Dependency graph for code analysis on emerging architectures
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shashkov, Mikhail Jurievich; Lipnikov, Konstantin
Direct acyclic dependency (DAG) graph is becoming the standard for modern multi-physics codes.The ideal DAG is the true block-scheme of a multi-physics code. Therefore, it is the convenient object for insitu analysis of the cost of computations and algorithmic bottlenecks related to statistical frequent data motion and dymanical machine state.
Multi-physics CFD simulations in engineering
NASA Astrophysics Data System (ADS)
Yamamoto, Makoto
2013-08-01
Nowadays Computational Fluid Dynamics (CFD) software is adopted as a design and analysis tool in a great number of engineering fields. We can say that single-physics CFD has been sufficiently matured in the practical point of view. The main target of existing CFD software is single-phase flows such as water and air. However, many multi-physics problems exist in engineering. Most of them consist of flow and other physics, and the interactions between different physics are very important. Obviously, multi-physics phenomena are critical in developing machines and processes. A multi-physics phenomenon seems to be very complex, and it is so difficult to be predicted by adding other physics to flow phenomenon. Therefore, multi-physics CFD techniques are still under research and development. This would be caused from the facts that processing speed of current computers is not fast enough for conducting a multi-physics simulation, and furthermore physical models except for flow physics have not been suitably established. Therefore, in near future, we have to develop various physical models and efficient CFD techniques, in order to success multi-physics simulations in engineering. In the present paper, I will describe the present states of multi-physics CFD simulations, and then show some numerical results such as ice accretion and electro-chemical machining process of a three-dimensional compressor blade which were obtained in my laboratory. Multi-physics CFD simulations would be a key technology in near future.
Salko, Robert K.; Schmidt, Rodney C.; Avramova, Maria N.
2014-11-23
This study describes major improvements to the computational infrastructure of the CTF subchannel code so that full-core, pincell-resolved (i.e., one computational subchannel per real bundle flow channel) simulations can now be performed in much shorter run-times, either in stand-alone mode or as part of coupled-code multi-physics calculations. These improvements support the goals of the Department Of Energy Consortium for Advanced Simulation of Light Water Reactors (CASL) Energy Innovation Hub to develop high fidelity multi-physics simulation tools for nuclear energy design and analysis.
Reduced-Order Modeling: New Approaches for Computational Physics
NASA Technical Reports Server (NTRS)
Beran, Philip S.; Silva, Walter A.
2001-01-01
In this paper, we review the development of new reduced-order modeling techniques and discuss their applicability to various problems in computational physics. Emphasis is given to methods ba'sed on Volterra series representations and the proper orthogonal decomposition. Results are reported for different nonlinear systems to provide clear examples of the construction and use of reduced-order models, particularly in the multi-disciplinary field of computational aeroelasticity. Unsteady aerodynamic and aeroelastic behaviors of two- dimensional and three-dimensional geometries are described. Large increases in computational efficiency are obtained through the use of reduced-order models, thereby justifying the initial computational expense of constructing these models and inotivatim,- their use for multi-disciplinary design analysis.
electromagnetics, eddy current, computer codes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gartling, David
TORO Version 4 is designed for finite element analysis of steady, transient and time-harmonic, multi-dimensional, quasi-static problems in electromagnetics. The code allows simulation of electrostatic fields, steady current flows, magnetostatics and eddy current problems in plane or axisymmetric, two-dimensional geometries. TORO is easily coupled to heat conduction and solid mechanics codes to allow multi-physics simulations to be performed.
Optimization of Multi-Fidelity Computer Experiments via the EQIE Criterion
DOE Office of Scientific and Technical Information (OSTI.GOV)
He, Xu; Tuo, Rui; Jeff Wu, C. F.
Computer experiments based on mathematical models are powerful tools for understanding physical processes. This article addresses the problem of kriging-based optimization for deterministic computer experiments with tunable accuracy. Our approach is to use multi- delity computer experiments with increasing accuracy levels and a nonstationary Gaussian process model. We propose an optimization scheme that sequentially adds new computer runs by following two criteria. The first criterion, called EQI, scores candidate inputs with given level of accuracy, and the second criterion, called EQIE, scores candidate combinations of inputs and accuracy. Here, from simulation results and a real example using finite element analysis,more » our method out-performs the expected improvement (EI) criterion which works for single-accuracy experiments.« less
Optimization of Multi-Fidelity Computer Experiments via the EQIE Criterion
He, Xu; Tuo, Rui; Jeff Wu, C. F.
