-11-03

We introduce QPROT, a statistical framework and computational tool for differential protein expression analysis using protein intensity data. QPROT is an extension of the QSPEC suite, originally developed for spectral count data, adapted for the analysis using continuously measured protein-level intensity data. QPROT offers a new intensity normalization procedure and model-based differential expression analysis, both of which account for missing data. Determination of differential expression of each protein is based on the standardized Z-statistic based on the posterior distribution of the log fold change parameter, guided by the false discovery rate estimated by a well-known Empirical Bayes method. We evaluated the classification performance of QPROT using the quantification calibration data from the clinical proteomic technology assessment for cancer (CPTAC) study and a recently published Escherichia coli benchmark dataset, with evaluation of FDR accuracy in the latter. QPROT is a statistical framework with computational software tool for comparative quantitative proteomics analysis. It features various extensions of QSPEC method originally built for spectral count data analysis, including probabilistic treatment of missing values in protein intensity data. With the increasing popularity of label-free quantitative proteomics data, the proposed method and accompanying software suite will be immediately useful for many proteomics laboratories. This article is part of a Special Issue entitled: Computational Proteomics. Copyright © 2015 Elsevier B.V. All rights reserved.

Data communication network at the ASRM facility

NASA Astrophysics Data System (ADS)

Moorhead, Robert J., II; Smith, Wayne D.

1993-08-01

This report describes the simulation of the overall communication network structure for the Advanced Solid Rocket Motor (ASRM) facility being built at Yellow Creek near Iuka, Mississippi as of today. The report is compiled using information received from NASA/MSFC, LMSC, AAD, and RUST Inc. As per the information gathered, the overall network structure will have one logical FDDI ring acting as a backbone for the whole complex. The buildings will be grouped into two categories viz. manufacturing intensive and manufacturing non-intensive. The manufacturing intensive buildings will be connected via FDDI to the Operational Information System (OIS) in the main computing center in B_1000. The manufacturing non-intensive buildings will be connected by 10BASE-FL to the OIS through the Business Information System (BIS) hub in the main computing center. All the devices inside B_1000 will communicate with the BIS. The workcells will be connected to the Area Supervisory Computers (ASCs) through the nearest manufacturing intensive hub and one of the OIS hubs. Comdisco's Block Oriented Network Simulator (BONeS) has been used to simulate the performance of the network. BONeS models a network topology, traffic, data structures, and protocol functions using a graphical interface. The main aim of the simulations was to evaluate the loading of the OIS, the BIS, and the ASCs, and the network links by the traffic generated by the workstations and workcells throughout the site.

Data communication network at the ASRM facility

NASA Technical Reports Server (NTRS)

Moorhead, Robert J., II; Smith, Wayne D.

1993-01-01

This report describes the simulation of the overall communication network structure for the Advanced Solid Rocket Motor (ASRM) facility being built at Yellow Creek near Iuka, Mississippi as of today. The report is compiled using information received from NASA/MSFC, LMSC, AAD, and RUST Inc. As per the information gathered, the overall network structure will have one logical FDDI ring acting as a backbone for the whole complex. The buildings will be grouped into two categories viz. manufacturing intensive and manufacturing non-intensive. The manufacturing intensive buildings will be connected via FDDI to the Operational Information System (OIS) in the main computing center in B_1000. The manufacturing non-intensive buildings will be connected by 10BASE-FL to the OIS through the Business Information System (BIS) hub in the main computing center. All the devices inside B_1000 will communicate with the BIS. The workcells will be connected to the Area Supervisory Computers (ASCs) through the nearest manufacturing intensive hub and one of the OIS hubs. Comdisco's Block Oriented Network Simulator (BONeS) has been used to simulate the performance of the network. BONeS models a network topology, traffic, data structures, and protocol functions using a graphical interface. The main aim of the simulations was to evaluate the loading of the OIS, the BIS, and the ASCs, and the network links by the traffic generated by the workstations and workcells throughout the site.

A micro-hydrology computation ordering algorithm

NASA Astrophysics Data System (ADS)

Croley, Thomas E.

1980-11-01

Discrete-distributed-parameter models are essential for watershed modelling where practical consideration of spatial variations in watershed properties and inputs is desired. Such modelling is necessary for analysis of detailed hydrologic impacts from management strategies and land-use effects. Trade-offs between model validity and model complexity exist in resolution of the watershed. Once these are determined, the watershed is then broken into sub-areas which each have essentially spatially-uniform properties. Lumped-parameter (micro-hydrology) models are applied to these sub-areas and their outputs are combined through the use of a computation ordering technique, as illustrated by many discrete-distributed-parameter hydrology models. Manual ordering of these computations requires fore-thought, and is tedious, error prone, sometimes storage intensive and least adaptable to changes in watershed resolution. A programmable algorithm for ordering micro-hydrology computations is presented that enables automatic ordering of computations within the computer via an easily understood and easily implemented "node" definition, numbering and coding scheme. This scheme and the algorithm are detailed in logic flow-charts and an example application is presented. Extensions and modifications of the algorithm are easily made for complex geometries or differing microhydrology models. The algorithm is shown to be superior to manual ordering techniques and has potential use in high-resolution studies.

Simulating pad-electrodes with high-definition arrays in transcranial electric stimulation

NASA Astrophysics Data System (ADS)

Kempe, René; Huang, Yu; Parra, Lucas C.

2014-04-01

Objective. Research studies on transcranial electric stimulation, including direct current, often use a computational model to provide guidance on the placing of sponge-electrode pads. However, the expertise and computational resources needed for finite element modeling (FEM) make modeling impractical in a clinical setting. Our objective is to make the exploration of different electrode configurations accessible to practitioners. We provide an efficient tool to estimate current distributions for arbitrary pad configurations while obviating the need for complex simulation software. Approach. To efficiently estimate current distributions for arbitrary pad configurations we propose to simulate pads with an array of high-definition (HD) electrodes and use an efficient linear superposition to then quickly evaluate different electrode configurations. Main results. Numerical results on ten different pad configurations on a normal individual show that electric field intensity simulated with the sampled array deviates from the solutions with pads by only 5% and the locations of peak magnitude fields have a 94% overlap when using a dense array of 336 electrodes. Significance. Computationally intensive FEM modeling of the HD array needs to be performed only once, perhaps on a set of standard heads that can be made available to multiple users. The present results confirm that by using these models one can now quickly and accurately explore and select pad-electrode montages to match a particular clinical need.

Randomized algorithms for high quality treatment planning in volumetric modulated arc therapy

NASA Astrophysics Data System (ADS)

Yang, Yu; Dong, Bin; Wen, Zaiwen

2017-02-01

In recent years, volumetric modulated arc therapy (VMAT) has been becoming a more and more important radiation technique widely used in clinical application for cancer treatment. One of the key problems in VMAT is treatment plan optimization, which is complicated due to the constraints imposed by the involved equipments. In this paper, we consider a model with four major constraints: the bound on the beam intensity, an upper bound on the rate of the change of the beam intensity, the moving speed of leaves of the multi-leaf collimator (MLC) and its directional-convexity. We solve the model by a two-stage algorithm: performing minimization with respect to the shapes of the aperture and the beam intensities alternatively. Specifically, the shapes of the aperture are obtained by a greedy algorithm whose performance is enhanced by random sampling in the leaf pairs with a decremental rate. The beam intensity is optimized using a gradient projection method with non-monotonic line search. We further improve the proposed algorithm by an incremental random importance sampling of the voxels to reduce the computational cost of the energy functional. Numerical simulations on two clinical cancer date sets demonstrate that our method is highly competitive to the state-of-the-art algorithms in terms of both computational time and quality of treatment planning.

Computational Cardiac Anatomy Using MRI

PubMed Central

Beg, Mirza Faisal; Helm, Patrick A.; McVeigh, Elliot; Miller, Michael I.; Winslow, Raimond L.

2005-01-01

Ventricular geometry and fiber orientation may undergo global or local remodeling in cardiac disease. However, there are as yet no mathematical and computational methods for quantifying variation of geometry and fiber orientation or the nature of their remodeling in disease. Toward this goal, a landmark and image intensity-based large deformation diffeomorphic metric mapping (LDDMM) method to transform heart geometry into common coordinates for quantification of shape and form was developed. Two automated landmark placement methods for modeling tissue deformations expected in different cardiac pathologies are presented. The transformations, computed using the combined use of landmarks and image intensities, yields high-registration accuracy of heart anatomies even in the presence of significant variation of cardiac shape and form. Once heart anatomies have been registered, properties of tissue geometry and cardiac fiber orientation in corresponding regions of different hearts may be quantified. PMID:15508155

Computational Pathology to Discriminate Benign from Malignant Intraductal Proliferations of the Breast

PubMed Central

Oh, Eun-Yeong; Lerwill, Melinda F.; Brachtel, Elena F.; Jones, Nicholas C.; Knoblauch, Nicholas W.; Montaser-Kouhsari, Laleh; Johnson, Nicole B.; Rao, Luigi K. F.; Faulkner-Jones, Beverly; Wilbur, David C.; Schnitt, Stuart J.; Beck, Andrew H.

2014-01-01

The categorization of intraductal proliferative lesions of the breast based on routine light microscopic examination of histopathologic sections is in many cases challenging, even for experienced pathologists. The development of computational tools to aid pathologists in the characterization of these lesions would have great diagnostic and clinical value. As a first step to address this issue, we evaluated the ability of computational image analysis to accurately classify DCIS and UDH and to stratify nuclear grade within DCIS. Using 116 breast biopsies diagnosed as DCIS or UDH from the Massachusetts General Hospital (MGH), we developed a computational method to extract 392 features corresponding to the mean and standard deviation in nuclear size and shape, intensity, and texture across 8 color channels. We used L1-regularized logistic regression to build classification models to discriminate DCIS from UDH. The top-performing model contained 22 active features and achieved an AUC of 0.95 in cross-validation on the MGH data-set. We applied this model to an external validation set of 51 breast biopsies diagnosed as DCIS or UDH from the Beth Israel Deaconess Medical Center, and the model achieved an AUC of 0.86. The top-performing model contained active features from all color-spaces and from the three classes of features (morphology, intensity, and texture), suggesting the value of each for prediction. We built models to stratify grade within DCIS and obtained strong performance for stratifying low nuclear grade vs. high nuclear grade DCIS (AUC = 0.98 in cross-validation) with only moderate performance for discriminating low nuclear grade vs. intermediate nuclear grade and intermediate nuclear grade vs. high nuclear grade DCIS (AUC = 0.83 and 0.69, respectively). These data show that computational pathology models can robustly discriminate benign from malignant intraductal proliferative lesions of the breast and may aid pathologists in the diagnosis and classification of these lesions. PMID:25490766

Robust active contour via additive local and global intensity information based on local entropy

NASA Astrophysics Data System (ADS)

Yuan, Shuai; Monkam, Patrice; Zhang, Feng; Luan, Fangjun; Koomson, Ben Alfred

2018-01-01

Active contour-based image segmentation can be a very challenging task due to many factors such as high intensity inhomogeneity, presence of noise, complex shape, weak boundaries objects, and dependence on the position of the initial contour. We propose a level set-based active contour method to segment complex shape objects from images corrupted by noise and high intensity inhomogeneity. The energy function of the proposed method results from combining the global intensity information and local intensity information with some regularization factors. First, the global intensity term is proposed based on a scheme formulation that considers two intensity values for each region instead of one, which outperforms the well-known Chan-Vese model in delineating the image information. Second, the local intensity term is formulated based on local entropy computed considering the distribution of the image brightness and using the generalized Gaussian distribution as the kernel function. Therefore, it can accurately handle high intensity inhomogeneity and noise. Moreover, our model is not dependent on the position occupied by the initial curve. Finally, extensive experiments using various images have been carried out to illustrate the performance of the proposed method.

A comparison of FUV dayglows measured by STSAT-1/FIMS with the AURIC model in a geomagnetic quiet condition

NASA Astrophysics Data System (ADS)

Kam, Hosik; Kim, Yong Ha; Hong, Jun-Seok; Lee, Joon-Chan; Choi, Yeon-Ju; Min, Kyung Wook

2014-09-01

The Korea scientific microsatellite, STSAT-1 (Science and Technology Satellite-1), was launched in 2003 and observed far ultraviolet (FUV) airglow from the upper atmosphere with a Far-ultraviolet IMaging Spectrograph (FIMS) at an altitude of 690 km. The FIMS consists of a dual-band imaging spectrograph of 900-1150 Å (S-band) and 1340-1715 Å (L-band). Limb scanning observations were performed only at the S-band, resulting in intensity profiles of OI 989 Å, OI 1026 Å, NII 1085 Å and NI 1134 Å emission lines near the horizon. We compare these emission intensities with those computed by using a theoretical model, the AURIC (Atmospheric Ultraviolet Radiance Integrated Code). The intensities of the OI 1026 Å, NII 1085 Å and NI 1134 Å emissions measured by using the FIMS are overall consistent with the values computed by using AURIC under the thermospheric and solar activity conditions on August 6, 1984, which is close to the FIMS's observation condition. We find that the FIMS dayglow intensity profiles match reasonably well with AURIC intensity profiles for the MSIS90 oxygen atom density profiles within factors of 0.5 and 2. However, the FIMS intensities of the OI 989 Å line are about 2 ˜ 4 times stronger than the AURIC intensities, which is expected because AURIC does not properly simulate resonance scattering of airglow and solar photons at 989 Å by atomic oxygen in the thermosphere. We also find that the maximum tangential altitudes of the oxygen bearing dayglows (OI 989 Å, OI 1026 Å) are higher than those of the nitrogen-bearing dayglows (NII 1085 Å, NI 1134 Å), which is confirmed by using AURIC model calculations. This is expected because the oxygen atoms are distributed at higher altitudes in the thermosphere than the nitrogen molecules. Validations of the qualities of both the FIMS instrument and the AURIC model indicate that AURIC should be updated with improved thermospheric models and with measured solar FUV spectra for better agreement with the observations. Once the updated AURIC model is available, one can extract valuable information on the densities and compositions of the thermosphere from limb scanning observations with an FUV instrument such as FIMS.

A multidimensional stability model for predicting shallow landslide size and shape across landscapes

Treesearch

David G. Milledge; Dino Bellugi; Jim A. McKean; Alexander L. Densmore; William E. Dietrich

2014-01-01

The size of a shallow landslide is a fundamental control on both its hazard and geomorphic importance. Existing models are either unable to predict landslide size or are computationally intensive such that they cannot practically be applied across landscapes. We derive a model appropriate for natural slopes that is capable of predicting shallow landslide size but...

Computing mammographic density from a multiple regression model constructed with image-acquisition parameters from a full-field digital mammographic unit

PubMed Central

Lu, Lee-Jane W.; Nishino, Thomas K.; Khamapirad, Tuenchit; Grady, James J; Leonard, Morton H.; Brunder, Donald G.

2009-01-01

Breast density (the percentage of fibroglandular tissue in the breast) has been suggested to be a useful surrogate marker for breast cancer risk. It is conventionally measured using screen-film mammographic images by a labor intensive histogram segmentation method (HSM). We have adapted and modified the HSM for measuring breast density from raw digital mammograms acquired by full-field digital mammography. Multiple regression model analyses showed that many of the instrument parameters for acquiring the screening mammograms (e.g. breast compression thickness, radiological thickness, radiation dose, compression force, etc) and image pixel intensity statistics of the imaged breasts were strong predictors of the observed threshold values (model R2=0.93) and %density (R2=0.84). The intra-class correlation coefficient of the %-density for duplicate images was estimated to be 0.80, using the regression model-derived threshold values, and 0.94 if estimated directly from the parameter estimates of the %-density prediction regression model. Therefore, with additional research, these mathematical models could be used to compute breast density objectively, automatically bypassing the HSM step, and could greatly facilitate breast cancer research studies. PMID:17671343

Comprehensive Validation of an Intermittency Transport Model for Transitional Low-Pressure Turbine Flows

NASA Technical Reports Server (NTRS)

Suzen, Y. B.; Huang, P. G.

2005-01-01

A transport equation for the intermittency factor is employed to predict transitional flows under the effects of pressure gradients, freestream turbulence intensities, Reynolds number variations, flow separation and reattachment. and unsteady wake-blade interactions representing diverse operating conditions encountered in low-pressure turbines. The intermittent behaviour of the transitional flows is taken into account and incorporated into computations by modifying the eddy viscosity, Mu(sub t), with the intermittency factor, gamma. Turbulent quantities are predicted by using Menter's two-equation turbulence model (SST). The onset location of transition is obtained from correlations based on boundary-layer momentum thickness, acceleration parameter, and turbulence intensity. The intermittency factor is obtained from a transport model which can produce both the experimentally observed streamwise variation of intermittency and a realistic profile in the cross stream direction. The intermittency transport model is tested and validated against several well documented low pressure turbine experiments ranging from flat plate cases to unsteady wake-blade interaction experiments. Overall, good agreement between the experimental data and computational results is obtained illustrating the predicting capabilities of the model and the current intermittency transport modelling approach for transitional flow simulations.

Copula Models for Sociology: Measures of Dependence and Probabilities for Joint Distributions

ERIC Educational Resources Information Center

Vuolo, Mike

2017-01-01

Often in sociology, researchers are confronted with nonnormal variables whose joint distribution they wish to explore. Yet, assumptions of common measures of dependence can fail or estimating such dependence is computationally intensive. This article presents the copula method for modeling the joint distribution of two random variables, including…

TethysCluster: A comprehensive approach for harnessing cloud resources for hydrologic modeling

NASA Astrophysics Data System (ADS)

Nelson, J.; Jones, N.; Ames, D. P.

2015-12-01

Advances in water resources modeling are improving the information that can be supplied to support decisions affecting the safety and sustainability of society. However, as water resources models become more sophisticated and data-intensive they require more computational power to run. Purchasing and maintaining the computing facilities needed to support certain modeling tasks has been cost-prohibitive for many organizations. With the advent of the cloud, the computing resources needed to address this challenge are now available and cost-effective, yet there still remains a significant technical barrier to leverage these resources. This barrier inhibits many decision makers and even trained engineers from taking advantage of the best science and tools available. Here we present the Python tools TethysCluster and CondorPy, that have been developed to lower the barrier to model computation in the cloud by providing (1) programmatic access to dynamically scalable computing resources, (2) a batch scheduling system to queue and dispatch the jobs to the computing resources, (3) data management for job inputs and outputs, and (4) the ability to dynamically create, submit, and monitor computing jobs. These Python tools leverage the open source, computing-resource management, and job management software, HTCondor, to offer a flexible and scalable distributed-computing environment. While TethysCluster and CondorPy can be used independently to provision computing resources and perform large modeling tasks, they have also been integrated into Tethys Platform, a development platform for water resources web apps, to enable computing support for modeling workflows and decision-support systems deployed as web apps.

Neuro-genetic non-invasive temperature estimation: intensity and spatial prediction.

PubMed

Teixeira, César A; Ruano, M Graça; Ruano, António E; Pereira, Wagner C A

2008-06-01

The existence of proper non-invasive temperature estimators is an essential aspect when thermal therapy applications are envisaged. These estimators must be good predictors to enable temperature estimation at different operational situations, providing better control of the therapeutic instrumentation. In this work, radial basis functions artificial neural networks were constructed to access temperature evolution on an ultrasound insonated medium. The employed models were radial basis functions neural networks with external dynamics induced by their inputs. Both the most suited set of model inputs and number of neurons in the network were found using the multi-objective genetic algorithm. The neural models were validated in two situations: the operating ones, as used in the construction of the network; and in 11 unseen situations. The new data addressed two new spatial locations and a new intensity level, assessing the intensity and space prediction capacity of the proposed model. Good performance was obtained during the validation process both in terms of the spatial points considered and whenever the new intensity level was within the range of applied intensities. A maximum absolute error of 0.5 degrees C+/-10% (0.5 degrees C is the gold-standard threshold in hyperthermia/diathermia) was attained with low computationally complex models. The results confirm that the proposed neuro-genetic approach enables foreseeing temperature propagation, in connection to intensity and space parameters, thus enabling the assessment of different operating situations with proper temperature resolution.

The dipole moment surface for hydrogen sulfide H2S

NASA Astrophysics Data System (ADS)

Azzam, Ala`a. A. A.; Lodi, Lorenzo; Yurchenko, Sergey N.; Tennyson, Jonathan

2015-08-01

In this work we perform a systematic ab initio study of the dipole moment surface (DMS) of H2S at various levels of theory and of its effect on the intensities of vibration-rotation transitions; H2S intensities are known from the experiment to display anomalies which have so far been difficult to reproduce by theoretical calculations. We use the transition intensities from the HITRAN database of 14 vibrational bands for our comparisons. The intensities of all fundamental bands show strong sensitivity to the ab initio method used for constructing the DMS while hot, overtone and combination bands up to 4000 cm-1 do not. The core-correlation and relativistic effects are found to be important for computed line intensities, for instance affecting the most intense fundamental band (ν2) by about 20%. Our recommended DMS, called ALYT2, is based on the CCSD(T)/aug-cc-pV(6+d)Z level of theory supplemented by a core-correlation/relativistic corrective surface obtained at the CCSD[T]/aug-cc-pCV5Z-DK level. The corresponding computed intensities agree significantly better (to within 10%) with experimental data taken directly from original papers. Worse agreement (differences of about 25%) is found for those HITRAN intensities obtained from fitted effective dipole models, suggesting the presence of underlying problems in those fits.

Evaluating open-source cloud computing solutions for geosciences

NASA Astrophysics Data System (ADS)

Huang, Qunying; Yang, Chaowei; Liu, Kai; Xia, Jizhe; Xu, Chen; Li, Jing; Gui, Zhipeng; Sun, Min; Li, Zhenglong

2013-09-01

Many organizations start to adopt cloud computing for better utilizing computing resources by taking advantage of its scalability, cost reduction, and easy to access characteristics. Many private or community cloud computing platforms are being built using open-source cloud solutions. However, little has been done to systematically compare and evaluate the features and performance of open-source solutions in supporting Geosciences. This paper provides a comprehensive study of three open-source cloud solutions, including OpenNebula, Eucalyptus, and CloudStack. We compared a variety of features, capabilities, technologies and performances including: (1) general features and supported services for cloud resource creation and management, (2) advanced capabilities for networking and security, and (3) the performance of the cloud solutions in provisioning and operating the cloud resources as well as the performance of virtual machines initiated and managed by the cloud solutions in supporting selected geoscience applications. Our study found that: (1) no significant performance differences in central processing unit (CPU), memory and I/O of virtual machines created and managed by different solutions, (2) OpenNebula has the fastest internal network while both Eucalyptus and CloudStack have better virtual machine isolation and security strategies, (3) Cloudstack has the fastest operations in handling virtual machines, images, snapshots, volumes and networking, followed by OpenNebula, and (4) the selected cloud computing solutions are capable for supporting concurrent intensive web applications, computing intensive applications, and small-scale model simulations without intensive data communication.

Vacuum ultraviolet line radiation measurements of a shock-heated nitrogen plasma

NASA Technical Reports Server (NTRS)

Mcclenahan, J. O.

1972-01-01

Line radiation, in the wavelength region from 1040 to 2500 A from nitrogen plasmas, was measured at conditions typical of those produced in the shock layer in front of vehicles entering the earth's atmosphere at superorbital velocities. The radiation was also predicted with a typical radiation transport computer program to determine whether such calculations adequately model plasmas for the conditions tested. The results of the comparison show that the radiant intensities of the lines between 1040 and 1700 A are actually lower than are predicted by such computer models.

An inverse problem strategy based on forward model evaluations: Gradient-based optimization without adjoint solves

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

Aguilo Valentin, Miguel Alejandro

2016-07-01

This study presents a new nonlinear programming formulation for the solution of inverse problems. First, a general inverse problem formulation based on the compliance error functional is presented. The proposed error functional enables the computation of the Lagrange multipliers, and thus the first order derivative information, at the expense of just one model evaluation. Therefore, the calculation of the Lagrange multipliers does not require the solution of the computationally intensive adjoint problem. This leads to significant speedups for large-scale, gradient-based inverse problems.

Numerical Analysis of Crack Tip Plasticity and History Effects under Mixed Mode Conditions

NASA Astrophysics Data System (ADS)

Lopez-Crespo, Pablo; Pommier, Sylvie

The plastic behaviour in the crack tip region has a strong influence on the fatigue life of engineering components. In general, residual stresses developed as a consequence of the plasticity being constrained around the crack tip have a significant role on both the direction of crack propagation and the propagation rate. Finite element methods (FEM) are commonly employed in order to model plasticity. However, if millions of cycles need to be modelled to predict the fatigue behaviour of a component, the method becomes computationally too expensive. By employing a multiscale approach, very precise analyses computed by FEM can be brought to a global scale. The data generated using the FEM enables us to identify a global cyclic elastic-plastic model for the crack tip region. Once this model is identified, it can be employed directly, with no need of additional FEM computations, resulting in fast computations. This is done by partitioning local displacement fields computed by FEM into intensity factors (global data) and spatial fields. A Karhunen-Loeve algorithm developed for image processing was employed for this purpose. In addition, the partitioning is done such as to distinguish into elastic and plastic components. Each of them is further divided into opening mode and shear mode parts. The plastic flow direction was determined with the above approach on a centre cracked panel subjected to a wide range of mixed-mode loading conditions. It was found to agree well with the maximum tangential stress criterion developed by Erdogan and Sih, provided that the loading direction is corrected for residual stresses. In this approach, residual stresses are measured at the global scale through internal intensity factors.

Tropical Cyclone Intensity in Global Models

NASA Astrophysics Data System (ADS)

Davis, C. A.; Wang, W.; Ahijevych, D.

2017-12-01

In recent years, global prediction and climate models have begun to depict intense tropical cyclones, even up to Category 5 on the Saffir-Simpson scale. In light of the limitation of horizontal resolution in such models, we examine the how well these models treat tropical cyclone intensity, measured from several different perspectives. The models evaluated include the operational Global Forecast System, with a grid spacing of about 13 km, and the Model for Prediction Across Scales, with a variable resolution of 15 km over the Northwest Pacific transitioning to 60 km elsewhere. We focus on the Northwest Pacific for the period July-October, 2016. Results indicate that discrimination of tropical cyclone intensity is reasonably good up to roughly category 3 storms. The models are able to capture storms of category 4 intensity, but still exhibit a negative intensity bias of 20-30 knots at lead times beyond 5 days. This is partly indicative of the large number of super-typhoons that occurred in 2016. The question arises of how well global models should represent intensity, given that it is unreasonable for them to depict the inner core of many intense tropical cyclones with a grid increment of 13-15 km. We compute an expected "best-case" prediction of intensity based on filtering the observed wind profiles of Atlantic tropical cyclones according to different hypothetical model resolutions. The Atlantic is used because of the significant number of reconnaissance missions and more reliable estimate of wind radii. Results indicate that, even under the most optimistic assumptions, models with horizontal grid spacing of 1/4 degree or coarser should not produce a realistic number of category 4 and 5 storms unless there are errors in spatial attributes of the wind field. Furthermore, models with a grid spacing of 1/4 degree or greater are unlikely to systematically discriminate hurricanes with differing intensity. Finally, for simple wind profiles, it is shown how an accurate representation of maximum wind on a coarse grid will lead to an overestimate of horizontally integrated kinetic energy by a factor of two or more.

MIRO Computational Model

NASA Technical Reports Server (NTRS)

Broderick, Daniel

2010-01-01

A computational model calculates the excitation of water rotational levels and emission-line spectra in a cometary coma with applications for the Micro-wave Instrument for Rosetta Orbiter (MIRO). MIRO is a millimeter-submillimeter spectrometer that will be used to study the nature of cometary nuclei, the physical processes of outgassing, and the formation of the head region of a comet (coma). The computational model is a means to interpret the data measured by MIRO. The model is based on the accelerated Monte Carlo method, which performs a random angular, spatial, and frequency sampling of the radiation field to calculate the local average intensity of the field. With the model, the water rotational level populations in the cometary coma and the line profiles for the emission from the water molecules as a function of cometary parameters (such as outgassing rate, gas temperature, and gas and electron density) and observation parameters (such as distance to the comet and beam width) are calculated.

Computing moment to moment BOLD activation for real-time neurofeedback

PubMed Central

Hinds, Oliver; Ghosh, Satrajit; Thompson, Todd W.; Yoo, Julie J.; Whitfield-Gabrieli, Susan; Triantafyllou, Christina; Gabrieli, John D.E.

2013-01-01

Estimating moment to moment changes in blood oxygenation level dependent (BOLD) activation levels from functional magnetic resonance imaging (fMRI) data has applications for learned regulation of regional activation, brain state monitoring, and brain-machine interfaces. In each of these contexts, accurate estimation of the BOLD signal in as little time as possible is desired. This is a challenging problem due to the low signal-to-noise ratio of fMRI data. Previous methods for real-time fMRI analysis have either sacrificed the ability to compute moment to moment activation changes by averaging several acquisitions into a single activation estimate or have sacrificed accuracy by failing to account for prominent sources of noise in the fMRI signal. Here we present a new method for computing the amount of activation present in a single fMRI acquisition that separates moment to moment changes in the fMRI signal intensity attributable to neural sources from those due to noise, resulting in a feedback signal more reflective of neural activation. This method computes an incremental general linear model fit to the fMRI timeseries, which is used to calculate the expected signal intensity at each new acquisition. The difference between the measured intensity and the expected intensity is scaled by the variance of the estimator in order to transform this residual difference into a statistic. Both synthetic and real data were used to validate this method and compare it to the only other published real-time fMRI method. PMID:20682350

Linear Array Ambient Noise Adjoint Tomography Reveals Intense Crust-Mantle Interactions in North China Craton

NASA Astrophysics Data System (ADS)

Zhang, Chao; Yao, Huajian; Liu, Qinya; Zhang, Ping; Yuan, Yanhua O.; Feng, Jikun; Fang, Lihua

2018-01-01

We present a 2-D ambient noise adjoint tomography technique for a linear array with a significant reduction in computational cost and show its application to an array in North China. We first convert the observed data for 3-D media, i.e., surface-wave empirical Green's functions (EGFs) to the reconstructed EGFs (REGFs) for 2-D media using a 3-D/2-D transformation scheme. Different from the conventional steps of measuring phase dispersion, this technology refines 2-D shear wave speeds along the profile directly from REGFs. With an initial model based on traditional ambient noise tomography, adjoint tomography updates the model by minimizing the frequency-dependent Rayleigh wave traveltime delays between the REGFs and synthetic Green functions calculated by the spectral-element method. The multitaper traveltime difference measurement is applied in four-period bands: 20-35 s, 15-30 s, 10-20 s, and 6-15 s. The recovered model shows detailed crustal structures including pronounced low-velocity anomalies in the lower crust and a gradual crust-mantle transition zone beneath the northern Trans-North China Orogen, which suggest the possible intense thermo-chemical interactions between mantle-derived upwelling melts and the lower crust, probably associated with the magmatic underplating during the Mesozoic to Cenozoic evolution of this region. To our knowledge, it is the first time that ambient noise adjoint tomography is implemented for a 2-D medium. Compared with the intensive computational cost and storage requirement of 3-D adjoint tomography, this method offers a computationally efficient and inexpensive alternative to imaging fine-scale crustal structures beneath linear arrays.

Planning intensive care unit design using computer simulation modeling: optimizing integration of clinical, operational, and architectural requirements.

PubMed

OʼHara, Susan

2014-01-01

Nurses have increasingly been regarded as critical members of the planning team as architects recognize their knowledge and value. But the nurses' role as knowledge experts can be expanded to leading efforts to integrate the clinical, operational, and architectural expertise through simulation modeling. Simulation modeling allows for the optimal merge of multifactorial data to understand the current state of the intensive care unit and predict future states. Nurses can champion the simulation modeling process and reap the benefits of a cost-effective way to test new designs, processes, staffing models, and future programming trends prior to implementation. Simulation modeling is an evidence-based planning approach, a standard, for integrating the sciences with real client data, to offer solutions for improving patient care.

The Human Brain Project and neuromorphic computing

PubMed Central

Calimera, Andrea; Macii, Enrico; Poncino, Massimo

Summary Understanding how the brain manages billions of processing units connected via kilometers of fibers and trillions of synapses, while consuming a few tens of Watts could provide the key to a completely new category of hardware (neuromorphic computing systems). In order to achieve this, a paradigm shift for computing as a whole is needed, which will see it moving away from current “bit precise” computing models and towards new techniques that exploit the stochastic behavior of simple, reliable, very fast, low-power computing devices embedded in intensely recursive architectures. In this paper we summarize how these objectives will be pursued in the Human Brain Project. PMID:24139655

Estimation of Radiative Efficiency of Chemicals with Potentially Significant Global Warming Potential.

PubMed

Betowski, Don; Bevington, Charles; Allison, Thomas C

2016-01-19

Halogenated chemical substances are used in a broad array of applications, and new chemical substances are continually being developed and introduced into commerce. While recent research has considerably increased our understanding of the global warming potentials (GWPs) of multiple individual chemical substances, this research inevitably lags behind the development of new chemical substances. There are currently over 200 substances known to have high GWP. Evaluation of schemes to estimate radiative efficiency (RE) based on computational chemistry are useful where no measured IR spectrum is available. This study assesses the reliability of values of RE calculated using computational chemistry techniques for 235 chemical substances against the best available values. Computed vibrational frequency data is used to estimate RE values using several Pinnock-type models, and reasonable agreement with reported values is found. Significant improvement is obtained through scaling of both vibrational frequencies and intensities. The effect of varying the computational method and basis set used to calculate the frequency data is discussed. It is found that the vibrational intensities have a strong dependence on basis set and are largely responsible for differences in computed RE values.

EIT amplitude noise spectroscopy

NASA Astrophysics Data System (ADS)

Whitenack, Benjamin; Tormey, Devan; O'Leary, Shannon; Crescimanno, Michael

2017-04-01

EIT Noise spectroscopy is usually studied by computing a correlation statistic based on temporal intensity variations of the two (circular polarization) propagation eigenstates. Studying the intensity noise correlations that result from amplitude mixing that we perform before and after the cell allows us to recast it in terms of the underlying amplitude noise. This leads to new tests of the quantum optics theory model and suggests an approach to the use of noise spectroscopy for vector magnetometry.

Linear static structural and vibration analysis on high-performance computers

NASA Technical Reports Server (NTRS)

Baddourah, M. A.; Storaasli, O. O.; Bostic, S. W.

1993-01-01

Parallel computers offer the oppurtunity to significantly reduce the computation time necessary to analyze large-scale aerospace structures. This paper presents algorithms developed for and implemented on massively-parallel computers hereafter referred to as Scalable High-Performance Computers (SHPC), for the most computationally intensive tasks involved in structural analysis, namely, generation and assembly of system matrices, solution of systems of equations and calculation of the eigenvalues and eigenvectors. Results on SHPC are presented for large-scale structural problems (i.e. models for High-Speed Civil Transport). The goal of this research is to develop a new, efficient technique which extends structural analysis to SHPC and makes large-scale structural analyses tractable.

High Performance Computing Modeling Advances Accelerator Science for High-Energy Physics

DOE PAGES

Amundson, James; Macridin, Alexandru; Spentzouris, Panagiotis

2014-07-28

The development and optimization of particle accelerators are essential for advancing our understanding of the properties of matter, energy, space, and time. Particle accelerators are complex devices whose behavior involves many physical effects on multiple scales. Therefore, advanced computational tools utilizing high-performance computing are essential for accurately modeling them. In the past decade, the US Department of Energy's SciDAC program has produced accelerator-modeling tools that have been employed to tackle some of the most difficult accelerator science problems. The authors discuss the Synergia framework and its applications to high-intensity particle accelerator physics. Synergia is an accelerator simulation package capable ofmore » handling the entire spectrum of beam dynamics simulations. Our authors present Synergia's design principles and its performance on HPC platforms.« less

Applications in Data-Intensive Computing

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

Shah, Anuj R.; Adkins, Joshua N.; Baxter, Douglas J.

2010-04-01

This book chapter, to be published in Advances in Computers, Volume 78, in 2010 describes applications of data intensive computing (DIC). This is an invited chapter resulting from a previous publication on DIC. This work summarizes efforts coming out of the PNNL's Data Intensive Computing Initiative. Advances in technology have empowered individuals with the ability to generate digital content with mouse clicks and voice commands. Digital pictures, emails, text messages, home videos, audio, and webpages are common examples of digital content that are generated on a regular basis. Data intensive computing facilitates human understanding of complex problems. Data-intensive applications providemore » timely and meaningful analytical results in response to exponentially growing data complexity and associated analysis requirements through the development of new classes of software, algorithms, and hardware.« less

Effect of initial conditions and of intra-event rainfall intensity variability on shallow landslide triggering return period

NASA Astrophysics Data System (ADS)

Peres, David Johnny; Cancelliere, Antonino

2016-04-01

Assessment of shallow landslide hazard is important for appropriate planning of mitigation measures. Generally, return period of slope instability is assumed as a quantitative metric to map landslide triggering hazard on a catchment. The most commonly applied approach to estimate such return period consists in coupling a physically-based landslide triggering model (hydrological and slope stability) with rainfall intensity-duration-frequency (IDF) curves. Among the drawbacks of such an approach, the following assumptions may be mentioned: (1) prefixed initial conditions, with no regard to their probability of occurrence, and (2) constant intensity-hyetographs. In our work we propose the use of a Monte Carlo simulation approach in order to investigate the effects of the two above mentioned assumptions. The approach is based on coupling a physically based hydrological and slope stability model with a stochastic rainfall time series generator. By this methodology a long series of synthetic rainfall data can be generated and given as input to a landslide triggering physically based model, in order to compute the return period of landslide triggering as the mean inter-arrival time of a factor of safety less than one. In particular, we couple the Neyman-Scott rectangular pulses model for hourly rainfall generation and the TRIGRS v.2 unsaturated model for the computation of transient response to individual rainfall events. Initial conditions are computed by a water table recession model that links initial conditions at a given event to the final response at the preceding event, thus taking into account variable inter-arrival time between storms. One-thousand years of synthetic hourly rainfall are generated to estimate return periods up to 100 years. Applications are first carried out to map landslide triggering hazard in the Loco catchment, located in highly landslide-prone area of the Peloritani Mountains, Sicily, Italy. Then a set of additional simulations are performed in order to compare the results obtained by the traditional IDF-based method with the Monte Carlo ones. Results indicate that both variability of initial conditions and of intra-event rainfall intensity significantly affect return period estimation. In particular, the common assumption of an initial water table depth at the base of the pervious strata may lead in practice to an overestimation of return period up to one order of magnitude, while the assumption of constant-intensity hyetographs may yield an overestimation by a factor of two or three. Hence, it may be concluded that the analysed simplifications involved in the traditional IDF-based approach generally imply a non-conservative assessment of landslide triggering hazard.

Federated data storage system prototype for LHC experiments and data intensive science

NASA Astrophysics Data System (ADS)

Kiryanov, A.; Klimentov, A.; Krasnopevtsev, D.; Ryabinkin, E.; Zarochentsev, A.

2017-10-01

Rapid increase of data volume from the experiments running at the Large Hadron Collider (LHC) prompted physics computing community to evaluate new data handling and processing solutions. Russian grid sites and universities’ clusters scattered over a large area aim at the task of uniting their resources for future productive work, at the same time giving an opportunity to support large physics collaborations. In our project we address the fundamental problem of designing a computing architecture to integrate distributed storage resources for LHC experiments and other data-intensive science applications and to provide access to data from heterogeneous computing facilities. Studies include development and implementation of federated data storage prototype for Worldwide LHC Computing Grid (WLCG) centres of different levels and University clusters within one National Cloud. The prototype is based on computing resources located in Moscow, Dubna, Saint Petersburg, Gatchina and Geneva. This project intends to implement a federated distributed storage for all kind of operations such as read/write/transfer and access via WAN from Grid centres, university clusters, supercomputers, academic and commercial clouds. The efficiency and performance of the system are demonstrated using synthetic and experiment-specific tests including real data processing and analysis workflows from ATLAS and ALICE experiments, as well as compute-intensive bioinformatics applications (PALEOMIX) running on supercomputers. We present topology and architecture of the designed system, report performance and statistics for different access patterns and show how federated data storage can be used efficiently by physicists and biologists. We also describe how sharing data on a widely distributed storage system can lead to a new computing model and reformations of computing style, for instance how bioinformatics program running on supercomputers can read/write data from the federated storage.

Scalable Automated Model Search

DTIC Science & Technology

2014-05-20

ma- chines. Categories and Subject Descriptors Big Data [Distributed Computing]: Large scale optimization 1. INTRODUCTION Modern scientific and...from Continuum Analytics[1], and Apache Spark 0.8.1. Additionally, we made use of Hadoop 1.0.4 configured on local disks as our data store for the large...Borkar et al. Hyracks: A flexible and extensible foundation for data -intensive computing. In ICDE, 2011. [16] J. Canny and H. Zhao. Big data

Accuracy of RGD approximation for computing light scattering properties of diffusing and motile bacteria. [Rayleigh-Gans-Debye

NASA Technical Reports Server (NTRS)

Kottarchyk, M.; Chen, S.-H.; Asano, S.

1979-01-01

The study tests the accuracy of the Rayleigh-Gans-Debye (RGD) approximation against a rigorous scattering theory calculation for a simplified model of E. coli (about 1 micron in size) - a solid spheroid. A general procedure is formulated whereby the scattered field amplitude correlation function, for both polarized and depolarized contributions, can be computed for a collection of particles. An explicit formula is presented for the scattered intensity, both polarized and depolarized, for a collection of randomly diffusing or moving particles. Two specific cases for the intermediate scattering functions are considered: diffusing particles and freely moving particles with a Maxwellian speed distribution. The formalism is applied to microorganisms suspended in a liquid medium. Sensitivity studies revealed that for values of the relative index of refraction greater than 1.03, RGD could be in serious error in computing the intensity as well as correlation functions.

Influence of savanna fire on Australian monsoon season precipitation and circulation as simulated using a distributed computing environment

NASA Astrophysics Data System (ADS)

Lynch, Amanda H.; Abramson, David; Görgen, Klaus; Beringer, Jason; Uotila, Petteri

2007-10-01

Fires in the Australian savanna have been hypothesized to affect monsoon evolution, but the hypothesis is controversial and the effects have not been quantified. A distributed computing approach allows the development of a challenging experimental design that permits simultaneous variation of all fire attributes. The climate model simulations are distributed around multiple independent computer clusters in six countries, an approach that has potential for a range of other large simulation applications in the earth sciences. The experiment clarifies that savanna burning can shape the monsoon through two mechanisms. Boundary-layer circulation and large-scale convergence is intensified monotonically through increasing fire intensity and area burned. However, thresholds of fire timing and area are evident in the consequent influence on monsoon rainfall. In the optimal band of late, high intensity fires with a somewhat limited extent, it is possible for the wet season to be significantly enhanced.

pWeb: A High-Performance, Parallel-Computing Framework for Web-Browser-Based Medical Simulation.

PubMed

Halic, Tansel; Ahn, Woojin; De, Suvranu

2014-01-01

This work presents a pWeb - a new language and compiler for parallelization of client-side compute intensive web applications such as surgical simulations. The recently introduced HTML5 standard has enabled creating unprecedented applications on the web. Low performance of the web browser, however, remains the bottleneck of computationally intensive applications including visualization of complex scenes, real time physical simulations and image processing compared to native ones. The new proposed language is built upon web workers for multithreaded programming in HTML5. The language provides fundamental functionalities of parallel programming languages as well as the fork/join parallel model which is not supported by web workers. The language compiler automatically generates an equivalent parallel script that complies with the HTML5 standard. A case study on realistic rendering for surgical simulations demonstrates enhanced performance with a compact set of instructions.

A novel visual saliency analysis model based on dynamic multiple feature combination strategy

NASA Astrophysics Data System (ADS)

Lv, Jing; Ye, Qi; Lv, Wen; Zhang, Libao

2017-06-01

The human visual system can quickly focus on a small number of salient objects. This process was known as visual saliency analysis and these salient objects are called focus of attention (FOA). The visual saliency analysis mechanism can be used to extract the salient regions and analyze saliency of object in an image, which is time-saving and can avoid unnecessary costs of computing resources. In this paper, a novel visual saliency analysis model based on dynamic multiple feature combination strategy is introduced. In the proposed model, we first generate multi-scale feature maps of intensity, color and orientation features using Gaussian pyramids and the center-surround difference. Then, we evaluate the contribution of all feature maps to the saliency map according to the area of salient regions and their average intensity, and attach different weights to different features according to their importance. Finally, we choose the largest salient region generated by the region growing method to perform the evaluation. Experimental results show that the proposed model cannot only achieve higher accuracy in saliency map computation compared with other traditional saliency analysis models, but also extract salient regions with arbitrary shapes, which is of great value for the image analysis and understanding.

3D robust Chan-Vese model for industrial computed tomography volume data segmentation

NASA Astrophysics Data System (ADS)

Liu, Linghui; Zeng, Li; Luan, Xiao

2013-11-01

Industrial computed tomography (CT) has been widely applied in many areas of non-destructive testing (NDT) and non-destructive evaluation (NDE). In practice, CT volume data to be dealt with may be corrupted by noise. This paper addresses the segmentation of noisy industrial CT volume data. Motivated by the research on the Chan-Vese (CV) model, we present a region-based active contour model that draws upon intensity information in local regions with a controllable scale. In the presence of noise, a local energy is firstly defined according to the intensity difference within a local neighborhood. Then a global energy is defined to integrate local energy with respect to all image points. In a level set formulation, this energy is represented by a variational level set function, where a surface evolution equation is derived for energy minimization. Comparative analysis with the CV model indicates the comparable performance of the 3D robust Chan-Vese (RCV) model. The quantitative evaluation also shows the segmentation accuracy of 3D RCV. In addition, the efficiency of our approach is validated under several types of noise, such as Poisson noise, Gaussian noise, salt-and-pepper noise and speckle noise.

High performance hybrid functional Petri net simulations of biological pathway models on CUDA.

PubMed

Chalkidis, Georgios; Nagasaki, Masao; Miyano, Satoru

2011-01-01

Hybrid functional Petri nets are a wide-spread tool for representing and simulating biological models. Due to their potential of providing virtual drug testing environments, biological simulations have a growing impact on pharmaceutical research. Continuous research advancements in biology and medicine lead to exponentially increasing simulation times, thus raising the demand for performance accelerations by efficient and inexpensive parallel computation solutions. Recent developments in the field of general-purpose computation on graphics processing units (GPGPU) enabled the scientific community to port a variety of compute intensive algorithms onto the graphics processing unit (GPU). This work presents the first scheme for mapping biological hybrid functional Petri net models, which can handle both discrete and continuous entities, onto compute unified device architecture (CUDA) enabled GPUs. GPU accelerated simulations are observed to run up to 18 times faster than sequential implementations. Simulating the cell boundary formation by Delta-Notch signaling on a CUDA enabled GPU results in a speedup of approximately 7x for a model containing 1,600 cells.

Fast Learning for Immersive Engagement in Energy Simulations

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

Bush, Brian W; Bugbee, Bruce; Gruchalla, Kenny M

The fast computation which is critical for immersive engagement with and learning from energy simulations would be furthered by developing a general method for creating rapidly computed simplified versions of NREL's computation-intensive energy simulations. Created using machine learning techniques, these 'reduced form' simulations can provide statistically sound estimates of the results of the full simulations at a fraction of the computational cost with response times - typically less than one minute of wall-clock time - suitable for real-time human-in-the-loop design and analysis. Additionally, uncertainty quantification techniques can document the accuracy of the approximate models and their domain of validity. Approximationmore » methods are applicable to a wide range of computational models, including supply-chain models, electric power grid simulations, and building models. These reduced-form representations cannot replace or re-implement existing simulations, but instead supplement them by enabling rapid scenario design and quality assurance for large sets of simulations. We present an overview of the framework and methods we have implemented for developing these reduced-form representations.« less

Multiple Detector Optimization for Hidden Radiation Source Detection

DTIC Science & Technology

2015-03-26

important in achieving operationally useful methods for optimizing detector emplacement, the 2-D attenuation model approach promises to speed up the...process of hidden source detection significantly. The model focused on detection of the full energy peak of a radiation source. Methods to optimize... radioisotope identification is possible without using a computationally intensive stochastic model such as the Monte Carlo n-Particle (MCNP) code

Efficient Transition Probability Computation for Continuous-Time Branching Processes via Compressed Sensing.

PubMed

Xu, Jason; Minin, Vladimir N

2015-07-01

Branching processes are a class of continuous-time Markov chains (CTMCs) with ubiquitous applications. A general difficulty in statistical inference under partially observed CTMC models arises in computing transition probabilities when the discrete state space is large or uncountable. Classical methods such as matrix exponentiation are infeasible for large or countably infinite state spaces, and sampling-based alternatives are computationally intensive, requiring integration over all possible hidden events. Recent work has successfully applied generating function techniques to computing transition probabilities for linear multi-type branching processes. While these techniques often require significantly fewer computations than matrix exponentiation, they also become prohibitive in applications with large populations. We propose a compressed sensing framework that significantly accelerates the generating function method, decreasing computational cost up to a logarithmic factor by only assuming the probability mass of transitions is sparse. We demonstrate accurate and efficient transition probability computations in branching process models for blood cell formation and evolution of self-replicating transposable elements in bacterial genomes.

Efficient Transition Probability Computation for Continuous-Time Branching Processes via Compressed Sensing

PubMed Central

Xu, Jason; Minin, Vladimir N.

2016-01-01

Branching processes are a class of continuous-time Markov chains (CTMCs) with ubiquitous applications. A general difficulty in statistical inference under partially observed CTMC models arises in computing transition probabilities when the discrete state space is large or uncountable. Classical methods such as matrix exponentiation are infeasible for large or countably infinite state spaces, and sampling-based alternatives are computationally intensive, requiring integration over all possible hidden events. Recent work has successfully applied generating function techniques to computing transition probabilities for linear multi-type branching processes. While these techniques often require significantly fewer computations than matrix exponentiation, they also become prohibitive in applications with large populations. We propose a compressed sensing framework that significantly accelerates the generating function method, decreasing computational cost up to a logarithmic factor by only assuming the probability mass of transitions is sparse. We demonstrate accurate and efficient transition probability computations in branching process models for blood cell formation and evolution of self-replicating transposable elements in bacterial genomes. PMID:26949377

DEPOSITION OF SULFATE ACID AEROSOLS IN THE DEVELOPING HUMAN LUNG

EPA Science Inventory

Computations of aerosol deposition as affected by (i) aerosol hygroscopicity, (ii) human age, and (iii) respiratory intensity are accomplished using a validated mathematical model. he interactive effects are very complicated but systematic. ew general observations can be made; ra...

0-6767 : evaluation of existing smartphone applications and data needs for travel survey.

DOT National Transportation Integrated Search

2014-08-01

Current and reliable data on traffic movements : play a key role in transportation planning, : modeling, and air quality analysis. Traditional : travel surveys conducted via paper or computer : are costly, time consuming, and labor intensive : for su...

Cone-beam x-ray luminescence computed tomography based on x-ray absorption dosage.

PubMed

Liu, Tianshuai; Rong, Junyan; Gao, Peng; Zhang, Wenli; Liu, Wenlei; Zhang, Yuanke; Lu, Hongbing

2018-02-01

With the advances of x-ray excitable nanophosphors, x-ray luminescence computed tomography (XLCT) has become a promising hybrid imaging modality. In particular, a cone-beam XLCT (CB-XLCT) system has demonstrated its potential in in vivo imaging with the advantage of fast imaging speed over other XLCT systems. Currently, the imaging models of most XLCT systems assume that nanophosphors emit light based on the intensity distribution of x-ray within the object, not completely reflecting the nature of the x-ray excitation process. To improve the imaging quality of CB-XLCT, an imaging model that adopts an excitation model of nanophosphors based on x-ray absorption dosage is proposed in this study. To solve the ill-posed inverse problem, a reconstruction algorithm that combines the adaptive Tikhonov regularization method with the imaging model is implemented for CB-XLCT reconstruction. Numerical simulations and phantom experiments indicate that compared with the traditional forward model based on x-ray intensity, the proposed dose-based model could improve the image quality of CB-XLCT significantly in terms of target shape, localization accuracy, and image contrast. In addition, the proposed model behaves better in distinguishing closer targets, demonstrating its advantage in improving spatial resolution. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Defining the computational structure of the motion detector in Drosophila

PubMed Central

Clark, Damon A.; Bursztyn, Limor; Horowitz, Mark; Schnitzer, Mark J.; Clandinin, Thomas R.

2011-01-01

SUMMARY Many animals rely on visual motion detection for survival. Motion information is extracted from spatiotemporal intensity patterns on the retina, a paradigmatic neural computation. A phenomenological model, the Hassenstein-Reichardt Correlator (HRC), relates visual inputs to neural and behavioral responses to motion, but the circuits that implement this computation remain unknown. Using cell-type specific genetic silencing, minimal motion stimuli, and in vivo calcium imaging, we examine two critical HRC inputs. These two pathways respond preferentially to light and dark moving edges. We demonstrate that these pathways perform overlapping but complementary subsets of the computations underlying the HRC. A numerical model implementing differential weighting of these operations displays the observed edge preferences. Intriguingly, these pathways are distinguished by their sensitivities to a stimulus correlation that corresponds to an illusory percept, “reverse phi”, that affects many species. Thus, this computational architecture may be widely used to achieve edge selectivity in motion detection. PMID:21689602

A study of model parameters associated with the urban climate using HCMM data. [analysis of St. Louis, Missouri infrared imagery

NASA Technical Reports Server (NTRS)

1981-01-01

Progress in the study of the intensity of the urban heat island is reported. The intensity of the heat island is commonly defined as the temperature difference between the center of the city and the surrounding suburban and rural regions. The intensity is considered as a function of changes in the season and changes in meteorological conditions in order to derive various parameters which may be used in numerical models for urban climate. Twelve case studies were selected and CCT's were ordered. In situ data was obtained from sixteen stations scattered about the city of St. Louis. Upper-air meteorological data were obtained and the water vapor and the temperature data were processed. Atmospheric transmissivities were computed for each of the case studies.

GEM System: automatic prototyping of cell-wide metabolic pathway models from genomes.

PubMed

Arakawa, Kazuharu; Yamada, Yohei; Shinoda, Kosaku; Nakayama, Yoichi; Tomita, Masaru

2006-03-23

Successful realization of a "systems biology" approach to analyzing cells is a grand challenge for our understanding of life. However, current modeling approaches to cell simulation are labor-intensive, manual affairs, and therefore constitute a major bottleneck in the evolution of computational cell biology. We developed the Genome-based Modeling (GEM) System for the purpose of automatically prototyping simulation models of cell-wide metabolic pathways from genome sequences and other public biological information. Models generated by the GEM System include an entire Escherichia coli metabolism model comprising 968 reactions of 1195 metabolites, achieving 100% coverage when compared with the KEGG database, 92.38% with the EcoCyc database, and 95.06% with iJR904 genome-scale model. The GEM System prototypes qualitative models to reduce the labor-intensive tasks required for systems biology research. Models of over 90 bacterial genomes are available at our web site.

SU-F-J-94: Development of a Plug-in Based Image Analysis Tool for Integration Into Treatment Planning

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

Owen, D; Anderson, C; Mayo, C

Purpose: To extend the functionality of a commercial treatment planning system (TPS) to support (i) direct use of quantitative image-based metrics within treatment plan optimization and (ii) evaluation of dose-functional volume relationships to assist in functional image adaptive radiotherapy. Methods: A script was written that interfaces with a commercial TPS via an Application Programming Interface (API). The script executes a program that performs dose-functional volume analyses. Written in C#, the script reads the dose grid and correlates it with image data on a voxel-by-voxel basis through API extensions that can access registration transforms. A user interface was designed through WinFormsmore » to input parameters and display results. To test the performance of this program, image- and dose-based metrics computed from perfusion SPECT images aligned to the treatment planning CT were generated, validated, and compared. Results: The integration of image analysis information was successfully implemented as a plug-in to a commercial TPS. Perfusion SPECT images were used to validate the calculation and display of image-based metrics as well as dose-intensity metrics and histograms for defined structures on the treatment planning CT. Various biological dose correction models, custom image-based metrics, dose-intensity computations, and dose-intensity histograms were applied to analyze the image-dose profile. Conclusion: It is possible to add image analysis features to commercial TPSs through custom scripting applications. A tool was developed to enable the evaluation of image-intensity-based metrics in the context of functional targeting and avoidance. In addition to providing dose-intensity metrics and histograms that can be easily extracted from a plan database and correlated with outcomes, the system can also be extended to a plug-in optimization system, which can directly use the computed metrics for optimization of post-treatment tumor or normal tissue response models. Supported by NIH - P01 - CA059827.« less

Lithographic image simulation for the 21st century with 19th-century tools

NASA Astrophysics Data System (ADS)

Gordon, Ronald L.; Rosenbluth, Alan E.

2004-01-01

Simulation of lithographic processes in semiconductor manufacturing has gone from a crude learning tool 20 years ago to a critical part of yield enhancement strategy today. Although many disparate models, championed by equally disparate communities, exist to describe various photoresist development phenomena, these communities would all agree that the one piece of the simulation picture that can, and must, be computed accurately is the image intensity in the photoresist. The imaging of a photomask onto a thin-film stack is one of the only phenomena in the lithographic process that is described fully by well-known, definitive physical laws. Although many approximations are made in the derivation of the Fourier transform relations between the mask object, the pupil, and the image, these and their impacts are well-understood and need little further investigation. The imaging process in optical lithography is modeled as a partially-coherent, Kohler illumination system. As Hopkins has shown, we can separate the computation into 2 pieces: one that takes information about the illumination source, the projection lens pupil, the resist stack, and the mask size or pitch, and the other that only needs the details of the mask structure. As the latter piece of the calculation can be expressed as a fast Fourier transform, it is the first piece that dominates. This piece involves computation of a potentially large number of numbers called Transmission Cross-Coefficients (TCCs), which are correlations of the pupil function weighted with the illumination intensity distribution. The advantage of performing the image calculations this way is that the computation of these TCCs represents an up-front cost, not to be repeated if one is only interested in changing the mask features, which is the case in Model-Based Optical Proximity Correction (MBOPC). The down side, however, is that the number of these expensive double integrals that must be performed increases as the square of the mask unit cell area; this number can cause even the fastest computers to balk if one needs to study medium- or long-range effects. One can reduce this computational burden by approximating with a smaller area, but accuracy is usually a concern, especially when building a model that will purportedly represent a manufacturing process. This work will review the current methodologies used to simulate the intensity distribution in air above the resist and address the above problems. More to the point, a methodology has been developed to eliminate the expensive numerical integrations in the TCC calculations, as the resulting integrals in many cases of interest can be either evaluated analytically, or replaced by analytical functions accurate to within machine precision. With the burden of computing these numbers lightened, more accurate representations of the image field can be realized, and better overall models are then possible.

Enabling large-scale viscoelastic calculations via neural network acceleration

NASA Astrophysics Data System (ADS)

Robinson DeVries, P.; Thompson, T. B.; Meade, B. J.

2017-12-01

One of the most significant challenges involved in efforts to understand the effects of repeated earthquake cycle activity are the computational costs of large-scale viscoelastic earthquake cycle models. Deep artificial neural networks (ANNs) can be used to discover new, compact, and accurate computational representations of viscoelastic physics. Once found, these efficient ANN representations may replace computationally intensive viscoelastic codes and accelerate large-scale viscoelastic calculations by more than 50,000%. This magnitude of acceleration enables the modeling of geometrically complex faults over thousands of earthquake cycles across wider ranges of model parameters and at larger spatial and temporal scales than have been previously possible. Perhaps most interestingly from a scientific perspective, ANN representations of viscoelastic physics may lead to basic advances in the understanding of the underlying model phenomenology. We demonstrate the potential of artificial neural networks to illuminate fundamental physical insights with specific examples.

Queuing theory models for computer networks

NASA Technical Reports Server (NTRS)

Galant, David C.

1989-01-01

A set of simple queuing theory models which can model the average response of a network of computers to a given traffic load has been implemented using a spreadsheet. The impact of variations in traffic patterns and intensities, channel capacities, and message protocols can be assessed using them because of the lack of fine detail in the network traffic rates, traffic patterns, and the hardware used to implement the networks. A sample use of the models applied to a realistic problem is included in appendix A. Appendix B provides a glossary of terms used in this paper. This Ames Research Center computer communication network is an evolving network of local area networks (LANs) connected via gateways and high-speed backbone communication channels. Intelligent planning of expansion and improvement requires understanding the behavior of the individual LANs as well as the collection of networks as a whole.

The COBAIN (COntact Binary Atmospheres with INterpolation) Code for Radiative Transfer

NASA Astrophysics Data System (ADS)

Kochoska, Angela; Prša, Andrej; Horvat, Martin

2018-01-01

Standard binary star modeling codes make use of pre-existing solutions of the radiative transfer equation in stellar atmospheres. The various model atmospheres available today are consistently computed for single stars, under different assumptions - plane-parallel or spherical atmosphere approximation, local thermodynamical equilibrium (LTE) or non-LTE (NLTE), etc. However, they are nonetheless being applied to contact binary atmospheres by populating the surface corresponding to each component separately and neglecting any mixing that would typically occur at the contact boundary. In addition, single stellar atmosphere models do not take into account irradiance from a companion star, which can pose a serious problem when modeling close binaries. 1D atmosphere models are also solved under the assumption of an atmosphere in hydrodynamical equilibrium, which is not necessarily the case for contact atmospheres, as the potentially different densities and temperatures can give rise to flows that play a key role in the heat and radiation transfer.To resolve the issue of erroneous modeling of contact binary atmospheres using single star atmosphere tables, we have developed a generalized radiative transfer code for computation of the normal emergent intensity of a stellar surface, given its geometry and internal structure. The code uses a regular mesh of equipotential surfaces in a discrete set of spherical coordinates, which are then used to interpolate the values of the structural quantites (density, temperature, opacity) in any given point inside the mesh. The radiaitive transfer equation is numerically integrated in a set of directions spanning the unit sphere around each point and iterated until the intensity values for all directions and all mesh points converge within a given tolerance. We have found that this approach, albeit computationally expensive, is the only one that can reproduce the intensity distribution of the non-symmetric contact binary atmosphere and can be used with any existing or new model of the structure of contact binaries. We present results on several test objects and future prospects of the implementation in state-of-the-art binary star modeling software.

Fast neuromimetic object recognition using FPGA outperforms GPU implementations.

PubMed

Orchard, Garrick; Martin, Jacob G; Vogelstein, R Jacob; Etienne-Cummings, Ralph

2013-08-01

Recognition of objects in still images has traditionally been regarded as a difficult computational problem. Although modern automated methods for visual object recognition have achieved steadily increasing recognition accuracy, even the most advanced computational vision approaches are unable to obtain performance equal to that of humans. This has led to the creation of many biologically inspired models of visual object recognition, among them the hierarchical model and X (HMAX) model. HMAX is traditionally known to achieve high accuracy in visual object recognition tasks at the expense of significant computational complexity. Increasing complexity, in turn, increases computation time, reducing the number of images that can be processed per unit time. In this paper we describe how the computationally intensive and biologically inspired HMAX model for visual object recognition can be modified for implementation on a commercial field-programmable aate Array, specifically the Xilinx Virtex 6 ML605 evaluation board with XC6VLX240T FPGA. We show that with minor modifications to the traditional HMAX model we can perform recognition on images of size 128 × 128 pixels at a rate of 190 images per second with a less than 1% loss in recognition accuracy in both binary and multiclass visual object recognition tasks.

Bringing MapReduce Closer To Data With Active Drives

NASA Astrophysics Data System (ADS)

Golpayegani, N.; Prathapan, S.; Warmka, R.; Wyatt, B.; Halem, M.; Trantham, J. D.; Markey, C. A.

2017-12-01

Moving computation closer to the data location has been a much theorized improvement to computation for decades. The increase in processor performance, the decrease in processor size and power requirement combined with the increase in data intensive computing has created a push to move computation as close to data as possible. We will show the next logical step in this evolution in computing: moving computation directly to storage. Hypothetical systems, known as Active Drives, have been proposed as early as 1998. These Active Drives would have a general-purpose CPU on each disk allowing for computations to be performed on them without the need to transfer the data to the computer over the system bus or via a network. We will utilize Seagate's Active Drives to perform general purpose parallel computing using the MapReduce programming model directly on each drive. We will detail how the MapReduce programming model can be adapted to the Active Drive compute model to perform general purpose computing with comparable results to traditional MapReduce computations performed via Hadoop. We will show how an Active Drive based approach significantly reduces the amount of data leaving the drive when performing several common algorithms: subsetting and gridding. We will show that an Active Drive based design significantly improves data transfer speeds into and out of drives compared to Hadoop's HDFS while at the same time keeping comparable compute speeds as Hadoop.

Transforming parts of a differential equations system to difference equations as a method for run-time savings in NONMEM.

PubMed

Petersson, K J F; Friberg, L E; Karlsson, M O

2010-10-01

Computer models of biological systems grow more complex as computing power increase. Often these models are defined as differential equations and no analytical solutions exist. Numerical integration is used to approximate the solution; this can be computationally intensive, time consuming and be a large proportion of the total computer runtime. The performance of different integration methods depend on the mathematical properties of the differential equations system at hand. In this paper we investigate the possibility of runtime gains by calculating parts of or the whole differential equations system at given time intervals, outside of the differential equations solver. This approach was tested on nine models defined as differential equations with the goal to reduce runtime while maintaining model fit, based on the objective function value. The software used was NONMEM. In four models the computational runtime was successfully reduced (by 59-96%). The differences in parameter estimates, compared to using only the differential equations solver were less than 12% for all fixed effects parameters. For the variance parameters, estimates were within 10% for the majority of the parameters. Population and individual predictions were similar and the differences in OFV were between 1 and -14 units. When computational runtime seriously affects the usefulness of a model we suggest evaluating this approach for repetitive elements of model building and evaluation such as covariate inclusions or bootstraps.

The atmospheric emission method of calculating the neutral atmosphere and charged particle densities in the upper atmosphere

NASA Astrophysics Data System (ADS)

McElroy, Kenneth L., Jr.

1992-12-01

A method is presented for the determination of neutral gas densities in the ionosphere from rocket-borne measurements of UV atmospheric emissions. Computer models were used to calculate an initial guess for the neutral atmosphere. Using this neutral atmosphere, intensity profiles for the N2 (0,5) Vegard-Kaplan band, the N2 Lyman-Birge-Hopfield band system, and the OI2972 A line were calculated and compared with the March 1990 NPS MUSTANG data. The neutral atmospheric model was modified and the intensity profiles recalculated until a fit with the data was obtained. The neutral atmosphere corresponding to the intensity profile that fit the data was assumed to be the atmospheric composition prevailing at the time of the observation. The ion densities were then calculated from the neutral atmosphere using a photochemical model. The electron density profile calculated by this model was compared with the electron density profile measured by the U.S. Air Force Geophysics Laboratory at a nearby site.

SURROGATE MODEL DEVELOPMENT AND VALIDATION FOR RELIABILITY ANALYSIS OF REACTOR PRESSURE VESSELS

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

Hoffman, William M.; Riley, Matthew E.; Spencer, Benjamin W.

In nuclear light water reactors (LWRs), the reactor coolant, core and shroud are contained within a massive, thick walled steel vessel known as a reactor pressure vessel (RPV). Given the tremendous size of these structures, RPVs typically contain a large population of pre-existing flaws introduced in the manufacturing process. After many years of operation, irradiation-induced embrittlement makes these vessels increasingly susceptible to fracture initiation at the locations of the pre-existing flaws. Because of the uncertainty in the loading conditions, flaw characteristics and material properties, probabilistic methods are widely accepted and used in assessing RPV integrity. The Fracture Analysis of Vesselsmore » – Oak Ridge (FAVOR) computer program developed by researchers at Oak Ridge National Laboratory is widely used for this purpose. This program can be used in order to perform deterministic and probabilistic risk-informed analyses of the structural integrity of an RPV subjected to a range of thermal-hydraulic events. FAVOR uses a one-dimensional representation of the global response of the RPV, which is appropriate for the beltline region, which experiences the most embrittlement, and employs an influence coefficient technique to rapidly compute stress intensity factors for axis-aligned surface-breaking flaws. The Grizzly code is currently under development at Idaho National Laboratory (INL) to be used as a general multiphysics simulation tool to study a variety of degradation mechanisms in nuclear power plant components. The first application of Grizzly has been to study fracture in embrittled RPVs. Grizzly can be used to model the thermo-mechanical response of an RPV under transient conditions observed in a pressurized thermal shock (PTS) scenario. The global response of the vessel provides boundary conditions for local 3D models of the material in the vicinity of a flaw. Fracture domain integrals are computed to obtain stress intensity factors, which can in turn be used to assess whether a fracture would initiate at a pre-existing flaw. To use Grizzly for probabilistic analysis, it is necessary to have a way to rapidly evaluate stress intensity factors. To accomplish this goal, a reduced order model (ROM) has been developed to efficiently represent the behavior of a detailed 3D Grizzly model used to calculate fracture parameters. This approach uses the stress intensity factor influence coefficient method that has been used with great success in FAVOR. Instead of interpolating between tabulated solutions, as FAVOR does, the ROM approach uses a response surface methodology to compute fracture solutions based on a sampled set of results used to train the ROM. The main advantages of this approach are that the process of generating the training data can be fully automated, and the procedure can be readily used to consider more general flaw configurations. This paper demonstrates the procedure used to generate a ROM to rapidly compute stress intensity factors for axis-aligned flaws. The results from this procedure are in good agreement with those produced using the traditional influence coefficient interpolation procedure, which gives confidence in this method. This paves the way for applying this procedure for more general flaw configurations.« less

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

Heroux, Michael; Lethin, Richard

Programming models and environments play the essential roles in high performance computing of enabling the conception, design, implementation and execution of science and engineering application codes. Programmer productivity is strongly influenced by the effectiveness of our programming models and environments, as is software sustainability since our codes have lifespans measured in decades, so the advent of new computing architectures, increased concurrency, concerns for resilience, and the increasing demands for high-fidelity, multi-physics, multi-scale and data-intensive computations mean that we have new challenges to address as part of our fundamental R&D requirements. Fortunately, we also have new tools and environments that makemore » design, prototyping and delivery of new programming models easier than ever. The combination of new and challenging requirements and new, powerful toolsets enables significant synergies for the next generation of programming models and environments R&D. This report presents the topics discussed and results from the 2014 DOE Office of Science Advanced Scientific Computing Research (ASCR) Programming Models & Environments Summit, and subsequent discussions among the summit participants and contributors to topics in this report.« less

Quantitative image analysis of immunohistochemical stains using a CMYK color model

PubMed Central

Pham, Nhu-An; Morrison, Andrew; Schwock, Joerg; Aviel-Ronen, Sarit; Iakovlev, Vladimir; Tsao, Ming-Sound; Ho, James; Hedley, David W

2007-01-01

Background Computer image analysis techniques have decreased effects of observer biases, and increased the sensitivity and the throughput of immunohistochemistry (IHC) as a tissue-based procedure for the evaluation of diseases. Methods We adapted a Cyan/Magenta/Yellow/Key (CMYK) model for automated computer image analysis to quantify IHC stains in hematoxylin counterstained histological sections. Results The spectral characteristics of the chromogens AEC, DAB and NovaRed as well as the counterstain hematoxylin were first determined using CMYK, Red/Green/Blue (RGB), normalized RGB and Hue/Saturation/Lightness (HSL) color models. The contrast of chromogen intensities on a 0–255 scale (24-bit image file) as well as compared to the hematoxylin counterstain was greatest using the Yellow channel of a CMYK color model, suggesting an improved sensitivity for IHC evaluation compared to other color models. An increase in activated STAT3 levels due to growth factor stimulation, quantified using the Yellow channel image analysis was associated with an increase detected by Western blotting. Two clinical image data sets were used to compare the Yellow channel automated method with observer-dependent methods. First, a quantification of DAB-labeled carbonic anhydrase IX hypoxia marker in 414 sections obtained from 138 biopsies of cervical carcinoma showed strong association between Yellow channel and positive color selection results. Second, a linear relationship was also demonstrated between Yellow intensity and visual scoring for NovaRed-labeled epidermal growth factor receptor in 256 non-small cell lung cancer biopsies. Conclusion The Yellow channel image analysis method based on a CMYK color model is independent of observer biases for threshold and positive color selection, applicable to different chromogens, tolerant of hematoxylin, sensitive to small changes in IHC intensity and is applicable to simple automation procedures. These characteristics are advantageous for both basic as well as clinical research in an unbiased, reproducible and high throughput evaluation of IHC intensity. PMID:17326824

ASTEC and MODEL: Controls software development at Goddard Space Flight Center

NASA Technical Reports Server (NTRS)

Downing, John P.; Bauer, Frank H.; Surber, Jeffrey L.

1993-01-01

The ASTEC (Analysis and Simulation Tools for Engineering Controls) software is under development at the Goddard Space Flight Center (GSFC). The design goal is to provide a wide selection of controls analysis tools at the personal computer level, as well as the capability to upload compute-intensive jobs to a mainframe or supercomputer. In the last three years the ASTEC (Analysis and Simulation Tools for Engineering Controls) software has been under development. ASTEC is meant to be an integrated collection of controls analysis tools for use at the desktop level. MODEL (Multi-Optimal Differential Equation Language) is a translator that converts programs written in the MODEL language to FORTRAN. An upgraded version of the MODEL program will be merged into ASTEC. MODEL has not been modified since 1981 and has not kept with changes in computers or user interface techniques. This paper describes the changes made to MODEL in order to make it useful in the 90's and how it relates to ASTEC.

Supercomputer applications in molecular modeling.

PubMed

Gund, T M

1988-01-01

An overview of the functions performed by molecular modeling is given. Molecular modeling techniques benefiting from supercomputing are described, namely, conformation, search, deriving bioactive conformations, pharmacophoric pattern searching, receptor mapping, and electrostatic properties. The use of supercomputers for problems that are computationally intensive, such as protein structure prediction, protein dynamics and reactivity, protein conformations, and energetics of binding is also examined. The current status of supercomputing and supercomputer resources are discussed.

Empirical improvements for estimating earthquake response spectra with random‐vibration theory

USGS Publications Warehouse

Boore, David; Thompson, Eric M.

2012-01-01

The stochastic method of ground‐motion simulation is often used in combination with the random‐vibration theory to directly compute ground‐motion intensity measures, thereby bypassing the more computationally intensive time‐domain simulations. Key to the application of random‐vibration theory to simulate response spectra is determining the duration (Drms) used in computing the root‐mean‐square oscillator response. Boore and Joyner (1984) originally proposed an equation for Drms , which was improved upon by Liu and Pezeshk (1999). Though these equations are both substantial improvements over using the duration of the ground‐motion excitation for Drms , we document systematic differences between the ground‐motion intensity measures derived from the random‐vibration and time‐domain methods for both of these Drms equations. These differences are generally less than 10% for most magnitudes, distances, and periods of engineering interest. Given the systematic nature of the differences, however, we feel that improved equations are warranted. We empirically derive new equations from time‐domain simulations for eastern and western North America seismological models. The new equations improve the random‐vibration simulations over a wide range of magnitudes, distances, and oscillator periods.

Temperature, Velocity, and Mean Turbulence Structure in Stongly-Heated Internal Gas Flows

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

McEligot, Donald Marinus; Mikielewicz, D. P.; Shehata, A. M.

2002-10-01

The main objective of the present study is to examine whether "simple" turbulence models (i.e., models requiring two partial differential equations or less for turbulent transport) are suitable for use under conditions of forced flow of gas at low Reynolds numbers in tubes with intense heating, leading to large variations of fluid properties and considerable modification of turbulence. Eleven representative models are considered. The ability of such models to handle such flows was assessed by means of computational simulations of the carefully designed experiments of Shehata and McEligot (IJHMT 41 (1998) 4297) at heating rates of q+in˜0.0018, 0.0035 and 0.0045,more » yielding flows ranging from essentially turbulent to laminarized. The resulting comparisons of computational results with experiments showed that the model by Launder and Sharma (Lett. Heat Transfer 1 (1974) 131) performed best in predicting axial wall temperature profiles. Overall, agreement between the measured velocity and temperature distributions and those calculated using the Launder–Sharma model is good, which gives confidence in the values forecast for the turbulence quantities produced. These have been used to assist in arriving at a better understanding of the influences of intense heating, and hence strong variation of fluid properties, on turbulent flow in tubes.« less

Surrogates for numerical simulations; optimization of eddy-promoter heat exchangers

NASA Technical Reports Server (NTRS)

Patera, Anthony T.; Patera, Anthony

1993-01-01

Although the advent of fast and inexpensive parallel computers has rendered numerous previously intractable calculations feasible, many numerical simulations remain too resource-intensive to be directly inserted in engineering optimization efforts. An attractive alternative to direct insertion considers models for computational systems: the expensive simulation is evoked only to construct and validate a simplified, input-output model; this simplified input-output model then serves as a simulation surrogate in subsequent engineering optimization studies. A simple 'Bayesian-validated' statistical framework for the construction, validation, and purposive application of static computer simulation surrogates is presented. As an example, dissipation-transport optimization of laminar-flow eddy-promoter heat exchangers are considered: parallel spectral element Navier-Stokes calculations serve to construct and validate surrogates for the flowrate and Nusselt number; these surrogates then represent the originating Navier-Stokes equations in the ensuing design process.

A Computational Approach for Probabilistic Analysis of Water Impact Simulations

NASA Technical Reports Server (NTRS)

Horta, Lucas G.; Mason, Brian H.; Lyle, Karen H.

2009-01-01

NASA's development of new concepts for the Crew Exploration Vehicle Orion presents many similar challenges to those worked in the sixties during the Apollo program. However, with improved modeling capabilities, new challenges arise. For example, the use of the commercial code LS-DYNA, although widely used and accepted in the technical community, often involves high-dimensional, time consuming, and computationally intensive simulations. The challenge is to capture what is learned from a limited number of LS-DYNA simulations to develop models that allow users to conduct interpolation of solutions at a fraction of the computational time. This paper presents a description of the LS-DYNA model, a brief summary of the response surface techniques, the analysis of variance approach used in the sensitivity studies, equations used to estimate impact parameters, results showing conditions that might cause injuries, and concluding remarks.

Room temperature linelists for CO2 asymmetric isotopologues with ab initio computed intensities

NASA Astrophysics Data System (ADS)

Zak, Emil J.; Tennyson, Jonathan; Polyansky, Oleg L.; Lodi, Lorenzo; Zobov, Nikolay F.; Tashkun, Sergei A.; Perevalov, Valery I.

2017-12-01

The present paper reports room temperature line lists for six asymmetric isotopologues of carbon dioxide: 16O12C18O (628), 16O12C17O (627), 16O13C18O (638),16O13C17O (637), 17O12C18O (728) and 17O13C18O (738), covering the range 0-8000 cm-1. Variational rotation-vibration wavefunctions and energy levels are computed using the DVR3D software suite and a high quality semi-empirical potential energy surface (PES), followed by computation of intensities using an ab initio dipole moment surface (DMS). A theoretical procedure for quantifying sensitivity of line intensities to minor distortions of the PES/DMS renders our theoretical model as critically evaluated. Several recent high quality measurements and theoretical approaches are discussed to provide a benchmark of our results against the most accurate available data. Indeed, the thesis of transferability of accuracy among different isotopologues with the use of mass-independent PES is supported by several examples. Thereby, we conclude that the majority of line intensities for strong bands are predicted with sub-percent accuracy. Accurate line positions are generated using an effective Hamiltonian, constructed from the latest experiments. This study completes the list of relevant isotopologues of carbon dioxide; these line lists are available to remote sensing studies and inclusion in databases.

In Situ Three-Dimensional Reciprocal-Space Mapping of Diffuse Scattering Intensity Distribution and Data Analysis for Precursor Phenomenon in Shape-Memory Alloy

NASA Astrophysics Data System (ADS)

Cheng, Tian-Le; Ma, Fengde D.; Zhou, Jie E.; Jennings, Guy; Ren, Yang; Jin, Yongmei M.; Wang, Yu U.

2012-01-01

Diffuse scattering contains rich information on various structural disorders, thus providing a useful means to study the nanoscale structural deviations from the average crystal structures determined by Bragg peak analysis. Extraction of maximal information from diffuse scattering requires concerted efforts in high-quality three-dimensional (3D) data measurement, quantitative data analysis and visualization, theoretical interpretation, and computer simulations. Such an endeavor is undertaken to study the correlated dynamic atomic position fluctuations caused by thermal vibrations (phonons) in precursor state of shape-memory alloys. High-quality 3D diffuse scattering intensity data around representative Bragg peaks are collected by using in situ high-energy synchrotron x-ray diffraction and two-dimensional digital x-ray detector (image plate). Computational algorithms and codes are developed to construct the 3D reciprocal-space map of diffuse scattering intensity distribution from the measured data, which are further visualized and quantitatively analyzed to reveal in situ physical behaviors. Diffuse scattering intensity distribution is explicitly formulated in terms of atomic position fluctuations to interpret the experimental observations and identify the most relevant physical mechanisms, which help set up reduced structural models with minimal parameters to be efficiently determined by computer simulations. Such combined procedures are demonstrated by a study of phonon softening phenomenon in precursor state and premartensitic transformation of Ni-Mn-Ga shape-memory alloy.

Physical models and primary design of reactor based slow positron source at CMRR

NASA Astrophysics Data System (ADS)

Wang, Guanbo; Li, Rundong; Qian, Dazhi; Yang, Xin

2018-07-01

Slow positron facilities are widely used in material science. A high intensity slow positron source is now at the design stage based on the China Mianyang Research Reactor (CMRR). This paper describes the physical models and our primary design. We use different computer programs or mathematical formula to simulate different physical process, and validate them by proper experiments. Considering the feasibility, we propose a primary design, containing a cadmium shield, a honeycomb arranged W tubes assembly, electrical lenses, and a solenoid. It is planned to be vertically inserted in the Si-doping channel. And the beam intensity is expected to be 5 ×109

High-resolution Modeling Assisted Design of Customized and Individualized Transcranial Direct Current Stimulation Protocols

PubMed Central

Bikson, Marom; Rahman, Asif; Datta, Abhishek; Fregni, Felipe; Merabet, Lotfi

2012-01-01

Objectives Transcranial direct current stimulation (tDCS) is a neuromodulatory technique that delivers low-intensity currents facilitating or inhibiting spontaneous neuronal activity. tDCS is attractive since dose is readily adjustable by simply changing electrode number, position, size, shape, and current. In the recent past, computational models have been developed with increased precision with the goal to help customize tDCS dose. The aim of this review is to discuss the incorporation of high-resolution patient-specific computer modeling to guide and optimize tDCS. Methods In this review, we discuss the following topics: (i) The clinical motivation and rationale for models of transcranial stimulation is considered pivotal in order to leverage the flexibility of neuromodulation; (ii) The protocols and the workflow for developing high-resolution models; (iii) The technical challenges and limitations of interpreting modeling predictions, and (iv) Real cases merging modeling and clinical data illustrating the impact of computational models on the rational design of rehabilitative electrotherapy. Conclusions Though modeling for non-invasive brain stimulation is still in its development phase, it is predicted that with increased validation, dissemination, simplification and democratization of modeling tools, computational forward models of neuromodulation will become useful tools to guide the optimization of clinical electrotherapy. PMID:22780230

Determination of the Global-Average Charge Moment of a Lightning Flash Using Schumann Resonances and the LIS/OTD Lightning Data

NASA Astrophysics Data System (ADS)

Boldi, Robert; Williams, Earle; Guha, Anirban

2018-01-01

In this paper, we use (1) the 20 year record of Schumann resonance (SR) signals measured at West Greenwich Rhode Island, USA, (2) the 19 year Lightning Imaging Sensor (LIS)/Optical Transient Detector (OTD) lightning data, and (3) the normal mode equations for a uniform cavity model to quantify the relationship between the observed Schumann resonance modal intensity and the global-average vertical charge moment change M (C km) per lightning flash. This work, by integrating SR measurements with satellite-based optical measurements of global flash rate, accomplishes this quantification for the first time. To do this, we first fit the intensity spectra of the observed SR signals to an eight-mode, three parameter per mode, (symmetric) Lorentzian line shape model. Next, using the LIS/OTD lightning data and the normal mode equations for a uniform cavity model, we computed the expected climatological-daily-average intensity spectra. We then regressed the observed modal intensity values against the expected modal intensity values to find the best fit value of the global-average vertical charge moment change of a lightning flash (M) to be 41 C km per flash with a 99% confidence interval of ±3.9 C km per flash, independent of mode. Mode independence argues that the model adequately captured the modal intensity, the most important fit parameter herein considered. We also tested this relationship for the presence of residual modal intensity at zero lightning flashes per second and found no evidence that modal intensity is significantly different than zero at zero lightning flashes per second, setting an upper limit to the amount of nonlightning contributions to the observed modal intensity.

Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics.

PubMed

Wu, Xiao-Lin; Sun, Chuanyu; Beissinger, Timothy M; Rosa, Guilherme Jm; Weigel, Kent A; Gatti, Natalia de Leon; Gianola, Daniel

2012-09-25

Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selection, which uses whole-genome molecular data to predict the genetic merit of candidate animals for breeding purposes. In this regard, parallel computing can overcome the bottlenecks that can arise from series computing. Hence, a major goal of the present study is to bridge the gap to high-performance Bayesian computation in the context of animal breeding and genetics. Parallel Monte Carlo Markov chain algorithms and strategies are described in the context of animal breeding and genetics. Parallel Monte Carlo algorithms are introduced as a starting point including their applications to computing single-parameter and certain multiple-parameter models. Then, two basic approaches for parallel Markov chain Monte Carlo are described: one aims at parallelization within a single chain; the other is based on running multiple chains, yet some variants are discussed as well. Features and strategies of the parallel Markov chain Monte Carlo are illustrated using real data, including a large beef cattle dataset with 50K SNP genotypes. Parallel Markov chain Monte Carlo algorithms are useful for computing complex Bayesian models, which does not only lead to a dramatic speedup in computing but can also be used to optimize model parameters in complex Bayesian models. Hence, we anticipate that use of parallel Markov chain Monte Carlo will have a profound impact on revolutionizing the computational tools for genomic selection programs.

Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics

PubMed Central

2012-01-01

Background Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selection, which uses whole-genome molecular data to predict the genetic merit of candidate animals for breeding purposes. In this regard, parallel computing can overcome the bottlenecks that can arise from series computing. Hence, a major goal of the present study is to bridge the gap to high-performance Bayesian computation in the context of animal breeding and genetics. Results Parallel Monte Carlo Markov chain algorithms and strategies are described in the context of animal breeding and genetics. Parallel Monte Carlo algorithms are introduced as a starting point including their applications to computing single-parameter and certain multiple-parameter models. Then, two basic approaches for parallel Markov chain Monte Carlo are described: one aims at parallelization within a single chain; the other is based on running multiple chains, yet some variants are discussed as well. Features and strategies of the parallel Markov chain Monte Carlo are illustrated using real data, including a large beef cattle dataset with 50K SNP genotypes. Conclusions Parallel Markov chain Monte Carlo algorithms are useful for computing complex Bayesian models, which does not only lead to a dramatic speedup in computing but can also be used to optimize model parameters in complex Bayesian models. Hence, we anticipate that use of parallel Markov chain Monte Carlo will have a profound impact on revolutionizing the computational tools for genomic selection programs. PMID:23009363

Safety Metrics for Human-Computer Controlled Systems

NASA Technical Reports Server (NTRS)

Leveson, Nancy G; Hatanaka, Iwao

2000-01-01

The rapid growth of computer technology and innovation has played a significant role in the rise of computer automation of human tasks in modem production systems across all industries. Although the rationale for automation has been to eliminate "human error" or to relieve humans from manual repetitive tasks, various computer-related hazards and accidents have emerged as a direct result of increased system complexity attributed to computer automation. The risk assessment techniques utilized for electromechanical systems are not suitable for today's software-intensive systems or complex human-computer controlled systems.This thesis will propose a new systemic model-based framework for analyzing risk in safety-critical systems where both computers and humans are controlling safety-critical functions. A new systems accident model will be developed based upon modem systems theory and human cognitive processes to better characterize system accidents, the role of human operators, and the influence of software in its direct control of significant system functions Better risk assessments will then be achievable through the application of this new framework to complex human-computer controlled systems.

First experiences with model based iterative reconstructions influence on quantitative plaque volume and intensity measurements in coronary computed tomography angiography.

PubMed

Precht, H; Kitslaar, P H; Broersen, A; Gerke, O; Dijkstra, J; Thygesen, J; Egstrup, K; Lambrechtsen, J

2017-02-01

Investigate the influence of adaptive statistical iterative reconstruction (ASIR) and the model-based IR (Veo) reconstruction algorithm in coronary computed tomography angiography (CCTA) images on quantitative measurements in coronary arteries for plaque volumes and intensities. Three patients had three independent dose reduced CCTA performed and reconstructed with 30% ASIR (CTDI vol at 6.7 mGy), 60% ASIR (CTDI vol 4.3 mGy) and Veo (CTDI vol at 1.9 mGy). Coronary plaque analysis was performed for each measured CCTA volumes, plaque burden and intensities. Plaque volume and plaque burden show a decreasing tendency from ASIR to Veo as median volume for ASIR is 314 mm 3 and 337 mm 3 -252 mm 3 for Veo and plaque burden is 42% and 44% for ASIR to 39% for Veo. The lumen and vessel volume decrease slightly from 30% ASIR to 60% ASIR with 498 mm 3 -391 mm 3 for lumen volume and vessel volume from 939 mm 3 to 830 mm 3 . The intensities did not change overall between the different reconstructions for either lumen or plaque. We found a tendency of decreasing plaque volumes and plaque burden but no change in intensities with the use of low dose Veo CCTA (1.9 mGy) compared to dose reduced ASIR CCTA (6.7 mGy & 4.3 mGy), although more studies are warranted. Copyright © 2016 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.

An Analogue VLSI Implementation of the Meddis Inner Hair Cell Model

NASA Astrophysics Data System (ADS)

McEwan, Alistair; van Schaik, André

2003-12-01

The Meddis inner hair cell model is a widely accepted, but computationally intensive computer model of mammalian inner hair cell function. We have produced an analogue VLSI implementation of this model that operates in real time in the current domain by using translinear and log-domain circuits. The circuit has been fabricated on a chip and tested against the Meddis model for (a) rate level functions for onset and steady-state response, (b) recovery after masking, (c) additivity, (d) two-component adaptation, (e) phase locking, (f) recovery of spontaneous activity, and (g) computational efficiency. The advantage of this circuit, over other electronic inner hair cell models, is its nearly exact implementation of the Meddis model which can be tuned to behave similarly to the biological inner hair cell. This has important implications on our ability to simulate the auditory system in real time. Furthermore, the technique of mapping a mathematical model of first-order differential equations to a circuit of log-domain filters allows us to implement real-time neuromorphic signal processors for a host of models using the same approach.

A sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory.

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

Johnson, J. D.; Oberkampf, William Louis; Helton, Jon Craig

2006-10-01

Evidence theory provides an alternative to probability theory for the representation of epistemic uncertainty in model predictions that derives from epistemic uncertainty in model inputs, where the descriptor epistemic is used to indicate uncertainty that derives from a lack of knowledge with respect to the appropriate values to use for various inputs to the model. The potential benefit, and hence appeal, of evidence theory is that it allows a less restrictive specification of uncertainty than is possible within the axiomatic structure on which probability theory is based. Unfortunately, the propagation of an evidence theory representation for uncertainty through a modelmore » is more computationally demanding than the propagation of a probabilistic representation for uncertainty, with this difficulty constituting a serious obstacle to the use of evidence theory in the representation of uncertainty in predictions obtained from computationally intensive models. This presentation describes and illustrates a sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory. Preliminary trials indicate that the presented strategy can be used to propagate uncertainty representations based on evidence theory in analysis situations where naive sampling-based (i.e., unsophisticated Monte Carlo) procedures are impracticable due to computational cost.« less

Enhancing Manufacturing Process Education via Computer Simulation and Visualization

ERIC Educational Resources Information Center

Manohar, Priyadarshan A.; Acharya, Sushil; Wu, Peter

2014-01-01

Industrially significant metal manufacturing processes such as melting, casting, rolling, forging, machining, and forming are multi-stage, complex processes that are labor, time, and capital intensive. Academic research develops mathematical modeling of these processes that provide a theoretical framework for understanding the process variables…

Computational enhancements for the Virginia Department of Transportation Regional River Severe Storm (R2S2) Model

DOT National Transportation Integrated Search

2017-05-01

Climate change introduces infrastructure flooding challenges, especially for coastal regions with low topographic relief. More frequently occurring intense storms and sea level rise are two projected impacts of climate change that will lead to increa...

Ab initio calculation of resonant Raman intensities of transition metal dichalcogenides

NASA Astrophysics Data System (ADS)

Miranda, Henrique; Reichardt, Sven; Molina-Sanchez, Alejandro; Wirtz, Ludger

Raman spectroscopy is used to characterize optical and vibrational properties of materials. Its computational simulation is important for the interpretation of experimental results. Two approaches are the bond polarizability model and density functional perturbation theory. However, both are known to not capture resonance effects. These resonances and quantum interference effects are important to correctly reproduce the intensities as a function of laser energy as, e.g., reported for the case of multi-layer MoTe21.We present two fully ab initio approaches that overcome this limitation. In the first, we calculate finite difference derivatives of the dielectric susceptibility with the phonon displacements2. In the second we calculate electron-light and electron-phonon matrix elements from density functional theory and use them to evaluate expressions for the Raman intensity derived from time-dependent perturbation theory. These expressions are implemented in a computer code that performs the calculations as a post-processing step. We compare both methods and study the case of triple-layer MoTe2. Luxembourg National Research Fund (FNR).

First-Order Model Management With Variable-Fidelity Physics Applied to Multi-Element Airfoil Optimization

NASA Technical Reports Server (NTRS)

Alexandrov, N. M.; Nielsen, E. J.; Lewis, R. M.; Anderson, W. K.

2000-01-01

First-order approximation and model management is a methodology for a systematic use of variable-fidelity models or approximations in optimization. The intent of model management is to attain convergence to high-fidelity solutions with minimal expense in high-fidelity computations. The savings in terms of computationally intensive evaluations depends on the ability of the available lower-fidelity model or a suite of models to predict the improvement trends for the high-fidelity problem, Variable-fidelity models can be represented by data-fitting approximations, variable-resolution models. variable-convergence models. or variable physical fidelity models. The present work considers the use of variable-fidelity physics models. We demonstrate the performance of model management on an aerodynamic optimization of a multi-element airfoil designed to operate in the transonic regime. Reynolds-averaged Navier-Stokes equations represent the high-fidelity model, while the Euler equations represent the low-fidelity model. An unstructured mesh-based analysis code FUN2D evaluates functions and sensitivity derivatives for both models. Model management for the present demonstration problem yields fivefold savings in terms of high-fidelity evaluations compared to optimization done with high-fidelity computations alone.

High-resolution stochastic generation of extreme rainfall intensity for urban drainage modelling applications

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

2016-04-01

Urban drainage response is highly dependent on the spatial and temporal structure of rainfall. Therefore, measuring and simulating rainfall at a high spatial and temporal resolution is a fundamental step to fully assess urban drainage system reliability and related uncertainties. This is even more relevant when considering extreme rainfall events. However, the current space-time rainfall models have limitations in capturing extreme rainfall intensity statistics for short durations. Here, we use the STREAP (Space-Time Realizations of Areal Precipitation) model, which is a novel stochastic rainfall generator for simulating high-resolution rainfall fields that preserve the spatio-temporal structure of rainfall and its statistical characteristics. The model enables a generation of rain fields at 102 m and minute scales in a fast and computer-efficient way matching the requirements for hydrological analysis of urban drainage systems. The STREAP model was applied successfully in the past to generate high-resolution extreme rainfall intensities over a small domain. A sub-catchment in the city of Luzern (Switzerland) was chosen as a case study to: (i) evaluate the ability of STREAP to disaggregate extreme rainfall intensities for urban drainage applications; (ii) assessing the role of stochastic climate variability of rainfall in flow response and (iii) evaluate the degree of non-linearity between extreme rainfall intensity and system response (i.e. flow) for a small urban catchment. The channel flow at the catchment outlet is simulated by means of a calibrated hydrodynamic sewer model.

Inexact hardware for modelling weather & climate

NASA Astrophysics Data System (ADS)

Düben, Peter D.; McNamara, Hugh; Palmer, Tim

2014-05-01

The use of stochastic processing hardware and low precision arithmetic in atmospheric models is investigated. Stochastic processors allow hardware-induced faults in calculations, sacrificing exact calculations in exchange for improvements in performance and potentially accuracy and a reduction in power consumption. A similar trade-off is achieved using low precision arithmetic, with improvements in computation and communication speed and savings in storage and memory requirements. As high-performance computing becomes more massively parallel and power intensive, these two approaches may be important stepping stones in the pursuit of global cloud resolving atmospheric modelling. The impact of both, hardware induced faults and low precision arithmetic is tested in the dynamical core of a global atmosphere model. Our simulations show that both approaches to inexact calculations do not substantially affect the quality of the model simulations, provided they are restricted to act only on smaller scales. This suggests that inexact calculations at the small scale could reduce computation and power costs without adversely affecting the quality of the simulations.

Novel hybrid GPU-CPU implementation of parallelized Monte Carlo parametric expectation maximization estimation method for population pharmacokinetic data analysis.

PubMed

Ng, C M

2013-10-01

The development of a population PK/PD model, an essential component for model-based drug development, is both time- and labor-intensive. A graphical-processing unit (GPU) computing technology has been proposed and used to accelerate many scientific computations. The objective of this study was to develop a hybrid GPU-CPU implementation of parallelized Monte Carlo parametric expectation maximization (MCPEM) estimation algorithm for population PK data analysis. A hybrid GPU-CPU implementation of the MCPEM algorithm (MCPEMGPU) and identical algorithm that is designed for the single CPU (MCPEMCPU) were developed using MATLAB in a single computer equipped with dual Xeon 6-Core E5690 CPU and a NVIDIA Tesla C2070 GPU parallel computing card that contained 448 stream processors. Two different PK models with rich/sparse sampling design schemes were used to simulate population data in assessing the performance of MCPEMCPU and MCPEMGPU. Results were analyzed by comparing the parameter estimation and model computation times. Speedup factor was used to assess the relative benefit of parallelized MCPEMGPU over MCPEMCPU in shortening model computation time. The MCPEMGPU consistently achieved shorter computation time than the MCPEMCPU and can offer more than 48-fold speedup using a single GPU card. The novel hybrid GPU-CPU implementation of parallelized MCPEM algorithm developed in this study holds a great promise in serving as the core for the next-generation of modeling software for population PK/PD analysis.

ESnet: Large-Scale Science and Data Management ( (LBNL Summer Lecture Series)

ScienceCinema

Johnston, Bill

2017-12-09

Summer Lecture Series 2004: Bill Johnston of Berkeley Lab's Computing Sciences is a distinguished networking and computing researcher. He managed the Energy Sciences Network (ESnet), a leading-edge, high-bandwidth network funded by DOE's Office of Science. Used for everything from videoconferencing to climate modeling, and flexible enough to accommodate a wide variety of data-intensive applications and services, ESNet's traffic volume is doubling every year and currently surpasses 200 terabytes per month.

Investigation of the effect of atmospheric dust on the determination of total ozone from the earth's ultraviolet reflectivity measurements, 1

NASA Technical Reports Server (NTRS)

Dave, J. V.

1976-01-01

Two computer algorithms are described. These algorithms were used for computing the aximuth-independent component of the intensity of the monochromatic radiation emerging at the top of a pseudo-spherical atmosphere with arbitrary vertical distribution of ozone, and with any arbitrary height distribution of up to two different kinds of aerosol. This atmospheric model was assumed to rest on a surface obeying Lambert's law of reflection.

A Cyber-ITS Framework for Massive Traffic Data Analysis Using Cyber Infrastructure

PubMed Central

Fontaine, Michael D.

2013-01-01

Traffic data is commonly collected from widely deployed sensors in urban areas. This brings up a new research topic, data-driven intelligent transportation systems (ITSs), which means to integrate heterogeneous traffic data from different kinds of sensors and apply it for ITS applications. This research, taking into consideration the significant increase in the amount of traffic data and the complexity of data analysis, focuses mainly on the challenge of solving data-intensive and computation-intensive problems. As a solution to the problems, this paper proposes a Cyber-ITS framework to perform data analysis on Cyber Infrastructure (CI), by nature parallel-computing hardware and software systems, in the context of ITS. The techniques of the framework include data representation, domain decomposition, resource allocation, and parallel processing. All these techniques are based on data-driven and application-oriented models and are organized as a component-and-workflow-based model in order to achieve technical interoperability and data reusability. A case study of the Cyber-ITS framework is presented later based on a traffic state estimation application that uses the fusion of massive Sydney Coordinated Adaptive Traffic System (SCATS) data and GPS data. The results prove that the Cyber-ITS-based implementation can achieve a high accuracy rate of traffic state estimation and provide a significant computational speedup for the data fusion by parallel computing. PMID:23766690

A Cyber-ITS framework for massive traffic data analysis using cyber infrastructure.

PubMed

Xia, Yingjie; Hu, Jia; Fontaine, Michael D

2013-01-01

Traffic data is commonly collected from widely deployed sensors in urban areas. This brings up a new research topic, data-driven intelligent transportation systems (ITSs), which means to integrate heterogeneous traffic data from different kinds of sensors and apply it for ITS applications. This research, taking into consideration the significant increase in the amount of traffic data and the complexity of data analysis, focuses mainly on the challenge of solving data-intensive and computation-intensive problems. As a solution to the problems, this paper proposes a Cyber-ITS framework to perform data analysis on Cyber Infrastructure (CI), by nature parallel-computing hardware and software systems, in the context of ITS. The techniques of the framework include data representation, domain decomposition, resource allocation, and parallel processing. All these techniques are based on data-driven and application-oriented models and are organized as a component-and-workflow-based model in order to achieve technical interoperability and data reusability. A case study of the Cyber-ITS framework is presented later based on a traffic state estimation application that uses the fusion of massive Sydney Coordinated Adaptive Traffic System (SCATS) data and GPS data. The results prove that the Cyber-ITS-based implementation can achieve a high accuracy rate of traffic state estimation and provide a significant computational speedup for the data fusion by parallel computing.

Effect of nonlinearity on lesion formation for high-intensity focused ultrasound (HIFU) exposures

NASA Astrophysics Data System (ADS)

Lee, Paul; Lizzi, Frederic L.; Ketterling, Jeffrey A.; Vecchio, Christopher J.

2004-05-01

This study examined the effects of nonlinear propagation phenomena on two types of HIFU transducers (5 MHz) being used for thermal treatments of disease. The first transducer is a 5-element annular array. The second is a transducer with a 5-strip electrode; its multilobed focused beam is designed to efficiently produce broad, paddle-shaped lesions. The beam patterns of these transducers were computed using a variety of excitation patterns for electronic focusing of the annular array and variation of lesion size for the strip-electrode transducer. A range of intensities was studied to determine how nonlinear propagation affects the beam shape, constituent frequency content, grating lobes, etc. These 3D computations used a finite-amplitude beam propagation model that combined the angular spectrum method and Burger's equation to compute the diffraction and nonlinear effects, respectively. Computed beam patterns were compared with hydrophone measurements for each transducer. The linear and nonlinear beam patterns were used to compute the absorbed thermal dose, and the bioheat equation was evaluated to calculate 3D temperature rises and geometry of induced lesions. Computed lesion sizes and shapes were compared to in vitro lesions created by each HIFU transducer. [Work supported by NCI and NHLBI Grant 5R01 CA84588.

Optimizing ion channel models using a parallel genetic algorithm on graphical processors.

PubMed

Ben-Shalom, Roy; Aviv, Amit; Razon, Benjamin; Korngreen, Alon

2012-01-01

We have recently shown that we can semi-automatically constrain models of voltage-gated ion channels by combining a stochastic search algorithm with ionic currents measured using multiple voltage-clamp protocols. Although numerically successful, this approach is highly demanding computationally, with optimization on a high performance Linux cluster typically lasting several days. To solve this computational bottleneck we converted our optimization algorithm for work on a graphical processing unit (GPU) using NVIDIA's CUDA. Parallelizing the process on a Fermi graphic computing engine from NVIDIA increased the speed ∼180 times over an application running on an 80 node Linux cluster, considerably reducing simulation times. This application allows users to optimize models for ion channel kinetics on a single, inexpensive, desktop "super computer," greatly reducing the time and cost of building models relevant to neuronal physiology. We also demonstrate that the point of algorithm parallelization is crucial to its performance. We substantially reduced computing time by solving the ODEs (Ordinary Differential Equations) so as to massively reduce memory transfers to and from the GPU. This approach may be applied to speed up other data intensive applications requiring iterative solutions of ODEs. Copyright © 2012 Elsevier B.V. All rights reserved.

A virtual observatory for photoionized nebulae: the Mexican Million Models database (3MdB).

NASA Astrophysics Data System (ADS)

Morisset, C.; Delgado-Inglada, G.; Flores-Fajardo, N.

2015-04-01

Photoionization models obtained with numerical codes are widely used to study the physics of the interstellar medium (planetary nebulae, HII regions, etc). Grids of models are performed to understand the effects of the different parameters used to describe the regions on the observables (mainly emission line intensities). Most of the time, only a small part of the computed results of such grids are published, and they are sometimes hard to obtain in a user-friendly format. We present here the Mexican Million Models dataBase (3MdB), an effort to resolve both of these issues in the form of a database of photoionization models, easily accessible through the MySQL protocol, and containing a lot of useful outputs from the models, such as the intensities of 178 emission lines, the ionic fractions of all the ions, etc. Some examples of the use of the 3MdB are also presented.

A spherical harmonics intensity model for 3D segmentation and 3D shape analysis of heterochromatin foci.

PubMed

Eck, Simon; Wörz, Stefan; Müller-Ott, Katharina; Hahn, Matthias; Biesdorf, Andreas; Schotta, Gunnar; Rippe, Karsten; Rohr, Karl

2016-08-01

The genome is partitioned into regions of euchromatin and heterochromatin. The organization of heterochromatin is important for the regulation of cellular processes such as chromosome segregation and gene silencing, and their misregulation is linked to cancer and other diseases. We present a model-based approach for automatic 3D segmentation and 3D shape analysis of heterochromatin foci from 3D confocal light microscopy images. Our approach employs a novel 3D intensity model based on spherical harmonics, which analytically describes the shape and intensities of the foci. The model parameters are determined by fitting the model to the image intensities using least-squares minimization. To characterize the 3D shape of the foci, we exploit the computed spherical harmonics coefficients and determine a shape descriptor. We applied our approach to 3D synthetic image data as well as real 3D static and real 3D time-lapse microscopy images, and compared the performance with that of previous approaches. It turned out that our approach yields accurate 3D segmentation results and performs better than previous approaches. We also show that our approach can be used for quantifying 3D shape differences of heterochromatin foci. Copyright © 2016 Elsevier B.V. All rights reserved.

Probabilistic segmentation and intensity estimation for microarray images.

PubMed

Gottardo, Raphael; Besag, Julian; Stephens, Matthew; Murua, Alejandro

2006-01-01

We describe a probabilistic approach to simultaneous image segmentation and intensity estimation for complementary DNA microarray experiments. The approach overcomes several limitations of existing methods. In particular, it (a) uses a flexible Markov random field approach to segmentation that allows for a wider range of spot shapes than existing methods, including relatively common 'doughnut-shaped' spots; (b) models the image directly as background plus hybridization intensity, and estimates the two quantities simultaneously, avoiding the common logical error that estimates of foreground may be less than those of the corresponding background if the two are estimated separately; and (c) uses a probabilistic modeling approach to simultaneously perform segmentation and intensity estimation, and to compute spot quality measures. We describe two approaches to parameter estimation: a fast algorithm, based on the expectation-maximization and the iterated conditional modes algorithms, and a fully Bayesian framework. These approaches produce comparable results, and both appear to offer some advantages over other methods. We use an HIV experiment to compare our approach to two commercial software products: Spot and Arrayvision.

Solving difficult problems creatively: a role for energy optimised deterministic/stochastic hybrid computing

PubMed Central

Palmer, Tim N.; O’Shea, Michael

2015-01-01

How is the brain configured for creativity? What is the computational substrate for ‘eureka’ moments of insight? Here we argue that creative thinking arises ultimately from a synergy between low-energy stochastic and energy-intensive deterministic processing, and is a by-product of a nervous system whose signal-processing capability per unit of available energy has become highly energy optimised. We suggest that the stochastic component has its origin in thermal (ultimately quantum decoherent) noise affecting the activity of neurons. Without this component, deterministic computational models of the brain are incomplete. PMID:26528173

Math and Data Exploration

ERIC Educational Resources Information Center

Liu, Dennis

2010-01-01

Biology is well suited for mathematical description, from the perfect geometry of viruses, to equations that describe the flux of ions across cellular membranes, to computationally intensive models for protein folding. For this short Web review, however, the author focuses on how mathematics helps biologists sort, evaluate, and draw conclusions…

A probabilistic tornado wind hazard model for the continental United States

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

Hossain, Q; Kimball, J; Mensing, R

A probabilistic tornado wind hazard model for the continental United States (CONUS) is described. The model incorporates both aleatory (random) and epistemic uncertainties associated with quantifying the tornado wind hazard parameters. The temporal occurrences of tornadoes within the continental United States (CONUS) is assumed to be a Poisson process. A spatial distribution of tornado touchdown locations is developed empirically based on the observed historical events within the CONUS. The hazard model is an aerial probability model that takes into consideration the size and orientation of the facility, the length and width of the tornado damage area (idealized as a rectanglemore » and dependent on the tornado intensity scale), wind speed variation within the damage area, tornado intensity classification errors (i.e.,errors in assigning a Fujita intensity scale based on surveyed damage), and the tornado path direction. Epistemic uncertainties in describing the distributions of the aleatory variables are accounted for by using more than one distribution model to describe aleatory variations. The epistemic uncertainties are based on inputs from a panel of experts. A computer program, TORNADO, has been developed incorporating this model; features of this program are also presented.« less

Mean-field thalamocortical modeling of longitudinal EEG acquired during intensive meditation training.