2017-01-31
Computer experiments based on mathematical models are powerful tools for understanding physical processes. This article addresses the problem of kriging-based optimization for deterministic computer experiments with tunable accuracy. Our approach is to use multi- delity computer experiments with increasing accuracy levels and a nonstationary Gaussian process model. We propose an optimization scheme that sequentially adds new computer runs by following two criteria. The first criterion, called EQI, scores candidate inputs with given level of accuracy, and the second criterion, called EQIE, scores candidate combinations of inputs and accuracy. Here, from simulation results and a real example using finite element analysis,more » our method out-performs the expected improvement (EI) criterion which works for single-accuracy experiments.« less
Advanced graphical user interface for multi-physics simulations using AMST
NASA Astrophysics Data System (ADS)
Hoffmann, Florian; Vogel, Frank
2017-07-01
Numerical modelling of particulate matter has gained much popularity in recent decades. Advanced Multi-physics Simulation Technology (AMST) is a state-of-the-art three dimensional numerical modelling technique combining the eX-tended Discrete Element Method (XDEM) with Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) [1]. One major limitation of this code is the lack of a graphical user interface (GUI) meaning that all pre-processing has to be made directly in a HDF5-file. This contribution presents the first graphical pre-processor developed for AMST.
Geant4 Computing Performance Benchmarking and Monitoring
Dotti, Andrea; Elvira, V. Daniel; Folger, Gunter; ...
2015-12-23
Performance evaluation and analysis of large scale computing applications is essential for optimal use of resources. As detector simulation is one of the most compute intensive tasks and Geant4 is the simulation toolkit most widely used in contemporary high energy physics (HEP) experiments, it is important to monitor Geant4 through its development cycle for changes in computing performance and to identify problems and opportunities for code improvements. All Geant4 development and public releases are being profiled with a set of applications that utilize different input event samples, physics parameters, and detector configurations. Results from multiple benchmarking runs are compared tomore » previous public and development reference releases to monitor CPU and memory usage. Observed changes are evaluated and correlated with code modifications. Besides the full summary of call stack and memory footprint, a detailed call graph analysis is available to Geant4 developers for further analysis. The set of software tools used in the performance evaluation procedure, both in sequential and multi-threaded modes, include FAST, IgProf and Open|Speedshop. In conclusion, the scalability of the CPU time and memory performance in multi-threaded application is evaluated by measuring event throughput and memory gain as a function of the number of threads for selected event samples.« less
NASA Technical Reports Server (NTRS)
Thomas, Valerie L.; Koblinsky, Chester J.; Webster, Ferris; Zlotnicki, Victor; Green, James L.
1987-01-01
The Space Physics Analysis Network (SPAN) is a multi-mission, correlative data comparison network which links space and Earth science research and data analysis computers. It provides a common working environment for sharing computer resources, sharing computer peripherals, solving proprietary problems, and providing the potential for significant time and cost savings for correlative data analysis. This is one of a series of discipline-specific SPAN documents which are intended to complement the SPAN primer and SPAN Management documents. Their purpose is to provide the discipline scientists with a comprehensive set of documents to assist in the use of SPAN for discipline specific scientific research.