PubMed

Saggar, Manish; Zanesco, Anthony P; King, Brandon G; Bridwell, David A; MacLean, Katherine A; Aichele, Stephen R; Jacobs, Tonya L; Wallace, B Alan; Saron, Clifford D; Miikkulainen, Risto

2015-07-01

Meditation training has been shown to enhance attention and improve emotion regulation. However, the brain processes associated with such training are poorly understood and a computational modeling framework is lacking. Modeling approaches that can realistically simulate neurophysiological data while conforming to basic anatomical and physiological constraints can provide a unique opportunity to generate concrete and testable hypotheses about the mechanisms supporting complex cognitive tasks such as meditation. Here we applied the mean-field computational modeling approach using the scalp-recorded electroencephalogram (EEG) collected at three assessment points from meditating participants during two separate 3-month-long shamatha meditation retreats. We modeled cortical, corticothalamic, and intrathalamic interactions to generate a simulation of EEG signals recorded across the scalp. We also present two novel extensions to the mean-field approach that allow for: (a) non-parametric analysis of changes in model parameter values across all channels and assessments; and (b) examination of variation in modeled thalamic reticular nucleus (TRN) connectivity over the retreat period. After successfully fitting whole-brain EEG data across three assessment points within each retreat, two model parameters were found to replicably change across both meditation retreats. First, after training, we observed an increased temporal delay between modeled cortical and thalamic cells. This increase provides a putative neural mechanism for a previously observed reduction in individual alpha frequency in these same participants. Second, we found decreased inhibitory connection strength between the TRN and secondary relay nuclei (SRN) of the modeled thalamus after training. This reduction in inhibitory strength was found to be associated with increased dynamical stability of the model. Altogether, this paper presents the first computational approach, taking core aspects of physiology and anatomy into account, to formally model brain processes associated with intensive meditation training. The observed changes in model parameters inform theoretical accounts of attention training through meditation, and may motivate future study on the use of meditation in a variety of clinical populations. Copyright © 2015 Elsevier Inc. All rights reserved.

A Longitudinal Investigation of the Effects of Computer Anxiety on Performance in a Computing-Intensive Environment

ERIC Educational Resources Information Center

Buche, Mari W.; Davis, Larry R.; Vician, Chelley

2007-01-01

Computers are pervasive in business and education, and it would be easy to assume that all individuals embrace technology. However, evidence shows that roughly 30 to 40 percent of individuals experience some level of computer anxiety. Many academic programs involve computing-intensive courses, but the actual effects of this exposure on computer…

Accelerating Climate Simulations Through Hybrid Computing

NASA Technical Reports Server (NTRS)

Zhou, Shujia; Sinno, Scott; Cruz, Carlos; Purcell, Mark

2009-01-01

Unconventional multi-core processors (e.g., IBM Cell B/E and NYIDIDA GPU) have emerged as accelerators in climate simulation. However, climate models typically run on parallel computers with conventional processors (e.g., Intel and AMD) using MPI. Connecting accelerators to this architecture efficiently and easily becomes a critical issue. When using MPI for connection, we identified two challenges: (1) identical MPI implementation is required in both systems, and; (2) existing MPI code must be modified to accommodate the accelerators. In response, we have extended and deployed IBM Dynamic Application Virtualization (DAV) in a hybrid computing prototype system (one blade with two Intel quad-core processors, two IBM QS22 Cell blades, connected with Infiniband), allowing for seamlessly offloading compute-intensive functions to remote, heterogeneous accelerators in a scalable, load-balanced manner. Currently, a climate solar radiation model running with multiple MPI processes has been offloaded to multiple Cell blades with approx.10% network overhead.

Data and results of a laboratory investigation of microprocessor upset caused by simulated lightning-induced analog transients

NASA Technical Reports Server (NTRS)

Belcastro, C. M.

1984-01-01

Advanced composite aircraft designs include fault-tolerant computer-based digital control systems with thigh reliability requirements for adverse as well as optimum operating environments. Since aircraft penetrate intense electromagnetic fields during thunderstorms, onboard computer systems maya be subjected to field-induced transient voltages and currents resulting in functional error modes which are collectively referred to as digital system upset. A methodology was developed for assessing the upset susceptibility of a computer system onboard an aircraft flying through a lightning environment. Upset error modes in a general-purpose microprocessor were studied via tests which involved the random input of analog transients which model lightning-induced signals onto interface lines of an 8080-based microcomputer from which upset error data were recorded. The application of Markov modeling to upset susceptibility estimation is discussed and a stochastic model development.

Computationally-efficient optical coherence elastography to assess degenerative osteoarthritis based on ultrasound-induced fringe washout (Conference Presentation)

NASA Astrophysics Data System (ADS)

Tong, Minh Q.; Hasan, M. Monirul; Gregory, Patrick D.; Shah, Jasmine; Park, B. Hyle; Hirota, Koji; Liu, Junze; Choi, Andy; Low, Karen; Nam, Jin

2017-02-01

We demonstrate a computationally-efficient optical coherence elastography (OCE) method based on fringe washout. By introducing ultrasound in alternating depth profile, we can obtain information on the mechanical properties of a sample within acquisition of a single image. This can be achieved by simply comparing the intensity in adjacent depth profiles in order to quantify the degree of fringe washout. Phantom agar samples with various densities were measured and quantified by our OCE technique, the correlation to Young's modulus measurement by atomic force micrscopy (AFM) were observed. Knee cartilage samples of monoiodo acetate-induced arthiritis (MIA) rat models were utilized to replicate cartilage damages where our proposed OCE technique along with intensity and birefringence analyses and AFM measurements were applied. The results indicate that our OCE technique shows a correlation to the techniques as polarization-sensitive OCT, AFM Young's modulus measurements and histology were promising. Our OCE is applicable to any of existing OCT systems and demonstrated to be computationally-efficient.

The Dynamo package for tomography and subtomogram averaging: components for MATLAB, GPU computing and EC2 Amazon Web Services

PubMed Central

Castaño-Díez, Daniel

2017-01-01

Dynamo is a package for the processing of tomographic data. As a tool for subtomogram averaging, it includes different alignment and classification strategies. Furthermore, its data-management module allows experiments to be organized in groups of tomograms, while offering specialized three-dimensional tomographic browsers that facilitate visualization, location of regions of interest, modelling and particle extraction in complex geometries. Here, a technical description of the package is presented, focusing on its diverse strategies for optimizing computing performance. Dynamo is built upon mbtools (middle layer toolbox), a general-purpose MATLAB library for object-oriented scientific programming specifically developed to underpin Dynamo but usable as an independent tool. Its structure intertwines a flexible MATLAB codebase with precompiled C++ functions that carry the burden of numerically intensive operations. The package can be delivered as a precompiled standalone ready for execution without a MATLAB license. Multicore parallelization on a single node is directly inherited from the high-level parallelization engine provided for MATLAB, automatically imparting a balanced workload among the threads in computationally intense tasks such as alignment and classification, but also in logistic-oriented tasks such as tomogram binning and particle extraction. Dynamo supports the use of graphical processing units (GPUs), yielding considerable speedup factors both for native Dynamo procedures (such as the numerically intensive subtomogram alignment) and procedures defined by the user through its MATLAB-based GPU library for three-dimensional operations. Cloud-based virtual computing environments supplied with a pre-installed version of Dynamo can be publicly accessed through the Amazon Elastic Compute Cloud (EC2), enabling users to rent GPU computing time on a pay-as-you-go basis, thus avoiding upfront investments in hardware and longterm software maintenance. PMID:28580909

The Dynamo package for tomography and subtomogram averaging: components for MATLAB, GPU computing and EC2 Amazon Web Services.

PubMed

Castaño-Díez, Daniel

2017-06-01

Dynamo is a package for the processing of tomographic data. As a tool for subtomogram averaging, it includes different alignment and classification strategies. Furthermore, its data-management module allows experiments to be organized in groups of tomograms, while offering specialized three-dimensional tomographic browsers that facilitate visualization, location of regions of interest, modelling and particle extraction in complex geometries. Here, a technical description of the package is presented, focusing on its diverse strategies for optimizing computing performance. Dynamo is built upon mbtools (middle layer toolbox), a general-purpose MATLAB library for object-oriented scientific programming specifically developed to underpin Dynamo but usable as an independent tool. Its structure intertwines a flexible MATLAB codebase with precompiled C++ functions that carry the burden of numerically intensive operations. The package can be delivered as a precompiled standalone ready for execution without a MATLAB license. Multicore parallelization on a single node is directly inherited from the high-level parallelization engine provided for MATLAB, automatically imparting a balanced workload among the threads in computationally intense tasks such as alignment and classification, but also in logistic-oriented tasks such as tomogram binning and particle extraction. Dynamo supports the use of graphical processing units (GPUs), yielding considerable speedup factors both for native Dynamo procedures (such as the numerically intensive subtomogram alignment) and procedures defined by the user through its MATLAB-based GPU library for three-dimensional operations. Cloud-based virtual computing environments supplied with a pre-installed version of Dynamo can be publicly accessed through the Amazon Elastic Compute Cloud (EC2), enabling users to rent GPU computing time on a pay-as-you-go basis, thus avoiding upfront investments in hardware and longterm software maintenance.

Rationale, design and baseline characteristics of a randomized controlled trial of a web-based computer-tailored physical activity intervention for adults from Quebec City.

PubMed

Boudreau, François; Walthouwer, Michel Jean Louis; de Vries, Hein; Dagenais, Gilles R; Turbide, Ginette; Bourlaud, Anne-Sophie; Moreau, Michel; Côté, José; Poirier, Paul

2015-10-09

The relationship between physical activity and cardiovascular disease (CVD) protection is well documented. Numerous factors (e.g. patient motivation, lack of facilities, physician time constraints) can contribute to poor PA adherence. Web-based computer-tailored interventions offer an innovative way to provide tailored feedback and to empower adults to engage in regular moderate- to vigorous-intensity PA. To describe the rationale, design and content of a web-based computer-tailored PA intervention for Canadian adults enrolled in a randomized controlled trial (RCT). 244 men and women aged between 35 and 70 years, without CVD or physical disability, not participating in regular moderate- to vigorous-intensity PA, and familiar with and having access to a computer at home, were recruited from the Quebec City Prospective Urban and Rural Epidemiological (PURE) study centre. Participants were randomized into two study arms: 1) an experimental group receiving the intervention and 2) a waiting list control group. The fully automated web-based computer-tailored PA intervention consists of seven 10- to 15-min sessions over an 8-week period. The theoretical underpinning of the intervention is based on the I-Change Model. The aim of the intervention was to reach a total of 150 min per week of moderate- to vigorous-intensity aerobic PA. This study will provide useful information before engaging in a large RCT to assess the long-term participation and maintenance of PA, the potential impact of regular PA on CVD risk factors and the cost-effectiveness of a web-based computer-tailored intervention. ISRCTN36353353 registered on 24/07/2014.

Three-dimensional plant architecture and sunlit-shaded patterns: a stochastic model of light dynamics in canopies.

PubMed

Retkute, Renata; Townsend, Alexandra J; Murchie, Erik H; Jensen, Oliver E; Preston, Simon P

2018-05-25

Diurnal changes in solar position and intensity combined with the structural complexity of plant architecture result in highly variable and dynamic light patterns within the plant canopy. This affects productivity through the complex ways that photosynthesis responds to changes in light intensity. Current methods to characterize light dynamics, such as ray-tracing, are able to produce data with excellent spatio-temporal resolution but are computationally intensive and the resulting data are complex and high-dimensional. This necessitates development of more economical models for summarizing the data and for simulating realistic light patterns over the course of a day. High-resolution reconstructions of field-grown plants are assembled in various configurations to form canopies, and a forward ray-tracing algorithm is applied to the canopies to compute light dynamics at high (1 min) temporal resolution. From the ray-tracer output, the sunlit or shaded state for each patch on the plants is determined, and these data are used to develop a novel stochastic model for the sunlit-shaded patterns. The model is designed to be straightforward to fit to data using maximum likelihood estimation, and fast to simulate from. For a wide range of contrasting 3-D canopies, the stochastic model is able to summarize, and replicate in simulations, key features of the light dynamics. When light patterns simulated from the stochastic model are used as input to a model of photoinhibition, the predicted reduction in carbon gain is similar to that from calculations based on the (extremely costly) ray-tracer data. The model provides a way to summarize highly complex data in a small number of parameters, and a cost-effective way to simulate realistic light patterns. Simulations from the model will be particularly useful for feeding into larger-scale photosynthesis models for calculating how light dynamics affects the photosynthetic productivity of canopies.

Improving the Efficiency of Abdominal Aortic Aneurysm Wall Stress Computations

PubMed Central

Zelaya, Jaime E.; Goenezen, Sevan; Dargon, Phong T.; Azarbal, Amir-Farzin; Rugonyi, Sandra

2014-01-01

An abdominal aortic aneurysm is a pathological dilation of the abdominal aorta, which carries a high mortality rate if ruptured. The most commonly used surrogate marker of rupture risk is the maximal transverse diameter of the aneurysm. More recent studies suggest that wall stress from models of patient-specific aneurysm geometries extracted, for instance, from computed tomography images may be a more accurate predictor of rupture risk and an important factor in AAA size progression. However, quantification of wall stress is typically computationally intensive and time-consuming, mainly due to the nonlinear mechanical behavior of the abdominal aortic aneurysm walls. These difficulties have limited the potential of computational models in clinical practice. To facilitate computation of wall stresses, we propose to use a linear approach that ensures equilibrium of wall stresses in the aneurysms. This proposed linear model approach is easy to implement and eliminates the burden of nonlinear computations. To assess the accuracy of our proposed approach to compute wall stresses, results from idealized and patient-specific model simulations were compared to those obtained using conventional approaches and to those of a hypothetical, reference abdominal aortic aneurysm model. For the reference model, wall mechanical properties and the initial unloaded and unstressed configuration were assumed to be known, and the resulting wall stresses were used as reference for comparison. Our proposed linear approach accurately approximates wall stresses for varying model geometries and wall material properties. Our findings suggest that the proposed linear approach could be used as an effective, efficient, easy-to-use clinical tool to estimate patient-specific wall stresses. PMID:25007052

Hybrid supply chain model for material requirement planning under financial constraints: A case study

NASA Astrophysics Data System (ADS)

Curci, Vita; Dassisti, Michele; Josefa, Mula Bru; Manuel, Díaz Madroñero

2014-10-01

Supply chain model (SCM) are potentially capable to integrate different aspects in supporting decision making for enterprise management tasks. The aim of the paper is to propose an hybrid mathematical programming model for optimization of production requirements resources planning. The preliminary model was conceived bottom-up from a real industrial case analysed oriented to maximize cash flow. Despite the intense computational effort required to converge to a solution, optimisation done brought good result in solving the objective function.

Understanding Coronal Heating through Time-Series Analysis and Nanoflare Modeling

NASA Astrophysics Data System (ADS)

Romich, Kristine; Viall, Nicholeen

2018-01-01

Periodic intensity fluctuations in coronal loops, a signature of temperature evolution, have been observed using the Atmospheric Imaging Assembly (AIA) aboard NASA’s Solar Dynamics Observatory (SDO) spacecraft. We examine the proposal that nanoflares, or impulsive bursts of energy release in the solar atmosphere, are responsible for the intensity fluctuations as well as the megakelvin-scale temperatures observed in the corona. Drawing on the work of Cargill (2014) and Bradshaw & Viall (2016), we develop a computer model of the energy released by a sequence of nanoflare events in a single magnetic flux tube. We then use EBTEL (Enthalpy-Based Thermal Evolution of Loops), a hydrodynamic model of plasma response to energy input, to simulate intensity as a function of time across the coronal AIA channels. We test the EBTEL output for periodicities using a spectral code based on Mann and Lees’ (1996) multitaper method and present preliminary results here. Our ultimate goal is to establish whether quasi-continuous or impulsive energy bursts better approximate the original SDO data.

The 1895 Ljubljana earthquake: can the intensity data points discriminate which one of the nearby faults was the causative one?

NASA Astrophysics Data System (ADS)

Tiberi, Lara; Costa, Giovanni; Jamšek Rupnik, Petra; Cecić, Ina; Suhadolc, Peter

2018-05-01

The earthquake (Mw 6 from the SHEEC defined by the MDPs) that occurred in the central part of Slovenia on 14 April, 1895, affected a broad region, causing deaths, injuries, and destruction. This event was much studied but not fully explained; in particular, its causative source model is still debated. The aim of this work is to contribute to the identification of the seismogenic source of this destructive event, calculating peak ground velocity values through the use of different ground motion prediction equations (GMPEs) and computing a series of ground motion scenarios based on the result of an inversion work proposed by Jukić in 2009 and on various fault models in the surroundings of Ljubljana: Vič, Želimlje, Borovnica, Vodice, Ortnek, Mišjedolski, and Dobrepolje faults. The synthetic seismograms, at the basis of our computations, are calculated using the multi-modal summation technique and a kinematic approach for extended sources, with a maximum peak ground velocity value of 1 Hz. The qualitative and quantitative comparison of these simulations with the macroseismic intensity database allows us to discriminate between various sources and configurations. The quantitative validation of the seismic source is done using ad hoc ground motion to intensity conversion equations (GMICEs), expressly calculated for this study. This study allows us to identify the most probable causative source model of this event, contributing to the improvement of the seismotectonic knowledge of this region. The candidate fault that has the lowest values of average differences between observed and calculated intensities and chi-squared is a strike slip fault with a toward-north rupture as the Ortnek fault.

MultiPhyl: a high-throughput phylogenomics webserver using distributed computing

PubMed Central

Keane, Thomas M.; Naughton, Thomas J.; McInerney, James O.

2007-01-01

With the number of fully sequenced genomes increasing steadily, there is greater interest in performing large-scale phylogenomic analyses from large numbers of individual gene families. Maximum likelihood (ML) has been shown repeatedly to be one of the most accurate methods for phylogenetic construction. Recently, there have been a number of algorithmic improvements in maximum-likelihood-based tree search methods. However, it can still take a long time to analyse the evolutionary history of many gene families using a single computer. Distributed computing refers to a method of combining the computing power of multiple computers in order to perform some larger overall calculation. In this article, we present the first high-throughput implementation of a distributed phylogenetics platform, MultiPhyl, capable of using the idle computational resources of many heterogeneous non-dedicated machines to form a phylogenetics supercomputer. MultiPhyl allows a user to upload hundreds or thousands of amino acid or nucleotide alignments simultaneously and perform computationally intensive tasks such as model selection, tree searching and bootstrapping of each of the alignments using many desktop machines. The program implements a set of 88 amino acid models and 56 nucleotide maximum likelihood models and a variety of statistical methods for choosing between alternative models. A MultiPhyl webserver is available for public use at: http://www.cs.nuim.ie/distributed/multiphyl.php. PMID:17553837

Model selection for the North American Breeding Bird Survey: A comparison of methods

USGS Publications Warehouse

Link, William; Sauer, John; Niven, Daniel

2017-01-01

The North American Breeding Bird Survey (BBS) provides data for >420 bird species at multiple geographic scales over 5 decades. Modern computational methods have facilitated the fitting of complex hierarchical models to these data. It is easy to propose and fit new models, but little attention has been given to model selection. Here, we discuss and illustrate model selection using leave-one-out cross validation, and the Bayesian Predictive Information Criterion (BPIC). Cross-validation is enormously computationally intensive; we thus evaluate the performance of the Watanabe-Akaike Information Criterion (WAIC) as a computationally efficient approximation to the BPIC. Our evaluation is based on analyses of 4 models as applied to 20 species covered by the BBS. Model selection based on BPIC provided no strong evidence of one model being consistently superior to the others; for 14/20 species, none of the models emerged as superior. For the remaining 6 species, a first-difference model of population trajectory was always among the best fitting. Our results show that WAIC is not reliable as a surrogate for BPIC. Development of appropriate model sets and their evaluation using BPIC is an important innovation for the analysis of BBS data.

A Bayesian and Physics-Based Ground Motion Parameters Map Generation System

NASA Astrophysics Data System (ADS)

Ramirez-Guzman, L.; Quiroz, A.; Sandoval, H.; Perez-Yanez, C.; Ruiz, A. L.; Delgado, R.; Macias, M. A.; Alcántara, L.

2014-12-01

We present the Ground Motion Parameters Map Generation (GMPMG) system developed by the Institute of Engineering at the National Autonomous University of Mexico (UNAM). The system delivers estimates of information associated with the social impact of earthquakes, engineering ground motion parameters (gmp), and macroseismic intensity maps. The gmp calculated are peak ground acceleration and velocity (pga and pgv) and response spectral acceleration (SA). The GMPMG relies on real-time data received from strong ground motion stations belonging to UNAM's networks throughout Mexico. Data are gathered via satellite and internet service providers, and managed with the data acquisition software Earthworm. The system is self-contained and can perform all calculations required for estimating gmp and intensity maps due to earthquakes, automatically or manually. An initial data processing, by baseline correcting and removing records containing glitches or low signal-to-noise ratio, is performed. The system then assigns a hypocentral location using first arrivals and a simplified 3D model, followed by a moment tensor inversion, which is performed using a pre-calculated Receiver Green's Tensors (RGT) database for a realistic 3D model of Mexico. A backup system to compute epicentral location and magnitude is in place. A Bayesian Kriging is employed to combine recorded values with grids of computed gmp. The latter are obtained by using appropriate ground motion prediction equations (for pgv, pga and SA with T=0.3, 0.5, 1 and 1.5 s ) and numerical simulations performed in real time, using the aforementioned RGT database (for SA with T=2, 2.5 and 3 s). Estimated intensity maps are then computed using SA(T=2S) to Modified Mercalli Intensity correlations derived for central Mexico. The maps are made available to the institutions in charge of the disaster prevention systems. In order to analyze the accuracy of the maps, we compare them against observations not considered in the computations, and present some examples of recent earthquakes. We conclude that the system provides information with a fair goodness-of-fit against observations. This project is partially supported by DGAPA-PAPIIT (UNAM) project TB100313-RR170313.

Defining the computational structure of the motion detector in Drosophila.

PubMed

Clark, Damon A; Bursztyn, Limor; Horowitz, Mark A; Schnitzer, Mark J; Clandinin, Thomas R

2011-06-23

Many animals rely on visual motion detection for survival. Motion information is extracted from spatiotemporal intensity patterns on the retina, a paradigmatic neural computation. A phenomenological model, the Hassenstein-Reichardt correlator (HRC), relates visual inputs to neural activity and behavioral responses to motion, but the circuits that implement this computation remain unknown. By using cell-type specific genetic silencing, minimal motion stimuli, and in vivo calcium imaging, we examine two critical HRC inputs. These two pathways respond preferentially to light and dark moving edges. We demonstrate that these pathways perform overlapping but complementary subsets of the computations underlying the HRC. A numerical model implementing differential weighting of these operations displays the observed edge preferences. Intriguingly, these pathways are distinguished by their sensitivities to a stimulus correlation that corresponds to an illusory percept, "reverse phi," that affects many species. Thus, this computational architecture may be widely used to achieve edge selectivity in motion detection. Copyright © 2011 Elsevier Inc. All rights reserved.

Integration of scheduling and discrete event simulation systems to improve production flow planning

NASA Astrophysics Data System (ADS)

Krenczyk, D.; Paprocka, I.; Kempa, W. M.; Grabowik, C.; Kalinowski, K.

2016-08-01

The increased availability of data and computer-aided technologies such as MRPI/II, ERP and MES system, allowing producers to be more adaptive to market dynamics and to improve production scheduling. Integration of production scheduling and computer modelling, simulation and visualization systems can be useful in the analysis of production system constraints related to the efficiency of manufacturing systems. A integration methodology based on semi-automatic model generation method for eliminating problems associated with complexity of the model and labour-intensive and time-consuming process of simulation model creation is proposed. Data mapping and data transformation techniques for the proposed method have been applied. This approach has been illustrated through examples of practical implementation of the proposed method using KbRS scheduling system and Enterprise Dynamics simulation system.

AUTOMATED GIS WATERSHED ANALYSIS TOOLS FOR RUSLE/SEDMOD SOIL EROSION AND SEDIMENTATION MODELING

EPA Science Inventory

A comprehensive procedure for computing soil erosion and sediment delivery metrics has been developed using a suite of automated Arc Macro Language (AML ) scripts and a pair of processing- intensive ANSI C++ executable programs operating on an ESRI ArcGIS 8.x Workstation platform...

In vitro data and in silico models for computational toxicology (Teratology Society ILSI HESI workshop)

EPA Science Inventory

The challenge of assessing the potential developmental health risks for the tens of thousands of environmental chemicals is beyond the capacity for resource-intensive animal protocols. Large data streams coming from high-throughput (HTS) and high-content (HCS) profiling of biolog...

Extending the Utility of the Parabolic Approximation in Medical Ultrasound Using Wide-Angle Diffraction Modeling.

PubMed

Soneson, Joshua E

2017-04-01

Wide-angle parabolic models are commonly used in geophysics and underwater acoustics but have seen little application in medical ultrasound. Here, a wide-angle model for continuous-wave high-intensity ultrasound beams is derived, which approximates the diffraction process more accurately than the commonly used Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation without increasing implementation complexity or computing time. A method for preventing the high spatial frequencies often present in source boundary conditions from corrupting the solution is presented. Simulations of shallowly focused axisymmetric beams using both the wide-angle and standard parabolic models are compared to assess the accuracy with which they model diffraction effects. The wide-angle model proposed here offers improved focusing accuracy and less error throughout the computational domain than the standard parabolic model, offering a facile method for extending the utility of existing KZK codes.

Low-frequency sound propagation modeling over a locally-reacting boundary using the parabolic approximation

NASA Technical Reports Server (NTRS)

Robertson, J. S.; Siegman, W. L.; Jacobson, M. J.

1989-01-01

There is substantial interest in the analytical and numerical modeling of low-frequency, long-range atmospheric acoustic propagation. Ray-based models, because of frequency limitations, do not always give an adequate prediction of quantities such as sound pressure or intensity levels. However, the parabolic approximation method, widely used in ocean acoustics, and often more accurate than ray models for lower frequencies of interest, can be applied to acoustic propagation in the atmosphere. Modifications of an existing implicit finite-difference implementation for computing solutions to the parabolic approximation are discussed. A locally-reacting boundary is used together with a one-parameter impedance model. Intensity calculations are performed for a number of flow resistivity values in both quiescent and windy atmospheres. Variations in the value of this parameter are shown to have substantial effects on the spatial variation of the acoustic signal.

Data intensive computing at Sandia.

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

Wilson, Andrew T.

2010-09-01

Data-Intensive Computing is parallel computing where you design your algorithms and your software around efficient access and traversal of a data set; where hardware requirements are dictated by data size as much as by desired run times usually distilling compact results from massive data.

CT to Cone-beam CT Deformable Registration With Simultaneous Intensity Correction

PubMed Central

Zhen, Xin; Gu, Xuejun; Yan, Hao; Zhou, Linghong; Jia, Xun; Jiang, Steve B.

2012-01-01

Computed tomography (CT) to cone-beam computed tomography (CBCT) deformable image registration (DIR) is a crucial step in adaptive radiation therapy. Current intensity-based registration algorithms, such as demons, may fail in the context of CT-CBCT DIR because of inconsistent intensities between the two modalities. In this paper, we propose a variant of demons, called Deformation with Intensity Simultaneously Corrected (DISC), to deal with CT-CBCT DIR. DISC distinguishes itself from the original demons algorithm by performing an adaptive intensity correction step on the CBCT image at every iteration step of the demons registration. Specifically, the intensity correction of a voxel in CBCT is achieved by matching the first and the second moments of the voxel intensities inside a patch around the voxel with those on the CT image. It is expected that such a strategy can remove artifacts in the CBCT image, as well as ensuring the intensity consistency between the two modalities. DISC is implemented on computer graphics processing units (GPUs) in compute unified device architecture (CUDA) programming environment. The performance of DISC is evaluated on a simulated patient case and six clinical head-and-neck cancer patient data. It is found that DISC is robust against the CBCT artifacts and intensity inconsistency and significantly improves the registration accuracy when compared with the original demons. PMID:23032638

A Bayesian approach for parameter estimation and prediction using a computationally intensive model

DOE PAGES

Higdon, Dave; McDonnell, Jordan D.; Schunck, Nicolas; ...

2015-02-05

Bayesian methods have been successful in quantifying uncertainty in physics-based problems in parameter estimation and prediction. In these cases, physical measurements y are modeled as the best fit of a physics-based modelmore » $$\\eta (\\theta )$$, where θ denotes the uncertain, best input setting. Hence the statistical model is of the form $$y=\\eta (\\theta )+\\epsilon ,$$ where $$\\epsilon $$ accounts for measurement, and possibly other, error sources. When nonlinearity is present in $$\\eta (\\cdot )$$, the resulting posterior distribution for the unknown parameters in the Bayesian formulation is typically complex and nonstandard, requiring computationally demanding computational approaches such as Markov chain Monte Carlo (MCMC) to produce multivariate draws from the posterior. Although generally applicable, MCMC requires thousands (or even millions) of evaluations of the physics model $$\\eta (\\cdot )$$. This requirement is problematic if the model takes hours or days to evaluate. To overcome this computational bottleneck, we present an approach adapted from Bayesian model calibration. This approach combines output from an ensemble of computational model runs with physical measurements, within a statistical formulation, to carry out inference. A key component of this approach is a statistical response surface, or emulator, estimated from the ensemble of model runs. We demonstrate this approach with a case study in estimating parameters for a density functional theory model, using experimental mass/binding energy measurements from a collection of atomic nuclei. Lastly, we also demonstrate how this approach produces uncertainties in predictions for recent mass measurements obtained at Argonne National Laboratory.« less

Automatic liver segmentation from abdominal CT volumes using graph cuts and border marching.

PubMed

Liao, Miao; Zhao, Yu-Qian; Liu, Xi-Yao; Zeng, Ye-Zhan; Zou, Bei-Ji; Wang, Xiao-Fang; Shih, Frank Y

2017-05-01

Identifying liver regions from abdominal computed tomography (CT) volumes is an important task for computer-aided liver disease diagnosis and surgical planning. This paper presents a fully automatic method for liver segmentation from CT volumes based on graph cuts and border marching. An initial slice is segmented by density peak clustering. Based on pixel- and patch-wise features, an intensity model and a PCA-based regional appearance model are developed to enhance the contrast between liver and background. Then, these models as well as the location constraint estimated iteratively are integrated into graph cuts in order to segment the liver in each slice automatically. Finally, a vessel compensation method based on the border marching is used to increase the segmentation accuracy. Experiments are conducted on a clinical data set we created and also on the MICCAI2007 Grand Challenge liver data. The results show that the proposed intensity, appearance models, and the location constraint are significantly effective for liver recognition, and the undersegmented vessels can be compensated by the border marching based method. The segmentation performances in terms of VOE, RVD, ASD, RMSD, and MSD as well as the average running time achieved by our method on the SLIVER07 public database are 5.8 ± 3.2%, -0.1 ± 4.1%, 1.0 ± 0.5mm, 2.0 ± 1.2mm, 21.2 ± 9.3mm, and 4.7 minutes, respectively, which are superior to those of existing methods. The proposed method does not require time-consuming training process and statistical model construction, and is capable of dealing with complicated shapes and intensity variations successfully. Copyright © 2017 Elsevier B.V. All rights reserved.

Geographic Information System and Remote Sensing Approach with Hydrologic Rational Model for Flood Event Analysis in Jakarta

NASA Astrophysics Data System (ADS)

Aditya, M. R.; Hernina, R.; Rokhmatuloh

2017-12-01

Rapid development in Jakarta which generates more impervious surface has reduced the amount of rainfall infiltration into soil layer and increases run-off. In some events, continuous high rainfall intensity could create sudden flood in Jakarta City. This article used rainfall data of Jakarta during 10 February 2015 to compute rainfall intensity and then interpolate it with ordinary kriging technique. Spatial distribution of rainfall intensity then overlaid with run-off coefficient based on certain land use type of the study area. Peak run-off within each cell resulted from hydrologic rational model then summed for the whole study area to generate total peak run-off. For this study area, land use types consisted of 51.9 % industrial, 37.57% parks, and 10.54% residential with estimated total peak run-off 6.04 m3/sec, 0.39 m3/sec, and 0.31 m3/sec, respectively.

Center for Technology for Advanced Scientific Componet Software (TASCS)

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

Govindaraju, Madhusudhan

Advanced Scientific Computing Research Computer Science FY 2010Report Center for Technology for Advanced Scientific Component Software: Distributed CCA State University of New York, Binghamton, NY, 13902 Summary The overall objective of Binghamton's involvement is to work on enhancements of the CCA environment, motivated by the applications and research initiatives discussed in the proposal. This year we are working on re-focusing our design and development efforts to develop proof-of-concept implementations that have the potential to significantly impact scientific components. We worked on developing parallel implementations for non-hydrostatic code and worked on a model coupling interface for biogeochemical computations coded in MATLAB.more » We also worked on the design and implementation modules that will be required for the emerging MapReduce model to be effective for scientific applications. Finally, we focused on optimizing the processing of scientific datasets on multi-core processors. Research Details We worked on the following research projects that we are working on applying to CCA-based scientific applications. 1. Non-Hydrostatic Hydrodynamics: Non-static hydrodynamics are significantly more accurate at modeling internal waves that may be important in lake ecosystems. Non-hydrostatic codes, however, are significantly more computationally expensive, often prohibitively so. We have worked with Chin Wu at the University of Wisconsin to parallelize non-hydrostatic code. We have obtained a speed up of about 26 times maximum. Although this is significant progress, we hope to improve the performance further, such that it becomes a practical alternative to hydrostatic codes. 2. Model-coupling for water-based ecosystems: To answer pressing questions about water resources requires that physical models (hydrodynamics) be coupled with biological and chemical models. Most hydrodynamics codes are written in Fortran, however, while most ecologists work in MATLAB. This disconnect creates a great barrier. To address this, we are working on a model coupling interface that will allow biogeochemical computations written in MATLAB to couple with Fortran codes. This will greatly improve the productivity of ecosystem scientists. 2. Low overhead and Elastic MapReduce Implementation Optimized for Memory and CPU-Intensive Applications: Since its inception, MapReduce has frequently been associated with Hadoop and large-scale datasets. Its deployment at Amazon in the cloud, and its applications at Yahoo! for large-scale distributed document indexing and database building, among other tasks, have thrust MapReduce to the forefront of the data processing application domain. The applicability of the paradigm however extends far beyond its use with data intensive applications and diskbased systems, and can also be brought to bear in processing small but CPU intensive distributed applications. MapReduce however carries its own burdens. Through experiments using Hadoop in the context of diverse applications, we uncovered latencies and delay conditions potentially inhibiting the expected performance of a parallel execution in CPU-intensive applications. Furthermore, as it currently stands, MapReduce is favored for data-centric applications, and as such tends to be solely applied to disk-based applications. The paradigm, falls short in bringing its novelty to diskless systems dedicated to in-memory applications, and compute intensive programs processing much smaller data, but requiring intensive computations. In this project, we focused both on the performance of processing large-scale hierarchical data in distributed scientific applications, as well as the processing of smaller but demanding input sizes primarily used in diskless, and memory resident I/O systems. We designed LEMO-MR [1], a Low overhead, elastic, configurable for in- memory applications, and on-demand fault tolerance, an optimized implementation of MapReduce, for both on disk and in memory applications. We conducted experiments to identify not only the necessary components of this model, but also trade offs and factors to be considered. We have initial results to show the efficacy of our implementation in terms of potential speedup that can be achieved for representative data sets used by cloud applications. We have quantified the performance gains exhibited by our MapReduce implementation over Apache Hadoop in a compute intensive environment. 3. Cache Performance Optimization for Processing XML and HDF-based Application Data on Multi-core Processors: It is important to design and develop scientific middleware libraries to harness the opportunities presented by emerging multi-core processors. Implementations of scientific middleware and applications that do not adapt to the programming paradigm when executing on emerging processors can severely impact the overall performance. In this project, we focused on the utilization of the L2 cache, which is a critical shared resource on chip multiprocessors (CMP). The access pattern of the shared L2 cache, which is dependent on how the application schedules and assigns processing work to each thread, can either enhance or hurt the ability to hide memory latency on a multi-core processor. Therefore, while processing scientific datasets such as HDF5, it is essential to conduct fine-grained analysis of cache utilization, to inform scheduling decisions in multi-threaded programming. In this project, using the TAU toolkit for performance feedback from dual- and quad-core machines, we conducted performance analysis and recommendations on how processing threads can be scheduled on multi-core nodes to enhance the performance of a class of scientific applications that requires processing of HDF5 data. In particular, we quantified the gains associated with the use of the adaptations we have made to the Cache-Affinity and Balanced-Set scheduling algorithms to improve L2 cache performance, and hence the overall application execution time [2]. References: 1. Zacharia Fadika, Madhusudhan Govindaraju, ``MapReduce Implementation for Memory-Based and Processing Intensive Applications'', accepted in 2nd IEEE International Conference on Cloud Computing Technology and Science, Indianapolis, USA, Nov 30 - Dec 3, 2010. 2. Rajdeep Bhowmik, Madhusudhan Govindaraju, ``Cache Performance Optimization for Processing XML-based Application Data on Multi-core Processors'', in proceedings of The 10th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, May 17-20, 2010, Melbourne, Victoria, Australia. Contact Information: Madhusudhan Govindaraju Binghamton University State University of New York (SUNY) mgovinda@cs.binghamton.edu Phone: 607-777-4904« less

A comparative study of highly-ionized Al plasma based on dual pulse laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Khalil, A. A. I.; Younis, W. O.; Gandol, M. A.

2017-03-01

We built a collinear dual-pulse laser-induced breakdown spectroscopy (DP-LIBS) system to study the aluminum (Al) plasma emission by installing a pair of Nd: YAG lasers operating at 266 and 1064 nm. The spectral intensities of selected aluminum doubly-ionized lines were employed to evaluate the optical emission spectra. The influences of the energy ratio of two pulsed lasers on the LIBS intensity for different Al doubly-ionized spectral lines were investigated. The de-excitation rate parameters of the excited ion and the electron impact excitation were computed using the analytical formulas proposed by Smeets and Vriens. The transition probabilities and energy states were computed using Hibbert's configuration interaction, computer package (CIV3). By solving the coupled rate equations including 1 s 22 s 22 p 6n s (2S), 1 s 22 s 22 p 6n p (2P), 1 s 22 s 22 p 6n d (2D) (n = 3-5) and 1 s 22 s 22 p 6n f (2F) (n = 4, 5) states, the level population densities were computed. We also proposed a theoretical population model in order to investigate the effectiveness of the various processes that might affect the population of the upper levels in Al plasma by using the rate coefficients. In addition, the population densities for the 19 upper levels were also computed. Good compatibility between the experimental and the theoretical model data had been observed. Our results might be significant as reference data for the optimization of the DP-LIBS spectrometry and diagnostics of laser produced plasmas.

Effect of low-intensity pulsed ultrasound stimulation on gap healing in a rabbit osteotomy model evaluated by quantitative micro-computed tomography-based cross-sectional moment of inertia.

PubMed

Tobita, Kenji; Matsumoto, Takuya; Ohashi, Satoru; Bessho, Masahiko; Kaneko, Masako; Ohnishi, Isao

2012-07-01

It has been previously demonstrated that low-intensity pulsed ultrasound stimulation (LIPUS) enhances formation of the medullary canal and cortex in a gap-healing model of the tibia in rabbits, shortens the time required for remodeling, and enhances mineralization of the callus. In the current study, the mechanical integrity of these models was confirmed. In order to do this, the cross-sectional moment of inertia (CSMI) obtained from quantitative micro-computed tomography scans was calculated, and a comparison was made with a four-point bending test. This parameter can be analyzed in any direction, and three directions were selected in order to adopt an XYZ coordinate (X and Y for bending; Z for torsion). The present results demonstrated that LIPUS improved earlier restoration of bending stiffness at the healing site. In addition, LIPUS was effective not only in the ultrasound-irradiated plane, but also in the other two planes. CSMI may provide the structural as well as compositional determinants to assess fracture healing and would be very useful to replace the mechanical testing.

A feasibility study on porting the community land model onto accelerators using OpenACC

DOE PAGES

Wang, Dali; Wu, Wei; Winkler, Frank; ...

2014-01-01

As environmental models (such as Accelerated Climate Model for Energy (ACME), Parallel Reactive Flow and Transport Model (PFLOTRAN), Arctic Terrestrial Simulator (ATS), etc.) became more and more complicated, we are facing enormous challenges regarding to porting those applications onto hybrid computing architecture. OpenACC appears as a very promising technology, therefore, we have conducted a feasibility analysis on porting the Community Land Model (CLM), a terrestrial ecosystem model within the Community Earth System Models (CESM)). Specifically, we used automatic function testing platform to extract a small computing kernel out of CLM, then we apply this kernel into the actually CLM dataflowmore » procedure, and investigate the strategy of data parallelization and the benefit of data movement provided by current implementation of OpenACC. Even it is a non-intensive kernel, on a single 16-core computing node, the performance (based on the actual computation time using one GPU) of OpenACC implementation is 2.3 time faster than that of OpenMP implementation using single OpenMP thread, but it is 2.8 times slower than the performance of OpenMP implementation using 16 threads. On multiple nodes, MPI_OpenACC implementation demonstrated very good scalability on up to 128 GPUs on 128 computing nodes. This study also provides useful information for us to look into the potential benefits of “deep copy” capability and “routine” feature of OpenACC standards. In conclusion, we believe that our experience on the environmental model, CLM, can be beneficial to many other scientific research programs who are interested to porting their large scale scientific code using OpenACC onto high-end computers, empowered by hybrid computing architecture.« less

Memory-Intensive Benchmarks: IRAM vs. Cache-Based Machines

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Gaeke, Brian R.; Husbands, Parry; Li, Xiaoye S.; Oliker, Leonid; Yelick, Katherine A.; Biegel, Bryan (Technical Monitor)

2002-01-01

The increasing gap between processor and memory performance has lead to new architectural models for memory-intensive applications. In this paper, we explore the performance of a set of memory-intensive benchmarks and use them to compare the performance of conventional cache-based microprocessors to a mixed logic and DRAM processor called VIRAM. The benchmarks are based on problem statements, rather than specific implementations, and in each case we explore the fundamental hardware requirements of the problem, as well as alternative algorithms and data structures that can help expose fine-grained parallelism or simplify memory access patterns. The benchmarks are characterized by their memory access patterns, their basic control structures, and the ratio of computation to memory operation.

Hybrid method to estimate two-layered superficial tissue optical properties from simulated data of diffuse reflectance spectroscopy.

PubMed

Hsieh, Hong-Po; Ko, Fan-Hua; Sung, Kung-Bin

2018-04-20

An iterative curve fitting method has been applied in both simulation [J. Biomed. Opt.17, 107003 (2012)JBOPFO1083-366810.1117/1.JBO.17.10.107003] and phantom [J. Biomed. Opt.19, 077002 (2014)JBOPFO1083-366810.1117/1.JBO.19.7.077002] studies to accurately extract optical properties and the top layer thickness of a two-layered superficial tissue model from diffuse reflectance spectroscopy (DRS) data. This paper describes a hybrid two-step parameter estimation procedure to address two main issues of the previous method, including (1) high computational intensity and (2) converging to local minima. The parameter estimation procedure contained a novel initial estimation step to obtain an initial guess, which was used by a subsequent iterative fitting step to optimize the parameter estimation. A lookup table was used in both steps to quickly obtain reflectance spectra and reduce computational intensity. On simulated DRS data, the proposed parameter estimation procedure achieved high estimation accuracy and a 95% reduction of computational time compared to previous studies. Furthermore, the proposed initial estimation step led to better convergence of the following fitting step. Strategies used in the proposed procedure could benefit both the modeling and experimental data processing of not only DRS but also related approaches such as near-infrared spectroscopy.

Main field and secular variation candidate models for the 12th IGRF generation after 10 months of Swarm measurements

NASA Astrophysics Data System (ADS)

Saturnino, Diana; Langlais, Benoit; Civet, François; Thébault, Erwan; Mandea, Mioara

2015-06-01

We describe the main field and secular variation candidate models for the 12th generation of the International Geomagnetic Reference Field model. These two models are derived from the same parent model, in which the main field is extrapolated to epoch 2015.0 using its associated secular variation. The parent model is exclusively based on measurements acquired by the European Space Agency Swarm mission between its launch on 11/22/2013 and 09/18/2014. It is computed up to spherical harmonic degree and order 25 for the main field, 13 for the secular variation, and 2 for the external field. A selection on local time rather than on true illumination of the spacecraft was chosen in order to keep more measurements. Data selection based on geomagnetic indices was used to minimize the external field contributions. Measurements were screened and outliers were carefully removed. The model uses magnetic field intensity measurements at all latitudes and magnetic field vector measurements equatorward of 50° absolute quasi-dipole magnetic latitude. A second model using only the vertical component of the measured magnetic field and the total intensity was computed. This companion model offers a slightly better fit to the measurements. These two models are compared and discussed.We discuss in particular the quality of the model which does not use the full vector measurements and underline that this approach may be used when only partial directional information is known. The candidate models and their associated companion models are retrospectively compared to the adopted IGRF which allows us to criticize our own choices.

Higher-order ice-sheet modelling accelerated by multigrid on graphics cards

NASA Astrophysics Data System (ADS)

Brædstrup, Christian; Egholm, David

2013-04-01

Higher-order ice flow modelling is a very computer intensive process owing primarily to the nonlinear influence of the horizontal stress coupling. When applied for simulating long-term glacial landscape evolution, the ice-sheet models must consider very long time series, while both high temporal and spatial resolution is needed to resolve small effects. The use of higher-order and full stokes models have therefore seen very limited usage in this field. However, recent advances in graphics card (GPU) technology for high performance computing have proven extremely efficient in accelerating many large-scale scientific computations. The general purpose GPU (GPGPU) technology is cheap, has a low power consumption and fits into a normal desktop computer. It could therefore provide a powerful tool for many glaciologists working on ice flow models. Our current research focuses on utilising the GPU as a tool in ice-sheet and glacier modelling. To this extent we have implemented the Integrated Second-Order Shallow Ice Approximation (iSOSIA) equations on the device using the finite difference method. To accelerate the computations, the GPU solver uses a non-linear Red-Black Gauss-Seidel iterator coupled with a Full Approximation Scheme (FAS) multigrid setup to further aid convergence. The GPU finite difference implementation provides the inherent parallelization that scales from hundreds to several thousands of cores on newer cards. We demonstrate the efficiency of the GPU multigrid solver using benchmark experiments.

Hierarchical Fuzzy Control Applied to Parallel Connected UPS Inverters Using Average Current Sharing Scheme

NASA Astrophysics Data System (ADS)

Singh, Santosh Kumar; Ghatak Choudhuri, Sumit

2018-05-01

Parallel connection of UPS inverters to enhance power rating is a widely accepted practice. Inter-modular circulating currents appear when multiple inverter modules are connected in parallel to supply variable critical load. Interfacing of modules henceforth requires an intensive design, using proper control strategy. The potentiality of human intuitive Fuzzy Logic (FL) control with imprecise system model is well known and thus can be utilised in parallel-connected UPS systems. Conventional FL controller is computational intensive, especially with higher number of input variables. This paper proposes application of Hierarchical-Fuzzy Logic control for parallel connected Multi-modular inverters system for reduced computational burden on the processor for a given switching frequency. Simulated results in MATLAB environment and experimental verification using Texas TMS320F2812 DSP are included to demonstrate feasibility of the proposed control scheme.

Using Computational Cognitive Modeling to Diagnose Possible Sources of Aviation Error

NASA Technical Reports Server (NTRS)

Byrne, M. D.; Kirlik, Alex

2003-01-01

We present a computational model of a closed-loop, pilot-aircraft-visual scene-taxiway system created to shed light on possible sources of taxi error. Creating the cognitive aspects of the model using ACT-R required us to conduct studies with subject matter experts to identify experiential adaptations pilots bring to taxiing. Five decision strategies were found, ranging from cognitively-intensive but precise, to fast, frugal but robust. We provide evidence for the model by comparing its behavior to a NASA Ames Research Center simulation of Chicago O'Hare surface operations. Decision horizons were highly variable; the model selected the most accurate strategy given time available. We found a signature in the simulation data of the use of globally robust heuristics to cope with short decision horizons as revealed by errors occurring most frequently at atypical taxiway geometries or clearance routes. These data provided empirical support for the model.

Bayesian parameter inference for stochastic biochemical network models using particle Markov chain Monte Carlo

PubMed Central

Golightly, Andrew; Wilkinson, Darren J.

2011-01-01

Computational systems biology is concerned with the development of detailed mechanistic models of biological processes. Such models are often stochastic and analytically intractable, containing uncertain parameters that must be estimated from time course data. In this article, we consider the task of inferring the parameters of a stochastic kinetic model defined as a Markov (jump) process. Inference for the parameters of complex nonlinear multivariate stochastic process models is a challenging problem, but we find here that algorithms based on particle Markov chain Monte Carlo turn out to be a very effective computationally intensive approach to the problem. Approximations to the inferential model based on stochastic differential equations (SDEs) are considered, as well as improvements to the inference scheme that exploit the SDE structure. We apply the methodology to a Lotka–Volterra system and a prokaryotic auto-regulatory network. PMID:23226583

Comparison of Coupled Radiative Flow Solutions with Project Fire 2 Flight Data

NASA Technical Reports Server (NTRS)

Olynick, David R.; Henline, W. D.; Chambers, Lin Hartung; Candler, G. V.

1995-01-01

A nonequilibrium, axisymmetric, Navier-Stokes flow solver with coupled radiation has been developed for use in the design or thermal protection systems for vehicles where radiation effects are important. The present method has been compared with an existing now and radiation solver and with the Project Fire 2 experimental data. Good agreement has been obtained over the entire Fire 2 trajectory with the experimentally determined values of the stagnation radiation intensity in the 0.2-6.2 eV range and with the total stagnation heating. The effects of a number of flow models are examined to determine which combination of physical models produces the best agreement with the experimental data. These models include radiation coupling, multitemperature thermal models, and finite rate chemistry. Finally, the computational efficiency of the present model is evaluated. The radiation properties model developed for this study is shown to offer significant computational savings compared to existing codes.

Trivariate characteristics of intensity fluctuations for heavily saturated optical systems.

PubMed

Das, Biman; Drake, Eli; Jack, John

2004-02-01

Trivariate cumulants of intensity fluctuations have been computed starting from a trivariate intensity probability distribution function, which rests on the assumption that the variation of intensity has a maximum entropy distribution with the constraint that the total intensity is constant. The assumption holds for optical systems such as a thin, long, mirrorless gas laser amplifier where under heavy gain saturation the total output approaches a constant intensity, although intensity of any mode fluctuates rapidly over the average intensity. The relations between trivariate cumulants and central moments that were needed for the computation of trivariate cumulants were derived. The results of the computation show that the cumulants have characteristic values that depend on the number of interacting modes in the system. The cumulant values approach zero when the number of modes is infinite, as expected. The results will be useful for comparison with the experimental triavariate statistics of heavily saturated optical systems such as the output from a thin, long, bidirectional gas laser amplifier.

Color segmentation in the HSI color space using the K-means algorithm

NASA Astrophysics Data System (ADS)

Weeks, Arthur R.; Hague, G. Eric

1997-04-01

Segmentation of images is an important aspect of image recognition. While grayscale image segmentation has become quite a mature field, much less work has been done with regard to color image segmentation. Until recently, this was predominantly due to the lack of available computing power and color display hardware that is required to manipulate true color images (24-bit). TOday, it is not uncommon to find a standard desktop computer system with a true-color 24-bit display, at least 8 million bytes of memory, and 2 gigabytes of hard disk storage. Segmentation of color images is not as simple as segmenting each of the three RGB color components separately. The difficulty of using the RGB color space is that it doesn't closely model the psychological understanding of color. A better color model, which closely follows that of human visual perception is the hue, saturation, intensity model. This color model separates the color components in terms of chromatic and achromatic information. Strickland et al. was able to show the importance of color in the extraction of edge features form an image. His method enhances the edges that are detectable in the luminance image with information from the saturation image. Segmentation of both the saturation and intensity components is easily accomplished with any gray scale segmentation algorithm, since these spaces are linear. The modulus 2(pi) nature of the hue color component makes its segmentation difficult. For example, a hue of 0 and 2(pi) yields the same color tint. Instead of applying separate image segmentation to each of the hue, saturation, and intensity components, a better method is to segment the chromatic component separately from the intensity component because of the importance that the chromatic information plays in the segmentation of color images. This paper presents a method of using the gray scale K-means algorithm to segment 24-bit color images. Additionally, this paper will show the importance the hue component plays in the segmentation of color images.

Architectural Aspects of Grid Computing and its Global Prospects for E-Science Community

NASA Astrophysics Data System (ADS)

Ahmad, Mushtaq

2008-05-01

The paper reviews the imminent Architectural Aspects of Grid Computing for e-Science community for scientific research and business/commercial collaboration beyond physical boundaries. Grid Computing provides all the needed facilities; hardware, software, communication interfaces, high speed internet, safe authentication and secure environment for collaboration of research projects around the globe. It provides highly fast compute engine for those scientific and engineering research projects and business/commercial applications which are heavily compute intensive and/or require humongous amounts of data. It also makes possible the use of very advanced methodologies, simulation models, expert systems and treasure of knowledge available around the globe under the umbrella of knowledge sharing. Thus it makes possible one of the dreams of global village for the benefit of e-Science community across the globe.

A parallel-processing approach to computing for the geographic sciences

USGS Publications Warehouse

Crane, Michael; Steinwand, Dan; Beckmann, Tim; Krpan, Greg; Haga, Jim; Maddox, Brian; Feller, Mark

2001-01-01

The overarching goal of this project is to build a spatially distributed infrastructure for information science research by forming a team of information science researchers and providing them with similar hardware and software tools to perform collaborative research. Four geographically distributed Centers of the U.S. Geological Survey (USGS) are developing their own clusters of low-cost personal computers into parallel computing environments that provide a costeffective way for the USGS to increase participation in the high-performance computing community. Referred to as Beowulf clusters, these hybrid systems provide the robust computing power required for conducting research into various areas, such as advanced computer architecture, algorithms to meet the processing needs for real-time image and data processing, the creation of custom datasets from seamless source data, rapid turn-around of products for emergency response, and support for computationally intense spatial and temporal modeling.

The role of fault surface geometry in the evolution of the fault deformation zone: comparing modeling with field example from the Vignanotica normal fault (Gargano, Southern Italy).

NASA Astrophysics Data System (ADS)

Maggi, Matteo; Cianfarra, Paola; Salvini, Francesco

2013-04-01

Faults have a (brittle) deformation zone that can be described as the presence of two distintive zones: an internal Fault core (FC) and an external Fault Damage Zone (FDZ). The FC is characterized by grinding processes that comminute the rock grains to a final grain-size distribution characterized by the prevalence of smaller grains over larger, represented by high fractal dimensions (up to 3.4). On the other hand, the FDZ is characterized by a network of fracture sets with characteristic attitudes (i.e. Riedel cleavages). This deformation pattern has important consequences on rock permeability. FC often represents hydraulic barriers, while FDZ, with its fracture connection, represents zones of higher permability. The observation of faults revealed that dimension and characteristics of FC and FDZ varies both in intensity and dimensions along them. One of the controlling factor in FC and FDZ development is the fault plane geometry. By changing its attitude, fault plane geometry locally alter the stress component produced by the fault kinematics and its combination with the bulk boundary conditions (regional stress field, fluid pressure, rocks rheology) is responsible for the development of zones of higher and lower fracture intensity with variable extension along the fault planes. Furthermore, the displacement along faults provides a cumulative deformation pattern that varies through time. The modeling of the fault evolution through time (4D modeling) is therefore required to fully describe the fracturing and therefore permeability. In this presentation we show a methodology developed to predict distribution of fracture intensity integrating seismic data and numerical modeling. Fault geometry is carefully reconstructed by interpolating stick lines from interpreted seismic sections converted to depth. The modeling is based on a mixed numerical/analytical method. Fault surface is discretized into cells with their geometric and rheological characteristics. For each cell, the acting stress and strength are computed by analytical laws (Coulomb failure). Total brittle deformation for each cell is then computed by cumulating the brittle failure values along the path of each cell belonging to one side onto the facing one. The brittle failure value is provided by the DF function, that is the difference between the computed shear and the strength of the cell at each step along its path by using the Frap in-house developed software. The width of the FC and the FDZ are computed as a function of the DF distribution and displacement around the fault. This methodology has been successfully applied to model the brittle deformation pattern of the Vignanotica normal fault (Gargano, Southern Italy) where fracture intensity is expressed by the dimensionless H/S ratio representing the ratio between the dimension and the spacing of homologous fracture sets (i.e., group of parallel fractures that can be ascribed to the same event/stage/stress field).

Beyond mean-field approximations for accurate and computationally efficient models of on-lattice chemical kinetics

NASA Astrophysics Data System (ADS)

Pineda, M.; Stamatakis, M.

2017-07-01

Modeling the kinetics of surface catalyzed reactions is essential for the design of reactors and chemical processes. The majority of microkinetic models employ mean-field approximations, which lead to an approximate description of catalytic kinetics by assuming spatially uncorrelated adsorbates. On the other hand, kinetic Monte Carlo (KMC) methods provide a discrete-space continuous-time stochastic formulation that enables an accurate treatment of spatial correlations in the adlayer, but at a significant computation cost. In this work, we use the so-called cluster mean-field approach to develop higher order approximations that systematically increase the accuracy of kinetic models by treating spatial correlations at a progressively higher level of detail. We further demonstrate our approach on a reduced model for NO oxidation incorporating first nearest-neighbor lateral interactions and construct a sequence of approximations of increasingly higher accuracy, which we compare with KMC and mean-field. The latter is found to perform rather poorly, overestimating the turnover frequency by several orders of magnitude for this system. On the other hand, our approximations, while more computationally intense than the traditional mean-field treatment, still achieve tremendous computational savings compared to KMC simulations, thereby opening the way for employing them in multiscale modeling frameworks.

Introduction to bioinformatics.

PubMed

Can, Tolga

2014-01-01

Bioinformatics is an interdisciplinary field mainly involving molecular biology and genetics, computer science, mathematics, and statistics. Data intensive, large-scale biological problems are addressed from a computational point of view. The most common problems are modeling biological processes at the molecular level and making inferences from collected data. A bioinformatics solution usually involves the following steps: Collect statistics from biological data. Build a computational model. Solve a computational modeling problem. Test and evaluate a computational algorithm. This chapter gives a brief introduction to bioinformatics by first providing an introduction to biological terminology and then discussing some classical bioinformatics problems organized by the types of data sources. Sequence analysis is the analysis of DNA and protein sequences for clues regarding function and includes subproblems such as identification of homologs, multiple sequence alignment, searching sequence patterns, and evolutionary analyses. Protein structures are three-dimensional data and the associated problems are structure prediction (secondary and tertiary), analysis of protein structures for clues regarding function, and structural alignment. Gene expression data is usually represented as matrices and analysis of microarray data mostly involves statistics analysis, classification, and clustering approaches. Biological networks such as gene regulatory networks, metabolic pathways, and protein-protein interaction networks are usually modeled as graphs and graph theoretic approaches are used to solve associated problems such as construction and analysis of large-scale networks.

Software for Brain Network Simulations: A Comparative Study

PubMed Central

Tikidji-Hamburyan, Ruben A.; Narayana, Vikram; Bozkus, Zeki; El-Ghazawi, Tarek A.

2017-01-01

Numerical simulations of brain networks are a critical part of our efforts in understanding brain functions under pathological and normal conditions. For several decades, the community has developed many software packages and simulators to accelerate research in computational neuroscience. In this article, we select the three most popular simulators, as determined by the number of models in the ModelDB database, such as NEURON, GENESIS, and BRIAN, and perform an independent evaluation of these simulators. In addition, we study NEST, one of the lead simulators of the Human Brain Project. First, we study them based on one of the most important characteristics, the range of supported models. Our investigation reveals that brain network simulators may be biased toward supporting a specific set of models. However, all simulators tend to expand the supported range of models by providing a universal environment for the computational study of individual neurons and brain networks. Next, our investigations on the characteristics of computational architecture and efficiency indicate that all simulators compile the most computationally intensive procedures into binary code, with the aim of maximizing their computational performance. However, not all simulators provide the simplest method for module development and/or guarantee efficient binary code. Third, a study of their amenability for high-performance computing reveals that NEST can almost transparently map an existing model on a cluster or multicore computer, while NEURON requires code modification if the model developed for a single computer has to be mapped on a computational cluster. Interestingly, parallelization is the weakest characteristic of BRIAN, which provides no support for cluster computations and limited support for multicore computers. Fourth, we identify the level of user support and frequency of usage for all simulators. Finally, we carry out an evaluation using two case studies: a large network with simplified neural and synaptic models and a small network with detailed models. These two case studies allow us to avoid any bias toward a particular software package. The results indicate that BRIAN provides the most concise language for both cases considered. Furthermore, as expected, NEST mostly favors large network models, while NEURON is better suited for detailed models. Overall, the case studies reinforce our general observation that simulators have a bias in the computational performance toward specific types of the brain network models. PMID:28775687

Mathematical and computational aspects of nonuniform frictional slip modeling

NASA Astrophysics Data System (ADS)

Gorbatikh, Larissa

2004-07-01

A mechanics-based model of non-uniform frictional sliding is studied from the mathematical/computational analysis point of view. This problem is of a key importance for a number of applications (particularly geomechanical ones), where materials interfaces undergo partial frictional sliding under compression and shear. We show that the problem is reduced to Dirichlet's problem for monotonic loading and to Riemman's problem for cyclic loading. The problem may look like a traditional crack interaction problem, however, it is confounded by the fact that locations of n sliding intervals are not known. They are to be determined from the condition for the stress intensity factors: KII=0 at the ends of the sliding zones. Computationally, it reduces to solving a system of 2n coupled non-linear algebraic equations involving singular integrals with unknown limits of integration.

Scaling and efficiency of PRISM in adaptive simulations of turbulent premixed flames

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

Tonse, Shaheen R.; Bell, J.B.; Brown, N.J.

1999-12-01

The dominant computational cost in modeling turbulent combustion phenomena numerically with high fidelity chemical mechanisms is the time required to solve the ordinary differential equations associated with chemical kinetics. One approach to reducing that computational cost is to develop an inexpensive surrogate model that accurately represents evolution of chemical kinetics. One such approach, PRISM, develops a polynomial representation of the chemistry evolution in a local region of chemical composition space. This representation is then stored for later use. As the computation proceeds, the chemistry evolution for other points within the same region are computed by evaluating these polynomials instead ofmore » calling an ordinary differential equation solver. If initial data for advancing the chemistry is encountered that is not in any region for which a polynomial is defined, the methodology dynamically samples that region and constructs a new representation for that region. The utility of this approach is determined by the size of the regions over which the representation provides a good approximation to the kinetics and the number of these regions that are necessary to model the subset of composition space that is active during a simulation. In this paper, we assess the PRISM methodology in the context of a turbulent premixed flame in two dimensions. We consider a range of turbulent intensities ranging from weak turbulence that has little effect on the flame to strong turbulence that tears pockets of burning fluid from the main flame. For each case, we explore a range of sizes for the local regions and determine the scaling behavior as a function of region size and turbulent intensity.« less

Verification of Electromagnetic Physics Models for Parallel Computing Architectures in the GeantV Project

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

Amadio, G.; et al.

An intensive R&D and programming effort is required to accomplish new challenges posed by future experimental high-energy particle physics (HEP) programs. The GeantV project aims to narrow the gap between the performance of the existing HEP detector simulation software and the ideal performance achievable, exploiting latest advances in computing technology. The project has developed a particle detector simulation prototype capable of transporting in parallel particles in complex geometries exploiting instruction level microparallelism (SIMD and SIMT), task-level parallelism (multithreading) and high-level parallelism (MPI), leveraging both the multi-core and the many-core opportunities. We present preliminary verification results concerning the electromagnetic (EM) physicsmore » models developed for parallel computing architectures within the GeantV project. In order to exploit the potential of vectorization and accelerators and to make the physics model effectively parallelizable, advanced sampling techniques have been implemented and tested. In this paper we introduce a set of automated statistical tests in order to verify the vectorized models by checking their consistency with the corresponding Geant4 models and to validate them against experimental data.« less

Probability density function of the intensity of a laser beam propagating in the maritime environment.

PubMed

Korotkova, Olga; Avramov-Zamurovic, Svetlana; Malek-Madani, Reza; Nelson, Charles

2011-10-10

A number of field experiments measuring the fluctuating intensity of a laser beam propagating along horizontal paths in the maritime environment is performed over sub-kilometer distances at the United States Naval Academy. Both above the ground and over the water links are explored. Two different detection schemes, one photographing the beam on a white board, and the other capturing the beam directly using a ccd sensor, gave consistent results. The probability density function (pdf) of the fluctuating intensity is reconstructed with the help of two theoretical models: the Gamma-Gamma and the Gamma-Laguerre, and compared with the intensity's histograms. It is found that the on-ground experimental results are in good agreement with theoretical predictions. The results obtained above the water paths lead to appreciable discrepancies, especially in the case of the Gamma-Gamma model. These discrepancies are attributed to the presence of the various scatterers along the path of the beam, such as water droplets, aerosols and other airborne particles. Our paper's main contribution is providing a methodology for computing the pdf function of the laser beam intensity in the maritime environment using field measurements.

Cross-correlation enhanced stability in a tumor cell growth model with immune surveillance driven by cross-correlated noises

NASA Astrophysics Data System (ADS)

Zeng, Chunhua; Zhou, Xiaofeng; Tao, Shufen

2009-12-01

The transient properties of a tumor cell growth model with immune surveillance driven by cross-correlated multiplicative and additive noises are investigated. The explicit expression of extinction rate from the state of a stable tumor to the state of extinction is obtained. Based on the numerical computations, we find the following: (i) the intensity of multiplicative noise D and the intensity of additive noise α enhance the extinction rate for the case of λ <= 0 (i.e. λ denotes cross-correlation intensity between two noises), but for the case of λ > 0, a critical noise intensity D or α exists at which the extinction rate is the smallest; D and α at first weaken the extinction rate and then enhance it. (ii) The immune rate β and the cross-correlation intensity λ play opposite roles on the extinction rate, i.e. β enhances the extinction rate of the tumor cell, while λ weakens the extinction rate of the tumor cell. Namely, the immune rate can enhance the extinction of the tumor cell and the cross-correlation between two noises can enhance stability of the cancer state.

2D Process-based Microbialite Growth Model

NASA Astrophysics Data System (ADS)

Airo, A.; Smith, A.

2007-12-01

A 2D process-based microbialite growth model (MGM) has been developed that integrates the coupled effects of the microbialite growth and sediment distribution within a two-dimensional cross-section of a subaqueous bedrock profile. Sediment transport is realized through particle erosion and deposition that are a function of local wave energy which is computed on the basis of linear wave theory. Surface-normal microbialite growth is directly correlated to light intensity, which is computed for every point of the microbialite surface by using a Henyey- Greenstein-type relation for scattering and the Beer's Law for absorption in the water column. Shadowing effects by surrounding obstacles and/or overlying sediment are also considered. Sediment particles can be incorporated into the microbialite framework if growth occurs in the presence of sediment. The resulting meter-size microbialite constructs develop morphologies that correspond well to natural microbialites. Furthermore, changes of environmental factors such as light intensity, wave energy, and bedrock profile result in morphological variations of the microbialites that would be expected on the basis of the current understanding of microbialite growth and development.

Nonparametric Bayesian Segmentation of a Multivariate Inhomogeneous Space-Time Poisson Process.

PubMed

Ding, Mingtao; He, Lihan; Dunson, David; Carin, Lawrence

2012-12-01

A nonparametric Bayesian model is proposed for segmenting time-evolving multivariate spatial point process data. An inhomogeneous Poisson process is assumed, with a logistic stick-breaking process (LSBP) used to encourage piecewise-constant spatial Poisson intensities. The LSBP explicitly favors spatially contiguous segments, and infers the number of segments based on the observed data. The temporal dynamics of the segmentation and of the Poisson intensities are modeled with exponential correlation in time, implemented in the form of a first-order autoregressive model for uniformly sampled discrete data, and via a Gaussian process with an exponential kernel for general temporal sampling. We consider and compare two different inference techniques: a Markov chain Monte Carlo sampler, which has relatively high computational complexity; and an approximate and efficient variational Bayesian analysis. The model is demonstrated with a simulated example and a real example of space-time crime events in Cincinnati, Ohio, USA.

ORBIT: A Code for Collective Beam Dynamics in High-Intensity Rings

NASA Astrophysics Data System (ADS)

Holmes, J. A.; Danilov, V.; Galambos, J.; Shishlo, A.; Cousineau, S.; Chou, W.; Michelotti, L.; Ostiguy, J.-F.; Wei, J.

2002-12-01

We are developing a computer code, ORBIT, specifically for beam dynamics calculations in high-intensity rings. Our approach allows detailed simulation of realistic accelerator problems. ORBIT is a particle-in-cell tracking code that transports bunches of interacting particles through a series of nodes representing elements, effects, or diagnostics that occur in the accelerator lattice. At present, ORBIT contains detailed models for strip-foil injection, including painting and foil scattering; rf focusing and acceleration; transport through various magnetic elements; longitudinal and transverse impedances; longitudinal, transverse, and three-dimensional space charge forces; collimation and limiting apertures; and the calculation of many useful diagnostic quantities. ORBIT is an object-oriented code, written in C++ and utilizing a scripting interface for the convenience of the user. Ongoing improvements include the addition of a library of accelerator maps, BEAMLINE/MXYZPTLK; the introduction of a treatment of magnet errors and fringe fields; the conversion of the scripting interface to the standard scripting language, Python; and the parallelization of the computations using MPI. The ORBIT code is an open source, powerful, and convenient tool for studying beam dynamics in high-intensity rings.

Enabling NVM for Data-Intensive Scientific Services

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

Carns, Philip; Jenkins, John; Seo, Sangmin

Specialized, transient data services are playing an increasingly prominent role in data-intensive scientific computing. These services offer flexible, on-demand pairing of applications with storage hardware using semantics that are optimized for the problem domain. Concurrent with this trend, upcoming scientific computing and big data systems will be deployed with emerging NVM technology to achieve the highest possible price/productivity ratio. Clearly, therefore, we must develop techniques to facilitate the confluence of specialized data services and NVM technology. In this work we explore how to enable the composition of NVM resources within transient distributed services while still retaining their essential performance characteristics.more » Our approach involves eschewing the conventional distributed file system model and instead projecting NVM devices as remote microservices that leverage user-level threads, RPC services, RMA-enabled network transports, and persistent memory libraries in order to maximize performance. We describe a prototype system that incorporates these concepts, evaluate its performance for key workloads on an exemplar system, and discuss how the system can be leveraged as a component of future data-intensive architectures.« less

On the relative intensity of Poisson’s spot

NASA Astrophysics Data System (ADS)

Reisinger, T.; Leufke, P. M.; Gleiter, H.; Hahn, H.

2017-03-01

The Fresnel diffraction phenomenon referred to as Poisson’s spot or spot of Arago has, beside its historical significance, become relevant in a number of fields. Among them are for example fundamental tests of the super-position principle in the transition from quantum to classical physics and the search for extra-solar planets using star shades. Poisson’s spot refers to the positive on-axis wave interference in the shadow of any spherical or circular obstacle. While the spot’s intensity is equal to the undisturbed field in the plane wave picture, its intensity in general depends on a number of factors, namely the size and wavelength of the source, the size and surface corrugation of the diffraction obstacle, and the distances between source, obstacle and detector. The intensity can be calculated by solving the Fresnel-Kirchhoff diffraction integral numerically, which however tends to be computationally expensive. We have therefore devised an analytical model for the on-axis intensity of Poisson’s spot relative to the intensity of the undisturbed wave field and successfully validated it both using a simple light diffraction setup and numerical methods. The model will be useful for optimizing future Poisson-spot matter-wave diffraction experiments and determining under what experimental conditions the spot can be observed.

A Large-Scale, High-Resolution Hydrological Model Parameter Data Set for Climate Change Impact Assessment for the Conterminous US

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

Oubeidillah, Abdoul A; Kao, Shih-Chieh; Ashfaq, Moetasim

2014-01-01

To extend geographical coverage, refine spatial resolution, and improve modeling efficiency, a computation- and data-intensive effort was conducted to organize a comprehensive hydrologic dataset with post-calibrated model parameters for hydro-climate impact assessment. Several key inputs for hydrologic simulation including meteorologic forcings, soil, land class, vegetation, and elevation were collected from multiple best-available data sources and organized for 2107 hydrologic subbasins (8-digit hydrologic units, HUC8s) in the conterminous United States at refined 1/24 (~4 km) spatial resolution. Using high-performance computing for intensive model calibration, a high-resolution parameter dataset was prepared for the macro-scale Variable Infiltration Capacity (VIC) hydrologic model. The VICmore » simulation was driven by DAYMET daily meteorological forcing and was calibrated against USGS WaterWatch monthly runoff observations for each HUC8. The results showed that this new parameter dataset may help reasonably simulate runoff at most US HUC8 subbasins. Based on this exhaustive calibration effort, it is now possible to accurately estimate the resources required for further model improvement across the entire conterminous United States. We anticipate that through this hydrologic parameter dataset, the repeated effort of fundamental data processing can be lessened, so that research efforts can emphasize the more challenging task of assessing climate change impacts. The pre-organized model parameter dataset will be provided to interested parties to support further hydro-climate impact assessment.« less

Automating FEA programming

NASA Technical Reports Server (NTRS)

Sharma, Naveen

1992-01-01

In this paper we briefly describe a combined symbolic and numeric approach for solving mathematical models on parallel computers. An experimental software system, PIER, is being developed in Common Lisp to synthesize computationally intensive and domain formulation dependent phases of finite element analysis (FEA) solution methods. Quantities for domain formulation like shape functions, element stiffness matrices, etc., are automatically derived using symbolic mathematical computations. The problem specific information and derived formulae are then used to generate (parallel) numerical code for FEA solution steps. A constructive approach to specify a numerical program design is taken. The code generator compiles application oriented input specifications into (parallel) FORTRAN77 routines with the help of built-in knowledge of the particular problem, numerical solution methods and the target computer.

Computational Software for Fitting Seismic Data to Epidemic-Type Aftershock Sequence Models

NASA Astrophysics Data System (ADS)

Chu, A.

2014-12-01

Modern earthquake catalogs are often analyzed using spatial-temporal point process models such as the epidemic-type aftershock sequence (ETAS) models of Ogata (1998). My work introduces software to implement two of ETAS models described in Ogata (1998). To find the Maximum-Likelihood Estimates (MLEs), my software provides estimates of the homogeneous background rate parameter and the temporal and spatial parameters that govern triggering effects by applying the Expectation-Maximization (EM) algorithm introduced in Veen and Schoenberg (2008). Despite other computer programs exist for similar data modeling purpose, using EM-algorithm has the benefits of stability and robustness (Veen and Schoenberg, 2008). Spatial shapes that are very long and narrow cause difficulties in optimization convergence and problems with flat or multi-modal log-likelihood functions encounter similar issues. My program uses a robust method to preset a parameter to overcome the non-convergence computational issue. In addition to model fitting, the software is equipped with useful tools for examining modeling fitting results, for example, visualization of estimated conditional intensity, and estimation of expected number of triggered aftershocks. A simulation generator is also given with flexible spatial shapes that may be defined by the user. This open-source software has a very simple user interface. The user may execute it on a local computer, and the program also has potential to be hosted online. Java language is used for the software's core computing part and an optional interface to the statistical package R is provided.

Distributed Damage Estimation for Prognostics based on Structural Model Decomposition

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Bregon, Anibal; Roychoudhury, Indranil

2011-01-01

Model-based prognostics approaches capture system knowledge in the form of physics-based models of components, and how they fail. These methods consist of a damage estimation phase, in which the health state of a component is estimated, and a prediction phase, in which the health state is projected forward in time to determine end of life. However, the damage estimation problem is often multi-dimensional and computationally intensive. We propose a model decomposition approach adapted from the diagnosis community, called possible conflicts, in order to both improve the computational efficiency of damage estimation, and formulate a damage estimation approach that is inherently distributed. Local state estimates are combined into a global state estimate from which prediction is performed. Using a centrifugal pump as a case study, we perform a number of simulation-based experiments to demonstrate the approach.

Experimental investigation and numerical modelling of positive corona discharge: ozone generation

NASA Astrophysics Data System (ADS)

Yanallah, K; Pontiga, F; Fernández-Rueda, A; Castellanos, A

2009-03-01

The spatial distribution of the species generated in a wire-cylinder positive corona discharge in pure oxygen has been computed using a plasma chemistry model that includes the most significant reactions between electrons, ions, atoms and molecules. The plasma chemistry model is included in the continuity equations of each species, which are coupled with Poisson's equation for the electric field and the energy conservation equation for the gas temperature. The current-voltage characteristic measured in the experiments has been used as an input data to the numerical simulation. The numerical model is able to reproduce the basic structure of the positive corona discharge and highlights the importance of Joule heating on ozone generation. The average ozone density has been computed as a function of current intensity and compared with the experimental measurements of ozone concentration determined by UV absorption spectroscopy.

Ionization Processes in the Atmosphere of Titan (Research Note). III. Ionization by High-Z Nuclei Cosmic Rays

NASA Technical Reports Server (NTRS)

Gronoff, G.; Mertens, C.; Lilensten, J.; Desorgher, L.; Fluckiger, E.; Velinov, P.

2011-01-01

Context. The Cassini-Huygens mission has revealed the importance of particle precipitation in the atmosphere of Titan thanks to in-situ measurements. These ionizing particles (electrons, protons, and cosmic rays) have a strong impact on the chemistry, hence must be modeled. Aims. We revisit our computation of ionization in the atmosphere of Titan by cosmic rays. The high-energy high-mass ions are taken into account to improve the precision of the calculation of the ion production profile. Methods. The Badhwahr and O Neill model for cosmic ray spectrum was adapted for the Titan model. We used the TransTitan model coupled with the Planetocosmics model to compute the ion production by cosmic rays. We compared the results with the NAIRAS/HZETRN ionization model used for the first time for a body that differs from the Earth. Results. The cosmic ray ionization is computed for five groups of cosmic rays, depending on their charge and mass: protons, alpha, Z = 8 (oxygen), Z = 14 (silicon), and Z = 26 (iron) nucleus. Protons and alpha particles ionize mainly at 65 km altitude, while the higher mass nucleons ionize at higher altitudes. Nevertheless, the ionization at higher altitude is insufficient to obscure the impact of Saturn s magnetosphere protons at a 500 km altitude. The ionization rate at the peak (altitude: 65 km, for all the different conditions) lies between 30 and 40/cu cm/s. Conclusions. These new computations show for the first time the importance of high Z cosmic rays on the ionization of the Titan atmosphere. The updated full ionization profile shape does not differ significantly from that found in our previous calculations (Paper I: Gronoff et al. 2009, 506, 955) but undergoes a strong increase in intensity below an altitude of 400 km, especially between 200 and 400 km altitude where alpha and heavier particles (in the cosmic ray spectrum) are responsible for 40% of the ionization. The comparison of several models of ionization and cosmic ray spectra (in intensity and composition) reassures us about the stability of the altitude of the ionization peak (65 km altitude) with respect to the solar activity.

The QuakeSim Project: Numerical Simulations for Active Tectonic Processes

NASA Technical Reports Server (NTRS)

Donnellan, Andrea; Parker, Jay; Lyzenga, Greg; Granat, Robert; Fox, Geoffrey; Pierce, Marlon; Rundle, John; McLeod, Dennis; Grant, Lisa; Tullis, Terry

2004-01-01

In order to develop a solid earth science framework for understanding and studying of active tectonic and earthquake processes, this task develops simulation and analysis tools to study the physics of earthquakes using state-of-the art modeling, data manipulation, and pattern recognition technologies. We develop clearly defined accessible data formats and code protocols as inputs to the simulations. these are adapted to high-performance computers because the solid earth system is extremely complex and nonlinear resulting in computationally intensive problems with millions of unknowns. With these tools it will be possible to construct the more complex models and simulations necessary to develop hazard assessment systems critical for reducing future losses from major earthquakes.

A parallel computing engine for a class of time critical processes.

PubMed

Nabhan, T M; Zomaya, A Y

1997-01-01

This paper focuses on the efficient parallel implementation of systems of numerically intensive nature over loosely coupled multiprocessor architectures. These analytical models are of significant importance to many real-time systems that have to meet severe time constants. A parallel computing engine (PCE) has been developed in this work for the efficient simplification and the near optimal scheduling of numerical models over the different cooperating processors of the parallel computer. First, the analytical system is efficiently coded in its general form. The model is then simplified by using any available information (e.g., constant parameters). A task graph representing the interconnections among the different components (or equations) is generated. The graph can then be compressed to control the computation/communication requirements. The task scheduler employs a graph-based iterative scheme, based on the simulated annealing algorithm, to map the vertices of the task graph onto a Multiple-Instruction-stream Multiple-Data-stream (MIMD) type of architecture. The algorithm uses a nonanalytical cost function that properly considers the computation capability of the processors, the network topology, the communication time, and congestion possibilities. Moreover, the proposed technique is simple, flexible, and computationally viable. The efficiency of the algorithm is demonstrated by two case studies with good results.

POM.gpu-v1.0: a GPU-based Princeton Ocean Model

NASA Astrophysics Data System (ADS)

Xu, S.; Huang, X.; Oey, L.-Y.; Xu, F.; Fu, H.; Zhang, Y.; Yang, G.

2015-09-01

Graphics processing units (GPUs) are an attractive solution in many scientific applications due to their high performance. However, most existing GPU conversions of climate models use GPUs for only a few computationally intensive regions. In the present study, we redesign the mpiPOM (a parallel version of the Princeton Ocean Model) with GPUs. Specifically, we first convert the model from its original Fortran form to a new Compute Unified Device Architecture C (CUDA-C) code, then we optimize the code on each of the GPUs, the communications between the GPUs, and the I / O between the GPUs and the central processing units (CPUs). We show that the performance of the new model on a workstation containing four GPUs is comparable to that on a powerful cluster with 408 standard CPU cores, and it reduces the energy consumption by a factor of 6.8.

Lattice Boltzmann Method for 3-D Flows with Curved Boundary

NASA Technical Reports Server (NTRS)

Mei, Renwei; Shyy, Wei; Yu, Dazhi; Luo, Li-Shi

2002-01-01

In this work, we investigate two issues that are important to computational efficiency and reliability in fluid dynamics applications of the lattice, Boltzmann equation (LBE): (1) Computational stability and accuracy of different lattice Boltzmann models and (2) the treatment of the boundary conditions on curved solid boundaries and their 3-D implementations. Three athermal 3-D LBE models (D3QI5, D3Ql9, and D3Q27) are studied and compared in terms of efficiency, accuracy, and robustness. The boundary treatment recently developed by Filippova and Hanel and Met et al. in 2-D is extended to and implemented for 3-D. The convergence, stability, and computational efficiency of the 3-D LBE models with the boundary treatment for curved boundaries were tested in simulations of four 3-D flows: (1) Fully developed flows in a square duct, (2) flow in a 3-D lid-driven cavity, (3) fully developed flows in a circular pipe, and (4) a uniform flow over a sphere. We found that while the fifteen-velocity 3-D (D3Ql5) model is more prone to numerical instability and the D3Q27 is more computationally intensive, the 63Q19 model provides a balance between computational reliability and efficiency. Through numerical simulations, we demonstrated that the boundary treatment for 3-D arbitrary curved geometry has second-order accuracy and possesses satisfactory stability characteristics.

The Impact of IBM Cell Technology on the Programming Paradigm in the Context of Computer Systems for Climate and Weather Models

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

Zhou, Shujia; Duffy, Daniel; Clune, Thomas

The call for ever-increasing model resolutions and physical processes in climate and weather models demands a continual increase in computing power. The IBM Cell processor's order-of-magnitude peak performance increase over conventional processors makes it very attractive to fulfill this requirement. However, the Cell's characteristics, 256KB local memory per SPE and the new low-level communication mechanism, make it very challenging to port an application. As a trial, we selected the solar radiation component of the NASA GEOS-5 climate model, which: (1) is representative of column physics components (half the total computational time), (2) has an extremely high computational intensity: the ratiomore » of computational load to main memory transfers, and (3) exhibits embarrassingly parallel column computations. In this paper, we converted the baseline code (single-precision Fortran) to C and ported it to an IBM BladeCenter QS20. For performance, we manually SIMDize four independent columns and include several unrolling optimizations. Our results show that when compared with the baseline implementation running on one core of Intel's Xeon Woodcrest, Dempsey, and Itanium2, the Cell is approximately 8.8x, 11.6x, and 12.8x faster, respectively. Our preliminary analysis shows that the Cell can also accelerate the dynamics component (~;;25percent total computational time). We believe these dramatic performance improvements make the Cell processor very competitive as an accelerator.« less

Temperature- and Intensity-Dependent Photovoltaic Measurements to Identify Dominant Recombination Pathways

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

Brandt, Riley E.; Mangan, Niall M.; Li, Jian V.

2016-11-21

In novel photovoltaic absorbers, it is often difficult to assess the root causes of low open-circuit voltages, which may be due to bulk recombination or sub-optimal contacts. In the present work, we discuss the role of temperature- and illumination-dependent device electrical measurements in quantifying and distinguishing these performance losses - in particular, for determining bounds on interface recombination velocities, band alignment, and minority carrier lifetime. We assess the accuracy of this approach by direct comparison to photoelectron spectroscopy. Then, we demonstrate how more computationally intensive model parameter fitting approaches can draw more insights from this broad measurement space. We applymore » this measurement and modeling approach to high-performance III-V and thin-film chalcogenide devices.« less

Model Reduction of Computational Aerothermodynamics for Multi-Discipline Analysis in High Speed Flows

NASA Astrophysics Data System (ADS)

Crowell, Andrew Rippetoe

This dissertation describes model reduction techniques for the computation of aerodynamic heat flux and pressure loads for multi-disciplinary analysis of hypersonic vehicles. NASA and the Department of Defense have expressed renewed interest in the development of responsive, reusable hypersonic cruise vehicles capable of sustained high-speed flight and access to space. However, an extensive set of technical challenges have obstructed the development of such vehicles. These technical challenges are partially due to both the inability to accurately test scaled vehicles in wind tunnels and to the time intensive nature of high-fidelity computational modeling, particularly for the fluid using Computational Fluid Dynamics (CFD). The aim of this dissertation is to develop efficient and accurate models for the aerodynamic heat flux and pressure loads to replace the need for computationally expensive, high-fidelity CFD during coupled analysis. Furthermore, aerodynamic heating and pressure loads are systematically evaluated for a number of different operating conditions, including: simple two-dimensional flow over flat surfaces up to three-dimensional flows over deformed surfaces with shock-shock interaction and shock-boundary layer interaction. An additional focus of this dissertation is on the implementation and computation of results using the developed aerodynamic heating and pressure models in complex fluid-thermal-structural simulations. Model reduction is achieved using a two-pronged approach. One prong focuses on developing analytical corrections to isothermal, steady-state CFD flow solutions in order to capture flow effects associated with transient spatially-varying surface temperatures and surface pressures (e.g., surface deformation, surface vibration, shock impingements, etc.). The second prong is focused on minimizing the computational expense of computing the steady-state CFD solutions by developing an efficient surrogate CFD model. The developed two-pronged approach is found to exhibit balanced performance in terms of accuracy and computational expense, relative to several existing approaches. This approach enables CFD-based loads to be implemented into long duration fluid-thermal-structural simulations.

Fermilab computing at the Intensity Frontier

DOE PAGES

Group, Craig; Fuess, S.; Gutsche, O.; ...

2015-12-23

The Intensity Frontier refers to a diverse set of particle physics experiments using high- intensity beams. In this paper I will focus the discussion on the computing requirements and solutions of a set of neutrino and muon experiments in progress or planned to take place at the Fermi National Accelerator Laboratory located near Chicago, Illinois. In addition, the experiments face unique challenges, but also have overlapping computational needs. In principle, by exploiting the commonality and utilizing centralized computing tools and resources, requirements can be satisfied efficiently and scientists of individual experiments can focus more on the science and less onmore » the development of tools and infrastructure.« less

Simulation of the modulation transfer function dependent on the partial Fourier fraction in dynamic contrast enhancement magnetic resonance imaging.

PubMed

Takatsu, Yasuo; Ueyama, Tsuyoshi; Miyati, Tosiaki; Yamamura, Kenichirou

2016-12-01

The image characteristics in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) depend on the partial Fourier fraction and contrast medium concentration. These characteristics were assessed and the modulation transfer function (MTF) was calculated by computer simulation. A digital phantom was created from signal intensity data acquired at different contrast medium concentrations on a breast model. The frequency images [created by fast Fourier transform (FFT)] were divided into 512 parts and rearranged to form a new image. The inverse FFT of this image yielded the MTF. From the reference data, three linear models (low, medium, and high) and three exponential models (slow, medium, and rapid) of the signal intensity were created. Smaller partial Fourier fractions, and higher gradients in the linear models, corresponded to faster MTF decline. The MTF more gradually decreased in the exponential models than in the linear models. The MTF, which reflects the image characteristics in DCE-MRI, was more degraded as the partial Fourier fraction decreased.

Energy transfer by radiation in non-grey atomic gases in isothermal and non-isothermal slabs

NASA Technical Reports Server (NTRS)

Poon, P. T. Y.

1975-01-01

A multiband model for the absorption coefficient of atomic hydrogen-helium plasmas is constructed which includes continuum and line contributions. Emission from 28 stronger lines of 106 that have been screened is considered, of which 21 are from hydrogen and 7 belong to helium, with reabsorption due to line-line, line-continuum overlap accurately accounted for. The model is utilized in the computation of intensities and fluxes from shock-heated slabs of 85% H2-15% He mixtures for slab thicknesses from 1 to 30 cm, temperature from 10,000 to 20,000 K, and for different densities. In conjunction with the multiband model, simple numerical schemes have been devised which provide a quick and comprehensive way of computing radiative energy transfer in nonisothermal and nongrey gases.

surf3d: A 3-D finite-element program for the analysis of surface and corner cracks in solids subjected to mode-1 loadings

NASA Technical Reports Server (NTRS)

Raju, I. S.; Newman, J. C., Jr.

1993-01-01

A computer program, surf3d, that uses the 3D finite-element method to calculate the stress-intensity factors for surface, corner, and embedded cracks in finite-thickness plates with and without circular holes, was developed. The cracks are assumed to be either elliptic or part eliptic in shape. The computer program uses eight-noded hexahedral elements to model the solid. The program uses a skyline storage and solver. The stress-intensity factors are evaluated using the force method, the crack-opening displacement method, and the 3-D virtual crack closure methods. In the manual the input to and the output of the surf3d program are described. This manual also demonstrates the use of the program and describes the calculation of the stress-intensity factors. Several examples with sample data files are included with the manual. To facilitate modeling of the user's crack configuration and loading, a companion program (a preprocessor program) that generates the data for the surf3d called gensurf was also developed. The gensurf program is a three dimensional mesh generator program that requires minimal input and that builds a complete data file for surf3d. The program surf3d is operational on Unix machines such as CRAY Y-MP, CRAY-2, and Convex C-220.

A Parallel and Incremental Approach for Data-Intensive Learning of Bayesian Networks.

PubMed

Yue, Kun; Fang, Qiyu; Wang, Xiaoling; Li, Jin; Liu, Weiyi

2015-12-01

Bayesian network (BN) has been adopted as the underlying model for representing and inferring uncertain knowledge. As the basis of realistic applications centered on probabilistic inferences, learning a BN from data is a critical subject of machine learning, artificial intelligence, and big data paradigms. Currently, it is necessary to extend the classical methods for learning BNs with respect to data-intensive computing or in cloud environments. In this paper, we propose a parallel and incremental approach for data-intensive learning of BNs from massive, distributed, and dynamically changing data by extending the classical scoring and search algorithm and using MapReduce. First, we adopt the minimum description length as the scoring metric and give the two-pass MapReduce-based algorithms for computing the required marginal probabilities and scoring the candidate graphical model from sample data. Then, we give the corresponding strategy for extending the classical hill-climbing algorithm to obtain the optimal structure, as well as that for storing a BN by pairs. Further, in view of the dynamic characteristics of the changing data, we give the concept of influence degree to measure the coincidence of the current BN with new data, and then propose the corresponding two-pass MapReduce-based algorithms for BNs incremental learning. Experimental results show the efficiency, scalability, and effectiveness of our methods.

Cyber-workstation for computational neuroscience.

PubMed

Digiovanna, Jack; Rattanatamrong, Prapaporn; Zhao, Ming; Mahmoudi, Babak; Hermer, Linda; Figueiredo, Renato; Principe, Jose C; Fortes, Jose; Sanchez, Justin C

2010-01-01

A Cyber-Workstation (CW) to study in vivo, real-time interactions between computational models and large-scale brain subsystems during behavioral experiments has been designed and implemented. The design philosophy seeks to directly link the in vivo neurophysiology laboratory with scalable computing resources to enable more sophisticated computational neuroscience investigation. The architecture designed here allows scientists to develop new models and integrate them with existing models (e.g. recursive least-squares regressor) by specifying appropriate connections in a block-diagram. Then, adaptive middleware transparently implements these user specifications using the full power of remote grid-computing hardware. In effect, the middleware deploys an on-demand and flexible neuroscience research test-bed to provide the neurophysiology laboratory extensive computational power from an outside source. The CW consolidates distributed software and hardware resources to support time-critical and/or resource-demanding computing during data collection from behaving animals. This power and flexibility is important as experimental and theoretical neuroscience evolves based on insights gained from data-intensive experiments, new technologies and engineering methodologies. This paper describes briefly the computational infrastructure and its most relevant components. Each component is discussed within a systematic process of setting up an in vivo, neuroscience experiment. Furthermore, a co-adaptive brain machine interface is implemented on the CW to illustrate how this integrated computational and experimental platform can be used to study systems neurophysiology and learning in a behavior task. We believe this implementation is also the first remote execution and adaptation of a brain-machine interface.

Cyber-Workstation for Computational Neuroscience

PubMed Central

DiGiovanna, Jack; Rattanatamrong, Prapaporn; Zhao, Ming; Mahmoudi, Babak; Hermer, Linda; Figueiredo, Renato; Principe, Jose C.; Fortes, Jose; Sanchez, Justin C.

2009-01-01

A Cyber-Workstation (CW) to study in vivo, real-time interactions between computational models and large-scale brain subsystems during behavioral experiments has been designed and implemented. The design philosophy seeks to directly link the in vivo neurophysiology laboratory with scalable computing resources to enable more sophisticated computational neuroscience investigation. The architecture designed here allows scientists to develop new models and integrate them with existing models (e.g. recursive least-squares regressor) by specifying appropriate connections in a block-diagram. Then, adaptive middleware transparently implements these user specifications using the full power of remote grid-computing hardware. In effect, the middleware deploys an on-demand and flexible neuroscience research test-bed to provide the neurophysiology laboratory extensive computational power from an outside source. The CW consolidates distributed software and hardware resources to support time-critical and/or resource-demanding computing during data collection from behaving animals. This power and flexibility is important as experimental and theoretical neuroscience evolves based on insights gained from data-intensive experiments, new technologies and engineering methodologies. This paper describes briefly the computational infrastructure and its most relevant components. Each component is discussed within a systematic process of setting up an in vivo, neuroscience experiment. Furthermore, a co-adaptive brain machine interface is implemented on the CW to illustrate how this integrated computational and experimental platform can be used to study systems neurophysiology and learning in a behavior task. We believe this implementation is also the first remote execution and adaptation of a brain-machine interface. PMID:20126436

Cloud-based Jupyter Notebooks for Water Data Analysis

NASA Astrophysics Data System (ADS)

Castronova, A. M.; Brazil, L.; Seul, M.

2017-12-01

The development and adoption of technologies by the water science community to improve our ability to openly collaborate and share workflows will have a transformative impact on how we address the challenges associated with collaborative and reproducible scientific research. Jupyter notebooks offer one solution by providing an open-source platform for creating metadata-rich toolchains for modeling and data analysis applications. Adoption of this technology within the water sciences, coupled with publicly available datasets from agencies such as USGS, NASA, and EPA enables researchers to easily prototype and execute data intensive toolchains. Moreover, implementing this software stack in a cloud-based environment extends its native functionality to provide researchers a mechanism to build and execute toolchains that are too large or computationally demanding for typical desktop computers. Additionally, this cloud-based solution enables scientists to disseminate data processing routines alongside journal publications in an effort to support reproducibility. For example, these data collection and analysis toolchains can be shared, archived, and published using the HydroShare platform or downloaded and executed locally to reproduce scientific analysis. This work presents the design and implementation of a cloud-based Jupyter environment and its application for collecting, aggregating, and munging various datasets in a transparent, sharable, and self-documented manner. The goals of this work are to establish a free and open source platform for domain scientists to (1) conduct data intensive and computationally intensive collaborative research, (2) utilize high performance libraries, models, and routines within a pre-configured cloud environment, and (3) enable dissemination of research products. This presentation will discuss recent efforts towards achieving these goals, and describe the architectural design of the notebook server in an effort to support collaborative and reproducible science.

Optimization of tomographic reconstruction workflows on geographically distributed resources

PubMed Central

Bicer, Tekin; Gürsoy, Doǧa; Kettimuthu, Rajkumar; De Carlo, Francesco; Foster, Ian T.

2016-01-01

New technological advancements in synchrotron light sources enable data acquisitions at unprecedented levels. This emergent trend affects not only the size of the generated data but also the need for larger computational resources. Although beamline scientists and users have access to local computational resources, these are typically limited and can result in extended execution times. Applications that are based on iterative processing as in tomographic reconstruction methods require high-performance compute clusters for timely analysis of data. Here, time-sensitive analysis and processing of Advanced Photon Source data on geographically distributed resources are focused on. Two main challenges are considered: (i) modeling of the performance of tomographic reconstruction workflows and (ii) transparent execution of these workflows on distributed resources. For the former, three main stages are considered: (i) data transfer between storage and computational resources, (i) wait/queue time of reconstruction jobs at compute resources, and (iii) computation of reconstruction tasks. These performance models allow evaluation and estimation of the execution time of any given iterative tomographic reconstruction workflow that runs on geographically distributed resources. For the latter challenge, a workflow management system is built, which can automate the execution of workflows and minimize the user interaction with the underlying infrastructure. The system utilizes Globus to perform secure and efficient data transfer operations. The proposed models and the workflow management system are evaluated by using three high-performance computing and two storage resources, all of which are geographically distributed. Workflows were created with different computational requirements using two compute-intensive tomographic reconstruction algorithms. Experimental evaluation shows that the proposed models and system can be used for selecting the optimum resources, which in turn can provide up to 3.13× speedup (on experimented resources). Moreover, the error rates of the models range between 2.1 and 23.3% (considering workflow execution times), where the accuracy of the model estimations increases with higher computational demands in reconstruction tasks. PMID:27359149

Segmentation and intensity estimation of microarray images using a gamma-t mixture model.

PubMed

Baek, Jangsun; Son, Young Sook; McLachlan, Geoffrey J

2007-02-15

We present a new approach to the analysis of images for complementary DNA microarray experiments. The image segmentation and intensity estimation are performed simultaneously by adopting a two-component mixture model. One component of this mixture corresponds to the distribution of the background intensity, while the other corresponds to the distribution of the foreground intensity. The intensity measurement is a bivariate vector consisting of red and green intensities. The background intensity component is modeled by the bivariate gamma distribution, whose marginal densities for the red and green intensities are independent three-parameter gamma distributions with different parameters. The foreground intensity component is taken to be the bivariate t distribution, with the constraint that the mean of the foreground is greater than that of the background for each of the two colors. The degrees of freedom of this t distribution are inferred from the data but they could be specified in advance to reduce the computation time. Also, the covariance matrix is not restricted to being diagonal and so it allows for nonzero correlation between R and G foreground intensities. This gamma-t mixture model is fitted by maximum likelihood via the EM algorithm. A final step is executed whereby nonparametric (kernel) smoothing is undertaken of the posterior probabilities of component membership. The main advantages of this approach are: (1) it enjoys the well-known strengths of a mixture model, namely flexibility and adaptability to the data; (2) it considers the segmentation and intensity simultaneously and not separately as in commonly used existing software, and it also works with the red and green intensities in a bivariate framework as opposed to their separate estimation via univariate methods; (3) the use of the three-parameter gamma distribution for the background red and green intensities provides a much better fit than the normal (log normal) or t distributions; (4) the use of the bivariate t distribution for the foreground intensity provides a model that is less sensitive to extreme observations; (5) as a consequence of the aforementioned properties, it allows segmentation to be undertaken for a wide range of spot shapes, including doughnut, sickle shape and artifacts. We apply our method for gridding, segmentation and estimation to cDNA microarray real images and artificial data. Our method provides better segmentation results in spot shapes as well as intensity estimation than Spot and spotSegmentation R language softwares. It detected blank spots as well as bright artifact for the real data, and estimated spot intensities with high-accuracy for the synthetic data. The algorithms were implemented in Matlab. The Matlab codes implementing both the gridding and segmentation/estimation are available upon request. Supplementary material is available at Bioinformatics online.

Anisotropic scattering of discrete particle arrays.

PubMed

Paul, Joseph S; Fu, Wai Chong; Dokos, Socrates; Box, Michael

2010-05-01

Far-field intensities of light scattered from a linear centro-symmetric array illuminated by a plane wave of incident light are estimated at a series of detector angles. The intensities are computed from the superposition of E-fields scattered by the individual array elements. An average scattering phase function is used to model the scattered fields of individual array elements. The nature of scattering from the array is investigated using an image (theta-phi plot) of the far-field intensities computed at a series of locations obtained by rotating the detector angle from 0 degrees to 360 degrees, corresponding to each angle of incidence in the interval [0 degrees 360 degrees]. The diffraction patterns observed from the theta-Phi plot are compared with those for isotropic scattering. In the absence of prior information on the array geometry, the intensities corresponding to theta-Phi pairs satisfying the Bragg condition are used to estimate the phase function. An algorithmic procedure is presented for this purpose and tested using synthetic data. The relative error between estimated and theoretical values of the phase function is shown to be determined by the mean spacing factor, the number of elements, and the far-field distance. An empirical relationship is presented to calculate the optimal far-field distance for a given specification of the percentage error.

Multivariate optical computing using a digital micromirror device for fluorescence and Raman spectroscopy.

PubMed

Smith, Zachary J; Strombom, Sven; Wachsmann-Hogiu, Sebastian

2011-08-29

A multivariate optical computer has been constructed consisting of a spectrograph, digital micromirror device, and photomultiplier tube that is capable of determining absolute concentrations of individual components of a multivariate spectral model. We present experimental results on ternary mixtures, showing accurate quantification of chemical concentrations based on integrated intensities of fluorescence and Raman spectra measured with a single point detector. We additionally show in simulation that point measurements based on principal component spectra retain the ability to classify cancerous from noncancerous T cells.

Surface wind accuracy for modeling mineral dust emissions: Comparing two regional models in a Bodélé case study

NASA Astrophysics Data System (ADS)

Laurent, B.; Heinold, B.; Tegen, I.; Bouet, C.; Cautenet, G.

2008-05-01

After a decade of research on improving the description of surface and soil features in desert regions to accurately model mineral dust emissions, we now emphasize the need for deeper evaluating the accuracy of modeled 10-m surface wind speeds U 10 . Two mesoscale models, the Lokal-Modell (LM) and the Regional Atmospheric Modeling System (RAMS), coupled with an explicit dust emission model have previously been used to simulate mineral dust events in the Bodélé region. We compare LM and RAMS U 10 , together with measurements at the Chicha site (BoDEx campaign) and Faya-Largeau meteorological station. Surface features and soil schemes are investigated to correctly simulate U 10 intensity and diurnal variability. The uncertainties in dust emissions computed with LM and RAMS U 10 and different soil databases are estimated. This sensitivity study shows the importance of accurate computation of surface winds to improve the quantification of regional dust emissions from the Bodélé

Inherent smoothness of intensity patterns for intensity modulated radiation therapy generated by simultaneous projection algorithms

NASA Astrophysics Data System (ADS)

Xiao, Ying; Michalski, Darek; Censor, Yair; Galvin, James M.

2004-07-01

The efficient delivery of intensity modulated radiation therapy (IMRT) depends on finding optimized beam intensity patterns that produce dose distributions, which meet given constraints for the tumour as well as any critical organs to be spared. Many optimization algorithms that are used for beamlet-based inverse planning are susceptible to large variations of neighbouring intensities. Accurately delivering an intensity pattern with a large number of extrema can prove impossible given the mechanical limitations of standard multileaf collimator (MLC) delivery systems. In this study, we apply Cimmino's simultaneous projection algorithm to the beamlet-based inverse planning problem, modelled mathematically as a system of linear inequalities. We show that using this method allows us to arrive at a smoother intensity pattern. Including nonlinear terms in the simultaneous projection algorithm to deal with dose-volume histogram (DVH) constraints does not compromise this property from our experimental observation. The smoothness properties are compared with those from other optimization algorithms which include simulated annealing and the gradient descent method. The simultaneous property of these algorithms is ideally suited to parallel computing technologies.

Polycyclic Aromatic Hydrocarbons with Aliphatic Sidegroups: Intensity Scaling for the C-H Stretching Modes and Astrophysical Implications

NASA Astrophysics Data System (ADS)

Yang, X. J.; Li, Aigen; Glaser, R.; Zhong, J. X.

2017-03-01

The so-called unidentified infrared emission (UIE) features at 3.3, 6.2, 7.7, 8.6, and 11.3 μ {{m}} ubiquitously seen in a wide variety of astrophysical regions are generally attributed to polycyclic aromatic hydrocarbon (PAH) molecules. Astronomical PAHs may have an aliphatic component, as revealed by the detection in many UIE sources of the aliphatic C-H stretching feature at 3.4 μ {{m}}. The ratio of the observed intensity of the 3.4 μ {{m}} feature to that of the 3.3 μ {{m}} aromatic C-H feature allows one to estimate the aliphatic fraction of the UIE carriers. This requires knowledge of the intrinsic oscillator strengths of the 3.3 μ {{m}} aromatic C-H stretch ({A}3.3) and the 3.4 μ {{m}} aliphatic C-H stretch ({A}3.4). Lacking experimental data on {A}3.3 and {A}3.4 for the UIE candidate materials, one often has to rely on quantum-chemical computations. Although the second-order Møller-Plesset (MP2) perturbation theory with a large basis set is more accurate than the B3LYP density functional theory, MP2 is computationally very demanding and impractical for large molecules. Based on methylated PAHs, we show here that, by scaling the band strengths computed at an inexpensive level (e.g., B3LYP/6-31G*), we are able to obtain band strengths as accurate as those computed at far more expensive levels (e.g., MP2/6-311+G(3df,3pd)). We calculate the model spectra of methylated PAHs and their cations excited by starlight of different spectral shapes and intensities. We find that {({I}3.4/{I}3.3)}{mod}, the ratio of the model intensity of the 3.4 μ {{m}} feature to that of the 3.3 μ {{m}} feature, is insensitive to the spectral shape and intensity of the exciting starlight. We derive a straightforward relation for determining the aliphatic fraction of the UIE carriers (I.e., the ratio of the number of C atoms in aliphatic units {N}{{C},{ali}} to that in aromatic rings {N}{{C},{aro}}) from the observed band ratios {({I}3.4/{I}3.3)}{obs}: {N}{{C},{ali}}/{N}{{C},{aro}}≈ 0.57× {({I}3.4/{I}3.3)}{obs} for neutrals and {N}{{C},{ali}}/{N}{{C},{aro}}≈ 0.26× {({I}3.4/{I}3.3)}{obs} for cations.

Computational Aspects of Data Assimilation and the ESMF

NASA Technical Reports Server (NTRS)

daSilva, A.

2003-01-01

The scientific challenge of developing advanced data assimilation applications is a daunting task. Independently developed components may have incompatible interfaces or may be written in different computer languages. The high-performance computer (HPC) platforms required by numerically intensive Earth system applications are complex, varied, rapidly evolving and multi-part systems themselves. Since the market for high-end platforms is relatively small, there is little robust middleware available to buffer the modeler from the difficulties of HPC programming. To complicate matters further, the collaborations required to develop large Earth system applications often span initiatives, institutions and agencies, involve geoscience, software engineering, and computer science communities, and cross national borders.The Earth System Modeling Framework (ESMF) project is a concerted response to these challenges. Its goal is to increase software reuse, interoperability, ease of use and performance in Earth system models through the use of a common software framework, developed in an open manner by leaders in the modeling community. The ESMF addresses the technical and to some extent the cultural - aspects of Earth system modeling, laying the groundwork for addressing the more difficult scientific aspects, such as the physical compatibility of components, in the future. In this talk we will discuss the general philosophy and architecture of the ESMF, focussing on those capabilities useful for developing advanced data assimilation applications.

A Computational Approach for Probabilistic Analysis of LS-DYNA Water Impact Simulations

NASA Technical Reports Server (NTRS)

Horta, Lucas G.; Mason, Brian H.; Lyle, Karen H.

2010-01-01

NASA s development of new concepts for the Crew Exploration Vehicle Orion presents many similar challenges to those worked in the sixties during the Apollo program. However, with improved modeling capabilities, new challenges arise. For example, the use of the commercial code LS-DYNA, although widely used and accepted in the technical community, often involves high-dimensional, time consuming, and computationally intensive simulations. Because of the computational cost, these tools are often used to evaluate specific conditions and rarely used for statistical analysis. The challenge is to capture what is learned from a limited number of LS-DYNA simulations to develop models that allow users to conduct interpolation of solutions at a fraction of the computational time. For this problem, response surface models are used to predict the system time responses to a water landing as a function of capsule speed, direction, attitude, water speed, and water direction. Furthermore, these models can also be used to ascertain the adequacy of the design in terms of probability measures. This paper presents a description of the LS-DYNA model, a brief summary of the response surface techniques, the analysis of variance approach used in the sensitivity studies, equations used to estimate impact parameters, results showing conditions that might cause injuries, and concluding remarks.