Design and implementation of space physics multi-model application integration based on web
NASA Astrophysics Data System (ADS)
Jiang, Wenping; Zou, Ziming
With the development of research on space environment and space science, how to develop network online computing environment of space weather, space environment and space physics models for Chinese scientific community is becoming more and more important in recent years. Currently, There are two software modes on space physics multi-model application integrated system (SPMAIS) such as C/S and B/S. the C/S mode which is traditional and stand-alone, demands a team or workshop from many disciplines and specialties to build their own multi-model application integrated system, that requires the client must be deployed in different physical regions when user visits the integrated system. Thus, this requirement brings two shortcomings: reducing the efficiency of researchers who use the models to compute; inconvenience of accessing the data. Therefore, it is necessary to create a shared network resource access environment which could help users to visit the computing resources of space physics models through the terminal quickly for conducting space science research and forecasting spatial environment. The SPMAIS develops high-performance, first-principles in B/S mode based on computational models of the space environment and uses these models to predict "Space Weather", to understand space mission data and to further our understanding of the solar system. the main goal of space physics multi-model application integration system (SPMAIS) is to provide an easily and convenient user-driven online models operating environment. up to now, the SPMAIS have contained dozens of space environment models , including international AP8/AE8 IGRF T96 models and solar proton prediction model geomagnetic transmission model etc. which are developed by Chinese scientists. another function of SPMAIS is to integrate space observation data sets which offers input data for models online high-speed computing. In this paper, service-oriented architecture (SOA) concept that divides system into independent modules according to different business needs is applied to solve the problem of the independence of the physical space between multiple models. The classic MVC(Model View Controller) software design pattern is concerned to build the architecture of space physics multi-model application integrated system. The JSP+servlet+javabean technology is used to integrate the web application programs of space physics multi-model. It solves the problem of multi-user requesting the same job of model computing and effectively balances each server computing tasks. In addition, we also complete follow tasks: establishing standard graphical user interface based on Java Applet application program; Designing the interface between model computing and model computing results visualization; Realizing three-dimensional network visualization without plug-ins; Using Java3D technology to achieve a three-dimensional network scene interaction; Improved ability to interact with web pages and dynamic execution capabilities, including rendering three-dimensional graphics, fonts and color control. Through the design and implementation of the SPMAIS based on Web, we provide an online computing and application runtime environment of space physics multi-model. The practical application improves that researchers could be benefit from our system in space physics research and engineering applications.
Dynamic Fracture Simulations of Explosively Loaded Cylinders
DOE Office of Scientific and Technical Information (OSTI.GOV)
Arthur, Carly W.; Goto, D. M.
2015-11-30
This report documents the modeling results of high explosive experiments investigating dynamic fracture of steel (AerMet® 100 alloy) cylinders. The experiments were conducted at Lawrence Livermore National Laboratory (LLNL) during 2007 to 2008 [10]. A principal objective of this study was to gain an understanding of dynamic material failure through the analysis of hydrodynamic computer code simulations. Two-dimensional and three-dimensional computational cylinder models were analyzed using the ALE3D multi-physics computer code.
Two-Step Multi-Physics Analysis of an Annular Linear Induction Pump for Fission Power Systems
NASA Technical Reports Server (NTRS)
Geng, Steven M.; Reid, Terry V.
2016-01-01
One of the key technologies associated with fission power systems (FPS) is the annular linear induction pump (ALIP). ALIPs are used to circulate liquid-metal fluid for transporting thermal energy from the nuclear reactor to the power conversion device. ALIPs designed and built to date for FPS project applications have not performed up to expectations. A unique, two-step approach was taken toward the multi-physics examination of an ALIP using ANSYS Maxwell 3D and Fluent. This multi-physics approach was developed so that engineers could investigate design variations that might improve pump performance. Of interest was to determine if simple geometric modifications could be made to the ALIP components with the goal of increasing the Lorentz forces acting on the liquid-metal fluid, which in turn would increase pumping capacity. The multi-physics model first calculates the Lorentz forces acting on the liquid metal fluid in the ALIP annulus. These forces are then used in a computational fluid dynamics simulation as (a) internal boundary conditions and (b) source functions in the momentum equations within the Navier-Stokes equations. The end result of the two-step analysis is a predicted pump pressure rise that can be compared with experimental data.
SPAN: Astronomy and astrophysics
NASA Technical Reports Server (NTRS)
Thomas, Valerie L.; Green, James L.; Warren, Wayne H., Jr.; Lopez-Swafford, Brian
1987-01-01
The Space Physics Analysis Network (SPAN) is a multi-mission, correlative data comparison network which links science research and data analysis computers in the U.S., Canada, and Europe. The purpose of this document is to provide Astronomy and Astrophysics scientists, currently reachable on SPAN, with basic information and contacts for access to correlative data bases, star catalogs, and other astrophysic facilities accessible over SPAN.
A Comparative Study of Multi-material Data Structures for Computational Physics Applications
DOE Office of Scientific and Technical Information (OSTI.GOV)
Garimella, Rao Veerabhadra; Robey, Robert W.
The data structures used to represent the multi-material state of a computational physics application can have a drastic impact on the performance of the application. We look at efficient data structures for sparse applications where there may be many materials, but only one or few in most computational cells. We develop simple performance models for use in selecting possible data structures and programming patterns. We verify the analytic models of performance through a small test program of the representative cases.