Optimized temporal pattern of brain stimulation designed by computational evolution

PubMed Central

Brocker, David T.; Swan, Brandon D.; So, Rosa Q.; Turner, Dennis A.; Gross, Robert E.; Grill, Warren M.

2017-01-01

Brain stimulation is a promising therapy for several neurological disorders, including Parkinson’s disease. Stimulation parameters are selected empirically and are limited to the frequency and intensity of stimulation. We used the temporal pattern of stimulation as a novel parameter of deep brain stimulation to ameliorate symptoms in a parkinsonian animal model and in humans with Parkinson’s disease. We used model-based computational evolution to optimize the stimulation pattern. The optimized pattern produced symptom relief comparable to that from standard high-frequency stimulation (a constant rate of 130 or 185 Hz) and outperformed frequency-matched standard stimulation in the parkinsonian rat and in patients. Both optimized and standard stimulation suppressed abnormal oscillatory activity in the basal ganglia of rats and humans. The results illustrate the utility of model-based computational evolution to design temporal pattern of stimulation to increase the efficiency of brain stimulation in Parkinson’s disease, thereby requiring substantially less energy than traditional brain stimulation. PMID:28053151

NCAR's Experimental Real-time Convection-allowing Ensemble Prediction System

NASA Astrophysics Data System (ADS)

Schwartz, C. S.; Romine, G. S.; Sobash, R.; Fossell, K.

2016-12-01

Since April 2015, the National Center for Atmospheric Research's (NCAR's) Mesoscale and Microscale Meteorology (MMM) Laboratory, in collaboration with NCAR's Computational Information Systems Laboratory (CISL), has been producing daily, real-time, 10-member, 48-hr ensemble forecasts with 3-km horizontal grid spacing over the conterminous United States (http://ensemble.ucar.edu). These computationally-intensive, next-generation forecasts are produced on the Yellowstone supercomputer, have been embraced by both amateur and professional weather forecasters, are widely used by NCAR and university researchers, and receive considerable attention on social media. Initial conditions are supplied by NCAR's Data Assimilation Research Testbed (DART) software and the forecast model is NCAR's Weather Research and Forecasting (WRF) model; both WRF and DART are community tools. This presentation will focus on cutting-edge research results leveraging the ensemble dataset, including winter weather predictability, severe weather forecasting, and power outage modeling. Additionally, the unique design of the real-time analysis and forecast system and computational challenges and solutions will be described.

A flexible tool for diagnosing water, energy, and entropy budgets in climate models

NASA Astrophysics Data System (ADS)

Lembo, Valerio; Lucarini, Valerio

2017-04-01

We have developed a new flexible software for studying the global energy budget, the hydrological cycle, and the material entropy production of global climate models. The program receives as input radiative, latent and sensible energy fluxes, with the requirement that the variable names are in agreement with the Climate and Forecast (CF) conventions for the production of NetCDF datasets. Annual mean maps, meridional sections and time series are computed by means of Climate Data Operators (CDO) collection of command line operators developed at Max-Planck Institute for Meteorology (MPI-M). If a land-sea mask is provided, the program also computes the required quantities separately on the continents and oceans. Depending on the user's choice, the program also calls the MATLAB software to compute meridional heat transports and location and intensities of the peaks in the two hemispheres. We are currently planning to adapt the program in order to be included in the Earth System Model eValuation Tool (ESMValTool) community diagnostics.

Nonlinear Model Predictive Control for Cooperative Control and Estimation

NASA Astrophysics Data System (ADS)

Ru, Pengkai

Recent advances in computational power have made it possible to do expensive online computations for control systems. It is becoming more realistic to perform computationally intensive optimization schemes online on systems that are not intrinsically stable and/or have very small time constants. Being one of the most important optimization based control approaches, model predictive control (MPC) has attracted a lot of interest from the research community due to its natural ability to incorporate constraints into its control formulation. Linear MPC has been well researched and its stability can be guaranteed in the majority of its application scenarios. However, one issue that still remains with linear MPC is that it completely ignores the system's inherent nonlinearities thus giving a sub-optimal solution. On the other hand, if achievable, nonlinear MPC, would naturally yield a globally optimal solution and take into account all the innate nonlinear characteristics. While an exact solution to a nonlinear MPC problem remains extremely computationally intensive, if not impossible, one might wonder if there is a middle ground between the two. We tried to strike a balance in this dissertation by employing a state representation technique, namely, the state dependent coefficient (SDC) representation. This new technique would render an improved performance in terms of optimality compared to linear MPC while still keeping the problem tractable. In fact, the computational power required is bounded only by a constant factor of the completely linearized MPC. The purpose of this research is to provide a theoretical framework for the design of a specific kind of nonlinear MPC controller and its extension into a general cooperative scheme. The controller is designed and implemented on quadcopter systems.

The tracking performance of distributed recoverable flight control systems subject to high intensity radiated fields

NASA Astrophysics Data System (ADS)

Wang, Rui

It is known that high intensity radiated fields (HIRF) can produce upsets in digital electronics, and thereby degrade the performance of digital flight control systems. Such upsets, either from natural or man-made sources, can change data values on digital buses and memory and affect CPU instruction execution. HIRF environments are also known to trigger common-mode faults, affecting nearly-simultaneously multiple fault containment regions, and hence reducing the benefits of n-modular redundancy and other fault-tolerant computing techniques. Thus, it is important to develop models which describe the integration of the embedded digital system, where the control law is implemented, as well as the dynamics of the closed-loop system. In this dissertation, theoretical tools are presented to analyze the relationship between the design choices for a class of distributed recoverable computing platforms and the tracking performance degradation of a digital flight control system implemented on such a platform while operating in a HIRF environment. Specifically, a tractable hybrid performance model is developed for a digital flight control system implemented on a computing platform inspired largely by the NASA family of fault-tolerant, reconfigurable computer architectures known as SPIDER (scalable processor-independent design for enhanced reliability). The focus will be on the SPIDER implementation, which uses the computer communication system known as ROBUS-2 (reliable optical bus). A physical HIRF experiment was conducted at the NASA Langley Research Center in order to validate the theoretical tracking performance degradation predictions for a distributed Boeing 747 flight control system subject to a HIRF environment. An extrapolation of these results for scenarios that could not be physically tested is also presented.

The effective application of a discrete transition model to explore cell-cycle regulation in yeast

PubMed Central

2013-01-01

Background Bench biologists often do not take part in the development of computational models for their systems, and therefore, they frequently employ them as “black-boxes”. Our aim was to construct and test a model that does not depend on the availability of quantitative data, and can be directly used without a need for intensive computational background. Results We present a discrete transition model. We used cell-cycle in budding yeast as a paradigm for a complex network, demonstrating phenomena such as sequential protein expression and activity, and cell-cycle oscillation. The structure of the network was validated by its response to computational perturbations such as mutations, and its response to mating-pheromone or nitrogen depletion. The model has a strong predicative capability, demonstrating how the activity of a specific transcription factor, Hcm1, is regulated, and what determines commitment of cells to enter and complete the cell-cycle. Conclusion The model presented herein is intuitive, yet is expressive enough to elucidate the intrinsic structure and qualitative behavior of large and complex regulatory networks. Moreover our model allowed us to examine multiple hypotheses in a simple and intuitive manner, giving rise to testable predictions. This methodology can be easily integrated as a useful approach for the study of networks, enriching experimental biology with computational insights. PMID:23915717

A computational model for epidural electrical stimulation of spinal sensorimotor circuits.

PubMed

Capogrosso, Marco; Wenger, Nikolaus; Raspopovic, Stanisa; Musienko, Pavel; Beauparlant, Janine; Bassi Luciani, Lorenzo; Courtine, Grégoire; Micera, Silvestro

2013-12-04

Epidural electrical stimulation (EES) of lumbosacral segments can restore a range of movements after spinal cord injury. However, the mechanisms and neural structures through which EES facilitates movement execution remain unclear. Here, we designed a computational model and performed in vivo experiments to investigate the type of fibers, neurons, and circuits recruited in response to EES. We first developed a realistic finite element computer model of rat lumbosacral segments to identify the currents generated by EES. To evaluate the impact of these currents on sensorimotor circuits, we coupled this model with an anatomically realistic axon-cable model of motoneurons, interneurons, and myelinated afferent fibers for antagonistic ankle muscles. Comparisons between computer simulations and experiments revealed the ability of the model to predict EES-evoked motor responses over multiple intensities and locations. Analysis of the recruited neural structures revealed the lack of direct influence of EES on motoneurons and interneurons. Simulations and pharmacological experiments demonstrated that EES engages spinal circuits trans-synaptically through the recruitment of myelinated afferent fibers. The model also predicted the capacity of spatially distinct EES to modulate side-specific limb movements and, to a lesser extent, extension versus flexion. These predictions were confirmed during standing and walking enabled by EES in spinal rats. These combined results provide a mechanistic framework for the design of spinal neuroprosthetic systems to improve standing and walking after neurological disorders.

Procedural wound geometry and blood flow generation for medical training simulators

NASA Astrophysics Data System (ADS)

Aras, Rifat; Shen, Yuzhong; Li, Jiang

2012-02-01

Efficient application of wound treatment procedures is vital in both emergency room and battle zone scenes. In order to train first responders for such situations, physical casualty simulation kits, which are composed of tens of individual items, are commonly used. Similar to any other training scenarios, computer simulations can be effective means for wound treatment training purposes. For immersive and high fidelity virtual reality applications, realistic 3D models are key components. However, creation of such models is a labor intensive process. In this paper, we propose a procedural wound geometry generation technique that parameterizes key simulation inputs to establish the variability of the training scenarios without the need of labor intensive remodeling of the 3D geometry. The procedural techniques described in this work are entirely handled by the graphics processing unit (GPU) to enable interactive real-time operation of the simulation and to relieve the CPU for other computational tasks. The visible human dataset is processed and used as a volumetric texture for the internal visualization of the wound geometry. To further enhance the fidelity of the simulation, we also employ a surface flow model for blood visualization. This model is realized as a dynamic texture that is composed of a height field and a normal map and animated at each simulation step on the GPU. The procedural wound geometry and the blood flow model are applied to a thigh model and the efficiency of the technique is demonstrated in a virtual surgery scene.

Assessing the relationship between computational speed and precision: a case study comparing an interpreted versus compiled programming language using a stochastic simulation model in diabetes care.

PubMed

McEwan, Phil; Bergenheim, Klas; Yuan, Yong; Tetlow, Anthony P; Gordon, Jason P

2010-01-01

Simulation techniques are well suited to modelling diseases yet can be computationally intensive. This study explores the relationship between modelled effect size, statistical precision, and efficiency gains achieved using variance reduction and an executable programming language. A published simulation model designed to model a population with type 2 diabetes mellitus based on the UKPDS 68 outcomes equations was coded in both Visual Basic for Applications (VBA) and C++. Efficiency gains due to the programming language were evaluated, as was the impact of antithetic variates to reduce variance, using predicted QALYs over a 40-year time horizon. The use of C++ provided a 75- and 90-fold reduction in simulation run time when using mean and sampled input values, respectively. For a series of 50 one-way sensitivity analyses, this would yield a total run time of 2 minutes when using C++, compared with 155 minutes for VBA when using mean input values. The use of antithetic variates typically resulted in a 53% reduction in the number of simulation replications and run time required. When drawing all input values to the model from distributions, the use of C++ and variance reduction resulted in a 246-fold improvement in computation time compared with VBA - for which the evaluation of 50 scenarios would correspondingly require 3.8 hours (C++) and approximately 14.5 days (VBA). The choice of programming language used in an economic model, as well as the methods for improving precision of model output can have profound effects on computation time. When constructing complex models, more computationally efficient approaches such as C++ and variance reduction should be considered; concerns regarding model transparency using compiled languages are best addressed via thorough documentation and model validation.

Fast Simulation of Membrane Filtration by Combining Particle Retention Mechanisms and Network Models

NASA Astrophysics Data System (ADS)

Krupp, Armin; Griffiths, Ian; Please, Colin

2016-11-01

Porous membranes are used for their particle retention capabilities in a wide range of industrial filtration processes. The underlying mechanisms for particle retention are complex and often change during the filtration process, making it hard to predict the change in permeability of the membrane during the process. Recently, stochastic network models have been shown to predict the change in permeability based on retention mechanisms, but remain computationally intensive. We show that the averaged behaviour of such a stochastic network model can efficiently be computed using a simple partial differential equation. Moreover, we also show that the geometric structure of the underlying membrane and particle-size distribution can be represented in our model, making it suitable for modelling particle retention in interconnected membranes as well. We conclude by demonstrating the particular application to microfluidic filtration, where the model can be used to efficiently compute a probability density for flux measurements based on the geometry of the pores and particles. A. U. K. is grateful for funding from Pall Corporation and the Mathematical Institute, University of Oxford. I.M.G. gratefully acknowledges support from the Royal Society through a University Research Fellowship.

Modeling of Flow Transition Using an Intermittency Transport Equation

NASA Technical Reports Server (NTRS)

Suzen, Y. B.; Huang, P. G.

1999-01-01

A new transport equation for intermittency factor is proposed to model transitional flows. The intermittent behavior of the transitional flows is incorporated into the computations by modifying the eddy viscosity, mu(sub t), obtainable from a turbulence model, with the intermittency factor, gamma: mu(sub t, sup *) = gamma.mu(sub t). In this paper, Menter's SST model (Menter, 1994) is employed to compute mu(sub t) and other turbulent quantities. The proposed intermittency transport equation can be considered as a blending of two models - Steelant and Dick (1996) and Cho and Chung (1992). The former was proposed for near-wall flows and was designed to reproduce the streamwise variation of the intermittency factor in the transition zone following Dhawan and Narasimha correlation (Dhawan and Narasimha, 1958) and the latter was proposed for free shear flows and was used to provide a realistic cross-stream variation of the intermittency profile. The new model was used to predict the T3 series experiments assembled by Savill (1993a, 1993b) including flows with different freestream turbulence intensities and two pressure-gradient cases. For all test cases good agreements between the computed results and the experimental data are observed.

ASME V\\&V challenge problem: Surrogate-based V&V

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

Beghini, Lauren L.; Hough, Patricia D.

2015-12-18

The process of verification and validation can be resource intensive. From the computational model perspective, the resource demand typically arises from long simulation run times on multiple cores coupled with the need to characterize and propagate uncertainties. In addition, predictive computations performed for safety and reliability analyses have similar resource requirements. For this reason, there is a tradeoff between the time required to complete the requisite studies and the fidelity or accuracy of the results that can be obtained. At a high level, our approach is cast within a validation hierarchy that provides a framework in which we perform sensitivitymore » analysis, model calibration, model validation, and prediction. The evidence gathered as part of these activities is mapped into the Predictive Capability Maturity Model to assess credibility of the model used for the reliability predictions. With regard to specific technical aspects of our analysis, we employ surrogate-based methods, primarily based on polynomial chaos expansions and Gaussian processes, for model calibration, sensitivity analysis, and uncertainty quantification in order to reduce the number of simulations that must be done. The goal is to tip the tradeoff balance to improving accuracy without increasing the computational demands.« less

Soot and Spectral Radiation Modeling for a High-Pressure Turbulent Spray Flame

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

Ferreryo-Fernandez, Sebastian; Paul, Chandan; Sircar, Arpan

Simulations are performed of a transient high-pressure turbulent n-dodecane spray flame under engine-relevant conditions. An unsteady RANS formulation is used, with detailed chemistry, a semi-empirical two-equation soot model, and a particle-based transported composition probability density function (PDF) method to account for unresolved turbulent fluctuations in composition and temperature. Results from the PDF model are compared with those from a locally well-stirred reactor (WSR) model to quantify the effects of turbulence-chemistry-soot interactions. Computed liquid and vapor penetration versus time, ignition delay, and flame lift-off height are in good agreement with experiment, and relatively small differences are seen between the WSR andmore » PDF models for these global quantities. Computed soot levels and spatial soot distributions from the WSR and PDF models show large differences, with PDF results being in better agreement with experimental measurements. An uncoupled photon Monte Carlo method with line-by-line spectral resolution is used to compute the spectral intensity distribution of the radiation leaving the flame. This provides new insight into the relative importance of molecular gas radiation versus soot radiation, and the importance of turbulent fluctuations on radiative heat transfer.« less

Hypervelocity Impact Test Fragment Modeling: Modifications to the Fragment Rotation Analysis and Lightcurve Code

NASA Technical Reports Server (NTRS)

Gouge, Michael F.

2011-01-01

Hypervelocity impact tests on test satellites are performed by members of the orbital debris scientific community in order to understand and typify the on-orbit collision breakup process. By analysis of these test satellite fragments, the fragment size and mass distributions are derived and incorporated into various orbital debris models. These same fragments are currently being put to new use using emerging technologies. Digital models of these fragments are created using a laser scanner. A group of computer programs referred to as the Fragment Rotation Analysis and Lightcurve code uses these digital representations in a multitude of ways that describe, measure, and model on-orbit fragments and fragment behavior. The Dynamic Rotation subroutine generates all of the possible reflected intensities from a scanned fragment as if it were observed to rotate dynamically while in orbit about the Earth. This calls an additional subroutine that graphically displays the intensities and the resulting frequency of those intensities as a range of solar phase angles in a Probability Density Function plot. This document reports the additions and modifications to the subset of the Fragment Rotation Analysis and Lightcurve concerned with the Dynamic Rotation and Probability Density Function plotting subroutines.

Multimodal Image Analysis in Alzheimer’s Disease via Statistical Modelling of Non-local Intensity Correlations

NASA Astrophysics Data System (ADS)

Lorenzi, Marco; Simpson, Ivor J.; Mendelson, Alex F.; Vos, Sjoerd B.; Cardoso, M. Jorge; Modat, Marc; Schott, Jonathan M.; Ourselin, Sebastien

2016-04-01

The joint analysis of brain atrophy measured with magnetic resonance imaging (MRI) and hypometabolism measured with positron emission tomography with fluorodeoxyglucose (FDG-PET) is of primary importance in developing models of pathological changes in Alzheimer’s disease (AD). Most of the current multimodal analyses in AD assume a local (spatially overlapping) relationship between MR and FDG-PET intensities. However, it is well known that atrophy and hypometabolism are prominent in different anatomical areas. The aim of this work is to describe the relationship between atrophy and hypometabolism by means of a data-driven statistical model of non-overlapping intensity correlations. For this purpose, FDG-PET and MRI signals are jointly analyzed through a computationally tractable formulation of partial least squares regression (PLSR). The PLSR model is estimated and validated on a large clinical cohort of 1049 individuals from the ADNI dataset. Results show that the proposed non-local analysis outperforms classical local approaches in terms of predictive accuracy while providing a plausible description of disease dynamics: early AD is characterised by non-overlapping temporal atrophy and temporo-parietal hypometabolism, while the later disease stages show overlapping brain atrophy and hypometabolism spread in temporal, parietal and cortical areas.

Adaptive quantification and longitudinal analysis of pulmonary emphysema with a hidden Markov measure field model.

PubMed

Hame, Yrjo; Angelini, Elsa D; Hoffman, Eric A; Barr, R Graham; Laine, Andrew F

2014-07-01

The extent of pulmonary emphysema is commonly estimated from CT scans by computing the proportional area of voxels below a predefined attenuation threshold. However, the reliability of this approach is limited by several factors that affect the CT intensity distributions in the lung. This work presents a novel method for emphysema quantification, based on parametric modeling of intensity distributions and a hidden Markov measure field model to segment emphysematous regions. The framework adapts to the characteristics of an image to ensure a robust quantification of emphysema under varying CT imaging protocols, and differences in parenchymal intensity distributions due to factors such as inspiration level. Compared to standard approaches, the presented model involves a larger number of parameters, most of which can be estimated from data, to handle the variability encountered in lung CT scans. The method was applied on a longitudinal data set with 87 subjects and a total of 365 scans acquired with varying imaging protocols. The resulting emphysema estimates had very high intra-subject correlation values. By reducing sensitivity to changes in imaging protocol, the method provides a more robust estimate than standard approaches. The generated emphysema delineations promise advantages for regional analysis of emphysema extent and progression.

Building Systems from Scratch: An Exploratory Study of Students Learning about Climate Change

ERIC Educational Resources Information Center

Puttick, Gillian; Tucker-Raymond, Eli

2018-01-01

Science and computational practices such as modeling and abstraction are critical to understanding the complex systems that are integral to climate science. Given the demonstrated affordances of game design in supporting such practices, we implemented a free 4-day intensive workshop for middle school girls that focused on using the visual…

Dayglow and night glow of the Venusian upper atmosphere. Modelling and observations

NASA Astrophysics Data System (ADS)

Gronoff, G.; Lilensten, J.; Simon, C.; Barthélemy, M.; Leblanc, F.

2007-08-01

Aims. We present the modelling of the production of excited states of O, CO and N2 in the Venusian upper atmosphere, which allows to compute the nightglow emissions. In the dayside, we also compute several emissions, taking advantage of the small influence of resonant scattering for forbidden transitions. Methods. We compute the photoionisation and the photodissociation mechanisms, and thus the photoelectron production. We compute electron impact excitation and ionisation through a multi-stream stationary kinetic transport code. Finally, we compute the ion recombination with a stationary chemical model. Results.We predict altitude density profiles for O(1S) and O(1D) states and the emissions corresponding to their different transitions. They are found to be very comparable to the observations without the need for stratospheric emissions. In the nightside, we highlight the role of the N + O+2 reaction in the creation of the O(1S) state. This reaction has been suggested by Rees in 1975 (Frederick, 1976). It has been discussed several times afterwhile and in spite of different studies, is still controversial. However, when we take it in consideration in Venus, it is shown to be the cause of almost 90% of the state production. We calculate the production intensities of O(3S) and O(5S) states, which are needed for radiative transfer models. For CO we compute the Cameron band and the fourth positive band emissions. For N2 we compute the LBH, first and second positive bands. All these values are successfully compared to the experiment when data are available. Conclusions. For the first time, a comprehensive model is proposed to compute dayglow and nightglow emissions of the Venusian upper atmosphere. It relies on previous works with noticeable improvements, both on the transport and on the chemical aspects. In the near future, a radiative transfer model will be used to compute optically thick lines in the dayglow, and a fluid model will be added to compute ionosphere densities and temperatures. We will present the first observational results from the Pic du Midi telescope in June 2007, in order to compare with our modelling.

Analytical Modeling of a Novel Transverse Flux Machine for Direct Drive Wind Turbine Applications: Preprint

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

Hasan, IIftekhar; Husain, Tausif; Uddin, Md Wasi

2015-08-24

This paper presents a nonlinear analytical model of a novel double-sided flux concentrating Transverse Flux Machine (TFM) based on the Magnetic Equivalent Circuit (MEC) model. The analytical model uses a series-parallel combination of flux tubes to predict the flux paths through different parts of the machine including air gaps, permanent magnets, stator, and rotor. The two-dimensional MEC model approximates the complex three-dimensional flux paths of the TFM and includes the effects of magnetic saturation. The model is capable of adapting to any geometry that makes it a good alternative for evaluating prospective designs of TFM compared to finite element solversmore » that are numerically intensive and require more computation time. A single-phase, 1-kW, 400-rpm machine is analytically modeled, and its resulting flux distribution, no-load EMF, and torque are verified with finite element analysis. The results are found to be in agreement, with less than 5% error, while reducing the computation time by 25 times.« less

Analytical Modeling of a Novel Transverse Flux Machine for Direct Drive Wind Turbine Applications

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

Hasan, IIftekhar; Husain, Tausif; Uddin, Md Wasi

2015-09-02

This paper presents a nonlinear analytical model of a novel double sided flux concentrating Transverse Flux Machine (TFM) based on the Magnetic Equivalent Circuit (MEC) model. The analytical model uses a series-parallel combination of flux tubes to predict the flux paths through different parts of the machine including air gaps, permanent magnets (PM), stator, and rotor. The two-dimensional MEC model approximates the complex three-dimensional flux paths of the TFM and includes the effects of magnetic saturation. The model is capable of adapting to any geometry which makes it a good alternative for evaluating prospective designs of TFM as compared tomore » finite element solvers which are numerically intensive and require more computation time. A single phase, 1 kW, 400 rpm machine is analytically modeled and its resulting flux distribution, no-load EMF and torque, verified with Finite Element Analysis (FEA). The results are found to be in agreement with less than 5% error, while reducing the computation time by 25 times.« less

On the analysis of para-ammonia observations

NASA Technical Reports Server (NTRS)

Kuiper, T. B. H.

1994-01-01

The intensities and optical depths of the (1, 1), (2, 2), and (2, 1) inversion transitions of ammonia can be calculated quite accurately without solving the equations of statistical equilibrium. A two-temperature partition function suffices. The excitation of the K-ladders can be approximated by using a temperature obtained from a two-level model with the (2, 1) and (1, 1) levels. Distribution of populations between the ladders is described with the kinetic temperature. This enables one to compute the (1, 1) and (2, 1) inversion transition excitation temperatures and optical depths. To compute the (2, 2) brightness temperatures, the fractional population of the (2, 2) doublet is computed from the population of the (1, 1) doublet using the 'true rotation temperature,' which is calculated using a three-level model with the (2, 1), (2, 2), and (1, 1) levels. In spite of some iterative steps, the calculation is quite fast.

Reducing software mass through behavior control. [of planetary roving robots

NASA Technical Reports Server (NTRS)

Miller, David P.

1992-01-01

Attention is given to the tradeoff between communication and computation as regards a planetary rover (both these subsystems are very power-intensive, and both can be the major driver of the rover's power subsystem, and therefore the minimum mass and size of the rover). Software techniques that can be used to reduce the requirements on both communciation and computation, allowing the overall robot mass to be greatly reduced, are discussed. Novel approaches to autonomous control, called behavior control, employ an entirely different approach, and for many tasks will yield a similar or superior level of autonomy to traditional control techniques, while greatly reducing the computational demand. Traditional systems have several expensive processes that operate serially, while behavior techniques employ robot capabilities that run in parallel. Traditional systems make extensive world models, while behavior control systems use minimal world models or none at all.

Flow in curved ducts of varying cross-section

NASA Astrophysics Data System (ADS)

Sotiropoulos, F.; Patel, V. C.

1992-07-01

Two numerical methods for solving the incompressible Navier-Stokes equations are compared with each other by applying them to calculate laminar and turbulent flows through curved ducts of regular cross-section. Detailed comparisons, between the computed solutions and experimental data, are carried out in order to validate the two methods and to identify their relative merits and disadvantages. Based on the conclusions of this comparative study a numerical method is developed for simulating viscous flows through curved ducts of varying cross-sections. The proposed method is capable of simulating the near-wall turbulence using fine computational meshes across the sublayer in conjunction with a two-layer k-epsilon model. Numerical solutions are obtained for: (1) a straight transition duct geometry, and (2) a hydroturbine draft-tube configuration at model scale Reynolds number for various inlet swirl intensities. The report also provides a detailed literature survey that summarizes all the experimental and computational work in the area of duct flows.

Interactive computer modeling of combustion chemistry and coalescence-dispersion modeling of turbulent combustion

NASA Technical Reports Server (NTRS)

Pratt, D. T.

1984-01-01

An interactive computer code for simulation of a high-intensity turbulent combustor as a single point inhomogeneous stirred reactor was developed from an existing batch processing computer code CDPSR. The interactive CDPSR code was used as a guide for interpretation and direction of DOE-sponsored companion experiments utilizing Xenon tracer with optical laser diagnostic techniques to experimentally determine the appropriate mixing frequency, and for validation of CDPSR as a mixing-chemistry model for a laboratory jet-stirred reactor. The coalescence-dispersion model for finite rate mixing was incorporated into an existing interactive code AVCO-MARK I, to enable simulation of a combustor as a modular array of stirred flow and plug flow elements, each having a prescribed finite mixing frequency, or axial distribution of mixing frequency, as appropriate. Further increase the speed and reliability of the batch kinetics integrator code CREKID was increased by rewriting in vectorized form for execution on a vector or parallel processor, and by incorporating numerical techniques which enhance execution speed by permitting specification of a very low accuracy tolerance.

A model of proto-object based saliency

PubMed Central

Russell, Alexander F.; Mihalaş, Stefan; von der Heydt, Rudiger; Niebur, Ernst; Etienne-Cummings, Ralph

2013-01-01

Organisms use the process of selective attention to optimally allocate their computational resources to the instantaneously most relevant subsets of a visual scene, ensuring that they can parse the scene in real time. Many models of bottom-up attentional selection assume that elementary image features, like intensity, color and orientation, attract attention. Gestalt psychologists, how-ever, argue that humans perceive whole objects before they analyze individual features. This is supported by recent psychophysical studies that show that objects predict eye-fixations better than features. In this report we present a neurally inspired algorithm of object based, bottom-up attention. The model rivals the performance of state of the art non-biologically plausible feature based algorithms (and outperforms biologically plausible feature based algorithms) in its ability to predict perceptual saliency (eye fixations and subjective interest points) in natural scenes. The model achieves this by computing saliency as a function of proto-objects that establish the perceptual organization of the scene. All computational mechanisms of the algorithm have direct neural correlates, and our results provide evidence for the interface theory of attention. PMID:24184601

A computational model for estimating recruitment of primary afferent fibers by intraneural stimulation in the dorsal root ganglia

NASA Astrophysics Data System (ADS)

Bourbeau, D. J.; Hokanson, J. A.; Rubin, J. E.; Weber, D. J.

2011-10-01

Primary afferent microstimulation has been proposed as a method for activating cutaneous and muscle afferent fibers to restore tactile and proprioceptive feedback after limb loss or peripheral neuropathy. Large populations of primary afferent fibers can be accessed directly by implanting microelectrode arrays in the dorsal root ganglia (DRG), which provide a compact and stable target for stimulating a diverse group of sensory fibers. To gain insight into factors affecting the number and types of primary afferents activated, we developed a computational model that simulates the recruitment of fibers in the feline L7 DRG. The model comprises two parts. The first part is a single-fiber model used to describe the current-distance relation and was based on the McIntyre-Richardson-Grill model for excitability. The second part uses the results of the singe-fiber model and published data on fiber size distributions to predict the probability of recruiting a given number of fibers as a function of stimulus intensity. The range of intensities over which exactly one fiber was recruited was approximately 0.5-5 µA (0.1-1 nC per phase); the stimulus intensity at which the probability of recruiting exactly one fiber was maximized was 2.3 µA. However, at 2.3 µA, it was also possible to recruit up to three fibers, albeit with a lower probability. Stimulation amplitudes up to 6 µA were tested with the population model, which showed that as the amplitude increased, the number of fibers recruited increased exponentially. The distribution of threshold amplitudes predicted by the model was similar to that previously reported by in vivo experimentation. Finally, the model suggested that medium diameter fibers (7.3-11.5 µm) may be recruited with much greater probability than large diameter fibers (12.8-16 µm). This model may be used to efficiently test a range of stimulation parameters and nerve morphologies to complement results from electrophysiology experiments and to aid in the design of microelectrode arrays for neural interfaces.

Large-scale Vertical Motions, Intensity Change and Precipitation Associated with Land falling Hurricane Katrina over the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Reddy, S. R.; Kwembe, T.; Zhang, Z.

2016-12-01

We investigated the possible relationship between the large- scale heat fluxes and intensity change associated with the landfall of Hurricane Katrina. After reaching the category 5 intensity on August 28th , 2005 over the central Gulf of Mexico, Katrina weekend to category 3 before making landfall (August 29th , 2005) on the Louisiana coast with the maximum sustained winds of over 110 knots. We also examined the vertical motions associated with the intensity change of the hurricane. The data for Convective Available Potential Energy for water vapor (CAPE), sea level pressure and wind speed were obtained from the Atmospheric Soundings, and NOAA National Hurricane Center (NHC), respectively for the period August 24 to September 3, 2005. We also computed vertical motions using CAPE values. The study showed that the large-scale heat fluxes reached maximum (7960W/m2) with the central pressure 905mb. The Convective Available Potential Energy and the vertical motions peaked 3-5 days before landfall. The large atmospheric vertical motions associated with the land falling hurricane Katrina produced severe weather including thunderstorm, tornadoes, storm surge and floods Numerical model (WRF/ARW) with data assimilations have been used for this research to investigate the model's performances on hurricane tracks and intensities associated with the hurricane Katrina, which began to strengthen until reaching Category 5 on 28 August 2005. The model was run on a doubly nested domain centered over the central Gulf of Mexico, with grid spacing of 90 km and 30 km for 6 hr periods, from August 28th to August 30th. The model output was compared with the observations and is capable of simulating the surface features, intensity change and track associated with hurricane Katrina.

Functional modeling of the human auditory brainstem response to broadband stimulationa)

PubMed Central

Verhulst, Sarah; Bharadwaj, Hari M.; Mehraei, Golbarg; Shera, Christopher A.; Shinn-Cunningham, Barbara G.

2015-01-01

Population responses such as the auditory brainstem response (ABR) are commonly used for hearing screening, but the relationship between single-unit physiology and scalp-recorded population responses are not well understood. Computational models that integrate physiologically realistic models of single-unit auditory-nerve (AN), cochlear nucleus (CN) and inferior colliculus (IC) cells with models of broadband peripheral excitation can be used to simulate ABRs and thereby link detailed knowledge of animal physiology to human applications. Existing functional ABR models fail to capture the empirically observed 1.2–2 ms ABR wave-V latency-vs-intensity decrease that is thought to arise from level-dependent changes in cochlear excitation and firing synchrony across different tonotopic sections. This paper proposes an approach where level-dependent cochlear excitation patterns, which reflect human cochlear filter tuning parameters, drive AN fibers to yield realistic level-dependent properties of the ABR wave-V. The number of free model parameters is minimal, producing a model in which various sources of hearing-impairment can easily be simulated on an individualized and frequency-dependent basis. The model fits latency-vs-intensity functions observed in human ABRs and otoacoustic emissions while maintaining rate-level and threshold characteristics of single-unit AN fibers. The simulations help to reveal which tonotopic regions dominate ABR waveform peaks at different stimulus intensities. PMID:26428802

Numerical simulation of stress amplification induced by crack interaction in human femur bone

NASA Astrophysics Data System (ADS)

Alia, Noor; Daud, Ruslizam; Ramli, Mohammad Fadzli; Azman, Wan Zuki; Faizal, Ahmad; Aisyah, Siti

2015-05-01

This research is about numerical simulation using a computational method which study on stress amplification induced by crack interaction in human femur bone. Cracks in human femur bone usually occur because of large load or stress applied on it. Usually, the fracture takes longer time to heal itself. At present, the crack interaction is still not well understood due to bone complexity. Thus, brittle fracture behavior of bone may be underestimated and inaccurate. This study aims to investigate the geometrical effect of double co-planar edge cracks on stress intensity factor (K) in femur bone. This research focuses to analyze the amplification effect on the fracture behavior of double co-planar edge cracks, where numerical model is developed using computational method. The concept of fracture mechanics and finite element method (FEM) are used to solve the interacting cracks problems using linear elastic fracture mechanics (LEFM) theory. As a result, this study has shown the identification of the crack interaction limit (CIL) and crack unification limit (CUL) exist in the human femur bone model developed. In future research, several improvements will be made such as varying the load, applying thickness on the model and also use different theory or method in calculating the stress intensity factor (K).

Computational approach to seasonal changes of living leaves.

PubMed

Tang, Ying; Wu, Dong-Yan; Fan, Jing

2013-01-01

This paper proposes a computational approach to seasonal changes of living leaves by combining the geometric deformations and textural color changes. The geometric model of a leaf is generated by triangulating the scanned image of a leaf using an optimized mesh. The triangular mesh of the leaf is deformed by the improved mass-spring model, while the deformation is controlled by setting different mass values for the vertices on the leaf model. In order to adaptively control the deformation of different regions in the leaf, the mass values of vertices are set to be in proportion to the pixels' intensities of the corresponding user-specified grayscale mask map. The geometric deformations as well as the textural color changes of a leaf are used to simulate the seasonal changing process of leaves based on Markov chain model with different environmental parameters including temperature, humidness, and time. Experimental results show that the method successfully simulates the seasonal changes of leaves.

Combination of the discontinuous Galerkin method with finite differences for simulation of seismic wave propagation

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

Lisitsa, Vadim, E-mail: lisitsavv@ipgg.sbras.ru; Novosibirsk State University, Novosibirsk; Tcheverda, Vladimir

We present an algorithm for the numerical simulation of seismic wave propagation in models with a complex near surface part and free surface topography. The approach is based on the combination of finite differences with the discontinuous Galerkin method. The discontinuous Galerkin method can be used on polyhedral meshes; thus, it is easy to handle the complex surfaces in the models. However, this approach is computationally intense in comparison with finite differences. Finite differences are computationally efficient, but in general, they require rectangular grids, leading to the stair-step approximation of the interfaces, which causes strong diffraction of the wavefield. Inmore » this research we present a hybrid algorithm where the discontinuous Galerkin method is used in a relatively small upper part of the model and finite differences are applied to the main part of the model.« less

Neurophysiological model of the normal and abnormal human pupil

NASA Technical Reports Server (NTRS)

Krenz, W.; Robin, M.; Barez, S.; Stark, L.

1985-01-01

Anatomical, experimental, and computer simulation studies were used to determine the structure of the neurophysiological model of the pupil size control system. The computer simulation of this model demonstrates the role played by each of the elements in the neurological pathways influencing the size of the pupil. Simulations of the effect of drugs and common abnormalities in the system help to illustrate the workings of the pathways and processes involved. The simulation program allows the user to select pupil condition (normal or an abnormality), specific site along the neurological pathway (retina, hypothalamus, etc.) drug class input (barbiturate, narcotic, etc.), stimulus/response mode, display mode, stimulus type and input waveform, stimulus or background intensity and frequency, the input and output conditions, and the response at the neuroanatomical site. The model can be used as a teaching aid or as a tool for testing hypotheses regarding the system.

Development of a dynamic computational model of social cognitive theory.

PubMed

Riley, William T; Martin, Cesar A; Rivera, Daniel E; Hekler, Eric B; Adams, Marc A; Buman, Matthew P; Pavel, Misha; King, Abby C

2016-12-01

Social cognitive theory (SCT) is among the most influential theories of behavior change and has been used as the conceptual basis of health behavior interventions for smoking cessation, weight management, and other health behaviors. SCT and other behavior theories were developed primarily to explain differences between individuals, but explanatory theories of within-person behavioral variability are increasingly needed as new technologies allow for intensive longitudinal measures and interventions adapted from these inputs. These within-person explanatory theoretical applications can be modeled as dynamical systems. SCT constructs, such as reciprocal determinism, are inherently dynamical in nature, but SCT has not been modeled as a dynamical system. This paper describes the development of a dynamical system model of SCT using fluid analogies and control systems principles drawn from engineering. Simulations of this model were performed to assess if the model performed as predicted based on theory and empirical studies of SCT. This initial model generates precise and testable quantitative predictions for future intensive longitudinal research. Dynamic modeling approaches provide a rigorous method for advancing health behavior theory development and refinement and for guiding the development of more potent and efficient interventions.

Exploring Ultrahigh-Intensity Laser-Plasma Interaction Physics with QED Particle-in-Cell Simulations

NASA Astrophysics Data System (ADS)

Luedtke, S. V.; Yin, L.; Labun, L. A.; Albright, B. J.; Stark, D. J.; Bird, R. F.; Nystrom, W. D.; Hegelich, B. M.

2017-10-01

Next generation high-intensity lasers are reaching intensity regimes where new physics-quantum electrodynamics (QED) corrections to otherwise classical plasma dynamics-becomes important. Modeling laser-plasma interactions in these extreme settings presents a challenge to traditional particle-in-cell (PIC) codes, which either do not have radiation reaction or include only classical radiation reaction. We discuss a semi-classical approach to adding quantum radiation reaction and photon production to the PIC code VPIC. We explore these intensity regimes with VPIC, compare with results from the PIC code PSC, and report on ongoing work to expand the capability of VPIC in these regimes. This work was supported by the U.S. DOE, Los Alamos National Laboratory Science program, LDRD program, NNSA (DE-NA0002008), and AFOSR (FA9550-14-1-0045). HPC resources provided by TACC, XSEDE, and LANL Institutional Computing.

Rainfall Intensity and Frequency Explain Production Basis Risk in Cumulative Rain Index Insurance

NASA Astrophysics Data System (ADS)

Muneepeerakul, Chitsomanus P.; Muneepeerakul, Rachata; Huffaker, Ray G.

2017-12-01

With minimal moral hazard and adverse selection, weather index insurance promises financial resilience to farmers struck by harsh weather conditions through swift compensation at affordable premium. Despite these advantages, the very nature of indexing gives rise to production basis risk as the selected weather indexes do not sufficiently correspond to actual damages. To address this problem, we develop a stochastic yield model, built upon a stochastic soil moisture model driven by marked Poisson rainfall. Our analysis shows that even under similar temperature and rainfall amount yields can differ significantly; this was empirically supported by a 2-year field experiment in which rain-fed maize was grown under very similar total rainfall. Here, the year with more intense, less-frequent rainfall produces a better yield—a rare counter evidence to most climate change projections. Through a stochastic yield model, we demonstrate the crucial roles of rainfall intensity and frequency in determining the yield. Importantly, the model allows us to compute rainfall pattern-related basis risk inherent in cumulative rain index insurance. The model results and a case study herein clearly show that total rainfall is a poor indicator of yield, imposing unnecessary production basis risk on farmers and false-positive payouts on insurers. Incorporating rainfall intensity and frequency in the design of rain index insurance can offer farmers better protection, while maintaining the attractive features of the weather index insurance and thus fulfilling its promise of financial resilience.

The Poynting-Stokes Tensor And Radiative Transfer In Turbid Media: The Microphysical Paradigm

NASA Astrophysics Data System (ADS)

Mishchenko, M. I.

2010-12-01

This paper solves the long-standing problem of establishing the fundamental physical link between the radiative transfer theory and macroscopic electromagnetics in the case of elastic scattering by a sparse discrete random medium. The radiative transfer equation (RTE) is derived directly from the macroscopic Maxwell equations by computing theoretically the appropriately defined so-called Poynting-Stokes tensor carrying informa-tion on both the direction, magnitude, and polarization characteristics of lo-cal electromagnetic energy flow. Our derivation from first principles shows that to compute the local Poynting vector averaged over a sufficiently long period of time, one can solve the RTE for the direction-dependent specific intensity column vector and then integrate the direction-weighted specific intensity over all directions. Furthermore, we demonstrate that the specific intensity (or specific intensity column vector) can be measured with a well-collimated radiometer (photopolarimeter), which provides the ultimate physical justification for the use of such instruments in radiation-budget and particle-characterization applications. However, the specific intensity cannot be interpreted in phenomenological terms as signifying the amount of elec-tromagnetic energy transported in a given direction per unit area normal to this direction per unit time per unit solid angle. Also, in the case of a densely packed scattering medium the relation of the measurement with a well-collimated radiometer to the time-averaged local Poynting vector re-mains uncertain, and the theoretical modeling of this measurement is likely to require a much more complicated approach than solving an RTE.

Statistical equilibrium calculations for silicon in early-type model stellar atmospheres

NASA Technical Reports Server (NTRS)

Kamp, L. W.

1976-01-01

Line profiles of 36 multiplets of silicon (Si) II, III, and IV were computed for a grid of model atmospheres covering the range from 15,000 to 35,000 K in effective temperature and 2.5 to 4.5 in log (gravity). The computations involved simultaneous solution of the steady-state statistical equilibrium equations for the populations and of the equation of radiative transfer in the lines. The variables were linearized, and successive corrections were computed until a minimal accuracy of 1/1000 in the line intensities was reached. The common assumption of local thermodynamic equilibrium (LTE) was dropped. The model atmospheres used also were computed by non-LTE methods. Some effects that were incorporated into the calculations were the depression of the continuum by free electrons, hydrogen and ionized helium line blocking, and auto-ionization and dielectronic recombination, which later were found to be insignificant. Use of radiation damping and detailed electron (quadratic Stark) damping constants had small but significant effects on the strong resonance lines of Si III and IV. For weak and intermediate-strength lines, large differences with respect to LTE computations, the results of which are also presented, were found in line shapes and strengths. For the strong lines the differences are generally small, except for the models at the hot, low-gravity extreme of our range. These computations should be useful in the interpretation of the spectra of stars in the spectral range B0-B5, luminosity classes III, IV, and V.

Optimization of tomographic reconstruction workflows on geographically distributed resources

DOE PAGES

Bicer, Tekin; Gursoy, Doga; Kettimuthu, Rajkumar; ...

2016-01-01

New technological advancements in synchrotron light sources enable data acquisitions at unprecedented levels. This emergent trend affects not only the size of the generated data but also the need for larger computational resources. Although beamline scientists and users have access to local computational resources, these are typically limited and can result in extended execution times. Applications that are based on iterative processing as in tomographic reconstruction methods require high-performance compute clusters for timely analysis of data. Here, time-sensitive analysis and processing of Advanced Photon Source data on geographically distributed resources are focused on. Two main challenges are considered: (i) modelingmore » of the performance of tomographic reconstruction workflows and (ii) transparent execution of these workflows on distributed resources. For the former, three main stages are considered: (i) data transfer between storage and computational resources, (i) wait/queue time of reconstruction jobs at compute resources, and (iii) computation of reconstruction tasks. These performance models allow evaluation and estimation of the execution time of any given iterative tomographic reconstruction workflow that runs on geographically distributed resources. For the latter challenge, a workflow management system is built, which can automate the execution of workflows and minimize the user interaction with the underlying infrastructure. The system utilizes Globus to perform secure and efficient data transfer operations. The proposed models and the workflow management system are evaluated by using three high-performance computing and two storage resources, all of which are geographically distributed. Workflows were created with different computational requirements using two compute-intensive tomographic reconstruction algorithms. Experimental evaluation shows that the proposed models and system can be used for selecting the optimum resources, which in turn can provide up to 3.13× speedup (on experimented resources). Furthermore, the error rates of the models range between 2.1 and 23.3% (considering workflow execution times), where the accuracy of the model estimations increases with higher computational demands in reconstruction tasks.« less

Optimization of tomographic reconstruction workflows on geographically distributed resources

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

Bicer, Tekin; Gursoy, Doga; Kettimuthu, Rajkumar

New technological advancements in synchrotron light sources enable data acquisitions at unprecedented levels. This emergent trend affects not only the size of the generated data but also the need for larger computational resources. Although beamline scientists and users have access to local computational resources, these are typically limited and can result in extended execution times. Applications that are based on iterative processing as in tomographic reconstruction methods require high-performance compute clusters for timely analysis of data. Here, time-sensitive analysis and processing of Advanced Photon Source data on geographically distributed resources are focused on. Two main challenges are considered: (i) modelingmore » of the performance of tomographic reconstruction workflows and (ii) transparent execution of these workflows on distributed resources. For the former, three main stages are considered: (i) data transfer between storage and computational resources, (i) wait/queue time of reconstruction jobs at compute resources, and (iii) computation of reconstruction tasks. These performance models allow evaluation and estimation of the execution time of any given iterative tomographic reconstruction workflow that runs on geographically distributed resources. For the latter challenge, a workflow management system is built, which can automate the execution of workflows and minimize the user interaction with the underlying infrastructure. The system utilizes Globus to perform secure and efficient data transfer operations. The proposed models and the workflow management system are evaluated by using three high-performance computing and two storage resources, all of which are geographically distributed. Workflows were created with different computational requirements using two compute-intensive tomographic reconstruction algorithms. Experimental evaluation shows that the proposed models and system can be used for selecting the optimum resources, which in turn can provide up to 3.13× speedup (on experimented resources). Furthermore, the error rates of the models range between 2.1 and 23.3% (considering workflow execution times), where the accuracy of the model estimations increases with higher computational demands in reconstruction tasks.« less

Geometry Modeling and Grid Generation for Design and Optimization

NASA Technical Reports Server (NTRS)

Samareh, Jamshid A.

1998-01-01

Geometry modeling and grid generation (GMGG) have played and will continue to play an important role in computational aerosciences. During the past two decades, tremendous progress has occurred in GMGG; however, GMGG is still the biggest bottleneck to routine applications for complicated Computational Fluid Dynamics (CFD) and Computational Structures Mechanics (CSM) models for analysis, design, and optimization. We are still far from incorporating GMGG tools in a design and optimization environment for complicated configurations. It is still a challenging task to parameterize an existing model in today's Computer-Aided Design (CAD) systems, and the models created are not always good enough for automatic grid generation tools. Designers may believe their models are complete and accurate, but unseen imperfections (e.g., gaps, unwanted wiggles, free edges, slivers, and transition cracks) often cause problems in gridding for CSM and CFD. Despite many advances in grid generation, the process is still the most labor-intensive and time-consuming part of the computational aerosciences for analysis, design, and optimization. In an ideal design environment, a design engineer would use a parametric model to evaluate alternative designs effortlessly and optimize an existing design for a new set of design objectives and constraints. For this ideal environment to be realized, the GMGG tools must have the following characteristics: (1) be automated, (2) provide consistent geometry across all disciplines, (3) be parametric, and (4) provide sensitivity derivatives. This paper will review the status of GMGG for analysis, design, and optimization processes, and it will focus on some emerging ideas that will advance the GMGG toward the ideal design environment.

Color appearance for photorealistic image synthesis

NASA Astrophysics Data System (ADS)

Marini, Daniele; Rizzi, Alessandro; Rossi, Maurizio

2000-12-01

Photorealistic Image Synthesis is a relevant research and application field in computer graphics, whose aim is to produce synthetic images that are undistinguishable from real ones. Photorealism is based upon accurate computational models of light material interaction, that allow us to compute the spectral intensity light field of a geometrically described scene. The fundamental methods are ray tracing and radiosity. While radiosity allows us to compute the diffuse component of the emitted and reflected light, applying ray tracing in a two pass solution we can also cope with non diffuse properties of the model surfaces. Both methods can be implemented to generate an accurate photometric distribution of light of the simulated environment. A still open problem is the visualization phase, whose purpose is to display the final result of the simulated mode on a monitor screen or on a printed paper. The tone reproduction problem consists of finding the best solution to compress the extended dynamic range of the computed light field into the limited range of the displayable colors. Recently some scholars have addressed this problem considering the perception stage of image formation, so including a model of the human visual system in the visualization process. In this paper we present a working hypothesis to solve the tone reproduction problem of synthetic image generation, integrating Retinex perception model into the photo realistic image synthesis context.

Limb-darkening coefficients for the purpose of pulsation mode identification for A-F stars. .

NASA Astrophysics Data System (ADS)

Barban, C.; Goupil, M. J.; van't Veer-Menneret, C.; Garrido, R.; Heiter, U.; Kupka, F.

Limb-darkening coefficients are computed from a set of model atmospheres with: a solar chemical composition, 6000 K< Teff < 8500 K (Delta T_eff=250 K), 2.5 < logg < 4.5 (Delta log g=0.1) and a microturbulent velocity of 2 km/s. Convection is included assuming either the turbulent convection approach of \\citet{cm} or the classical mixing length prescription with alpha =0.5 and 1.25. Four limb-darkening laws have been used: quadratic, cubic, square root and the one of \\citet{cl}. We compare the ATLAS 9 intensities and the ones computed from these laws. We find that Claret's law is the best law for almost all the models, independently of the convection prescription used.

[Parallel virtual reality visualization of extreme large medical datasets].

PubMed

Tang, Min

2010-04-01

On the basis of a brief description of grid computing, the essence and critical techniques of parallel visualization of extreme large medical datasets are discussed in connection with Intranet and common-configuration computers of hospitals. In this paper are introduced several kernel techniques, including the hardware structure, software framework, load balance and virtual reality visualization. The Maximum Intensity Projection algorithm is realized in parallel using common PC cluster. In virtual reality world, three-dimensional models can be rotated, zoomed, translated and cut interactively and conveniently through the control panel built on virtual reality modeling language (VRML). Experimental results demonstrate that this method provides promising and real-time results for playing the role in of a good assistant in making clinical diagnosis.

Solid particle dynamic behavior through twisted blade rows

NASA Technical Reports Server (NTRS)

Hamed, A.

1982-01-01

The particle trajectory calculations provide the essential information which is required for predicting the pattern and intensity of turbomachinery erosion. Consequently, the evaluation of the machine performance deterioration due to erosion is extremely sensitive to the accuracy of the flow field and blade geometry representation in the trajectory computational model. A model is presented that is simple and efficient yet versatile and general to be applicable to axial, radial and mixed flow machines, and to inlets, nozzles, return passages and separators. The results of the computations are presented for the particle trajectories through a row of twisted vanes in the inlet flow field. The effect of the particle size on their trajectories, blade impacts, and on their redistribution and separation are discussed.

An infrared scattering by evaporating droplets at the initial stage of a pool fire suppression by water sprays

NASA Astrophysics Data System (ADS)

Dombrovsky, Leonid A.; Dembele, Siaka; Wen, Jennifer X.

2018-06-01

The computational analysis of downward motion and evaporation of water droplets used to suppress a typical transient pool fire shows local regions of a high volume fraction of relatively small droplets. These droplets are comparable in size with the infrared wavelength in the range of intense flame radiation. The estimated scattering of the radiation by these droplets is considerable throughout the entire spectrum except for a narrow region in the vicinity of the main absorption peak of water where the anomalous refraction takes place. The calculations of infrared radiation field in the model pool fire indicate the strong effect of scattering which can be observed experimentally to validate the fire computational model.

The M-Integral for Computing Stress Intensity Factors in Generally Anisotropic Materials

NASA Technical Reports Server (NTRS)

Warzynek, P. A.; Carter, B. J.; Banks-Sills, L.

2005-01-01

The objective of this project is to develop and demonstrate a capability for computing stress intensity factors in generally anisotropic materials. These objectives have been met. The primary deliverable of this project is this report and the information it contains. In addition, we have delivered the source code for a subroutine that will compute stress intensity factors for anisotropic materials encoded in both the C and Python programming languages and made available a version of the FRANC3D program that incorporates this subroutine. Single crystal super alloys are commonly used for components in the hot sections of contemporary jet and rocket engines. Because these components have a uniform atomic lattice orientation throughout, they exhibit anisotropic material behavior. This means that stress intensity solutions developed for isotropic materials are not appropriate for the analysis of crack growth in these materials. Until now, a general numerical technique did not exist for computing stress intensity factors of cracks in anisotropic materials and cubic materials in particular. Such a capability was developed during the project and is described and demonstrated herein.

Effects of Computer-Based Practice on the Acquisition and Maintenance of Basic Academic Skills for Children with Moderate to Intensive Educational Needs

ERIC Educational Resources Information Center

Everhart, Julie M.; Alber-Morgan, Sheila R.; Park, Ju Hee

2011-01-01

This study investigated the effects of computer-based practice on the acquisition and maintenance of basic academic skills for two children with moderate to intensive disabilities. The special education teacher created individualized computer games that enabled the participants to independently practice academic skills that corresponded with their…

Electron transport theory in magnetic nanostructures

NASA Astrophysics Data System (ADS)

Choy, Tat-Sang

Magnetic nanostructure has been a new trend because of its application in making magnetic sensors, magnetic memories, and magnetic reading heads in hard disks drives. Although a variety of nanostructures have been realized in experiments in recent years by innovative sample growth techniques, the theoretical study of these devices remain a challenge. On one hand, atomic scale modeling is often required for studying the magnetic nanostructures; on the other, these structures often have a dimension on the order of one micrometer, which makes the calculation numerically intensive. In this work, we have studied the electron transport theory in magnetic nanostructures, with special attention to the giant magnetoresistance (GMR) structure. We have developed a model that includes the details of the band structure and disorder, both of which are both important in obtaining the conductivity. We have also developed an efficient algorithm to compute the conductivity in magnetic nanostructures. The model and the algorithm are general and can be applied to complicated structures. We have applied the theory to current-perpendicular-to-plane GMR structures and the results agree with experiments. Finally, we have searched for the atomic configuration with the highest GMR using the simulated annealing algorithm. This method is computationally intensive because we have to compute the GMR for 103 to 104 configurations. However it is still very efficient because the number of steps it takes to find the maximum is much smaller than the number of all possible GMR structures. We found that ultra-thin NiCu superlattices have surprisingly large GMR even at the moderate disorder in experiments. This finding may be useful in improving the GMR technology.

Investigation of beamed-energy ERH thruster performance

NASA Technical Reports Server (NTRS)

Myrabo, Leik N.; Strayer, T. Darton; Bossard, John A.; Richard, Jacques C.; Gallimore, Alec D.

1986-01-01

The objective of this study was to determine the performance of an External Radiation Heated (ERH) thruster. In this thruster, high intensity laser energy is focused to ignite either a Laser Supported Combustion (LSC) wave or a Laser Supported Detonation (LSD) wave. Thrust is generated as the LSC or LSD wave propagates over the thruster's surface, or in the proposed thruster configuration, the vehicle afterbody. Thrust models for the LSC and LSD waves were developed and simulated on a computer. Performance parameters investigated include the effect of laser intensity, flight Mach number, and altitude on mean-thrust and coupling coefficient of the ERH thruster. Results from these models suggest that the ERH thruster using LSC/LSD wave ignition could provide propulsion performance considerably greater than any propulsion system currently available.

Effects of high optical injection levels in polycrystalline Si wafers on carrier transport

NASA Astrophysics Data System (ADS)

Steele, Doneisha; Semichaevsky, Andrey

High levels of carrier injection in polycrystalline Si may arise, for example, in solar cells under concentrated sunlight. Mechanisms for non-radiative carrier recombination include trap-mediated SRH and higher-order processes, e.g., Auger recombination. In this paper we present our experimental results for intensity-dependent carrier lifetimes and conduction currents in polycrystalline Si wafers illuminated with pulses of up to 50 Sun intensity. We also use a computational model for carrier transport that includes both SRH and Auger recombination mechanisms, in order to explain our experiments. The model allows quantifying recombination rate dependence on carrier concentration. Our goal is to relate the recombination rates to Si microstructure and defect densities that are revealed by IR PL images. We acknowledge the NSF support through Grant 1505377.

Analysis of speckle and material properties in laider tracer

NASA Astrophysics Data System (ADS)

Ross, Jacob W.; Rigling, Brian D.; Watson, Edward A.

2017-04-01

The SAL simulation tool Laider Tracer models speckle: the random variation in intensity of an incident light beam across a rough surface. Within Laider Tracer, the speckle field is modeled as a 2-D array of jointly Gaussian random variables projected via ray tracing onto the scene of interest. Originally, all materials in Laider Tracer were treated as ideal diffuse scatterers, for which the far-field return computed uses the Lambertian Bidirectional Reflectance Distribution Function (BRDF). As presented here, we implement material properties into Laider Tracer via the Non-conventional Exploitation Factors Data System: a database of properties for thousands of different materials sampled at various wavelengths and incident angles. We verify the intensity behavior as a function of incident angle after material properties are added to the simulation.

Modelling of flow processes of the structured two-phase disperse systems (solid phase-liquid medium).

PubMed

Uriev, N B; Kuchin, I V

2007-10-31

A review of the basic theories and models of shear flow of suspensions is presented and the results of modeling of structured suspensions under flow conditions. The physical backgrounds and conditions of macroscopic discontinuity in the behaviour of high-concentrated systems are analyzed. The use of surfactants and imposed vibration for regulation of rheological properties of suspensions are considered. A review of the recent approaches and methods of computer simulation of concentrated suspensions is undertaken and results of computer simulation of suspensions are presented. Formation and destruction of the structure of suspension under static and dynamic conditions (including imposed combined shear and orthogonal oscillations) are discussed. The influence of interaction of particles as well as of some parameters characterizing a type and intensity of external perturbations on suspensions behavior is demonstrated.

Wildfire simulation using LES with synthetic-velocity SGS models

NASA Astrophysics Data System (ADS)

McDonough, J. M.; Tang, Tingting

2016-11-01

Wildland fires are becoming more prevalent and intense worldwide as climate change leads to warmer, drier conditions; and large-eddy simulation (LES) is receiving increasing attention for fire spread predictions as computing power continues to improve (see, e.g.,). We report results from wildfire simulations over general terrain employing implicit LES for solution of the incompressible Navier-Stokes (N.-S.) and thermal energy equations with Boussinesq approximation, altered with Darcy, Forchheimer and Brinkman extensions, to represent forested regions as porous media with varying (in both space and time) porosity and permeability. We focus on subgrid-scale (SGS) behaviors computed with a synthetic-velocity model, a discrete dynamical system, based on the poor man's N.-S. equations and investigate the ability of this model to produce fire whirls (tornadoes of fire) at the (unresolved) SGS level. Professor, Mechanical Engineering and Mathematics.

Statistical and temporal irradiance fluctuations modeling for a ground-to-geostationary satellite optical link.

PubMed

Camboulives, A-R; Velluet, M-T; Poulenard, S; Saint-Antonin, L; Michau, V

2018-02-01

An optical communication link performance between the ground and a geostationary satellite can be impaired by scintillation, beam wandering, and beam spreading due to its propagation through atmospheric turbulence. These effects on the link performance can be mitigated by tracking and error correction codes coupled with interleaving. Precise numerical tools capable of describing the irradiance fluctuations statistically and of creating an irradiance time series are needed to characterize the benefits of these techniques and optimize them. The wave optics propagation methods have proven their capability of modeling the effects of atmospheric turbulence on a beam, but these are known to be computationally intensive. We present an analytical-numerical model which provides good results on the probability density functions of irradiance fluctuations as well as a time series with an important saving of time and computational resources.

Toward in vivo diagnosis of skin cancer using multimode imaging dermoscopy: (II) molecular mapping of highly pigmented lesions

NASA Astrophysics Data System (ADS)

Vasefi, Fartash; MacKinnon, Nicholas; Farkas, Daniel L.

2014-03-01

We have developed a multimode imaging dermoscope that combines polarization and hyperspectral imaging with a computationally rapid analytical model. This approach employs specific spectral ranges of visible and near infrared wavelengths for mapping the distribution of specific skin bio-molecules. This corrects for the melanin-hemoglobin misestimation common to other systems, without resorting to complex and computationally intensive tissue optical models that are prone to inaccuracies due to over-modeling. Various human skin measurements including a melanocytic nevus, and venous occlusion conditions were investigated and compared with other ratiometric spectral imaging approaches. Access to the broad range of hyperspectral data in the visible and near-infrared range allows our algorithm to flexibly use different wavelength ranges for chromophore estimation while minimizing melanin-hemoglobin optical signature cross-talk.

Evaluating 20th Century precipitation characteristics between multi-scale atmospheric models with different land-atmosphere coupling

NASA Astrophysics Data System (ADS)

Phillips, M.; Denning, A. S.; Randall, D. A.; Branson, M.

2016-12-01

Multi-scale models of the atmosphere provide an opportunity to investigate processes that are unresolved by traditional Global Climate Models while at the same time remaining viable in terms of computational resources for climate-length time scales. The MMF represents a shift away from large horizontal grid spacing in traditional GCMs that leads to overabundant light precipitation and lack of heavy events, toward a model where precipitation intensity is allowed to vary over a much wider range of values. Resolving atmospheric motions on the scale of 4 km makes it possible to recover features of precipitation, such as intense downpours, that were previously only obtained by computationally expensive regional simulations. These heavy precipitation events may have little impact on large-scale moisture and energy budgets, but are outstanding in terms of interaction with the land surface and potential impact on human life. Three versions of the Community Earth System Model were used in this study; the standard CESM, the multi-scale `Super-Parameterized' CESM where large-scale parameterizations have been replaced with a 2D cloud-permitting model, and a multi-instance land version of the SP-CESM where each column of the 2D CRM is allowed to interact with an individual land unit. These simulations were carried out using prescribed Sea Surface Temperatures for the period from 1979-2006 with daily precipitation saved for all 28 years. Comparisons of the statistical properties of precipitation between model architectures and against observations from rain gauges were made, with specific focus on detection and evaluation of extreme precipitation events.

Application of a hybrid MPI/OpenMP approach for parallel groundwater model calibration using multi-core computers

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

Tang, Guoping; D'Azevedo, Ed F; Zhang, Fan

2010-01-01

Calibration of groundwater models involves hundreds to thousands of forward solutions, each of which may solve many transient coupled nonlinear partial differential equations, resulting in a computationally intensive problem. We describe a hybrid MPI/OpenMP approach to exploit two levels of parallelisms in software and hardware to reduce calibration time on multi-core computers. HydroGeoChem 5.0 (HGC5) is parallelized using OpenMP for direct solutions for a reactive transport model application, and a field-scale coupled flow and transport model application. In the reactive transport model, a single parallelizable loop is identified to account for over 97% of the total computational time using GPROF.more » Addition of a few lines of OpenMP compiler directives to the loop yields a speedup of about 10 on a 16-core compute node. For the field-scale model, parallelizable loops in 14 of 174 HGC5 subroutines that require 99% of the execution time are identified. As these loops are parallelized incrementally, the scalability is found to be limited by a loop where Cray PAT detects over 90% cache missing rates. With this loop rewritten, similar speedup as the first application is achieved. The OpenMP-parallelized code can be run efficiently on multiple workstations in a network or multiple compute nodes on a cluster as slaves using parallel PEST to speedup model calibration. To run calibration on clusters as a single task, the Levenberg Marquardt algorithm is added to HGC5 with the Jacobian calculation and lambda search parallelized using MPI. With this hybrid approach, 100 200 compute cores are used to reduce the calibration time from weeks to a few hours for these two applications. This approach is applicable to most of the existing groundwater model codes for many applications.« less

Dynamic Collaboration Infrastructure for Hydrologic Science

NASA Astrophysics Data System (ADS)

Tarboton, D. G.; Idaszak, R.; Castillo, C.; Yi, H.; Jiang, F.; Jones, N.; Goodall, J. L.

2016-12-01

Data and modeling infrastructure is becoming increasingly accessible to water scientists. HydroShare is a collaborative environment that currently offers water scientists the ability to access modeling and data infrastructure in support of data intensive modeling and analysis. It supports the sharing of and collaboration around "resources" which are social objects defined to include both data and models in a structured standardized format. Users collaborate around these objects via comments, ratings, and groups. HydroShare also supports web services and cloud based computation for the execution of hydrologic models and analysis and visualization of hydrologic data. However, the quantity and variety of data and modeling infrastructure available that can be accessed from environments like HydroShare is increasing. Storage infrastructure can range from one's local PC to campus or organizational storage to storage in the cloud. Modeling or computing infrastructure can range from one's desktop to departmental clusters to national HPC resources to grid and cloud computing resources. How does one orchestrate this vast number of data and computing infrastructure without needing to correspondingly learn each new system? A common limitation across these systems is the lack of efficient integration between data transport mechanisms and the corresponding high-level services to support large distributed data and compute operations. A scientist running a hydrology model from their desktop may require processing a large collection of files across the aforementioned storage and compute resources and various national databases. To address these community challenges a proof-of-concept prototype was created integrating HydroShare with RADII (Resource Aware Data-centric collaboration Infrastructure) to provide software infrastructure to enable the comprehensive and rapid dynamic deployment of what we refer to as "collaborative infrastructure." In this presentation we discuss the results of this proof-of-concept prototype which enabled HydroShare users to readily instantiate virtual infrastructure marshaling arbitrary combinations, varieties, and quantities of distributed data and computing infrastructure in addressing big problems in hydrology.

Application verification research of cloud computing technology in the field of real time aerospace experiment

NASA Astrophysics Data System (ADS)

Wan, Junwei; Chen, Hongyan; Zhao, Jing

2017-08-01

According to the requirements of real-time, reliability and safety for aerospace experiment, the single center cloud computing technology application verification platform is constructed. At the IAAS level, the feasibility of the cloud computing technology be applied to the field of aerospace experiment is tested and verified. Based on the analysis of the test results, a preliminary conclusion is obtained: Cloud computing platform can be applied to the aerospace experiment computing intensive business. For I/O intensive business, it is recommended to use the traditional physical machine.

Computational modeling of chemo-bio-mechanical coupling: a systems-biology approach toward wound healing.

PubMed

Buganza Tepole, A; Kuhl, E

2016-01-01

Wound healing is a synchronized cascade of chemical, biological, and mechanical phenomena, which act in concert to restore the damaged tissue. An imbalance between these events can induce painful scarring. Despite intense efforts to decipher the mechanisms of wound healing, the role of mechanics remains poorly understood. Here, we establish a computational systems biology model to identify the chemical, biological, and mechanical mechanisms of scar formation. First, we introduce the generic problem of coupled chemo-bio-mechanics. Then, we introduce the model problem of wound healing in terms of a particular chemical signal, inflammation, a particular biological cell type, fibroblasts, and a particular mechanical model, isotropic hyperelasticity. We explore the cross-talk between chemical, biological, and mechanical signals and show that all three fields have a significant impact on scar formation. Our model is the first step toward rigorous multiscale, multifield modeling in wound healing. Our formulation has the potential to improve effective wound management and optimize treatment on an individualized patient-specific basis.

Non-LTE line-blanketed model atmospheres of hot stars. 1: Hybrid complete linearization/accelerated lambda iteration method

NASA Technical Reports Server (NTRS)

Hubeny, I.; Lanz, T.

1995-01-01

A new munerical method for computing non-Local Thermodynamic Equilibrium (non-LTE) model stellar atmospheres is presented. The method, called the hybird complete linearization/accelerated lambda iretation (CL/ALI) method, combines advantages of both its constituents. Its rate of convergence is virtually as high as for the standard CL method, while the computer time per iteration is almost as low as for the standard ALI method. The method is formulated as the standard complete lineariation, the only difference being that the radiation intensity at selected frequency points is not explicity linearized; instead, it is treated by means of the ALI approach. The scheme offers a wide spectrum of options, ranging from the full CL to the full ALI method. We deonstrate that the method works optimally if the majority of frequency points are treated in the ALI mode, while the radiation intensity at a few (typically two to 30) frequency points is explicity linearized. We show how this method can be applied to calculate metal line-blanketed non-LTE model atmospheres, by using the idea of 'superlevels' and 'superlines' introduced originally by Anderson (1989). We calculate several illustrative models taking into accont several tens of thosands of lines of Fe III to Fe IV and show that the hybrid CL/ALI method provides a robust method for calculating non-LTE line-blanketed model atmospheres for a wide range of stellar parameters. The results for individual stellar types will be presented in subsequent papers in this series.

Development of a Cloud Resolving Model for Heterogeneous Supercomputers

NASA Astrophysics Data System (ADS)

Sreepathi, S.; Norman, M. R.; Pal, A.; Hannah, W.; Ponder, C.

2017-12-01

A cloud resolving climate model is needed to reduce major systematic errors in climate simulations due to structural uncertainty in numerical treatments of convection - such as convective storm systems. This research describes the porting effort to enable SAM (System for Atmosphere Modeling) cloud resolving model on heterogeneous supercomputers using GPUs (Graphical Processing Units). We have isolated a standalone configuration of SAM that is targeted to be integrated into the DOE ACME (Accelerated Climate Modeling for Energy) Earth System model. We have identified key computational kernels from the model and offloaded them to a GPU using the OpenACC programming model. Furthermore, we are investigating various optimization strategies intended to enhance GPU utilization including loop fusion/fission, coalesced data access and loop refactoring to a higher abstraction level. We will present early performance results, lessons learned as well as optimization strategies. The computational platform used in this study is the Summitdev system, an early testbed that is one generation removed from Summit, the next leadership class supercomputer at Oak Ridge National Laboratory. The system contains 54 nodes wherein each node has 2 IBM POWER8 CPUs and 4 NVIDIA Tesla P100 GPUs. This work is part of a larger project, ACME-MMF component of the U.S. Department of Energy(DOE) Exascale Computing Project. The ACME-MMF approach addresses structural uncertainty in cloud processes by replacing traditional parameterizations with cloud resolving "superparameterization" within each grid cell of global climate model. Super-parameterization dramatically increases arithmetic intensity, making the MMF approach an ideal strategy to achieve good performance on emerging exascale computing architectures. The goal of the project is to integrate superparameterization into ACME, and explore its full potential to scientifically and computationally advance climate simulation and prediction.

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

NASA Technical Reports Server (NTRS)

Thompson, Alexander; Lawson, John W.

2014-01-01

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

A cortical integrate-and-fire neural network model for blind decoding of visual prosthetic stimulation.

PubMed

Eiber, Calvin D; Morley, John W; Lovell, Nigel H; Suaning, Gregg J

2014-01-01

We present a computational model of the optic pathway which has been adapted to simulate cortical responses to visual-prosthetic stimulation. This model reproduces the statistically observed distributions of spikes for cortical recordings of sham and maximum-intensity stimuli, while simultaneously generating cellular receptive fields consistent with those observed using traditional visual neuroscience methods. By inverting this model to generate candidate phosphenes which could generate the responses observed to novel stimulation strategies, we hope to aid the development of said strategies in-vivo before being deployed in clinical settings.

Addressing Curse of Dimensionality in Sensitivity Analysis: How Can We Handle High-Dimensional Problems?

NASA Astrophysics Data System (ADS)

Safaei, S.; Haghnegahdar, A.; Razavi, S.

2016-12-01

Complex environmental models are now the primary tool to inform decision makers for the current or future management of environmental resources under the climate and environmental changes. These complex models often contain a large number of parameters that need to be determined by a computationally intensive calibration procedure. Sensitivity analysis (SA) is a very useful tool that not only allows for understanding the model behavior, but also helps in reducing the number of calibration parameters by identifying unimportant ones. The issue is that most global sensitivity techniques are highly computationally demanding themselves for generating robust and stable sensitivity metrics over the entire model response surface. Recently, a novel global sensitivity analysis method, Variogram Analysis of Response Surfaces (VARS), is introduced that can efficiently provide a comprehensive assessment of global sensitivity using the Variogram concept. In this work, we aim to evaluate the effectiveness of this highly efficient GSA method in saving computational burden, when applied to systems with extra-large number of input factors ( 100). We use a test function and a hydrological modelling case study to demonstrate the capability of VARS method in reducing problem dimensionality by identifying important vs unimportant input factors.

Graphics processing unit (GPU)-based computation of heat conduction in thermally anisotropic solids

NASA Astrophysics Data System (ADS)

Nahas, C. A.; Balasubramaniam, Krishnan; Rajagopal, Prabhu

2013-01-01

Numerical modeling of anisotropic media is a computationally intensive task since it brings additional complexity to the field problem in such a way that the physical properties are different in different directions. Largely used in the aerospace industry because of their lightweight nature, composite materials are a very good example of thermally anisotropic media. With advancements in video gaming technology, parallel processors are much cheaper today and accessibility to higher-end graphical processing devices has increased dramatically over the past couple of years. Since these massively parallel GPUs are very good in handling floating point arithmetic, they provide a new platform for engineers and scientists to accelerate their numerical models using commodity hardware. In this paper we implement a parallel finite difference model of thermal diffusion through anisotropic media using the NVIDIA CUDA (Compute Unified device Architecture). We use the NVIDIA GeForce GTX 560 Ti as our primary computing device which consists of 384 CUDA cores clocked at 1645 MHz with a standard desktop pc as the host platform. We compare the results from standard CPU implementation for its accuracy and speed and draw implications for simulation using the GPU paradigm.

Testing alternative ground water models using cross-validation and other methods

USGS Publications Warehouse

Foglia, L.; Mehl, S.W.; Hill, M.C.; Perona, P.; Burlando, P.

2007-01-01

Many methods can be used to test alternative ground water models. Of concern in this work are methods able to (1) rank alternative models (also called model discrimination) and (2) identify observations important to parameter estimates and predictions (equivalent to the purpose served by some types of sensitivity analysis). Some of the measures investigated are computationally efficient; others are computationally demanding. The latter are generally needed to account for model nonlinearity. The efficient model discrimination methods investigated include the information criteria: the corrected Akaike information criterion, Bayesian information criterion, and generalized cross-validation. The efficient sensitivity analysis measures used are dimensionless scaled sensitivity (DSS), composite scaled sensitivity, and parameter correlation coefficient (PCC); the other statistics are DFBETAS, Cook's D, and observation-prediction statistic. Acronyms are explained in the introduction. Cross-validation (CV) is a computationally intensive nonlinear method that is used for both model discrimination and sensitivity analysis. The methods are tested using up to five alternative parsimoniously constructed models of the ground water system of the Maggia Valley in southern Switzerland. The alternative models differ in their representation of hydraulic conductivity. A new method for graphically representing CV and sensitivity analysis results for complex models is presented and used to evaluate the utility of the efficient statistics. The results indicate that for model selection, the information criteria produce similar results at much smaller computational cost than CV. For identifying important observations, the only obviously inferior linear measure is DSS; the poor performance was expected because DSS does not include the effects of parameter correlation and PCC reveals large parameter correlations. ?? 2007 National Ground Water Association.

Methods for analysis of cracks in three-dimensional solids

NASA Technical Reports Server (NTRS)

Raju, I. S.; Newman, J. C., Jr.

1984-01-01

Analytical and numerical methods evaluating the stress-intensity factors for three-dimensional cracks in solids are presented, with reference to fatigue failure in aerospace structures. The exact solutions for embedded elliptical and circular cracks in infinite solids, and the approximate methods, including the finite-element, the boundary-integral equation, the line-spring models, and the mixed methods are discussed. Among the mixed methods, the superposition of analytical and finite element methods, the stress-difference, the discretization-error, the alternating, and the finite element-alternating methods are reviewed. Comparison of the stress-intensity factor solutions for some three-dimensional crack configurations showed good agreement. Thus, the choice of a particular method in evaluating the stress-intensity factor is limited only to the availability of resources and computer programs.

Determining X-ray source intensity and confidence bounds in crowded fields

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

Primini, F. A.; Kashyap, V. L., E-mail: fap@head.cfa.harvard.edu

We present a rigorous description of the general problem of aperture photometry in high-energy astrophysics photon-count images, in which the statistical noise model is Poisson, not Gaussian. We compute the full posterior probability density function for the expected source intensity for various cases of interest, including the important cases in which both source and background apertures contain contributions from the source, and when multiple source apertures partially overlap. A Bayesian approach offers the advantages of allowing one to (1) include explicit prior information on source intensities, (2) propagate posterior distributions as priors for future observations, and (3) use Poisson likelihoods,more » making the treatment valid in the low-counts regime. Elements of this approach have been implemented in the Chandra Source Catalog.« less

Efficient Simulation of Tropical Cyclone Pathways with Stochastic Perturbations

NASA Astrophysics Data System (ADS)

Webber, R.; Plotkin, D. A.; Abbot, D. S.; Weare, J.

2017-12-01

Global Climate Models (GCMs) are known to statistically underpredict intense tropical cyclones (TCs) because they fail to capture the rapid intensification and high wind speeds characteristic of the most destructive TCs. Stochastic parametrization schemes have the potential to improve the accuracy of GCMs. However, current analysis of these schemes through direct sampling is limited by the computational expense of simulating a rare weather event at fine spatial gridding. The present work introduces a stochastically perturbed parametrization tendency (SPPT) scheme to increase simulated intensity of TCs. We adapt the Weighted Ensemble algorithm to simulate the distribution of TCs at a fraction of the computational effort required in direct sampling. We illustrate the efficiency of the SPPT scheme by comparing simulations at different spatial resolutions and stochastic parameter regimes. Stochastic parametrization and rare event sampling strategies have great potential to improve TC prediction and aid understanding of tropical cyclogenesis. Since rising sea surface temperatures are postulated to increase the intensity of TCs, these strategies can also improve predictions about climate change-related weather patterns. The rare event sampling strategies used in the current work are not only a novel tool for studying TCs, but they may also be applied to sampling any range of extreme weather events.

High Performance Parallel Computational Nanotechnology

NASA Technical Reports Server (NTRS)

Saini, Subhash; Craw, James M. (Technical Monitor)

1995-01-01

At a recent press conference, NASA Administrator Dan Goldin encouraged NASA Ames Research Center to take a lead role in promoting research and development of advanced, high-performance computer technology, including nanotechnology. Manufacturers of leading-edge microprocessors currently perform large-scale simulations in the design and verification of semiconductor devices and microprocessors. Recently, the need for this intensive simulation and modeling analysis has greatly increased, due in part to the ever-increasing complexity of these devices, as well as the lessons of experiences such as the Pentium fiasco. Simulation, modeling, testing, and validation will be even more important for designing molecular computers because of the complex specification of millions of atoms, thousands of assembly steps, as well as the simulation and modeling needed to ensure reliable, robust and efficient fabrication of the molecular devices. The software for this capacity does not exist today, but it can be extrapolated from the software currently used in molecular modeling for other applications: semi-empirical methods, ab initio methods, self-consistent field methods, Hartree-Fock methods, molecular mechanics; and simulation methods for diamondoid structures. In as much as it seems clear that the application of such methods in nanotechnology will require powerful, highly powerful systems, this talk will discuss techniques and issues for performing these types of computations on parallel systems. We will describe system design issues (memory, I/O, mass storage, operating system requirements, special user interface issues, interconnects, bandwidths, and programming languages) involved in parallel methods for scalable classical, semiclassical, quantum, molecular mechanics, and continuum models; molecular nanotechnology computer-aided designs (NanoCAD) techniques; visualization using virtual reality techniques of structural models and assembly sequences; software required to control mini robotic manipulators for positional control; scalable numerical algorithms for reliability, verifications and testability. There appears no fundamental obstacle to simulating molecular compilers and molecular computers on high performance parallel computers, just as the Boeing 777 was simulated on a computer before manufacturing it.

How to generate and interpret fire characteristics charts for surface and crown fire behavior

Treesearch

Patricia L. Andrews; Faith Ann Heinsch; Luke Schelvan

2011-01-01

A fire characteristics chart is a graph that presents primary related fire behavior characteristics-rate of spread, flame length, fireline intensity, and heat per unit area. It helps communicate and interpret modeled or observed fire behavior. The Fire Characteristics Chart computer program plots either observed fire behavior or values that have been calculated by...

Modeling Studies of the MODIS Solar Diffuser Attenuation Screen and Comparison with On-Orbit Measurements

NASA Technical Reports Server (NTRS)

Waluschka, Eugene; Xiong, Xiao-Xiong; Guenther, Bruce; Barnes, William; VanSalomonson, Vincent V.

2004-01-01

The MODIS instrument relies on solar calibration to achieve the required radiometric accuracy. This solar calibration occurs as the TERRA spacecraft comes up over the North Pole. The earth underneath the spacecraft is still dark for approximately one minute and the sun is just rising over the earth's north polar regions. During this time the sun moves through about 4 degrees, the scan mirror rotates about 19 times and about 50 frames (exposures) are made of the white solar diffuser. For some of MODIS'S bands the brightness of the screen is reduced, to prevent detector saturation, by means of a pinhole screen, which produces approximately 600 pinhole images of the sun within the field of view of any one detector. Previous attempts at creating a detailed radiometric model of this calibration scenario produced intensity variations on the focal planes with insufficient detail to be useful. The current computational approach produces results, which take into account the motion of the sun and the scan mirror and produces variations, which strongly resemble the observed focal plane intensity variations. The computational approach and results and a comparison with actual observational data are presented.

Ambient noise adjoint tomography for a linear array in North China

NASA Astrophysics Data System (ADS)

Zhang, C.; Yao, H.; Liu, Q.; Yuan, Y. O.; Zhang, P.; Feng, J.; Fang, L.

2017-12-01

Ambient noise tomography based on dispersion data and ray theory has been widely utilized for imaging crustal structures. In order to improve the inversion accuracy, ambient noise tomography based on the 3D adjoint approach or full waveform inversion has been developed recently, however, the computational cost is tremendous. In this study we present 2D ambient noise adjoint tomography for a linear array in north China with significant computational efficiency compared to 3D ambient noise adjoint tomography. During the preprocessing, we first convert the observed data in 3D media, i.e., surface-wave empirical Green's functions (EGFs) from ambient noise cross-correlation, to the reconstructed EGFs in 2D media using a 3D/2D transformation scheme. Different from the conventional steps of measuring phase dispersion, the 2D adjoint tomography refines 2D shear wave speeds along the profile directly from the reconstructed Rayleigh wave EGFs in the period band 6-35s. With the 2D initial model extracted from the 3D model from traditional ambient noise tomography, adjoint tomography updates the model by minimizing the frequency-dependent Rayleigh wave traveltime misfits between the reconstructed EGFs and synthetic Green function (SGFs) in 2D media generated by the spectral-element method (SEM), with a preconditioned conjugate gradient method. The multitaper traveltime difference measurement is applied in four period bands during the inversion: 20-35s, 15-30s, 10-20s and 6-15s. The recovered model shows more detailed crustal structures with pronounced low velocity anomaly in the mid-lower crust beneath the junction of Taihang Mountains and Yin-Yan Mountains compared with the initial model. This low velocity structure may imply the possible intense crust-mantle interactions, probably associated with the magmatic underplating during the Mesozoic to Cenozoic evolution of the region. To our knowledge, it's first time that ambient noise adjoint tomography is implemented in 2D media. Considering the intensive computational cost and storage of 3D adjoint tomography, this 2D ambient noise adjoint tomography has potential advantages to get high-resolution 2D crustal structures with limited computational resource.

Cloud Based Metalearning System for Predictive Modeling of Biomedical Data

PubMed Central

Vukićević, Milan

2014-01-01

Rapid growth and storage of biomedical data enabled many opportunities for predictive modeling and improvement of healthcare processes. On the other side analysis of such large amounts of data is a difficult and computationally intensive task for most existing data mining algorithms. This problem is addressed by proposing a cloud based system that integrates metalearning framework for ranking and selection of best predictive algorithms for data at hand and open source big data technologies for analysis of biomedical data. PMID:24892101

Stereo electro-optical tracker study for the measurement of model deformations at the National Transonic Facility

NASA Astrophysics Data System (ADS)

Hertel, R. J.; Hoilman, K. A.

1982-01-01

The effects of model vibration, camera and window nonlinearities, and aerodynamic disturbances in the optical path on the measurement of target position is examined. Window distortion, temperature and pressure changes, laminar and turbulent boundary layers, shock waves, target intensity and, target vibration are also studied. A general computer program was developed to trace optical rays through these disturbances. The use of a charge injection device camera as an alternative to the image dissector camera was examined.

DIaaS: Data-Intensive workflows as a service - Enabling easy composition and deployment of data-intensive workflows on Virtual Research Environments

NASA Astrophysics Data System (ADS)

Filgueira, R.; Ferreira da Silva, R.; Deelman, E.; Atkinson, M.

2016-12-01

We present the Data-Intensive workflows as a Service (DIaaS) model for enabling easy data-intensive workflow composition and deployment on clouds using containers. DIaaS model backbone is Asterism, an integrated solution for running data-intensive stream-based applications on heterogeneous systems, which combines the benefits of dispel4py with Pegasus workflow systems. The stream-based executions of an Asterism workflow are managed by dispel4py, while the data movement between different e-Infrastructures, and the coordination of the application execution are automatically managed by Pegasus. DIaaS combines Asterism framework with Docker containers to provide an integrated, complete, easy-to-use, portable approach to run data-intensive workflows on distributed platforms. Three containers integrate the DIaaS model: a Pegasus node, and an MPI and an Apache Storm clusters. Container images are described as Dockerfiles (available online at http://github.com/dispel4py/pegasus_dispel4py), linked to Docker Hub for providing continuous integration (automated image builds), and image storing and sharing. In this model, all required software (workflow systems and execution engines) for running scientific applications are packed into the containers, which significantly reduces the effort (and possible human errors) required by scientists or VRE administrators to build such systems. The most common use of DIaaS will be to act as a backend of VREs or Scientific Gateways to run data-intensive applications, deploying cloud resources upon request. We have demonstrated the feasibility of DIaaS using the data-intensive seismic ambient noise cross-correlation application (Figure 1). The application preprocesses (Phase1) and cross-correlates (Phase2) traces from several seismic stations. The application is submitted via Pegasus (Container1), and Phase1 and Phase2 are executed in the MPI (Container2) and Storm (Container3) clusters respectively. Although both phases could be executed within the same environment, this setup demonstrates the flexibility of DIaaS to run applications across e-Infrastructures. In summary, DIaaS delivers specialized software to execute data-intensive applications in a scalable, efficient, and robust manner reducing the engineering time and computational cost.

An integrated decision support system for TRAC: A proposal

NASA Technical Reports Server (NTRS)

Mukkamala, Ravi

1991-01-01

Optimal allocation and usage of resources is a key to effective management. Resources of concern to TRAC are: Manpower (PSY), Money (Travel, contracts), Computing, Data, Models, etc. Management activities of TRAC include: Planning, Programming, Tasking, Monitoring, Updating, and Coordinating. Existing systems are insufficient, not completely automated, manpower intensive, and has the potential for data inconsistency exists. A system is proposed which suggests a means to integrate all project management activities of TRAC through the development of a sophisticated software and by utilizing the existing computing systems and network resources. The systems integration proposal is examined in detail.

Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle-Pock algorithm

PubMed Central

Sidky, Emil Y.; Jørgensen, Jakob H.; Pan, Xiaochuan

2012-01-01

The primal-dual optimization algorithm developed in Chambolle and Pock (CP), 2011 is applied to various convex optimization problems of interest in computed tomography (CT) image reconstruction. This algorithm allows for rapid prototyping of optimization problems for the purpose of designing iterative image reconstruction algorithms for CT. The primal-dual algorithm is briefly summarized in the article, and its potential for prototyping is demonstrated by explicitly deriving CP algorithm instances for many optimization problems relevant to CT. An example application modeling breast CT with low-intensity X-ray illumination is presented. PMID:22538474

Applications of Multi-Agent Technology to Power Systems

NASA Astrophysics Data System (ADS)

Nagata, Takeshi

Currently, agents are focus of intense on many sub-fields of computer science and artificial intelligence. Agents are being used in an increasingly wide variety of applications. Many important computing applications such as planning, process control, communication networks and concurrent systems will benefit from using multi-agent system approach. A multi-agent system is a structure given by an environment together with a set of artificial agents capable to act on this environment. Multi-agent models are oriented towards interactions, collaborative phenomena, and autonomy. This article presents the applications of multi-agent technology to the power systems.

Early years of Computational Statistical Mechanics

NASA Astrophysics Data System (ADS)

Mareschal, Michel

2018-05-01

Evidence that a model of hard spheres exhibits a first-order solid-fluid phase transition was provided in the late fifties by two new numerical techniques known as Monte Carlo and Molecular Dynamics. This result can be considered as the starting point of computational statistical mechanics: at the time, it was a confirmation of a counter-intuitive (and controversial) theoretical prediction by J. Kirkwood. It necessitated an intensive collaboration between the Los Alamos team, with Bill Wood developing the Monte Carlo approach, and the Livermore group, where Berni Alder was inventing Molecular Dynamics. This article tells how it happened.

Construction of an advanced software tool for planetary atmospheric modeling

NASA Technical Reports Server (NTRS)

Friedland, Peter; Keller, Richard M.; Mckay, Christopher P.; Sims, Michael H.; Thompson, David E.

1993-01-01

Scientific model-building can be a time intensive and painstaking process, often involving the development of large complex computer programs. Despite the effort involved, scientific models cannot be distributed easily and shared with other scientists. In general, implemented scientific models are complicated, idiosyncratic, and difficult for anyone but the original scientist/programmer to understand. We propose to construct a scientific modeling software tool that serves as an aid to the scientist in developing, using and sharing models. The proposed tool will include an interactive intelligent graphical interface and a high-level domain-specific modeling language. As a testbed for this research, we propose to develop a software prototype in the domain of planetary atmospheric modeling.

Construction of an advanced software tool for planetary atmospheric modeling

NASA Technical Reports Server (NTRS)

Friedland, Peter; Keller, Richard M.; Mckay, Christopher P.; Sims, Michael H.; Thompson, David E.

1992-01-01

Scientific model-building can be a time intensive and painstaking process, often involving the development of large complex computer programs. Despite the effort involved, scientific models cannot be distributed easily and shared with other scientists. In general, implemented scientific models are complicated, idiosyncratic, and difficult for anyone but the original scientist/programmer to understand. We propose to construct a scientific modeling software tool that serves as an aid to the scientist in developing, using and sharing models. The proposed tool will include an interactive intelligent graphical interface and a high-level domain-specific modeling language. As a test bed for this research, we propose to develop a software prototype in the domain of planetary atmospheric modeling.

Shorebird Migration Patterns in Response to Climate Change: A Modeling Approach

NASA Technical Reports Server (NTRS)

Smith, James A.

2010-01-01

The availability of satellite remote sensing observations at multiple spatial and temporal scales, coupled with advances in climate modeling and information technologies offer new opportunities for the application of mechanistic models to predict how continental scale bird migration patterns may change in response to environmental change. In earlier studies, we explored the phenotypic plasticity of a migratory population of Pectoral sandpipers by simulating the movement patterns of an ensemble of 10,000 individual birds in response to changes in stopover locations as an indicator of the impacts of wetland loss and inter-annual variability on the fitness of migratory shorebirds. We used an individual based, biophysical migration model, driven by remotely sensed land surface data, climate data, and biological field data. Mean stop-over durations and stop-over frequency with latitude predicted from our model for nominal cases were consistent with results reported in the literature and available field data. In this study, we take advantage of new computing capabilities enabled by recent GP-GPU computing paradigms and commodity hardware (general purchase computing on graphics processing units). Several aspects of our individual based (agent modeling) approach lend themselves well to GP-GPU computing. We have been able to allocate compute-intensive tasks to the graphics processing units, and now simulate ensembles of 400,000 birds at varying spatial resolutions along the central North American flyway. We are incorporating additional, species specific, mechanistic processes to better reflect the processes underlying bird phenotypic plasticity responses to different climate change scenarios in the central U.S.

Spacecraft thermal balance testing using infrared sources

NASA Technical Reports Server (NTRS)

Tan, G. B. T.; Walker, J. B.

1982-01-01

A thermal balance test (controlled flux intensity) on a simple black dummy spacecraft using IR lamps was performed and evaluated, the latter being aimed specifically at thermal mathematical model (TMM) verification. For reference purposes the model was also subjected to a solar simulation test (SST). The results show that the temperature distributions measured during IR testing for two different model attitudes under steady state conditions are reproducible with a TMM. The TMM test data correlation is not as accurate for IRT as for SST. Using the standard deviation of the temperature difference distribution (analysis minus test) the SST data correlation is better by a factor of 1.8 to 2.5. The lower figure applies to the measured and the higher to the computer-generated IR flux intensity distribution. Techniques of lamp power control are presented. A continuing work program is described which is aimed at quantifying the differences between solar simulation and infrared techniques for a model representing the thermal radiating surfaces of a large communications spacecraft.

Pulse-coupled neural nets: translation, rotation, scale, distortion, and intensity signal invariance for images.

PubMed

Johnson, J L

1994-09-10

The linking-field neural network model of Eckhorn et al. [Neural Comput. 2, 293-307 (1990)] was introduced to explain the experimentally observed synchronous activity among neural assemblies in the cat cortex induced by feature-dependent visual activity. The model produces synchronous bursts of pulses from neurons with similar activity, effectively grouping them by phase and pulse frequency. It gives a basic new function: grouping by similarity. The synchronous bursts are obtained in the limit of strong linking strengths. The linking-field model in the limit of moderate-to-weak linking characterized by few if any multiple bursts is investigated. In this limit dynamic, locally periodic traveling waves exist whose time signal encodes the geometrical structure of a two-dimensional input image. The signal can be made insensitive to translation, scale, rotation, distortion, and intensity. The waves transmit information beyond the physical interconnect distance. The model is implemented in an optical hybrid demonstration system. Results of the simulations and the optical system are presented.

Health Informatics for Neonatal Intensive Care Units: An Analytical Modeling Perspective

PubMed Central

Mench-Bressan, Nadja; McGregor, Carolyn; Pugh, James Edward

2015-01-01

The effective use of data within intensive care units (ICUs) has great potential to create new cloud-based health analytics solutions for disease prevention or earlier condition onset detection. The Artemis project aims to achieve the above goals in the area of neonatal ICUs (NICU). In this paper, we proposed an analytical model for the Artemis cloud project which will be deployed at McMaster Children’s Hospital in Hamilton. We collect not only physiological data but also the infusion pumps data that are attached to NICU beds. Using the proposed analytical model, we predict the amount of storage, memory, and computation power required for the system. Capacity planning and tradeoff analysis would be more accurate and systematic by applying the proposed analytical model in this paper. Numerical results are obtained using real inputs acquired from McMaster Children’s Hospital and a pilot deployment of the system at The Hospital for Sick Children (SickKids) in Toronto. PMID:27170907

Extinction time of a stochastic predator-prey model by the generalized cell mapping method

NASA Astrophysics Data System (ADS)

Han, Qun; Xu, Wei; Hu, Bing; Huang, Dongmei; Sun, Jian-Qiao

2018-03-01

The stochastic response and extinction time of a predator-prey model with Gaussian white noise excitations are studied by the generalized cell mapping (GCM) method based on the short-time Gaussian approximation (STGA). The methods for stochastic response probability density functions (PDFs) and extinction time statistics are developed. The Taylor expansion is used to deal with non-polynomial nonlinear terms of the model for deriving the moment equations with Gaussian closure, which are needed for the STGA in order to compute the one-step transition probabilities. The work is validated with direct Monte Carlo simulations. We have presented the transient responses showing the evolution from a Gaussian initial distribution to a non-Gaussian steady-state one. The effects of the model parameter and noise intensities on the steady-state PDFs are discussed. It is also found that the effects of noise intensities on the extinction time statistics are opposite to the effects on the limit probability distributions of the survival species.

Mobile computing device configured to compute irradiance, glint, and glare of the sun

DOEpatents

Gupta, Vipin P; Ho, Clifford K; Khalsa, Siri Sahib

2014-03-11

Described herein are technologies pertaining to computing the solar irradiance distribution on a surface of a receiver in a concentrating solar power system or glint/glare emitted from a reflective entity. A mobile computing device includes at least one camera that captures images of the Sun and the entity of interest, wherein the images have pluralities of pixels having respective pluralities of intensity values. Based upon the intensity values of the pixels in the respective images, the solar irradiance distribution on the surface of the entity or glint/glare corresponding to the entity is computed by the mobile computing device.

PHYSICS OF ECLIPSING BINARIES. II. TOWARD THE INCREASED MODEL FIDELITY

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

Prša, A.; Conroy, K. E.; Horvat, M.

The precision of photometric and spectroscopic observations has been systematically improved in the last decade, mostly thanks to space-borne photometric missions and ground-based spectrographs dedicated to finding exoplanets. The field of eclipsing binary stars strongly benefited from this development. Eclipsing binaries serve as critical tools for determining fundamental stellar properties (masses, radii, temperatures, and luminosities), yet the models are not capable of reproducing observed data well, either because of the missing physics or because of insufficient precision. This led to a predicament where radiative and dynamical effects, insofar buried in noise, started showing up routinely in the data, but weremore » not accounted for in the models. PHOEBE (PHysics Of Eclipsing BinariEs; http://phoebe-project.org) is an open source modeling code for computing theoretical light and radial velocity curves that addresses both problems by incorporating missing physics and by increasing the computational fidelity. In particular, we discuss triangulation as a superior surface discretization algorithm, meshing of rotating single stars, light travel time effects, advanced phase computation, volume conservation in eccentric orbits, and improved computation of local intensity across the stellar surfaces that includes the photon-weighted mode, the enhanced limb darkening treatment, the better reflection treatment, and Doppler boosting. Here we present the concepts on which PHOEBE is built and proofs of concept that demonstrate the increased model fidelity.« less

Modelling the light-scattering properties of a planetary-regolith analog sample

NASA Astrophysics Data System (ADS)

Vaisanen, T.; Markkanen, J.; Hadamcik, E.; Levasseur-Regourd, A. C.; Lasue, J.; Blum, J.; Penttila, A.; Muinonen, K.

2017-12-01

Solving the scattering properties of asteroid surfaces can be made cheaper, faster, and more accurate with reliable physics-based electromagnetic scattering programs for large and dense random media. Existing exact methods fail to produce solutions for such large systems and it is essential to develop approximate methods. Radiative transfer (RT) is an approximate method which works for sparse random media such as atmospheres fails when applied to dense media. In order to make the method applicable to dense media, we have developed a radiative-transfer coherent-backscattering method (RT-CB) with incoherent interactions. To show the current progress with the RT-CB, we have modeled a planetary-regolith analog sample. The analog sample is a low-density agglomerate produced by random ballistic deposition of almost equisized silicate spheres studied using the PROGRA2-surf experiment. The scattering properties were then computed with the RT-CB assuming that the silicate spheres were equisized and that there were a Gaussian particle size distribution. The results were then compared to the measured data and the intensity plot is shown below. The phase functions are normalized to unity at the 40-deg phase angle. The tentative intensity modeling shows good match with the measured data, whereas the polarization modeling shows discrepancies. In summary, the current RT-CB modeling is promising, but more work needs to be carried out, in particular, for modeling the polarization. Acknowledgments. Research supported by European Research Council with Advanced Grant No. 320773 SAEMPL, Scattering and Absorption of ElectroMagnetic waves in ParticuLate media. Computational resources provided by CSC - IT Centre for Science Ltd, Finland.

Two-part models with stochastic processes for modelling longitudinal semicontinuous data: Computationally efficient inference and modelling the overall marginal mean.

PubMed

Yiu, Sean; Tom, Brian Dm

2017-01-01

Several researchers have described two-part models with patient-specific stochastic processes for analysing longitudinal semicontinuous data. In theory, such models can offer greater flexibility than the standard two-part model with patient-specific random effects. However, in practice, the high dimensional integrations involved in the marginal likelihood (i.e. integrated over the stochastic processes) significantly complicates model fitting. Thus, non-standard computationally intensive procedures based on simulating the marginal likelihood have so far only been proposed. In this paper, we describe an efficient method of implementation by demonstrating how the high dimensional integrations involved in the marginal likelihood can be computed efficiently. Specifically, by using a property of the multivariate normal distribution and the standard marginal cumulative distribution function identity, we transform the marginal likelihood so that the high dimensional integrations are contained in the cumulative distribution function of a multivariate normal distribution, which can then be efficiently evaluated. Hence, maximum likelihood estimation can be used to obtain parameter estimates and asymptotic standard errors (from the observed information matrix) of model parameters. We describe our proposed efficient implementation procedure for the standard two-part model parameterisation and when it is of interest to directly model the overall marginal mean. The methodology is applied on a psoriatic arthritis data set concerning functional disability.

Energy intensity of computer manufacturing: hybrid assessment combining process and economic input-output methods.

PubMed

Williams, Eric

2004-11-15

The total energy and fossil fuels used in producing a desktop computer with 17-in. CRT monitor are estimated at 6400 megajoules (MJ) and 260 kg, respectively. This indicates that computer manufacturing is energy intensive: the ratio of fossil fuel use to product weight is 11, an order of magnitude larger than the factor of 1-2 for many other manufactured goods. This high energy intensity of manufacturing, combined with rapid turnover in computers, results in an annual life cycle energy burden that is surprisingly high: about 2600 MJ per year, 1.3 times that of a refrigerator. In contrast with many home appliances, life cycle energy use of a computer is dominated by production (81%) as opposed to operation (19%). Extension of usable lifespan (e.g. by reselling or upgrading) is thus a promising approach to mitigating energy impacts as well as other environmental burdens associated with manufacturing and disposal.

Modeling of sedimentation and resuspension processes induced by intensive internal gravity waves in the coastal water systems with the use of the advection-diffusion equation for sediment concentration

NASA Astrophysics Data System (ADS)

Rouvinskaya, Ekaterina; Kurkin, Andrey; Kurkina, Oxana

2017-04-01

Intensive internal gravity waves influence bottom topography in the coastal zone. They induce substantial flows in the bottom layer that are essential for the formation of suspension and for the sediment transport. It is necessary to develop a mathematical model to predict the state of the seabed near the coastline to assess and ensure safety during the building and operation of the hydraulic engineering constructions. There are many models which are used to predict the impact of storm waves on the sediment transport processes. Such models for the impact of the tsunami waves are also actively developing. In recent years, the influence of intense internal waves on the sedimentation processes is also of a special interest. In this study we adapt one of such models, that is based on the advection-diffusion equation and allows to study processes of resuspension under the influence of internal gravity waves in the coastal zone, for solving the specific practical problems. During the numerical simulation precomputed velocity values are substituted in the advection - diffusion equation for sediment concentration at each time step and each node of the computational grid. Velocity values are obtained by the simulation of the internal waves' dynamics by using the IGW Research software package for numerical integration of fully nonlinear two-dimensional (vertical plane) system of equations of hydrodynamics of inviscid incompressible stratified fluid in the Boussinesq approximation bearing in mind the impact of barotropic tide. It is necessary to set the initial velocity and density distribution in the computational domain, bottom topography, as well as the value of the Coriolis parameter and, if necessary, the parameters of the tidal wave to carry out numerical calculations in the software package IGW Research. To initialize the background conditions of the numerical model we used data records obtained in the summer in the southern part of the shelf zone of Sakhalin Island from 1999 to 2003, provided by SakhNIRO, Russia. The process of assimilation of field data with numerical model is described in detail in our previous studies. It has been shown that process of suspension formation is quite intense for the investigated condition. Concentration of suspended particles significantly increases during the tide, especially on naturally uneven bottom relief as well as on the right boundary of the computational domain (near shoreline). Pronounced nepheloid layer is produced. Its thickness is about 5.6 m. At the phase of low tide, the process of suspension sediment production stops, and suspended particles are beginning to settle because of the small vertical velocities. Thickness of nepheloid layer is actively reduced. Obviously, this should lead to a change in the bottom relief. The presented results of research were obtained with the support of the Russian President's scholarship for young scientists and graduate students SP-2311.2016.5.

EMPIRICAL DETERMINATION OF EINSTEIN A-COEFFICIENT RATIOS OF BRIGHT [Fe II] LINES

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

Giannini, T.; Antoniucci, S.; Nisini, B.

The Einstein spontaneous rates (A-coefficients) of Fe{sup +} lines have been computed by several authors with results that differ from each other by up to 40%. Consequently, models for line emissivities suffer from uncertainties that in turn affect the determination of the physical conditions at the base of line excitation. We provide an empirical determination of the A-coefficient ratios of bright [Fe II] lines that would represent both a valid benchmark for theoretical computations and a reference for the physical interpretation of the observed lines. With the ESO-Very Large Telescope X-shooter instrument between 3000 Å and 24700 Å, we obtainedmore » a spectrum of the bright Herbig-Haro object HH 1. We detect around 100 [Fe II] lines, some of which with a signal-to-noise ratios ≥100. Among these latter lines, we selected those emitted by the same level, whose dereddened intensity ratios are direct functions of the Einstein A-coefficient ratios. From the same X-shooter spectrum, we got an accurate estimate of the extinction toward HH 1 through intensity ratios of atomic species, H I  recombination lines and H{sub 2} ro-vibrational transitions. We provide seven reliable A-coefficient ratios between bright [Fe II] lines, which are compared with the literature determinations. In particular, the A-coefficient ratios involving the brightest near-infrared lines (λ12570/λ16440 and λ13209/λ16440) are in better agreement with the predictions by the Quinet et al. relativistic Hartree-Fock model. However, none of the theoretical models predict A-coefficient ratios in agreement with all of our determinations. We also show that literature data of near-infrared intensity ratios better agree with our determinations than with theoretical expectations.« less

Information content of household-stratified epidemics.

PubMed

Kinyanjui, T M; Pellis, L; House, T

2016-09-01

Household structure is a key driver of many infectious diseases, as well as a natural target for interventions such as vaccination programs. Many theoretical and conceptual advances on household-stratified epidemic models are relatively recent, but have successfully managed to increase the applicability of such models to practical problems. To be of maximum realism and hence benefit, they require parameterisation from epidemiological data, and while household-stratified final size data has been the traditional source, increasingly time-series infection data from households are becoming available. This paper is concerned with the design of studies aimed at collecting time-series epidemic data in order to maximize the amount of information available to calibrate household models. A design decision involves a trade-off between the number of households to enrol and the sampling frequency. Two commonly used epidemiological study designs are considered: cross-sectional, where different households are sampled at every time point, and cohort, where the same households are followed over the course of the study period. The search for an optimal design uses Bayesian computationally intensive methods to explore the joint parameter-design space combined with the Shannon entropy of the posteriors to estimate the amount of information in each design. For the cross-sectional design, the amount of information increases with the sampling intensity, i.e., the designs with the highest number of time points have the most information. On the other hand, the cohort design often exhibits a trade-off between the number of households sampled and the intensity of follow-up. Our results broadly support the choices made in existing epidemiological data collection studies. Prospective problem-specific use of our computational methods can bring significant benefits in guiding future study designs. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Techniques to derive geometries for image-based Eulerian computations

PubMed Central

Dillard, Seth; Buchholz, James; Vigmostad, Sarah; Kim, Hyunggun; Udaykumar, H.S.

2014-01-01

Purpose The performance of three frequently used level set-based segmentation methods is examined for the purpose of defining features and boundary conditions for image-based Eulerian fluid and solid mechanics models. The focus of the evaluation is to identify an approach that produces the best geometric representation from a computational fluid/solid modeling point of view. In particular, extraction of geometries from a wide variety of imaging modalities and noise intensities, to supply to an immersed boundary approach, is targeted. Design/methodology/approach Two- and three-dimensional images, acquired from optical, X-ray CT, and ultrasound imaging modalities, are segmented with active contours, k-means, and adaptive clustering methods. Segmentation contours are converted to level sets and smoothed as necessary for use in fluid/solid simulations. Results produced by the three approaches are compared visually and with contrast ratio, signal-to-noise ratio, and contrast-to-noise ratio measures. Findings While the active contours method possesses built-in smoothing and regularization and produces continuous contours, the clustering methods (k-means and adaptive clustering) produce discrete (pixelated) contours that require smoothing using speckle-reducing anisotropic diffusion (SRAD). Thus, for images with high contrast and low to moderate noise, active contours are generally preferable. However, adaptive clustering is found to be far superior to the other two methods for images possessing high levels of noise and global intensity variations, due to its more sophisticated use of local pixel/voxel intensity statistics. Originality/value It is often difficult to know a priori which segmentation will perform best for a given image type, particularly when geometric modeling is the ultimate goal. This work offers insight to the algorithm selection process, as well as outlining a practical framework for generating useful geometric surfaces in an Eulerian setting. PMID:25750470

Electronic transport in VO 2 —Experimentally calibrated Boltzmann transport modeling

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

Kinaci, Alper; Kado, Motohisa; Rosenmann, Daniel

2015-12-28

Materials that undergo metal-insulator transitions (MITs) are under intense study because the transition is scientifically fascinating and technologically promising for various applications. Among these materials, VO2 has served as a prototype due to its favorable transition temperature. While the physical underpinnings of the transition have been heavily investigated experimentally and computationally, quantitative modeling of electronic transport in the two phases has yet to be undertaken. In this work, we establish a density-functional-theory (DFT)-based approach to model electronic transport properties in VO2 in the semiconducting and metallic regimes, focusing on band transport using the Boltzmann transport equations. We synthesized high qualitymore » VO2 films and measured the transport quantities across the transition, in order to calibrate the free parameters in the model. We find that the experimental calibration of the Hubbard correction term can efficiently and adequately model the metallic and semiconducting phases, allowing for further computational design of MIT materials for desirable transport properties.« less

Predictive modeling of dynamic fracture growth in brittle materials with machine learning

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

Moore, Bryan A.; Rougier, Esteban; O’Malley, Daniel

We use simulation data from a high delity Finite-Discrete Element Model to build an e cient Machine Learning (ML) approach to predict fracture growth and coalescence. Our goal is for the ML approach to be used as an emulator in place of the computationally intensive high delity models in an uncertainty quanti cation framework where thousands of forward runs are required. The failure of materials with various fracture con gurations (size, orientation and the number of initial cracks) are explored and used as data to train our ML model. This novel approach has shown promise in predicting spatial (path tomore » failure) and temporal (time to failure) aspects of brittle material failure. Predictions of where dominant fracture paths formed within a material were ~85% accurate and the time of material failure deviated from the actual failure time by an average of ~16%. Additionally, the ML model achieves a reduction in computational cost by multiple orders of magnitude.« less

Development of a General Form CO 2 and Brine Flux Input Model

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

Mansoor, K.; Sun, Y.; Carroll, S.

2014-08-01

The National Risk Assessment Partnership (NRAP) project is developing a science-based toolset for the quantitative analysis of the potential risks associated with changes in groundwater chemistry from CO 2 injection. In order to address uncertainty probabilistically, NRAP is developing efficient, reduced-order models (ROMs) as part of its approach. These ROMs are built from detailed, physics-based process models to provide confidence in the predictions over a range of conditions. The ROMs are designed to reproduce accurately the predictions from the computationally intensive process models at a fraction of the computational time, thereby allowing the utilization of Monte Carlo methods to probemore » variability in key parameters. This report presents the procedures used to develop a generalized model for CO 2 and brine leakage fluxes based on the output of a numerical wellbore simulation. The resulting generalized parameters and ranges reported here will be used for the development of third-generation groundwater ROMs.« less

Predictive modeling of dynamic fracture growth in brittle materials with machine learning

DOE PAGES

Moore, Bryan A.; Rougier, Esteban; O’Malley, Daniel; ...

2018-02-22

We use simulation data from a high delity Finite-Discrete Element Model to build an e cient Machine Learning (ML) approach to predict fracture growth and coalescence. Our goal is for the ML approach to be used as an emulator in place of the computationally intensive high delity models in an uncertainty quanti cation framework where thousands of forward runs are required. The failure of materials with various fracture con gurations (size, orientation and the number of initial cracks) are explored and used as data to train our ML model. This novel approach has shown promise in predicting spatial (path tomore » failure) and temporal (time to failure) aspects of brittle material failure. Predictions of where dominant fracture paths formed within a material were ~85% accurate and the time of material failure deviated from the actual failure time by an average of ~16%. Additionally, the ML model achieves a reduction in computational cost by multiple orders of magnitude.« less

WDEC: A Code for Modeling White Dwarf Structure and Pulsations

NASA Astrophysics Data System (ADS)

Bischoff-Kim, Agnès; Montgomery, Michael H.

2018-05-01

The White Dwarf Evolution Code (WDEC), written in Fortran, makes models of white dwarf stars. It is fast, versatile, and includes the latest physics. The code evolves hot (∼100,000 K) input models down to a chosen effective temperature by relaxing the models to be solutions of the equations of stellar structure. The code can also be used to obtain g-mode oscillation modes for the models. WDEC has a long history going back to the late 1960s. Over the years, it has been updated and re-packaged for modern computer architectures and has specifically been used in computationally intensive asteroseismic fitting. Generations of white dwarf astronomers and dozens of publications have made use of the WDEC, although the last true instrument paper is the original one, published in 1975. This paper discusses the history of the code, necessary to understand why it works the way it does, details the physics and features in the code today, and points the reader to where to find the code and a user guide.

The solar ionisation rate deduced from Ulysses measurements and its implications to interplanetary Lyman alpha-intensity

NASA Technical Reports Server (NTRS)

Summanen, T.; Kyroelae, E.

1995-01-01

We have developed a computer code which can be used to study 3-dimensional and time-dependent effects of the solar cycle on the interplanetary (IP) hydrogen distribution. The code is based on the inverted Monte Carlo simulation. In this work we have modelled the temporal behaviour of the solar ionisation rate. We have assumed that during the most of the time of the solar cycle there is an anisotopic latitudinal structure but right at the solar maximum the anisotropy disappears. The effects of this behaviour will be discussed both in regard to the IP hydrogen distribution and IP Lyman a a-intensity.

On the red giant titanium oxide bands

NASA Astrophysics Data System (ADS)

Hanni, L.; Sitska, J.

1985-12-01

The dependence of TiO absorption in cool oxygen-sequence giant stars on the Teff and log g of their atmospheres is investigated theoretically on the basis of spectra simulated using the computer program described by Hanni (1983) and the giant model atmospheres of Johnson et al. (1980). The temperature dependence of the intensity jumps at the head of the alpha(1.0) band is determined from simulated spectra, and the jumps are related to spectral types using the calibration of Ridgway et al. (1980). The results are presented in tables and graphs and shown to be in good agreement with the empirical Teff/intensity-jump correlation of Boyarchuk (1969).

Machine learning: Trends, perspectives, and prospects.

PubMed

Jordan, M I; Mitchell, T M

2015-07-17

Machine learning addresses the question of how to build computers that improve automatically through experience. It is one of today's most rapidly growing technical fields, lying at the intersection of computer science and statistics, and at the core of artificial intelligence and data science. Recent progress in machine learning has been driven both by the development of new learning algorithms and theory and by the ongoing explosion in the availability of online data and low-cost computation. The adoption of data-intensive machine-learning methods can be found throughout science, technology and commerce, leading to more evidence-based decision-making across many walks of life, including health care, manufacturing, education, financial modeling, policing, and marketing. Copyright © 2015, American Association for the Advancement of Science.

Computationally intensive econometrics using a distributed matrix-programming language.

PubMed

Doornik, Jurgen A; Hendry, David F; Shephard, Neil

2002-06-15

This paper reviews the need for powerful computing facilities in econometrics, focusing on concrete problems which arise in financial economics and in macroeconomics. We argue that the profession is being held back by the lack of easy-to-use generic software which is able to exploit the availability of cheap clusters of distributed computers. Our response is to extend, in a number of directions, the well-known matrix-programming interpreted language Ox developed by the first author. We note three possible levels of extensions: (i) Ox with parallelization explicit in the Ox code; (ii) Ox with a parallelized run-time library; and (iii) Ox with a parallelized interpreter. This paper studies and implements the first case, emphasizing the need for deterministic computing in science. We give examples in the context of financial economics and time-series modelling.

Environmental Modeling, Technology, and Communication for Land Falling Tropical Cyclone/Hurricane Prediction

PubMed Central

Tuluri, Francis; Reddy, R. Suseela; Anjaneyulu, Y.; Colonias, John; Tchounwou, Paul

2010-01-01

Katrina (a tropical cyclone/hurricane) began to strengthen reaching a Category 5 storm on 28th August, 2005 and its winds reached peak intensity of 175 mph and pressure levels as low as 902 mb. Katrina eventually weakened to a category 3 storm and made a landfall in Plaquemines Parish, Louisiana, Gulf of Mexico, south of Buras on 29th August 2005. We investigate the time series intensity change of the hurricane Katrina using environmental modeling and technology tools to develop an early and advanced warning and prediction system. Environmental Mesoscale Model (Weather Research Forecast, WRF) simulations are used for prediction of intensity change and track of the hurricane Katrina. The model is run on a doubly nested domain centered over the central Gulf of Mexico, with grid spacing of 90 km and 30 km for 6 h periods, from August 28th to August 30th. The model results are in good agreement with the observations suggesting that the model is capable of simulating the surface features, intensity change and track and precipitation associated with hurricane Katrina. We computed the maximum vertical velocities (Wmax) using Convective Available Kinetic Energy (CAPE) obtained at the equilibrium level (EL), from atmospheric soundings over the Gulf Coast stations during the hurricane land falling for the period August 21–30, 2005. The large vertical atmospheric motions associated with the land falling hurricane Katrina produced severe weather including thunderstorms and tornadoes 2–3 days before landfall. The environmental modeling simulations in combination with sounding data show that the tools may be used as an advanced prediction and communication system (APCS) for land falling tropical cyclones/hurricanes. PMID:20623002

Global 7 km mesh nonhydrostatic Model Intercomparison Project for improving TYphoon forecast (TYMIP-G7): experimental design and preliminary results

NASA Astrophysics Data System (ADS)

Nakano, Masuo; Wada, Akiyoshi; Sawada, Masahiro; Yoshimura, Hiromasa; Onishi, Ryo; Kawahara, Shintaro; Sasaki, Wataru; Nasuno, Tomoe; Yamaguchi, Munehiko; Iriguchi, Takeshi; Sugi, Masato; Takeuchi, Yoshiaki

2017-03-01

Recent advances in high-performance computers facilitate operational numerical weather prediction by global hydrostatic atmospheric models with horizontal resolutions of ˜ 10 km. Given further advances in such computers and the fact that the hydrostatic balance approximation becomes invalid for spatial scales < 10 km, the development of global nonhydrostatic models with high accuracy is urgently required. The Global 7 km mesh nonhydrostatic Model Intercomparison Project for improving TYphoon forecast (TYMIP-G7) is designed to understand and statistically quantify the advantages of high-resolution nonhydrostatic global atmospheric models to improve tropical cyclone (TC) prediction. A total of 137 sets of 5-day simulations using three next-generation nonhydrostatic global models with horizontal resolutions of 7 km and a conventional hydrostatic global model with a horizontal resolution of 20 km were run on the Earth Simulator. The three 7 km mesh nonhydrostatic models are the nonhydrostatic global spectral atmospheric Double Fourier Series Model (DFSM), the Multi-Scale Simulator for the Geoenvironment (MSSG) and the Nonhydrostatic ICosahedral Atmospheric Model (NICAM). The 20 km mesh hydrostatic model is the operational Global Spectral Model (GSM) of the Japan Meteorological Agency. Compared with the 20 km mesh GSM, the 7 km mesh models reduce systematic errors in the TC track, intensity and wind radii predictions. The benefits of the multi-model ensemble method were confirmed for the 7 km mesh nonhydrostatic global models. While the three 7 km mesh models reproduce the typical axisymmetric mean inner-core structure, including the primary and secondary circulations, the simulated TC structures and their intensities in each case are very different for each model. In addition, the simulated track is not consistently better than that of the 20 km mesh GSM. These results suggest that the development of more sophisticated initialization techniques and model physics is needed to further improve the TC prediction.

CelOWS: an ontology based framework for the provision of semantic web services related to biological models.

PubMed

Matos, Ely Edison; Campos, Fernanda; Braga, Regina; Palazzi, Daniele

2010-02-01

The amount of information generated by biological research has lead to an intensive use of models. Mathematical and computational modeling needs accurate description to share, reuse and simulate models as formulated by original authors. In this paper, we introduce the Cell Component Ontology (CelO), expressed in OWL-DL. This ontology captures both the structure of a cell model and the properties of functional components. We use this ontology in a Web project (CelOWS) to describe, query and compose CellML models, using semantic web services. It aims to improve reuse and composition of existent components and allow semantic validation of new models.

Predictive Model for Particle Residence Time Distributions in Riser Reactors. Part 1: Model Development and Validation

DOE PAGES

Foust, Thomas D.; Ziegler, Jack L.; Pannala, Sreekanth; ...

2017-02-28

Here in this computational study, we model the mixing of biomass pyrolysis vapor with solid catalyst in circulating riser reactors with a focus on the determination of solid catalyst residence time distributions (RTDs). A comprehensive set of 2D and 3D simulations were conducted for a pilot-scale riser using the Eulerian-Eulerian two-fluid modeling framework with and without sub-grid-scale models for the gas-solids interaction. A validation test case was also simulated and compared to experiments, showing agreement in the pressure gradient and RTD mean and spread. For simulation cases, it was found that for accurate RTD prediction, the Johnson and Jackson partialmore » slip solids boundary condition was required for all models and a sub-grid model is useful so that ultra high resolutions grids that are very computationally intensive are not required. Finally, we discovered a 2/3 scaling relation for the RTD mean and spread when comparing resolved 2D simulations to validated unresolved 3D sub-grid-scale model simulations.« less

On testing an unspecified function through a linear mixed effects model with multiple variance components

PubMed Central

Wang, Yuanjia; Chen, Huaihou

2012-01-01

Summary We examine a generalized F-test of a nonparametric function through penalized splines and a linear mixed effects model representation. With a mixed effects model representation of penalized splines, we imbed the test of an unspecified function into a test of some fixed effects and a variance component in a linear mixed effects model with nuisance variance components under the null. The procedure can be used to test a nonparametric function or varying-coefficient with clustered data, compare two spline functions, test the significance of an unspecified function in an additive model with multiple components, and test a row or a column effect in a two-way analysis of variance model. Through a spectral decomposition of the residual sum of squares, we provide a fast algorithm for computing the null distribution of the test, which significantly improves the computational efficiency over bootstrap. The spectral representation reveals a connection between the likelihood ratio test (LRT) in a multiple variance components model and a single component model. We examine our methods through simulations, where we show that the power of the generalized F-test may be higher than the LRT, depending on the hypothesis of interest and the true model under the alternative. We apply these methods to compute the genome-wide critical value and p-value of a genetic association test in a genome-wide association study (GWAS), where the usual bootstrap is computationally intensive (up to 108 simulations) and asymptotic approximation may be unreliable and conservative. PMID:23020801

On testing an unspecified function through a linear mixed effects model with multiple variance components.

PubMed

Wang, Yuanjia; Chen, Huaihou

2012-12-01

We examine a generalized F-test of a nonparametric function through penalized splines and a linear mixed effects model representation. With a mixed effects model representation of penalized splines, we imbed the test of an unspecified function into a test of some fixed effects and a variance component in a linear mixed effects model with nuisance variance components under the null. The procedure can be used to test a nonparametric function or varying-coefficient with clustered data, compare two spline functions, test the significance of an unspecified function in an additive model with multiple components, and test a row or a column effect in a two-way analysis of variance model. Through a spectral decomposition of the residual sum of squares, we provide a fast algorithm for computing the null distribution of the test, which significantly improves the computational efficiency over bootstrap. The spectral representation reveals a connection between the likelihood ratio test (LRT) in a multiple variance components model and a single component model. We examine our methods through simulations, where we show that the power of the generalized F-test may be higher than the LRT, depending on the hypothesis of interest and the true model under the alternative. We apply these methods to compute the genome-wide critical value and p-value of a genetic association test in a genome-wide association study (GWAS), where the usual bootstrap is computationally intensive (up to 10(8) simulations) and asymptotic approximation may be unreliable and conservative. © 2012, The International Biometric Society.

Eigen Spreading

DTIC Science & Technology

2008-02-27

between the PHY layer and for example a host PC computer . The PC wants to generate and receive a sequence of data packets. The PC may also want to send...the testbed is quite similar. Given the intense computational requirements of SVD and other matrix mode operations needed to support eigen spreading a...platform for real time operation. This task is probably the major challenge in the development of the testbed. All compute intensive tasks will be

Twisting Anderson pseudospins with light: Quench dynamics in THz-pumped BCS superconductors

NASA Astrophysics Data System (ADS)

Chou, Yang-Zhi; Liao, Yunxiang; Foster, Matthew

We study the preparation and the detection of coherent far-from-equilibrium BCS superconductor dynamics in THz pump-probe experiments. In a recent experiment, an intense monocycle THz pulse with center frequency ω = Δ was injected into a superconductor with BCS gap Δ the post-pump evolution was detected via the optical conductivity. It was argued that nonlinear coupling of the pump to the Anderson pseudospins of the superconductor induces coherent dynamics of the Higgs mode Δ (t) . We validate this picture in a 2D BCS model with a combination of exact numerics and the Lax reduction, and we compute the dynamical phase diagram. The main effect of the pump is to scramble the orientations of Anderson pseudospins along the Fermi surface by twisting them in the xy-plane. We show that more intense pulses can induce a far-from-equilibrium gapless phase (phase I), originally predicted in the context of interaction quenches. We show that the THz pump can reach phase I at much lower energy densities than an interaction quench, and we demonstrate that Lax reduction provides a quantitative tool for computing coherent BCS dynamics. We also compute the optical conductivity for the states discussed here.

Three-dimensional spiral CT during arterial portography: comparison of three rendering techniques.

PubMed

Heath, D G; Soyer, P A; Kuszyk, B S; Bliss, D F; Calhoun, P S; Bluemke, D A; Choti, M A; Fishman, E K

1995-07-01

The three most common techniques for three-dimensional reconstruction are surface rendering, maximum-intensity projection (MIP), and volume rendering. Surface-rendering algorithms model objects as collections of geometric primitives that are displayed with surface shading. The MIP algorithm renders an image by selecting the voxel with the maximum intensity signal along a line extended from the viewer's eye through the data volume. Volume-rendering algorithms sum the weighted contributions of all voxels along the line. Each technique has advantages and shortcomings that must be considered during selection of one for a specific clinical problem and during interpretation of the resulting images. With surface rendering, sharp-edged, clear three-dimensional reconstruction can be completed on modest computer systems; however, overlapping structures cannot be visualized and artifacts are a problem. MIP is computationally a fast technique, but it does not allow depiction of overlapping structures, and its images are three-dimensionally ambiguous unless depth cues are provided. Both surface rendering and MIP use less than 10% of the image data. In contrast, volume rendering uses nearly all of the data, allows demonstration of overlapping structures, and engenders few artifacts, but it requires substantially more computer power than the other techniques.

On edge-aware path-based color spatial sampling for Retinex: from Termite Retinex to Light Energy-driven Termite Retinex

NASA Astrophysics Data System (ADS)

Simone, Gabriele; Cordone, Roberto; Serapioni, Raul Paolo; Lecca, Michela

2017-05-01

Retinex theory estimates the human color sensation at any observed point by correcting its color based on the spatial arrangement of the colors in proximate regions. We revise two recent path-based, edge-aware Retinex implementations: Termite Retinex (TR) and Energy-driven Termite Retinex (ETR). As the original Retinex implementation, TR and ETR scan the neighborhood of any image pixel by paths and rescale their chromatic intensities by intensity levels computed by reworking the colors of the pixels on the paths. Our interest in TR and ETR is due to their unique, content-based scanning scheme, which uses the image edges to define the paths and exploits a swarm intelligence model for guiding the spatial exploration of the image. The exploration scheme of ETR has been showed to be particularly effective: its paths are local minima of an energy functional, designed to favor the sampling of image pixels highly relevant to color sensation. Nevertheless, since its computational complexity makes ETR poorly practicable, here we present a light version of it, named Light Energy-driven TR, and obtained from ETR by implementing a modified, optimized minimization procedure and by exploiting parallel computing.

A computationally efficient method for incorporating spike waveform information into decoding algorithms.

PubMed

Ventura, Valérie; Todorova, Sonia

2015-05-01

Spike-based brain-computer interfaces (BCIs) have the potential to restore motor ability to people with paralysis and amputation, and have shown impressive performance in the lab. To transition BCI devices from the lab to the clinic, decoding must proceed automatically and in real time, which prohibits the use of algorithms that are computationally intensive or require manual tweaking. A common choice is to avoid spike sorting and treat the signal on each electrode as if it came from a single neuron, which is fast, easy, and therefore desirable for clinical use. But this approach ignores the kinematic information provided by individual neurons recorded on the same electrode. The contribution of this letter is a linear decoding model that extracts kinematic information from individual neurons without spike-sorting the electrode signals. The method relies on modeling sample averages of waveform features as functions of kinematics, which is automatic and requires minimal data storage and computation. In offline reconstruction of arm trajectories of a nonhuman primate performing reaching tasks, the proposed method performs as well as decoders based on expertly manually and automatically sorted spikes.

Numerical estimation of cavitation intensity

NASA Astrophysics Data System (ADS)

Krumenacker, L.; Fortes-Patella, R.; Archer, A.

2014-03-01

Cavitation may appear in turbomachinery and in hydraulic orifices, venturis or valves, leading to performance losses, vibrations and material erosion. This study propose a new method to predict the cavitation intensity of the flow, based on a post-processing of unsteady CFD calculations. The paper presents the analyses of cavitating structures' evolution at two different scales: • A macroscopic one in which the growth of cavitating structures is calculated using an URANS software based on a homogeneous model. Simulations of cavitating flows are computed using a barotropic law considering presence of air and interfacial tension, and Reboud's correction on the turbulence model. • Then a small one where a Rayleigh-Plesset software calculates the acoustic energy generated by the implosion of the vapor/gas bubbles with input parameters from macroscopic scale. The volume damage rate of the material during incubation time is supposed to be a part of the cumulated acoustic energy received by the solid wall. The proposed analysis method is applied to calculations on hydrofoil and orifice geometries. Comparisons between model results and experimental works concerning flow characteristic (size of cavity, pressure,velocity) as well as pitting (erosion area, relative cavitation intensity) are presented.

Embodied Energy and GHG Emissions from Material Use in Conventional and Unconventional Oil and Gas Operations.

PubMed

Brandt, Adam R

2015-11-03

Environmental impacts embodied in oilfield capital equipment have not been thoroughly studied. In this paper, we present the first open-source model which computes the embodied energy and greenhouse gas (GHG) emissions associated with materials consumed in constructing oil and gas wells and associated infrastructure. The model includes well casing, wellbore cement, drilling mud, processing equipment, gas compression, and transport infrastructure. Default case results show that consumption of materials in constructing oilfield equipment consumes ∼0.014 MJ of primary energy per MJ of oil produced, and results in ∼1.3 gCO2-eq GHG emissions per MJ (lower heating value) of crude oil produced, an increase of 15% relative to upstream emissions assessed in earlier OPGEE model versions, and an increase of 1-1.5% of full life cycle emissions. A case study of a hydraulically fractured well in the Bakken formation of North Dakota suggests lower energy intensity (0.011 MJ/MJ) and emissions intensity (1.03 gCO2-eq/MJ) due to the high productivity of hydraulically fractured wells. Results are sensitive to per-well productivity, the complexity of wellbore casing design, and the energy and emissions intensity per kg of material consumed.

The red and green lines of atomic oxygen in the nightglow of Venus

NASA Technical Reports Server (NTRS)

Fox, J. L.

1990-01-01

O(1D) and O(1S), the excited states that give rise to the atomic oxygen red and green lines, are produced in the Venus nightglow in dissociative recombination of O2(+). The emissions should also be excited by precipitation of soft electrons, the suggested source of the 'auroral' emission features of atomic oxygen at 1304 and 1356 A, which have been reported from observations of the Pioneer Venus Orbiter Ultraviolet Spectrometer. No emisison at 6300 or 5577 A was detected, however, by the visible spectrophotometers on the Soviet spacecraft Veneras 9 and 10; upper limits have been placed on the intensities of these features. The constraints placed on models for the auroral production mechanism by the Venera upper limits by modeling the intensities of the red and green lines in the nightglow are evaluated, combining a model for the vibrational distribution of O2(+) on the nightside of Venus with rate coefficients recently computed by Guberman for production of O(1S) and O(1D) in dissociative recombination of O2(+) from different vibrational levels. The integrated overhead intensities are 1 - 2 R for the green line and about 46 R for the red line.

Approaches in highly parameterized inversion-PESTCommander, a graphical user interface for file and run management across networks

USGS Publications Warehouse

Karanovic, Marinko; Muffels, Christopher T.; Tonkin, Matthew J.; Hunt, Randall J.

2012-01-01

Models of environmental systems have become increasingly complex, incorporating increasingly large numbers of parameters in an effort to represent physical processes on a scale approaching that at which they occur in nature. Consequently, the inverse problem of parameter estimation (specifically, model calibration) and subsequent uncertainty analysis have become increasingly computation-intensive endeavors. Fortunately, advances in computing have made computational power equivalent to that of dozens to hundreds of desktop computers accessible through a variety of alternate means: modelers have various possibilities, ranging from traditional Local Area Networks (LANs) to cloud computing. Commonly used parameter estimation software is well suited to take advantage of the availability of such increased computing power. Unfortunately, logistical issues become increasingly important as an increasing number and variety of computers are brought to bear on the inverse problem. To facilitate efficient access to disparate computer resources, the PESTCommander program documented herein has been developed to provide a Graphical User Interface (GUI) that facilitates the management of model files ("file management") and remote launching and termination of "slave" computers across a distributed network of computers ("run management"). In version 1.0 described here, PESTCommander can access and ascertain resources across traditional Windows LANs: however, the architecture of PESTCommander has been developed with the intent that future releases will be able to access computing resources (1) via trusted domains established in Wide Area Networks (WANs) in multiple remote locations and (2) via heterogeneous networks of Windows- and Unix-based operating systems. The design of PESTCommander also makes it suitable for extension to other computational resources, such as those that are available via cloud computing. Version 1.0 of PESTCommander was developed primarily to work with the parameter estimation software PEST; the discussion presented in this report focuses on the use of the PESTCommander together with Parallel PEST. However, PESTCommander can be used with a wide variety of programs and models that require management, distribution, and cleanup of files before or after model execution. In addition to its use with the Parallel PEST program suite, discussion is also included in this report regarding the use of PESTCommander with the Global Run Manager GENIE, which was developed simultaneously with PESTCommander.

Is Model-Based Development a Favorable Approach for Complex and Safety-Critical Computer Systems on Commercial Aircraft?

NASA Technical Reports Server (NTRS)

Torres-Pomales, Wilfredo

2014-01-01

A system is safety-critical if its failure can endanger human life or cause significant damage to property or the environment. State-of-the-art computer systems on commercial aircraft are highly complex, software-intensive, functionally integrated, and network-centric systems of systems. Ensuring that such systems are safe and comply with existing safety regulations is costly and time-consuming as the level of rigor in the development process, especially the validation and verification activities, is determined by considerations of system complexity and safety criticality. A significant degree of care and deep insight into the operational principles of these systems is required to ensure adequate coverage of all design implications relevant to system safety. Model-based development methodologies, methods, tools, and techniques facilitate collaboration and enable the use of common design artifacts among groups dealing with different aspects of the development of a system. This paper examines the application of model-based development to complex and safety-critical aircraft computer systems. Benefits and detriments are identified and an overall assessment of the approach is given.

Estimation of turbulence intensity and shear factor for diurnal and nocturnal periods with an URANS flow solver coupled with WRF

NASA Astrophysics Data System (ADS)

Veiga Rodrigues, C.; Palma, J. M. L. M.

2014-06-01

Mesoscale results using the WRF model were downscaled from 3 km to 250 m resolution in a one-way coupling with VENTOS®/M. The results were compared against field measurements at one site comprising 4 meteorological masts, each with two sets of cup anemometers and wind vanes. The results showed that the addition of VENTOS®/M to the model chain improved the wind speed RMSE. Regarding the prediction of wind direction ambivalent results were obtained. Special attention was given to the prediction of turbulence intensity, particularly in reproducing its inverse proportionality with increasing wind speed (cf. IEC 61400-1 standard). The typical use of computational models in wind resource assessment, i.e., relying on decoupled methodologies and neutrally-stratified regimes, does not allow the representation of turbulence intensity for all wind speeds. The results obtained with VENTOS®/M were in agreement with the measured turbulence characteristics at both high and low wind speeds. Such was achieved without the coupling of any turbulence related field, relying solely on the turbulence model embedded in VENTOS®/M and its respective wall boundary conditions, based on Monin-Obukhov similarity theory. The behaviour under different stratification regimes was verified by analysing diurnal and nocturnal events separately.

Portable Brain-Computer Interface for the Intensive Care Unit Patient Communication Using Subject-Dependent SSVEP Identification.

PubMed

Dehzangi, Omid; Farooq, Muhamed

2018-01-01

A major predicament for Intensive Care Unit (ICU) patients is inconsistent and ineffective communication means. Patients rated most communication sessions as difficult and unsuccessful. This, in turn, can cause distress, unrecognized pain, anxiety, and fear. As such, we designed a portable BCI system for ICU communications (BCI4ICU) optimized to operate effectively in an ICU environment. The system utilizes a wearable EEG cap coupled with an Android app designed on a mobile device that serves as visual stimuli and data processing module. Furthermore, to overcome the challenges that BCI systems face today in real-world scenarios, we propose a novel subject-specific Gaussian Mixture Model- (GMM-) based training and adaptation algorithm. First, we incorporate subject-specific information in the training phase of the SSVEP identification model using GMM-based training and adaptation. We evaluate subject-specific models against other subjects. Subsequently, from the GMM discriminative scores, we generate the transformed vectors, which are passed to our predictive model. Finally, the adapted mixture mean scores of the subject-specific GMMs are utilized to generate the high-dimensional supervectors. Our experimental results demonstrate that the proposed system achieved 98.7% average identification accuracy, which is promising in order to provide effective and consistent communication for patients in the intensive care.

Computer vision research with new imaging technology

NASA Astrophysics Data System (ADS)

Hou, Guangqi; Liu, Fei; Sun, Zhenan

2015-12-01

Light field imaging is capable of capturing dense multi-view 2D images in one snapshot, which record both intensity values and directions of rays simultaneously. As an emerging 3D device, the light field camera has been widely used in digital refocusing, depth estimation, stereoscopic display, etc. Traditional multi-view stereo (MVS) methods only perform well on strongly texture surfaces, but the depth map contains numerous holes and large ambiguities on textureless or low-textured regions. In this paper, we exploit the light field imaging technology on 3D face modeling in computer vision. Based on a 3D morphable model, we estimate the pose parameters from facial feature points. Then the depth map is estimated through the epipolar plane images (EPIs) method. At last, the high quality 3D face model is exactly recovered via the fusing strategy. We evaluate the effectiveness and robustness on face images captured by a light field camera with different poses.

Computational models of intergroup competition and warfare.

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

Letendre, Kenneth; Abbott, Robert G.

2011-11-01

This document reports on the research of Kenneth Letendre, the recipient of a Sandia Graduate Research Fellowship at the University of New Mexico. Warfare is an extreme form of intergroup competition in which individuals make extreme sacrifices for the benefit of their nation or other group to which they belong. Among animals, limited, non-lethal competition is the norm. It is not fully understood what factors lead to warfare. We studied the global variation in the frequency of civil conflict among countries of the world, and its positive association with variation in the intensity of infectious disease. We demonstrated that themore » burden of human infectious disease importantly predicts the frequency of civil conflict and tested a causal model for this association based on the parasite-stress theory of sociality. We also investigated the organization of social foraging by colonies of harvester ants in the genus Pogonomyrmex, using both field studies and computer models.« less

Full Monte Carlo-Based Biologic Treatment Plan Optimization System for Intensity Modulated Carbon Ion Therapy on Graphics Processing Unit.

PubMed

Qin, Nan; Shen, Chenyang; Tsai, Min-Yu; Pinto, Marco; Tian, Zhen; Dedes, Georgios; Pompos, Arnold; Jiang, Steve B; Parodi, Katia; Jia, Xun

2018-01-01

One of the major benefits of carbon ion therapy is enhanced biological effectiveness at the Bragg peak region. For intensity modulated carbon ion therapy (IMCT), it is desirable to use Monte Carlo (MC) methods to compute the properties of each pencil beam spot for treatment planning, because of their accuracy in modeling physics processes and estimating biological effects. We previously developed goCMC, a graphics processing unit (GPU)-oriented MC engine for carbon ion therapy. The purpose of the present study was to build a biological treatment plan optimization system using goCMC. The repair-misrepair-fixation model was implemented to compute the spatial distribution of linear-quadratic model parameters for each spot. A treatment plan optimization module was developed to minimize the difference between the prescribed and actual biological effect. We used a gradient-based algorithm to solve the optimization problem. The system was embedded in the Varian Eclipse treatment planning system under a client-server architecture to achieve a user-friendly planning environment. We tested the system with a 1-dimensional homogeneous water case and 3 3-dimensional patient cases. Our system generated treatment plans with biological spread-out Bragg peaks covering the targeted regions and sparing critical structures. Using 4 NVidia GTX 1080 GPUs, the total computation time, including spot simulation, optimization, and final dose calculation, was 0.6 hour for the prostate case (8282 spots), 0.2 hour for the pancreas case (3795 spots), and 0.3 hour for the brain case (6724 spots). The computation time was dominated by MC spot simulation. We built a biological treatment plan optimization system for IMCT that performs simulations using a fast MC engine, goCMC. To the best of our knowledge, this is the first time that full MC-based IMCT inverse planning has been achieved in a clinically viable time frame. Copyright © 2017 Elsevier Inc. All rights reserved.

Normalizing a relativistic model of X-ray reflection. Definition of the reflection fraction and its implementation in relxill

NASA Astrophysics Data System (ADS)

Dauser, T.; García, J.; Walton, D. J.; Eikmann, W.; Kallman, T.; McClintock, J.; Wilms, J.

2016-05-01

Aims: The only relativistic reflection model that implements a parameter relating the intensity incident on an accretion disk to the observed intensity is relxill. The parameter used in earlier versions of this model, referred to as the reflection strength, is unsatisfactory; it has been superseded by a parameter that provides insight into the accretion geometry, namely the reflection fraction. The reflection fraction is defined as the ratio of the coronal intensity illuminating the disk to the coronal intensity that reaches the observer. Methods: The relxill model combines a general relativistic ray-tracing code and a photoionization code to compute the component of radiation reflected from an accretion that is illuminated by an external source. The reflection fraction is a particularly important parameter for relativistic models with well-defined geometry, such as the lamp post model, which is a focus of this paper. Results: Relativistic spectra are compared for three inclinations and for four values of the key parameter of the lamp post model, namely the height above the black hole of the illuminating, on-axis point source. In all cases, the strongest reflection is produced for low source heights and high spin. A low-spin black hole is shown to be incapable of producing enhanced relativistic reflection. Results for the relxill model are compared to those obtained with other models and a Monte Carlo simulation. Conclusions: Fitting data by using the relxill model and the recently implemented reflection fraction, the geometry of a system can be constrained. The reflection fraction is independent of system parameters such as inclination and black hole spin. The reflection-fraction parameter was implemented with the name refl_frac in all flavours of the relxill model, and the non-relativistic reflection model xillver, in v0.4a (18 January 2016).

Ground-motion modeling of the 1906 San Francisco earthquake, part I: Validation using the 1989 Loma Prieta earthquake

USGS Publications Warehouse

Aagaard, Brad T.; Brocher, T.M.; Dolenc, D.; Dreger, D.; Graves, R.W.; Harmsen, S.; Hartzell, S.; Larsen, S.; Zoback, M.L.

2008-01-01

We compute ground motions for the Beroza (1991) and Wald et al. (1991) source models of the 1989 magnitude 6.9 Loma Prieta earthquake using four different wave-propagation codes and recently developed 3D geologic and seismic velocity models. In preparation for modeling the 1906 San Francisco earthquake, we use this well-recorded earthquake to characterize how well our ground-motion simulations reproduce the observed shaking intensities and amplitude and durations of recorded motions throughout the San Francisco Bay Area. All of the simulations generate ground motions consistent with the large-scale spatial variations in shaking associated with rupture directivity and the geologic structure. We attribute the small variations among the synthetics to the minimum shear-wave speed permitted in the simulations and how they accommodate topography. Our long-period simulations, on average, under predict shaking intensities by about one-half modified Mercalli intensity (MMI) units (25%-35% in peak velocity), while our broadband simulations, on average, under predict the shaking intensities by one-fourth MMI units (16% in peak velocity). Discrepancies with observations arise due to errors in the source models and geologic structure. The consistency in the synthetic waveforms across the wave-propagation codes for a given source model suggests the uncertainty in the source parameters tends to exceed the uncertainty in the seismic velocity structure. In agreement with earlier studies, we find that a source model with slip more evenly distributed northwest and southeast of the hypocenter would be preferable to both the Beroza and Wald source models. Although the new 3D seismic velocity model improves upon previous velocity models, we identify two areas needing improvement. Nevertheless, we find that the seismic velocity model and the wave-propagation codes are suitable for modeling the 1906 earthquake and scenario events in the San Francisco Bay Area.

Normalizing a Relativistic Model of X-Ray Reflection Definition of the Reflection Fraction and Its Implementation in relxill

NASA Technical Reports Server (NTRS)

Dauser, T.; Garcia, J.; Walton, D. J.; Eikmann, W.; Kallman, T.; McClintock, J.; Wilms, J.

2016-01-01

Aims. The only relativistic reflection model that implements a parameter relating the intensity incident on an accretion disk to the observed intensity is relxill. The parameter used in earlier versions of this model, referred to as the reflection strength, is unsatisfactory; it has been superseded by a parameter that provides insight into the accretion geometry, namely the reflection fraction. The reflection fraction is defined as the ratio of the coronal intensity illuminating the disk to the coronal intensity that reaches the observer. Methods. The relxill model combines a general relativistic ray-tracing code and a photoionization code to compute the component of radiation reflected from an accretion that is illuminated by an external source. The reflection fraction is a particularly important parameter for relativistic models with well-defined geometry, such as the lamp post model, which is a focus of this paper. Results. Relativistic spectra are compared for three inclinations and for four values of the key parameter of the lamp post model,namely the height above the black hole of the illuminating, on-axis point source. In all cases, the strongest reflection is produced for low source heights and high spin. A low-spin black hole is shown to be incapable of producing enhanced relativistic reflection. Results for the relxill model are compared to those obtained with other models and a Monte Carlo simulation. Conclusions. Fitting data by using the relxill model and the recently implemented reflection fraction, the geometry of a system can be constrained. The reflection-fraction is independent of system parameters such as inclination and black hole spin. The reflection-fraction parameter was implemented with the name reflec_frac all flavours of the relxill model, and the non-relativistic reflection model xillver, in v0.4a (18 January 2016).

Impact of meteorological inflow uncertainty on tracer transport and source estimation in urban atmospheres

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

Lucas, Donald D.; Gowardhan, Akshay; Cameron-Smith, Philip

2015-08-08

Here, a computational Bayesian inverse technique is used to quantify the effects of meteorological inflow uncertainty on tracer transport and source estimation in a complex urban environment. We estimate a probability distribution of meteorological inflow by comparing wind observations to Monte Carlo simulations from the Aeolus model. Aeolus is a computational fluid dynamics model that simulates atmospheric and tracer flow around buildings and structures at meter-scale resolution. Uncertainty in the inflow is propagated through forward and backward Lagrangian dispersion calculations to determine the impact on tracer transport and the ability to estimate the release location of an unknown source. Ourmore » uncertainty methods are compared against measurements from an intensive observation period during the Joint Urban 2003 tracer release experiment conducted in Oklahoma City.« less

Numerical simulation of electron scattering by nanotube junctions

NASA Astrophysics Data System (ADS)

Brüning, J.; Grikurov, V. E.

2008-03-01

We demonstrate the possibility of computing the intensity of electronic transport through various junctions of three-dimensional metallic nanotubes. In particular, we observe that the magnetic field can be used to control the switch of electron in Y-type junctions. Keeping in mind the asymptotic modeling of reliable nanostructures by quantum graphs, we conjecture that the scattering matrix of the graph should be the same as the scattering matrix of its nanosize-prototype. The numerical computation of the latter gives a method for determining the "gluing" conditions at a graph. Exploring this conjecture, we show that the Kirchhoff conditions (which are commonly used on graphs) cannot be applied to model reliable junctions. This work is a natural extension of the paper [1], but it is written in a self-consistent manner.

Analysis of crack propagation in roller bearings using the boundary integral equation method - A mixed-mode loading problem

NASA Technical Reports Server (NTRS)

Ghosn, L. J.

1988-01-01

Crack propagation in a rotating inner raceway of a high-speed roller bearing is analyzed using the boundary integral method. The model consists of an edge plate under plane strain condition upon which varying Hertzian stress fields are superimposed. A multidomain boundary integral equation using quadratic elements was written to determine the stress intensity factors KI and KII at the crack tip for various roller positions. The multidomain formulation allows the two faces of the crack to be modeled in two different subregions, making it possible to analyze crack closure when the roller is positioned on or close to the crack line. KI and KII stress intensity factors along any direction were computed. These calculations permit determination of crack growth direction along which the average KI times the alternating KI is maximum.

Propagation of an ultra-short, intense laser in a relativistic fluid

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

Ritchie, A.B.; Decker, C.D.

1997-12-31

A Maxwell-relativistic fluid model is developed to describe the propagation of an ultrashort, intense laser pulse through an underdense plasma. The model makes use of numerically stabilizing fast Fourier transform (FFT) computational methods for both the Maxwell and fluid equations, and it is benchmarked against particle-in-cell (PIC) simulations. Strong fields generated in the wake of the laser are calculated, and the authors observe coherent wake-field radiation generated at harmonics of the plasma frequency due to nonlinearities in the laser-plasma interaction. For a plasma whose density is 10% of critical, the highest members of the plasma harmonic series begin to overlapmore » with the first laser harmonic, suggesting that widely used multiple-scales-theory, by which the laser and plasma frequencies are assumed to be separable, ceases to be a useful approximation.« less

bpshape wk4: a computer program that implements a physiological model for analyzing the shape of blood pressure waveforms

NASA Technical Reports Server (NTRS)

Ocasio, W. C.; Rigney, D. R.; Clark, K. P.; Mark, R. G.; Goldberger, A. L. (Principal Investigator)

1993-01-01

We describe the theory and computer implementation of a newly-derived mathematical model for analyzing the shape of blood pressure waveforms. Input to the program consists of an ECG signal, plus a single continuous channel of peripheral blood pressure, which is often obtained invasively from an indwelling catheter during intensive-care monitoring or non-invasively from a tonometer. Output from the program includes a set of parameter estimates, made for every heart beat. Parameters of the model can be interpreted in terms of the capacitance of large arteries, the capacitance of peripheral arteries, the inertance of blood flow, the peripheral resistance, and arterial pressure due to basal vascular tone. Aortic flow due to contraction of the left ventricle is represented by a forcing function in the form of a descending ramp, the area under which represents the stroke volume. Differential equations describing the model are solved by the method of Laplace transforms, permitting rapid parameter estimation by the Levenberg-Marquardt algorithm. Parameter estimates and their confidence intervals are given in six examples, which are chosen to represent a variety of pressure waveforms that are observed during intensive-care monitoring. The examples demonstrate that some of the parameters may fluctuate markedly from beat to beat. Our program will find application in projects that are intended to correlate the details of the blood pressure waveform with other physiological variables, pathological conditions, and the effects of interventions.

Numerical characteristics of quantum computer simulation

NASA Astrophysics Data System (ADS)

Chernyavskiy, A.; Khamitov, K.; Teplov, A.; Voevodin, V.; Voevodin, Vl.

2016-12-01

The simulation of quantum circuits is significantly important for the implementation of quantum information technologies. The main difficulty of such modeling is the exponential growth of dimensionality, thus the usage of modern high-performance parallel computations is relevant. As it is well known, arbitrary quantum computation in circuit model can be done by only single- and two-qubit gates, and we analyze the computational structure and properties of the simulation of such gates. We investigate the fact that the unique properties of quantum nature lead to the computational properties of the considered algorithms: the quantum parallelism make the simulation of quantum gates highly parallel, and on the other hand, quantum entanglement leads to the problem of computational locality during simulation. We use the methodology of the AlgoWiki project (algowiki-project.org) to analyze the algorithm. This methodology consists of theoretical (sequential and parallel complexity, macro structure, and visual informational graph) and experimental (locality and memory access, scalability and more specific dynamic characteristics) parts. Experimental part was made by using the petascale Lomonosov supercomputer (Moscow State University, Russia). We show that the simulation of quantum gates is a good base for the research and testing of the development methods for data intense parallel software, and considered methodology of the analysis can be successfully used for the improvement of the algorithms in quantum information science.

Seismic waveform modeling over cloud

NASA Astrophysics Data System (ADS)

Luo, Cong; Friederich, Wolfgang

2016-04-01

With the fast growing computational technologies, numerical simulation of seismic wave propagation achieved huge successes. Obtaining the synthetic waveforms through numerical simulation receives an increasing amount of attention from seismologists. However, computational seismology is a data-intensive research field, and the numerical packages usually come with a steep learning curve. Users are expected to master considerable amount of computer knowledge and data processing skills. Training users to use the numerical packages, correctly access and utilize the computational resources is a troubled task. In addition to that, accessing to HPC is also a common difficulty for many users. To solve these problems, a cloud based solution dedicated on shallow seismic waveform modeling has been developed with the state-of-the-art web technologies. It is a web platform integrating both software and hardware with multilayer architecture: a well designed SQL database serves as the data layer, HPC and dedicated pipeline for it is the business layer. Through this platform, users will no longer need to compile and manipulate various packages on the local machine within local network to perform a simulation. By providing users professional access to the computational code through its interfaces and delivering our computational resources to the users over cloud, users can customize the simulation at expert-level, submit and run the job through it.

A modeling approach to predict acoustic nonlinear field generated by a transmitter with an aluminum lens.

PubMed

Fan, Tingbo; Liu, Zhenbo; Chen, Tao; Li, Faqi; Zhang, Dong

2011-09-01

In this work, the authors propose a modeling approach to compute the nonlinear acoustic field generated by a flat piston transmitter with an attached aluminum lens. In this approach, the geometrical parameters (radius and focal length) of a virtual source are initially determined by Snell's refraction law and then adjusted based on the Rayleigh integral result in the linear case. Then, this virtual source is used with the nonlinear spheroidal beam equation (SBE) model to predict the nonlinear acoustic field in the focal region. To examine the validity of this approach, the calculated nonlinear result is compared with those from the Westervelt and (Khokhlov-Zabolotskaya-Kuznetsov) KZK equations for a focal intensity of 7 kW/cm(2). Results indicate that this approach could accurately describe the nonlinear acoustic field in the focal region with less computation time. The proposed modeling approach is shown to accurately describe the nonlinear acoustic field in the focal region. Compared with the Westervelt equation, the computation time of this approach is significantly reduced. It might also be applicable for the widely used concave focused transmitter with a large aperture angle.

Mechanism and computational model for Lyman-α-radiation generation by high-intensity-laser four-wave mixing in Kr-Ar gas

NASA Astrophysics Data System (ADS)

Louchev, Oleg A.; Bakule, Pavel; Saito, Norihito; Wada, Satoshi; Yokoyama, Koji; Ishida, Katsuhiko; Iwasaki, Masahiko

2011-09-01

We present a theoretical model combined with a computational study of a laser four-wave mixing process under optical discharge in which the non-steady-state four-wave amplitude equations are integrated with the kinetic equations of initial optical discharge and electron avalanche ionization in Kr-Ar gas. The model is validated by earlier experimental data showing strong inhibition of the generation of pulsed, tunable Lyman-α (Ly-α) radiation when using sum-difference frequency mixing of 212.6 nm and tunable infrared radiation (820-850 nm). The rigorous computational approach to the problem reveals the possibility and mechanism of strong auto-oscillations in sum-difference resonant Ly-α generation due to the combined effect of (i) 212.6-nm (2+1)-photon ionization producing initial electrons, followed by (ii) the electron avalanche dominated by 843-nm radiation, and (iii) the final breakdown of the phase matching condition. The model shows that the final efficiency of Ly-α radiation generation can achieve a value of ˜5×10-4 which is restricted by the total combined absorption of the fundamental and generated radiation.

Deployment of the OSIRIS EM-PIC code on the Intel Knights Landing architecture

NASA Astrophysics Data System (ADS)

Fonseca, Ricardo

2017-10-01

Electromagnetic particle-in-cell (EM-PIC) codes such as OSIRIS have found widespread use in modelling the highly nonlinear and kinetic processes that occur in several relevant plasma physics scenarios, ranging from astrophysical settings to high-intensity laser plasma interaction. Being computationally intensive, these codes require large scale HPC systems, and a continuous effort in adapting the algorithm to new hardware and computing paradigms. In this work, we report on our efforts on deploying the OSIRIS code on the new Intel Knights Landing (KNL) architecture. Unlike the previous generation (Knights Corner), these boards are standalone systems, and introduce several new features, include the new AVX-512 instructions and on-package MCDRAM. We will focus on the parallelization and vectorization strategies followed, as well as memory management, and present a detailed performance evaluation of code performance in comparison with the CPU code. This work was partially supported by Fundaçã para a Ciência e Tecnologia (FCT), Portugal, through Grant No. PTDC/FIS-PLA/2940/2014.

Ganalyzer: A tool for automatic galaxy image analysis

NASA Astrophysics Data System (ADS)

Shamir, Lior

2011-05-01

Ganalyzer is a model-based tool that automatically analyzes and classifies galaxy images. Ganalyzer works by separating the galaxy pixels from the background pixels, finding the center and radius of the galaxy, generating the radial intensity plot, and then computing the slopes of the peaks detected in the radial intensity plot to measure the spirality of the galaxy and determine its morphological class. Unlike algorithms that are based on machine learning, Ganalyzer is based on measuring the spirality of the galaxy, a task that is difficult to perform manually, and in many cases can provide a more accurate analysis compared to manual observation. Ganalyzer is simple to use, and can be easily embedded into other image analysis applications. Another advantage is its speed, which allows it to analyze ~10,000,000 galaxy images in five days using a standard modern desktop computer. These capabilities can make Ganalyzer a useful tool in analyzing large datasets of galaxy images collected by autonomous sky surveys such as SDSS, LSST or DES.

Mechanistic experimental pain assessment in computer users with and without chronic musculoskeletal pain.

PubMed

Ge, Hong-You; Vangsgaard, Steffen; Omland, Øyvind; Madeleine, Pascal; Arendt-Nielsen, Lars

2014-12-06

Musculoskeletal pain from the upper extremity and shoulder region is commonly reported by computer users. However, the functional status of central pain mechanisms, i.e., central sensitization and conditioned pain modulation (CPM), has not been investigated in this population. The aim was to evaluate sensitization and CPM in computer users with and without chronic musculoskeletal pain. Pressure pain threshold (PPT) mapping in the neck-shoulder (15 points) and the elbow (12 points) was assessed together with PPT measurement at mid-point in the tibialis anterior (TA) muscle among 47 computer users with chronic pain in the upper extremity and/or neck-shoulder pain (pain group) and 17 pain-free computer users (control group). Induced pain intensities and profiles over time were recorded using a 0-10 cm electronic visual analogue scale (VAS) in response to different levels of pressure stimuli on the forearm with a new technique of dynamic pressure algometry. The efficiency of CPM was assessed using cuff-induced pain as conditioning pain stimulus and PPT at TA as test stimulus. The demographics, job seniority and number of working hours/week using a computer were similar between groups. The PPTs measured at all 15 points in the neck-shoulder region were not significantly different between groups. There were no significant differences between groups neither in PPTs nor pain intensity induced by dynamic pressure algometry. No significant difference in PPT was observed in TA between groups. During CPM, a significant increase in PPT at TA was observed in both groups (P < 0.05) without significant differences between groups. For the chronic pain group, higher clinical pain intensity, lower PPT values from the neck-shoulder and higher pain intensity evoked by the roller were all correlated with less efficient descending pain modulation (P < 0.05). This suggests that the excitability of the central pain system is normal in a large group of computer users with low pain intensity chronic upper extremity and/or neck-shoulder pain and that increased excitability of the pain system cannot explain the reported pain. However, computer users with higher pain intensity and lower PPTs were found to have decreased efficiency in descending pain modulation.

Please Reduce Cycle Time

DTIC Science & Technology

2014-12-01

observed an ERP system implementation that encountered this exact model. The modified COTS software worked and passed the acceptance tests but never... software -intensive program. We decided to create a very detailed master sched- ule with multiple supporting subschedules that linked and Implementing ...processes in place as part of the COTS implementation . For hardware , COTS can also present some risks. Many pro- grams use COTS computers and servers

New Tools for Estimating and Managing Local/Regional Air Quality Impacts of Prescribed Burns

DTIC Science & Technology

2013-02-01

189 8.1.2 Conference Papers ...the dryer fuels and horizontal burn configuration would result in a more intense fire and provide emission factors closer to those from the flaming...the EPA web site, the CMAQ Model is a powerful computational tool used by EPA and states for air quality management in that it can be used to design

Use of Information and Communication Technology (ICT) and Perceived Health in Adolescence: The Role of Sleeping Habits and Waking-Time Tiredness

ERIC Educational Resources Information Center

Punamaki, Raija-Leena; Wallenius, Marjut; Nygard, Clase-Hakan; Saarni, Lea; Rimpela, Arja

2007-01-01

The first aim for this paper was to examine gender and age differences in the intensity of usage of information and communication technology (ICT: computer for digital playing, writing and e-mailing and communication, and Internet surfing, and mobile phone). Second, we modelled the possible mediating role of sleeping habits and waking-time…

Defect detection of castings in radiography images using a robust statistical feature.

PubMed

Zhao, Xinyue; He, Zaixing; Zhang, Shuyou

2014-01-01

One of the most commonly used optical methods for defect detection is radiographic inspection. Compared with methods that extract defects directly from the radiography image, model-based methods deal with the case of an object with complex structure well. However, detection of small low-contrast defects in nonuniformly illuminated images is still a major challenge for them. In this paper, we present a new method based on the grayscale arranging pairs (GAP) feature to detect casting defects in radiography images automatically. First, a model is built using pixel pairs with a stable intensity relationship based on the GAP feature from previously acquired images. Second, defects can be extracted by comparing the difference of intensity-difference signs between the input image and the model statistically. The robustness of the proposed method to noise and illumination variations has been verified on casting radioscopic images with defects. The experimental results showed that the average computation time of the proposed method in the testing stage is 28 ms per image on a computer with a Pentium Core 2 Duo 3.00 GHz processor. For the comparison, we also evaluated the performance of the proposed method as well as that of the mixture-of-Gaussian-based and crossing line profile methods. The proposed method achieved 2.7% and 2.0% false negative rates in the noise and illumination variation experiments, respectively.

On tear film breakup (TBU): dynamics and imaging.

PubMed

Braun, Richard J; Driscoll, Tobin A; Begley, Carolyn G; King-Smith, P Ewen; Siddique, Javed I

2018-06-13

We report the results of some recent experiments to visualize tear film dynamics. We then study a mathematical model for tear film thinning and tear film breakup (TBU), a term from the ocular surface literature. The thinning is driven by an imposed tear film thinning rate which is input from in vivo measurements. Solutes representing osmolarity and fluorescein are included in the model. Osmolarity causes osmosis from the model ocular surface, and the fluorescein is used to compute the intensity corresponding closely to in vivo observations. The imposed thinning can be either one-dimensional or axisymmetric, leading to streaks or spots of TBU, respectively. For a spatially-uniform (flat) film, osmosis would cease thinning and balance mass lost due to evaporation; for these space-dependent evaporation profiles TBU does occur because osmolarity diffuses out of the TBU into the surrounding tear film, in agreement with previous results. The intensity pattern predicted based on the fluorescein concentration is compared with the computed thickness profiles; this comparison is important for interpreting in vivo observations. The non-dimensionalization introduced leads to insight about the relative importance of the competing processes; it leads to a classification of large vs small TBU regions in which different physical effects are dominant. Many regions of TBU may be considered small, revealing that the flow inside the film has an appreciable influence on fluorescence imaging of the tear film.

Neural mechanisms of planning: A computational analysis using event-related fMRI

PubMed Central

Fincham, Jon M.; Carter, Cameron S.; van Veen, Vincent; Stenger, V. Andrew; Anderson, John R.

2002-01-01

To investigate the neural mechanisms of planning, we used a novel adaptation of the Tower of Hanoi (TOH) task and event-related functional MRI. Participants were trained in applying a specific strategy to an isomorph of the five-disk TOH task. After training, participants solved novel problems during event-related functional MRI. A computational cognitive model of the task was used to generate a reference time series representing the expected blood oxygen level-dependent response in brain areas involved in the manipulation and planning of goals. This time series was used as one term within a general linear modeling framework to identify brain areas in which the time course of activity varied as a function of goal-processing events. Two distinct time courses of activation were identified, one in which activation varied parametrically with goal-processing operations, and the other in which activation became pronounced only during goal-processing intensive trials. Regions showing the parametric relationship comprised a frontoparietal system and include right dorsolateral prefrontal cortex [Brodmann's area (BA 9)], bilateral parietal (BA 40/7), and bilateral premotor (BA 6) areas. Regions preferentially engaged only during goal-intensive processing include left inferior frontal gyrus (BA 44). The implications of these results for the current model, as well as for our understanding of the neural mechanisms of planning and functional specialization of the prefrontal cortex, are discussed. PMID:11880658

Interplanetary Lyman α background and the heliospheric interface

NASA Astrophysics Data System (ADS)

Quémerais, Eric; Sander, Bill R.; Clarke, John T.

2006-09-01

We present some recent measurements of the interplanetary Lyman α background which show a clear signature of the heliospheric interface. The Voyager 1 Ultraviolet Spectrometer has measured the variation of the upwind intensity from 1993 to 2006. The derived radial variation of the intensity is clearly slower than what is expected from a hot model computation. This shows that the hydrogen number density increases ahead of the spacecraft, toward the upwind direction. The data also show an abrupt change of slope in 1998 when the Voyager 1 spacecraft was at 65 AU from the sun. This may be linked to temporal variations induced at the heliospheric interface by the variations of solar activity. Interplanetary Lyman α line profiles measured at one AU from the sun also show a clear signature of the heliospheric interface. The SWAN instrument on-board the SOHO spacecraft has studied the line profiles between 1996 and 2002. It was found that the variations seen in line of sight velocities from solar minimum to solar maximum have a larger amplitude than what is derived from hot model computations. The observed features can be better understood when considering that some of the hydrogen atoms crossing the interface region are slowed down and heated. These results are in good agreement with the present models of the interface. Independent spectral observations made by the Hubble Space Telescope in 1995-2001 confirm the SWAN/SOHO measurements.

Estimating Function Approaches for Spatial Point Processes

NASA Astrophysics Data System (ADS)

Deng, Chong

Spatial point pattern data consist of locations of events that are often of interest in biological and ecological studies. Such data are commonly viewed as a realization from a stochastic process called spatial point process. To fit a parametric spatial point process model to such data, likelihood-based methods have been widely studied. However, while maximum likelihood estimation is often too computationally intensive for Cox and cluster processes, pairwise likelihood methods such as composite likelihood, Palm likelihood usually suffer from the loss of information due to the ignorance of correlation among pairs. For many types of correlated data other than spatial point processes, when likelihood-based approaches are not desirable, estimating functions have been widely used for model fitting. In this dissertation, we explore the estimating function approaches for fitting spatial point process models. These approaches, which are based on the asymptotic optimal estimating function theories, can be used to incorporate the correlation among data and yield more efficient estimators. We conducted a series of studies to demonstrate that these estmating function approaches are good alternatives to balance the trade-off between computation complexity and estimating efficiency. First, we propose a new estimating procedure that improves the efficiency of pairwise composite likelihood method in estimating clustering parameters. Our approach combines estimating functions derived from pairwise composite likeli-hood estimation and estimating functions that account for correlations among the pairwise contributions. Our method can be used to fit a variety of parametric spatial point process models and can yield more efficient estimators for the clustering parameters than pairwise composite likelihood estimation. We demonstrate its efficacy through a simulation study and an application to the longleaf pine data. Second, we further explore the quasi-likelihood approach on fitting second-order intensity function of spatial point processes. However, the original second-order quasi-likelihood is barely feasible due to the intense computation and high memory requirement needed to solve a large linear system. Motivated by the existence of geometric regular patterns in the stationary point processes, we find a lower dimension representation of the optimal weight function and propose a reduced second-order quasi-likelihood approach. Through a simulation study, we show that the proposed method not only demonstrates superior performance in fitting the clustering parameter but also merits in the relaxation of the constraint of the tuning parameter, H. Third, we studied the quasi-likelihood type estimating funciton that is optimal in a certain class of first-order estimating functions for estimating the regression parameter in spatial point process models. Then, by using a novel spectral representation, we construct an implementation that is computationally much more efficient and can be applied to more general setup than the original quasi-likelihood method.

Mechanics of the acoustic radiation force in tissue-like solids

NASA Astrophysics Data System (ADS)

Dontsov, Egor V.

The acoustic radiation force (ARF) is a phenomenon affiliated with the nonlinear effects of high-intensity wave propagation. It represents the mean momentum transfer from the sound wave to the medium, and allows for an effective computation of the mean motion (e.g. acoustic streaming in fluids) induced by a high-intensity sound wave. Nowadays, the high-intensity focused ultrasound is frequently used in medical diagnosis applications due to its ability to "push" inside the tissue with the radiation body force and facilitate the local quantification of tissue's viscoelastic properties. The main objectives of this study include: i) the theoretical investigation of the ARF in fluids and tissue-like solids generated respectively by the amplitude modulated plane wave and focused ultrasound; ii) computation of the nonlinear acoustic wave propagation when the amplitude of the focused ultrasound field is modulated by a low-frequency signal, and iii) modeling of the ARF-induced motion in tissue-like solids for the purpose of quantifying their nonlinear elasticity via the magnitude of the ARF. Regarding the first part, a comparison with the existing theory of the ARF reveals a number of key features that are brought to light by the new formulation, including the contributions to the ARF of ultrasound modulation and thermal expansion, as well as the precise role of constitutive nonlinearities in generating the sustained body force in tissue-like solids by a focused ultrasound beam. In the second part, the hybrid time-frequency domain algorithm for the numerical analysis of the nonlinear wave equation is proposed. The approach is validated by comparing the results to the finite-difference modeling in time domain. Regarding the third objective, the Fourier transform approach is used to compute the ARF-induced shear wave motion in tissue-mimicking phantoms. A comparison between the experiment (tests performed at the Mayo Clinic) and model permitted the estimation of a particular coefficient of nonlinear tissue elasticity from the amplitude of the ARF-generated shear waves. For completeness, the ARF estimates of this coefficient are verified via an established technique known as acoustoelasticity.

Automation based on knowledge modeling theory and its applications in engine diagnostic systems using Space Shuttle Main Engine vibrational data. M.S. Thesis

NASA Technical Reports Server (NTRS)

Kim, Jonnathan H.

1995-01-01

Humans can perform many complicated tasks without explicit rules. This inherent and advantageous capability becomes a hurdle when a task is to be automated. Modern computers and numerical calculations require explicit rules and discrete numerical values. In order to bridge the gap between human knowledge and automating tools, a knowledge model is proposed. Knowledge modeling techniques are discussed and utilized to automate a labor and time intensive task of detecting anomalous bearing wear patterns in the Space Shuttle Main Engine (SSME) High Pressure Oxygen Turbopump (HPOTP).

Extending the life of mature basins in the North Sea and imaging sub-basalt and sub-intrusive structures using seismic intensity monitoring.

NASA Astrophysics Data System (ADS)

De Siena, Luca; Rawlinson, Nicholas

2016-04-01

Non-standard seismic imaging (velocity, attenuation, and scattering tomography) of the North Sea basins by using unexploited seismic intensities from previous passive and active surveys are key for better imaging and monitoring fluid under the subsurface. These intensities provide unique solutions to the problem of locating/tracking gas/fluid movements in the crust and depicting sub-basalt and sub-intrusives in volcanic reservoirs. The proposed techniques have been tested in volcanic Islands (Deception Island) and have been proved effective at monitoring fracture opening, imaging buried fluid-filled bodies, and tracking water/gas interfaces. These novel seismic attributes are modelled in space and time and connected with the lithology of the sampled medium, specifically density and permeability with as key output a novel computational code with strong commercial potential.

Investigation of an Optimum Detection Scheme for a Star-Field Mapping System

NASA Technical Reports Server (NTRS)

Aldridge, M. D.; Credeur, L.

1970-01-01

An investigation was made to determine the optimum detection scheme for a star-field mapping system that uses coded detection resulting from starlight shining through specially arranged multiple slits of a reticle. The computer solution of equations derived from a theoretical model showed that the greatest probability of detection for a given star and background intensity occurred with the use of a single transparent slit. However, use of multiple slits improved the system's ability to reject the detection of undesirable lower intensity stars, but only by decreasing the probability of detection for lower intensity stars to be mapped. Also, it was found that the coding arrangement affected the root-mean-square star-position error and that detection is possible with error in the system's detected spin rate, though at a reduced probability.

Accelerating Wright–Fisher Forward Simulations on the Graphics Processing Unit

PubMed Central

Lawrie, David S.

2017-01-01

Forward Wright–Fisher simulations are powerful in their ability to model complex demography and selection scenarios, but suffer from slow execution on the Central Processor Unit (CPU), thus limiting their usefulness. However, the single-locus Wright–Fisher forward algorithm is exceedingly parallelizable, with many steps that are so-called “embarrassingly parallel,” consisting of a vast number of individual computations that are all independent of each other and thus capable of being performed concurrently. The rise of modern Graphics Processing Units (GPUs) and programming languages designed to leverage the inherent parallel nature of these processors have allowed researchers to dramatically speed up many programs that have such high arithmetic intensity and intrinsic concurrency. The presented GPU Optimized Wright–Fisher simulation, or “GO Fish” for short, can be used to simulate arbitrary selection and demographic scenarios while running over 250-fold faster than its serial counterpart on the CPU. Even modest GPU hardware can achieve an impressive speedup of over two orders of magnitude. With simulations so accelerated, one can not only do quick parametric bootstrapping of previously estimated parameters, but also use simulated results to calculate the likelihoods and summary statistics of demographic and selection models against real polymorphism data, all without restricting the demographic and selection scenarios that can be modeled or requiring approximations to the single-locus forward algorithm for efficiency. Further, as many of the parallel programming techniques used in this simulation can be applied to other computationally intensive algorithms important in population genetics, GO Fish serves as an exciting template for future research into accelerating computation in evolution. GO Fish is part of the Parallel PopGen Package available at: http://dl42.github.io/ParallelPopGen/. PMID:28768689

Conditions for NIR fluorescence-guided tumor resectioning in preclinical lung cancer model (Conference Presentation)

NASA Astrophysics Data System (ADS)

Kim, Minji; Quan, Yuhua; Choi, Byeong Hyun; Choi, Yeonho; Kim, Hyun Koo; Kim, Beop-Min

2016-03-01

Pulmonary nodule could be identified by intraoperative fluorescence imaging system from systemic injection of indocyanine green (ICG) which achieves enhanced permeability and retention (EPR) effects. This study was performed to evaluate optimal injection time of ICG for detecting cancer during surgery in rabbit lung cancer model. VX2 carcinoma cell was injected in rabbit lung under fluoroscopic computed tomography-guidance. Solitary lung cancer was confirmed on positron emitting tomography with CT (PET/CT) 2 weeks after inoculation. ICG was administered intravenously and fluorescent intensity of lung tumor was measured using the custom-built intraoperative color and fluorescence merged imaging system (ICFIS) for 15 hours. Solitary lung cancer was resected through thoracoscopic version of ICFIS. ICG was observed in all animals. Because Lung has fast blood pulmonary circulation, Fluorescent signal showed maximum intensity earlier than previous studies in other organs. Fluorescent intensity showed maximum intensity within 6-9 hours in rabbit lung cancer. Overall, Fluorescent intensity decreased with increasing time, however, all tumors were detectable using fluorescent images until 12 hours. In conclusion, while there had been studies in other organs showed that optimal injection time was at least 24 hours before operation, this study showed shorter optimal injection time at lung cancer. Since fluorescent signal showed the maximum intensity within 6-9 hours, cancer resection could be performed during this time. This data informed us that optimal injection time of ICG should be evaluated in each different solid organ tumor for fluorescent image guided surgery.

Accurate small and wide angle x-ray scattering profiles from atomic models of proteins and nucleic acids

NASA Astrophysics Data System (ADS)

Nguyen, Hung T.; Pabit, Suzette A.; Meisburger, Steve P.; Pollack, Lois; Case, David A.

2014-12-01

A new method is introduced to compute X-ray solution scattering profiles from atomic models of macromolecules. The three-dimensional version of the Reference Interaction Site Model (RISM) from liquid-state statistical mechanics is employed to compute the solvent distribution around the solute, including both water and ions. X-ray scattering profiles are computed from this distribution together with the solute geometry. We describe an efficient procedure for performing this calculation employing a Lebedev grid for the angular averaging. The intensity profiles (which involve no adjustable parameters) match experiment and molecular dynamics simulations up to wide angle for two proteins (lysozyme and myoglobin) in water, as well as the small-angle profiles for a dozen biomolecules taken from the BioIsis.net database. The RISM model is especially well-suited for studies of nucleic acids in salt solution. Use of fiber-diffraction models for the structure of duplex DNA in solution yields close agreement with the observed scattering profiles in both the small and wide angle scattering (SAXS and WAXS) regimes. In addition, computed profiles of anomalous SAXS signals (for Rb+ and Sr2+) emphasize the ionic contribution to scattering and are in reasonable agreement with experiment. In cases where an absolute calibration of the experimental data at q = 0 is available, one can extract a count of the excess number of waters and ions; computed values depend on the closure that is assumed in the solution of the Ornstein-Zernike equations, with results from the Kovalenko-Hirata closure being closest to experiment for the cases studied here.

Artificial intelligence support for scientific model-building

NASA Technical Reports Server (NTRS)

Keller, Richard M.

1992-01-01

Scientific model-building can be a time-intensive and painstaking process, often involving the development of large and complex computer programs. Despite the effort involved, scientific models cannot easily be distributed and shared with other scientists. In general, implemented scientific models are complex, idiosyncratic, and difficult for anyone but the original scientific development team to understand. We believe that artificial intelligence techniques can facilitate both the model-building and model-sharing process. In this paper, we overview our effort to build a scientific modeling software tool that aids the scientist in developing and using models. This tool includes an interactive intelligent graphical interface, a high-level domain specific modeling language, a library of physics equations and experimental datasets, and a suite of data display facilities.

Modelling total solar irradiance since 1878 from simulated magnetograms

NASA Astrophysics Data System (ADS)

Dasi-Espuig, M.; Jiang, J.; Krivova, N. A.; Solanki, S. K.

2014-10-01

Aims: We present a new model of total solar irradiance (TSI) based on magnetograms simulated with a surface flux transport model (SFTM) and the Spectral And Total Irradiance REconstructions (SATIRE) model. Our model provides daily maps of the distribution of the photospheric field and the TSI starting from 1878. Methods: The modelling is done in two main steps. We first calculate the magnetic flux on the solar surface emerging in active and ephemeral regions. The evolution of the magnetic flux in active regions (sunspots and faculae) is computed using a surface flux transport model fed with the observed record of sunspot group areas and positions. The magnetic flux in ephemeral regions is treated separately using the concept of overlapping cycles. We then use a version of the SATIRE model to compute the TSI. The area coverage and the distribution of different magnetic features as a function of time, which are required by SATIRE, are extracted from the simulated magnetograms and the modelled ephemeral region magnetic flux. Previously computed intensity spectra of the various types of magnetic features are employed. Results: Our model reproduces the PMOD composite of TSI measurements starting from 1978 at daily and rotational timescales more accurately than the previous version of the SATIRE model computing TSI over this period of time. The simulated magnetograms provide a more realistic representation of the evolution of the magnetic field on the photosphere and also allow us to make use of information on the spatial distribution of the magnetic fields before the times when observed magnetograms were available. We find that the secular increase in TSI since 1878 is fairly stable to modifications of the treatment of the ephemeral region magnetic flux.

Mathematical model of a rotational bioreactor for the dynamic cultivation of scaffold-adhered human mesenchymal stem cells for bone regeneration

NASA Astrophysics Data System (ADS)

Ganimedov, V. L.; Papaeva, E. O.; Maslov, N. A.; Larionov, P. M.

2017-09-01

Development of cell-mediated scaffold technologies for the treatment of critical bone defects is very important for the purpose of reparative bone regeneration. Today the properties of the bioreactor for cell-seeded scaffold cultivation are the subject of intensive research. We used the mathematical modeling of rotational reactor and construct computational algorithm with the help of ANSYS software package to develop this new procedure. The solution obtained with the help of the constructed computational algorithm is in good agreement with the analytical solution of Couette for the task of two coaxial cylinders. The series of flow computations for different rotation frequencies (1, 0.75, 0.5, 0.33, 1.125 Hz) was performed for the laminar flow regime approximation with the help of computational algorithm. It was found that Taylor vortices appear in the annular gap between the cylinders in a simulated bioreactor. It was obtained that shear stress in the range of interest (0.002-0.1 Pa) arise on outer surface of inner cylinder when it rotates with the frequency not exceeding 0.8 Hz. So the constructed mathematical model and the created computational algorithm for calculating the flow parameters allow predicting the shear stress and pressure values depending on the rotation frequency and geometric parameters, as well as optimizing the operating mode of the bioreactor.

Analysis of flow patterns in a patient-specific aortic dissection model.

PubMed

Cheng, Z; Tan, F P P; Riga, C V; Bicknell, C D; Hamady, M S; Gibbs, R G J; Wood, N B; Xu, X Y

2010-05-01

Aortic dissection is the most common acute catastrophic event affecting the thoracic aorta. The majority of patients presenting with an uncomplicated type B dissection are treated medically, but 25% of these patients develop subsequent aneurysmal dilatation of the thoracic aorta. This study aimed at gaining more detailed knowledge of the flow phenomena associated with this condition. Morphological features and flow patterns in a dissected aortic segment of a presurgery type B dissection patient were analyzed based on computed tomography images acquired from the patient. Computational simulations of blood flow in the patient-specific model were performed by employing a correlation-based transitional version of Menter's hybrid k-epsilon/k-omega shear stress transport turbulence model implemented in ANSYS CFX 11. Our results show that the dissected aorta is dominated by locally highly disturbed, and possibly turbulent, flow with strong recirculation. A significant proportion (about 80%) of the aortic flow enters the false lumen, which may further increase the dilatation of the aorta. High values of wall shear stress have been found around the tear on the true lumen wall, perhaps increasing the likelihood of expanding the tear. Turbulence intensity in the tear region reaches a maximum of 70% at midsystolic deceleration phase. Incorporating the non-Newtonian behavior of blood into the same transitional flow model has yielded a slightly lower peak wall shear stress and higher maximum turbulence intensity without causing discernible changes to the distribution patterns. Comparisons between the laminar and turbulent flow simulations show a qualitatively similar distribution of wall shear stress but a significantly higher magnitude with the transitional turbulence model.

External validation of the Intensive Care National Audit & Research Centre (ICNARC) risk prediction model in critical care units in Scotland.

PubMed

Harrison, David A; Lone, Nazir I; Haddow, Catriona; MacGillivray, Moranne; Khan, Angela; Cook, Brian; Rowan, Kathryn M

2014-01-01

Risk prediction models are used in critical care for risk stratification, summarising and communicating risk, supporting clinical decision-making and benchmarking performance. However, they require validation before they can be used with confidence, ideally using independently collected data from a different source to that used to develop the model. The aim of this study was to validate the Intensive Care National Audit & Research Centre (ICNARC) model using independently collected data from critical care units in Scotland. Data were extracted from the Scottish Intensive Care Society Audit Group (SICSAG) database for the years 2007 to 2009. Recoding and mapping of variables was performed, as required, to apply the ICNARC model (2009 recalibration) to the SICSAG data using standard computer algorithms. The performance of the ICNARC model was assessed for discrimination, calibration and overall fit and compared with that of the Acute Physiology And Chronic Health Evaluation (APACHE) II model. There were 29,626 admissions to 24 adult, general critical care units in Scotland between 1 January 2007 and 31 December 2009. After exclusions, 23,269 admissions were included in the analysis. The ICNARC model outperformed APACHE II on measures of discrimination (c index 0.848 versus 0.806), calibration (Hosmer-Lemeshow chi-squared statistic 18.8 versus 214) and overall fit (Brier's score 0.140 versus 0.157; Shapiro's R 0.652 versus 0.621). Model performance was consistent across the three years studied. The ICNARC model performed well when validated in an external population to that in which it was developed, using independently collected data.

Differences in muscle load between computer and non-computer work among office workers.

PubMed

Richter, J M; Mathiassen, S E; Slijper, H P; Over, E A B; Frens, M A

2009-12-01

Introduction of more non-computer tasks has been suggested to increase exposure variation and thus reduce musculoskeletal complaints (MSC) in computer-intensive office work. This study investigated whether muscle activity did, indeed, differ between computer and non-computer activities. Whole-day logs of input device use in 30 office workers were used to identify computer and non-computer work, using a range of classification thresholds (non-computer thresholds (NCTs)). Exposure during these activities was assessed by bilateral electromyography recordings from the upper trapezius and lower arm. Contrasts in muscle activity between computer and non-computer work were distinct but small, even at the individualised, optimal NCT. Using an average group-based NCT resulted in less contrast, even in smaller subgroups defined by job function or MSC. Thus, computer activity logs should be used cautiously as proxies of biomechanical exposure. Conventional non-computer tasks may have a limited potential to increase variation in muscle activity during computer-intensive office work.

Fast computation of quadrupole and hexadecapole approximations in microlensing with a single point-source evaluation

NASA Astrophysics Data System (ADS)

Cassan, Arnaud

2017-07-01

The exoplanet detection rate from gravitational microlensing has grown significantly in recent years thanks to a great enhancement of resources and improved observational strategy. Current observatories include ground-based wide-field and/or robotic world-wide networks of telescopes, as well as space-based observatories such as satellites Spitzer or Kepler/K2. This results in a large quantity of data to be processed and analysed, which is a challenge for modelling codes because of the complexity of the parameter space to be explored and the intensive computations required to evaluate the models. In this work, I present a method that allows to compute the quadrupole and hexadecapole approximations of the finite-source magnification with more efficiency than previously available codes, with routines about six times and four times faster, respectively. The quadrupole takes just about twice the time of a point-source evaluation, which advocates for generalizing its use to large portions of the light curves. The corresponding routines are available as open-source python codes.

Exploiting data representation for fault tolerance

DOE PAGES

Hoemmen, Mark Frederick; Elliott, J.; Sandia National Lab.; ...

2015-01-06

Incorrect computer hardware behavior may corrupt intermediate computations in numerical algorithms, possibly resulting in incorrect answers. Prior work models misbehaving hardware by randomly flipping bits in memory. We start by accepting this premise, and present an analytic model for the error introduced by a bit flip in an IEEE 754 floating-point number. We then relate this finding to the linear algebra concepts of normalization and matrix equilibration. In particular, we present a case study illustrating that normalizing both vector inputs of a dot product minimizes the probability of a single bit flip causing a large error in the dot product'smore » result. Moreover, the absolute error is either less than one or very large, which allows detection of large errors. Then, we apply this to the GMRES iterative solver. We count all possible errors that can be introduced through faults in arithmetic in the computationally intensive orthogonalization phase of GMRES, and show that when the matrix is equilibrated, the absolute error is bounded above by one.« less

Estimating population diversity with CatchAll

PubMed Central

Bunge, John; Woodard, Linda; Böhning, Dankmar; Foster, James A.; Connolly, Sean; Allen, Heather K.

2012-01-01

Motivation: The massive data produced by next-generation sequencing require advanced statistical tools. We address estimating the total diversity or species richness in a population. To date, only relatively simple methods have been implemented in available software. There is a need for software employing modern, computationally intensive statistical analyses including error, goodness-of-fit and robustness assessments. Results: We present CatchAll, a fast, easy-to-use, platform-independent program that computes maximum likelihood estimates for finite-mixture models, weighted linear regression-based analyses and coverage-based non-parametric methods, along with outlier diagnostics. Given sample ‘frequency count’ data, CatchAll computes 12 different diversity estimates and applies a model-selection algorithm. CatchAll also derives discounted diversity estimates to adjust for possibly uncertain low-frequency counts. It is accompanied by an Excel-based graphics program. Availability: Free executable downloads for Linux, Windows and Mac OS, with manual and source code, at www.northeastern.edu/catchall. Contact: jab18@cornell.edu PMID:22333246

AquaSAXS: a web server for computation and fitting of SAXS profiles with non-uniformally hydrated atomic models.

PubMed

Poitevin, Frédéric; Orland, Henri; Doniach, Sebastian; Koehl, Patrice; Delarue, Marc

2011-07-01

Small Angle X-ray Scattering (SAXS) techniques are becoming more and more useful for structural biologists and biochemists, thanks to better access to dedicated synchrotron beamlines, better detectors and the relative easiness of sample preparation. The ability to compute the theoretical SAXS profile of a given structural model, and to compare this profile with the measured scattering intensity, yields crucial structural informations about the macromolecule under study and/or its complexes in solution. An important contribution to the profile, besides the macromolecule itself and its solvent-excluded volume, is the excess density due to the hydration layer. AquaSAXS takes advantage of recently developed methods, such as AquaSol, that give the equilibrium solvent density map around macromolecules, to compute an accurate SAXS/WAXS profile of a given structure and to compare it to the experimental one. Here, we describe the interface architecture and capabilities of the AquaSAXS web server (http://lorentz.dynstr.pasteur.fr/aquasaxs.php).

Ames S-32 O-16 O-18 Line List for High-Resolution Experimental IR Analysis

NASA Technical Reports Server (NTRS)

Huang, Xinchuan; Schwenke, David W.; Lee, Timothy J.

2016-01-01

By comparing to the most recent experimental data and spectra of the SO2 628 ?1/?3 bands (see Ulenikov et al., JQSRT 168 (2016) 29-39), this study illustrates the reliability and accuracy of the Ames-296K SO2 line list, which is accurate enough to facilitate such high-resolution spectroscopic analysis. The SO2 628 IR line list is computed on a recently improved potential energy surface (PES) refinement, denoted Ames-Pre2, and the published purely ab initio CCSD(T)/aug-cc-pVQZ dipole moment surface. Progress has been made in both energy level convergence and rovibrational quantum number assignments agreeing with laboratory analysis models. The accuracy of the computed 628 energy levels and line list is similar to what has been achieved and reported for SO2 626 and 646, i.e. 0.01-0.03 cm(exp -1) for bands up to 5500 cm(exp -1). During the comparison, we found some discrepancies in addition to overall good agreements. The three-IR-list based feature-by-feature analysis in a 0.25 cm(exp -1) spectral window clearly demonstrates the power of the current Ames line lists with new assignments, correction of some errors, and intensity contributions from varied sources including other isotopologues. We are inclined to attribute part of detected discrepancies to an incomplete experimental analysis and missing intensity in the model. With complete line position, intensity, and rovibrational quantum numbers determined at 296 K, spectroscopic analysis is significantly facilitated especially for a spectral range exhibiting such an unusually high density of lines. The computed 628 rovibrational levels and line list are accurate enough to provide alternatives for the missing bands or suspicious assignments, as well as helpful to identify these isotopologues in various celestial environments. The next step will be to revisit the SO2 828 and 646 spectral analyses.

Lowering the barriers to computational modeling of Earth's surface: coupling Jupyter Notebooks with Landlab, HydroShare, and CyberGIS for research and education.

NASA Astrophysics Data System (ADS)

Bandaragoda, C.; Castronova, A. M.; Phuong, J.; Istanbulluoglu, E.; Strauch, R. L.; Nudurupati, S. S.; Tarboton, D. G.; Wang, S. W.; Yin, D.; Barnhart, K. R.; Tucker, G. E.; Hutton, E.; Hobley, D. E. J.; Gasparini, N. M.; Adams, J. M.

2017-12-01

The ability to test hypotheses about hydrology, geomorphology and atmospheric processes is invaluable to research in the era of big data. Although community resources are available, there remain significant educational, logistical and time investment barriers to their use. Knowledge infrastructure is an emerging intellectual framework to understand how people are creating, sharing and distributing knowledge - which has been dramatically transformed by Internet technologies. In addition to the technical and social components in a cyberinfrastructure system, knowledge infrastructure considers educational, institutional, and open source governance components required to advance knowledge. We are designing an infrastructure environment that lowers common barriers to reproducing modeling experiments for earth surface investigation. Landlab is an open-source modeling toolkit for building, coupling, and exploring two-dimensional numerical models. HydroShare is an online collaborative environment for sharing hydrologic data and models. CyberGIS-Jupyter is an innovative cyberGIS framework for achieving data-intensive, reproducible, and scalable geospatial analytics using the Jupyter Notebook based on ROGER - the first cyberGIS supercomputer, so that models that can be elastically reproduced through cloud computing approaches. Our team of geomorphologists, hydrologists, and computer geoscientists has created a new infrastructure environment that combines these three pieces of software to enable knowledge discovery. Through this novel integration, any user can interactively execute and explore their shared data and model resources. Landlab on HydroShare with CyberGIS-Jupyter supports the modeling continuum from fully developed modelling applications, prototyping new science tools, hands on research demonstrations for training workshops, and classroom applications. Computational geospatial models based on big data and high performance computing can now be more efficiently developed, improved, scaled, and seamlessly reproduced among multidisciplinary users, thereby expanding the active learning curriculum and research opportunities for students in earth surface modeling and informatics.

Evaluation of stress intensity factors for bi-material interface cracks using displacement jump methods

NASA Astrophysics Data System (ADS)

Nehar, K. C.; Hachi, B. E.; Cazes, F.; Haboussi, M.

2017-12-01

The aim of the present work is to investigate the numerical modeling of interfacial cracks that may appear at the interface between two isotropic elastic materials. The extended finite element method is employed to analyze brittle and bi-material interfacial fatigue crack growth by computing the mixed mode stress intensity factors (SIF). Three different approaches are introduced to compute the SIFs. In the first one, mixed mode SIF is deduced from the computation of the contour integral as per the classical J-integral method, whereas a displacement method is used to evaluate the SIF by using either one or two displacement jumps located along the crack path in the second and third approaches. The displacement jump method is rather classical for mono-materials, but has to our knowledge not been used up to now for a bi-material. Hence, use of displacement jump for characterizing bi-material cracks constitutes the main contribution of the present study. Several benchmark tests including parametric studies are performed to show the effectiveness of these computational methodologies for SIF considering static and fatigue problems of bi-material structures. It is found that results based on the displacement jump methods are in a very good agreement with those of exact solutions, such as for the J-integral method, but with a larger domain of applicability and a better numerical efficiency (less time consuming and less spurious boundary effect).

Microscale traffic simulation and emission estimation in a heavily trafficked roundabout in Madrid (Spain).

PubMed

Quaassdorff, Christina; Borge, Rafael; Pérez, Javier; Lumbreras, Julio; de la Paz, David; de Andrés, Juan Manuel

2016-10-01

This paper presents the evaluation of emissions from vehicle operations in a domain of 300m×300m covering a complex urban roundabout with high traffic density in Madrid. Micro-level simulation was successfully applied to estimate the emissions on a scale of meters. Two programs were used: i) VISSIM to simulate the traffic on the square and to compute velocity-time profiles; and ii) VERSIT+micro through ENVIVER that uses VISSIM outputs to compute the related emissions at vehicle level. Data collection was achieved by a measurement campaign obtaining empirical data of vehicle flows and traffic intensities. Twelve simulations of different traffic situations (scenarios) were conducted, representing different hours from several days in a week and the corresponding NOX and PM10 emissions were estimated. The results show a general reduction on average speeds for higher intensities due to braking-acceleration patterns that contribute to increase the average emission factor and, therefore, the total emissions in the domain, especially on weekdays. The emissions are clearly related to traffic volume, although maximum emission scenario does not correspond to the highest traffic intensity due to congestion and variations in fleet composition throughout the day. These results evidence the potential that local measures aimed at alleviating congestion may have in urban areas to reduce emissions. In general, scenario-averaged emission factors estimated with the VISSIM-VERSIT+micro modelling system fitted well those from the average-speed model COPERT, used as a preliminary validation of the results. The largest deviations between these two models occur in those scenarios with more congestion. The design and resolution of the microscale modelling system allow to reflect the impact of actual traffic conditions on driving patterns and related emissions, making it useful for the design of mitigation measures for specific traffic hot-spots. Copyright © 2016 Elsevier B.V. All rights reserved.

Validation of coupled atmosphere-fire behavior models

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

Bossert, J.E.; Reisner, J.M.; Linn, R.R.

1998-12-31

Recent advances in numerical modeling and computer power have made it feasible to simulate the dynamical interaction and feedback between the heat and turbulence induced by wildfires and the local atmospheric wind and temperature fields. At Los Alamos National Laboratory, the authors have developed a modeling system that includes this interaction by coupling a high resolution atmospheric dynamics model, HIGRAD, with a fire behavior model, BEHAVE, to predict the spread of wildfires. The HIGRAD/BEHAVE model is run at very high resolution to properly resolve the fire/atmosphere interaction. At present, these coupled wildfire model simulations are computationally intensive. The additional complexitymore » of these models require sophisticated methods for assuring their reliability in real world applications. With this in mind, a substantial part of the research effort is directed at model validation. Several instrumented prescribed fires have been conducted with multi-agency support and participation from chaparral, marsh, and scrub environments in coastal areas of Florida and inland California. In this paper, the authors first describe the data required to initialize the components of the wildfire modeling system. Then they present results from one of the Florida fires, and discuss a strategy for further testing and improvement of coupled weather/wildfire models.« less

Electron beam-generated Ar/N{sub 2} plasmas: The effect of nitrogen addition on the brightest argon emission lines

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

Lock, E. H., E-mail: evgeniya.lock@nrl.navy.mil, E-mail: scott.walton@nrl.navy.mil; Petrova, Tz. B.; Petrov, G. M.

2016-04-15

The effect of nitrogen addition on the emission intensities of the brightest argon lines produced in a low pressure argon/nitrogen electron beam-generated plasmas is characterized using optical emission spectroscopy. In particular, a decrease in the intensities of the 811.5 nm and 763.5 nm lines is observed, while the intensity of the 750.4 nm line remains unchanged as nitrogen is added. To explain this phenomenon, a non-equilibrium collisional-radiative model is developed and used to compute the population of argon excited states and line intensities as a function of gas composition. The results show that the addition of nitrogen to argon modifies the electron energymore » distribution function, reduces the electron temperature, and depopulates Ar metastables in exchange reactions with electrons and N{sub 2} molecules, all of which lead to changes in argon excited states population and thus the emission originating from the Ar 4p levels.« less

Localization of intense electromagnetic waves in plasmas.

PubMed

Shukla, Padma Kant; Eliasson, Bengt

2008-05-28

We present theoretical and numerical studies of the interaction between relativistically intense laser light and a two-temperature plasma consisting of one relativistically hot and one cold component of electrons. Such plasmas are frequently encountered in intense laser-plasma experiments where collisionless heating via Raman instabilities leads to a high-energetic tail in the electron distribution function. The electromagnetic waves (EMWs) are governed by the Maxwell equations, and the plasma is governed by the relativistic Vlasov and hydrodynamic equations. Owing to the interaction between the laser light and the plasma, we can have trapping of electrons in the intense wakefield of the laser pulse and the formation of relativistic electron holes (REHs) in which laser light is trapped. Such electron holes are characterized by a non-Maxwellian distribution of electrons where we have trapped and free electron populations. We present a model for the interaction between laser light and REHs, and computer simulations that show the stability and dynamics of the coupled electron hole and EMW envelopes.

Analytic and computational modelling of super-radiant pulse compression in plasma and comparisons with experiment

NASA Astrophysics Data System (ADS)

Shvets, Gennady; Kalmykov, Serguei; Dreher, Matthias; Meyer-Ter-Vehn, Juergen

2003-10-01

The strongly non-linear regime of Raman backscattering [1,2] holds the promise of compressing long low-intensity laser beams into ultra-short high intensity pulses. As the short pulse is amplified by the long counter-propagating pump via backscattering the pump off the nonlinear plasma wave, its duration shrinks and intensity grows. The increase of the bandwidth of the amplified pulse only occurs in the nonlinear amplification regime, and is its most telling signature. Recent experiments at MPQ carried out in the strongly nonlinear regime reveal two previously unobserved features: (i) bandwidth expansion, and (ii) breakdown of the initially smooth amplified pulse into several spikes. Using semi-analytic model and particle-in-cell simulations, we explain the multiple pulse formation by the synchrotron motion of plasma electrons in the ponderomotive potential. Self-similar solutions consisting of multiple spikes are derived, and their nonlinear frequency shifts evaluated. The nonlinear focusing of the pulse by the pump is predicted and compared with experimental observations. [1] G. Shvets et. al., Phys. Rev. Lett. 81, 4879 (1998). [2] A. Pukhov, Rep. Progr. Phys. 66, 47 (1998).

The effect of variable waveform low-intensity pulsed ultrasound in a fourth metacarpal osteotomy gap model in horses.

PubMed

McClure, S R; Miles, K; Vansickle, D; South, T

2010-08-01

The objective of this study was to evaluate the effects of variable waveform low-intensity ultrasound on the healing of a fracture gap of the fourth metacarpal bone in horses. A randomized, blinded, controlled trial was conducted in eight healthy adult horses. In each horse, a 1-cm osteotomy of the fourth metacarpal bone was created. One randomly selected metacarpal gap was treated daily with a 40-min session of ultrasound and the opposite gap was managed similarly with an inactive transducer. The fourth metacarpal bones were radiographed weekly. Fluorescent markers were administered at 14, 28, 56 and 70 d. At the completion of the study at day 84, the bones were harvested and evaluated with peripheral quantitative computed tomography (pQCT) and histology. There were no significant differences between treated and control bones for any of the radiographic, pQCT or histologic parameters evaluated. These findings suggested that low-intensity ultrasound did not affect bone formation in a fracture gap model in the horse. Copyright 2010 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Self-Channelling of a Short Laser Pulse at Relativistic Intensity in Near Critical Underdense Plasma

NASA Astrophysics Data System (ADS)

Willi, O.; Borghesi, M.; MacKinnon, A. J.; Barringer, L.; Gaillard, R.; Meyer, C.; Gizzi, L.; Pukhov, A.; Meyer-Ter-Vehn, J.

1996-11-01

Self channelling of a picosecond pulse at relativistic intensities has been observed in near critical underdense plasmas. The plasma was preformed by laser heating of a thin film. The interaction pulse (1-3 ps duration, 1.054 μm) was focused onto the plasma at irradiances above 5 × 10^18 W/cm^2. Self-channelling of the pulse was detected via second harmonic and optical probe measurements. Intense, localised 2ω emission suggests the formation of channel structures of less than 5 μm in diameter, extending for several Rayleigh lengths. The temporal evolution of the electron density profile across the channel was measured via interferometry with picosecond temporal resolution. PIC code simulations, performed for the conditions of the experiment, predict the formation of similar channel structures. In this model, in addition to relativistic and ponderomotive self-focusing mechanisms, pinching by large self-generated magnetic fields also contributes to the single channel formation. Measurements of magnetic fields were also performed that seem to be consistent with the computational model.

A computational model of pupil dilation

NASA Astrophysics Data System (ADS)

Johansson, Birger; Balkenius, Christian

2018-01-01

We present a system-level connectionist model of pupil control that includes brain regions believed to influence the size of the pupil. It includes parts of the sympathetic and parasympathetic nervous system together with the hypothalamus, amygdala, locus coeruleus, and cerebellum. Computer simulations show that the model is able to reproduce a number of important aspects of how the pupil reacts to different stimuli: (1) It reproduces the characteristic shape and latency of the light-reflex. (2) It elicits pupil dilation as a response to novel stimuli. (3) It produces pupil dilation when shown emotionally charged stimuli, and can be trained to respond to initially neutral stimuli through classical conditioning. (4) The model can learn to expect light changes for particular stimuli, such as images of the sun, and produces a "light-response" to such stimuli even when there is no change in light intensity. (5) It also reproduces the fear-inhibited light reflex effect where reactions to light increase is weaker after presentation of a conditioned stimulus that predicts punishment.

Computational Approach to Seasonal Changes of Living Leaves

PubMed Central

Wu, Dong-Yan

2013-01-01

This paper proposes a computational approach to seasonal changes of living leaves by combining the geometric deformations and textural color changes. The geometric model of a leaf is generated by triangulating the scanned image of a leaf using an optimized mesh. The triangular mesh of the leaf is deformed by the improved mass-spring model, while the deformation is controlled by setting different mass values for the vertices on the leaf model. In order to adaptively control the deformation of different regions in the leaf, the mass values of vertices are set to be in proportion to the pixels' intensities of the corresponding user-specified grayscale mask map. The geometric deformations as well as the textural color changes of a leaf are used to simulate the seasonal changing process of leaves based on Markov chain model with different environmental parameters including temperature, humidness, and time. Experimental results show that the method successfully simulates the seasonal changes of leaves. PMID:23533545

Modeling RNA polymerase interaction in mitochondria of chordates

PubMed Central

2012-01-01

Background In previous work, we introduced a concept, a mathematical model and its computer realization that describe the interaction between bacterial and phage type RNA polymerases, protein factors, DNA and RNA secondary structures during transcription, including transcription initiation and termination. The model accurately reproduces changes of gene transcription level observed in polymerase sigma-subunit knockout and heat shock experiments in plant plastids. The corresponding computer program and a user guide are available at http://lab6.iitp.ru/en/rivals. Here we apply the model to the analysis of transcription and (partially) translation processes in the mitochondria of frog, rat and human. Notably, mitochondria possess only phage-type polymerases. We consider the entire mitochondrial genome so that our model allows RNA polymerases to complete more than one circle on the DNA strand. Results Our model of RNA polymerase interaction during transcription initiation and elongation accurately reproduces experimental data obtained for plastids. Moreover, it also reproduces evidence on bulk RNA concentrations and RNA half-lives in the mitochondria of frog, human with or without the MELAS mutation, and rat with normal (euthyroid) or hyposecretion of thyroid hormone (hypothyroid). The transcription characteristics predicted by the model include: (i) the fraction of polymerases terminating at a protein-dependent terminator in both directions (the terminator polarization), (ii) the binding intensities of the regulatory protein factor (mTERF) with the termination site and, (iii) the transcription initiation intensities (initiation frequencies) of all promoters in all five conditions (frog, healthy human, human with MELAS syndrome, healthy rat, and hypothyroid rat with aberrant mtDNA methylation). Using the model, absolute levels of all gene transcription can be inferred from an arbitrary array of the three transcription characteristics, whereas, for selected genes only relative RNA concentrations have been experimentally determined. Conversely, these characteristics and absolute transcription levels can be obtained using relative RNA concentrations and RNA half-lives known from various experimental studies. In this case, the “inverse problem” is solved with multi-objective optimization. Conclusions In this study, we demonstrate that our model accurately reproduces all relevant experimental data available for plant plastids, as well as the mitochondria of chordates. Using experimental data, the model is applied to estimate binding intensities of phage-type RNA polymerases to their promoters as well as predicting terminator characteristics, including polarization. In addition, one can predict characteristics of phage-type RNA polymerases and the transcription process that are difficult to measure directly, e.g., the association between the promoter’s nucleotide composition and the intensity of polymerase binding. To illustrate the application of our model in functional predictions, we propose a possible mechanism for MELAS syndrome development in human involving a decrease of Phe-tRNA, Val-tRNA and rRNA concentrations in the cell. In addition, we describe how changes in methylation patterns of the mTERF binding site and three promoters in hypothyroid rat correlate with changes in intensities of the mTERF binding and transcription initiations. Finally, we introduce an auxiliary model to describe the interaction between polysomal mRNA and ribonucleases. PMID:22873568

Estimation of the distribution of low-intensity ultrasound mechanical index as a parameter affecting the proliferation of spermatogonia stem cells in vitro.

PubMed

Moghaddam, Zeinab Hormozi; Mokhtari-Dizaji, Manijhe; Movahedin, Mansoureh; Ravari, Mohammad Ehsan

2017-07-01

Considering the use of physical and mechanical stimulation, such as low-intensity ultrasound for proliferation and differentiation of stem cells, it is essential to understand the physical and acoustical mechanisms of acoustic waves in vitro. Mechanical index is used for quantifying acoustic cavitation and the relationship between acoustic pressure and the frequency. In this study, modeling of the mechanical index was applied to provide treatment protocol and to understand the effective physical processes on reproducibility of stem cells. Due to low intensity of ultrasound, Rayleigh integral model has been used for acoustic pressure computation. The acoustic pressure and mechanical index equations are modeled and solved to estimate optimal mechanical index for 28, 40, 150kHz and 1MHz frequencies. This model are solved in different intensities and distances from transducer in cylindrical coordinates. Based on the results of the mechanical index, regions with threshold mechanical index of 0.7 were identified for extracting of radiation arrangement to cell medium. Acoustic pressure distribution along the axial and radial was extracted. In order to validate the results of the modeling, the acoustic pressure in the water and near field depth was measured by a piston hydrophone. Results of modeling and experiments show that the model is consistent well to experimental results with 0.91 and 0.90 correlation of coefficient (p<0.05) for 1MHz and 40kHz. Low-intensity ultrasound with 0.40 mechanical index is more effective on enhancing the proliferation rate of the spermatogonia stem cells during the seven days of culture. In contrast, higher mechanical index has a harmful effect on the spermatogonial stem cells. Thus, considering cavitation threshold of different materials is necessary to find effective mechanical index ranges on proliferation for the used frequencies. This acoustic propagation model and ultrasound mechanical index assessments can be used with acceptable accuracy, for the extraction special arrangement of acoustic exposure used in biological conditions in vitro. This model provides proper treatment planning in vitro and in vivo by estimating the cavitation phenomenon. Copyright © 2017 Elsevier B.V. All rights reserved.

Parallel computer processing and modeling: applications for the ICU

NASA Astrophysics Data System (ADS)

Baxter, Grant; Pranger, L. Alex; Draghic, Nicole; Sims, Nathaniel M.; Wiesmann, William P.

2003-07-01

Current patient monitoring procedures in hospital intensive care units (ICUs) generate vast quantities of medical data, much of which is considered extemporaneous and not evaluated. Although sophisticated monitors to analyze individual types of patient data are routinely used in the hospital setting, this equipment lacks high order signal analysis tools for detecting long-term trends and correlations between different signals within a patient data set. Without the ability to continuously analyze disjoint sets of patient data, it is difficult to detect slow-forming complications. As a result, the early onset of conditions such as pneumonia or sepsis may not be apparent until the advanced stages. We report here on the development of a distributed software architecture test bed and software medical models to analyze both asynchronous and continuous patient data in real time. Hardware and software has been developed to support a multi-node distributed computer cluster capable of amassing data from multiple patient monitors and projecting near and long-term outcomes based upon the application of physiologic models to the incoming patient data stream. One computer acts as a central coordinating node; additional computers accommodate processing needs. A simple, non-clinical model for sepsis detection was implemented on the system for demonstration purposes. This work shows exceptional promise as a highly effective means to rapidly predict and thereby mitigate the effect of nosocomial infections.

New Approaches For Asteroid Spin State and Shape Modeling From Delay-Doppler Radar Images

NASA Astrophysics Data System (ADS)

Raissi, Chedy; Lamee, Mehdi; Mosiane, Olorato; Vassallo, Corinne; Busch, Michael W.; Greenberg, Adam; Benner, Lance A. M.; Naidu, Shantanu P.; Duong, Nicholas

2016-10-01

Delay-Doppler radar imaging is a powerful technique to characterize the trajectories, shapes, and spin states of near-Earth asteroids; and has yielded detailed models of dozens of objects. Reconstructing objects' shapes and spins from delay-Doppler data is a computationally intensive inversion problem. Since the 1990s, delay-Doppler data has been analyzed using the SHAPE software. SHAPE performs sequential single-parameter fitting, and requires considerable computer runtime and human intervention (Hudson 1993, Magri et al. 2007). Recently, multiple-parameter fitting algorithms have been shown to more efficiently invert delay-Doppler datasets (Greenberg & Margot 2015) - decreasing runtime while improving accuracy. However, extensive human oversight of the shape modeling process is still required. We have explored two new techniques to better automate delay-Doppler shape modeling: Bayesian optimization and a machine-learning neural network.One of the most time-intensive steps of the shape modeling process is to perform a grid search to constrain the target's spin state. We have implemented a Bayesian optimization routine that uses SHAPE to autonomously search the space of spin-state parameters. To test the efficacy of this technique, we compared it to results with human-guided SHAPE for asteroids 1992 UY4, 2000 RS11, and 2008 EV5. Bayesian optimization yielded similar spin state constraints within a factor of 3 less computer runtime.The shape modeling process could be further accelerated using a deep neural network to replace iterative fitting. We have implemented a neural network with a variational autoencoder (VAE), using a subset of known asteroid shapes and a large set of synthetic radar images as inputs to train the network. Conditioning the VAE in this manner allows the user to give the network a set of radar images and get a 3D shape model as an output. Additional development will be required to train a network to reliably render shapes from delay-Doppler images.This work was supported by NASA Ames, NVIDIA, Autodesk and the SETI Institute as part of the NASA Frontier Development Lab program.

Final Report: Quantification of Uncertainty in Extreme Scale Computations (QUEST)

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

Marzouk, Youssef; Conrad, Patrick; Bigoni, Daniele

QUEST (\\url{www.quest-scidac.org}) is a SciDAC Institute that is focused on uncertainty quantification (UQ) in large-scale scientific computations. Our goals are to (1) advance the state of the art in UQ mathematics, algorithms, and software; and (2) provide modeling, algorithmic, and general UQ expertise, together with software tools, to other SciDAC projects, thereby enabling and guiding a broad range of UQ activities in their respective contexts. QUEST is a collaboration among six institutions (Sandia National Laboratories, Los Alamos National Laboratory, the University of Southern California, Massachusetts Institute of Technology, the University of Texas at Austin, and Duke University) with a historymore » of joint UQ research. Our vision encompasses all aspects of UQ in leadership-class computing. This includes the well-founded setup of UQ problems; characterization of the input space given available data/information; local and global sensitivity analysis; adaptive dimensionality and order reduction; forward and inverse propagation of uncertainty; handling of application code failures, missing data, and hardware/software fault tolerance; and model inadequacy, comparison, validation, selection, and averaging. The nature of the UQ problem requires the seamless combination of data, models, and information across this landscape in a manner that provides a self-consistent quantification of requisite uncertainties in predictions from computational models. Accordingly, our UQ methods and tools span an interdisciplinary space across applied math, information theory, and statistics. The MIT QUEST effort centers on statistical inference and methods for surrogate or reduced-order modeling. MIT personnel have been responsible for the development of adaptive sampling methods, methods for approximating computationally intensive models, and software for both forward uncertainty propagation and statistical inverse problems. A key software product of the MIT QUEST effort is the MIT Uncertainty Quantification library, called MUQ (\\url{muq.mit.edu}).« less

A Hybrid MPI/OpenMP Approach for Parallel Groundwater Model Calibration on Multicore Computers

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

Tang, Guoping; D'Azevedo, Ed F; Zhang, Fan

2010-01-01

Groundwater model calibration is becoming increasingly computationally time intensive. We describe a hybrid MPI/OpenMP approach to exploit two levels of parallelism in software and hardware to reduce calibration time on multicore computers with minimal parallelization effort. At first, HydroGeoChem 5.0 (HGC5) is parallelized using OpenMP for a uranium transport model with over a hundred species involving nearly a hundred reactions, and a field scale coupled flow and transport model. In the first application, a single parallelizable loop is identified to consume over 97% of the total computational time. With a few lines of OpenMP compiler directives inserted into the code,more » the computational time reduces about ten times on a compute node with 16 cores. The performance is further improved by selectively parallelizing a few more loops. For the field scale application, parallelizable loops in 15 of the 174 subroutines in HGC5 are identified to take more than 99% of the execution time. By adding the preconditioned conjugate gradient solver and BICGSTAB, and using a coloring scheme to separate the elements, nodes, and boundary sides, the subroutines for finite element assembly, soil property update, and boundary condition application are parallelized, resulting in a speedup of about 10 on a 16-core compute node. The Levenberg-Marquardt (LM) algorithm is added into HGC5 with the Jacobian calculation and lambda search parallelized using MPI. With this hybrid approach, compute nodes at the number of adjustable parameters (when the forward difference is used for Jacobian approximation), or twice that number (if the center difference is used), are used to reduce the calibration time from days and weeks to a few hours for the two applications. This approach can be extended to global optimization scheme and Monte Carol analysis where thousands of compute nodes can be efficiently utilized.« less

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

Wang, Jun

Our group has been working with ANL collaborators on the topic bridging the gap between parallel file system and local file system during the course of this project period. We visited Argonne National Lab -- Dr. Robert Ross's group for one week in the past summer 2007. We looked over our current project progress and planned the activities for the incoming years 2008-09. The PI met Dr. Robert Ross several times such as HEC FSIO workshop 08, SC08 and SC10. We explored the opportunities to develop a production system by leveraging our current prototype to (SOGP+PVFS) a new PVFS version.more » We delivered SOGP+PVFS codes to ANL PVFS2 group in 2008.We also talked about exploring a potential project on developing new parallel programming models and runtime systems for data-intensive scalable computing (DISC). The methodology is to evolve MPI towards DISC by incorporating some functions of Google MapReduce parallel programming model. More recently, we are together exploring how to leverage existing works to perform (1) coordination/aggregation of local I/O operations prior to movement over the WAN, (2) efficient bulk data movement over the WAN, (3) latency hiding techniques for latency-intensive operations. Since 2009, we start applying Hadoop/MapReduce to some HEC applications with LANL scientists John Bent and Salman Habib. Another on-going work is to improve checkpoint performance at I/O forwarding Layer for the Road Runner super computer with James Nuetz and Gary Gridder at LANL. Two senior undergraduates from our research group did summer internships about high-performance file and storage system projects in LANL since 2008 for consecutive three years. Both of them are now pursuing Ph.D. degree in our group and will be 4th year in the PhD program in Fall 2011 and go to LANL to advance two above-mentioned works during this winter break. Since 2009, we have been collaborating with several computer scientists (Gary Grider, John bent, Parks Fields, James Nunez, Hsing-Bung Chen, etc) from HPC5 and James Ahrens from Advanced Computing Laboratory in Los Alamos National Laboratory. We hold a weekly conference and/or video meeting on advancing works at two fronts: the hardware/software infrastructure of building large-scale data intensive cluster and research publications. Our group members assist in constructing several onsite LANL data intensive clusters. Two parties have been developing software codes and research papers together using both sides resources.« less