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.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Runnels, Scott Robert; Bachrach, Harrison Ian; Carlson, Nils
The two primary purposes of LANL’s Computational Physics Student Summer Workshop are (1) To educate graduate and exceptional undergraduate students in the challenges and applications of computational physics of interest to LANL, and (2) Entice their interest toward those challenges. Computational physics is emerging as a discipline in its own right, combining expertise in mathematics, physics, and computer science. The mathematical aspects focus on numerical methods for solving equations on the computer as well as developing test problems with analytical solutions. The physics aspects are very broad, ranging from low-temperature material modeling to extremely high temperature plasma physics, radiation transportmore » and neutron transport. The computer science issues are concerned with matching numerical algorithms to emerging architectures and maintaining the quality of extremely large codes built to perform multi-physics calculations. Although graduate programs associated with computational physics are emerging, it is apparent that the pool of U.S. citizens in this multi-disciplinary field is relatively small and is typically not focused on the aspects that are of primary interest to LANL. Furthermore, more structured foundations for LANL interaction with universities in computational physics is needed; historically interactions rely heavily on individuals’ personalities and personal contacts. Thus a tertiary purpose of the Summer Workshop is to build an educational network of LANL researchers, university professors, and emerging students to advance the field and LANL’s involvement in it.« less
Proceedings 3rd NASA/IEEE Workshop on Formal Approaches to Agent-Based Systems (FAABS-III)
NASA Technical Reports Server (NTRS)
Hinchey, Michael (Editor); Rash, James (Editor); Truszkowski, Walt (Editor); Rouff, Christopher (Editor)
2004-01-01
These preceedings contain 18 papers and 4 poster presentation, covering topics such as: multi-agent systems, agent-based control, formalism, norms, as well as physical and biological models of agent-based systems. Some applications presented in the proceedings include systems analysis, software engineering, computer networks and robot control.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Aly, A.; Avramova, Maria; Ivanov, Kostadin
To correctly describe and predict this hydrogen distribution there is a need for multi-physics coupling to provide accurate three-dimensional azimuthal, radial, and axial temperature distributions in the cladding. Coupled high-fidelity reactor-physics codes with a sub-channel code as well as with a computational fluid dynamics (CFD) tool have been used to calculate detailed temperature distributions. These high-fidelity coupled neutronics/thermal-hydraulics code systems are coupled further with the fuel-performance BISON code with a kernel (module) for hydrogen. Both hydrogen migration and precipitation/dissolution are included in the model. Results from this multi-physics analysis is validated utilizing calculations of hydrogen distribution using models informed bymore » data from hydrogen experiments and PIE data.« less
Analysis of physics-based preconditioning for single-phase subchannel equations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hansel, J. E.; Ragusa, J. C.; Allu, S.
2013-07-01
The (single-phase) subchannel approximations are used throughout nuclear engineering to provide an efficient flow simulation because the computational burden is much smaller than for computational fluid dynamics (CFD) simulations, and empirical relations have been developed and validated to provide accurate solutions in appropriate flow regimes. Here, the subchannel equations have been recast in a residual form suitable for a multi-physics framework. The Eigen spectrum of the Jacobian matrix, along with several potential physics-based preconditioning approaches, are evaluated, and the the potential for improved convergence from preconditioning is assessed. The physics-based preconditioner options include several forms of reduced equations that decouplemore » the subchannels by neglecting crossflow, conduction, and/or both turbulent momentum and energy exchange between subchannels. Eigen-scopy analysis shows that preconditioning moves clusters of eigenvalues away from zero and toward one. A test problem is run with and without preconditioning. Without preconditioning, the solution failed to converge using GMRES, but application of any of the preconditioners allowed the solution to converge. (authors)« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Runnels, Scott Robert; Caldwell, Wendy; Brown, Barton Jed
The two primary purposes of LANL’s Computational Physics Student Summer Workshop are (1) To educate graduate and exceptional undergraduate students in the challenges and applications of computational physics of interest to LANL, and (2) Entice their interest toward those challenges. Computational physics is emerging as a discipline in its own right, combining expertise in mathematics, physics, and computer science. The mathematical aspects focus on numerical methods for solving equations on the computer as well as developing test problems with analytical solutions. The physics aspects are very broad, ranging from low-temperature material modeling to extremely high temperature plasma physics, radiation transportmore » and neutron transport. The computer science issues are concerned with matching numerical algorithms to emerging architectures and maintaining the quality of extremely large codes built to perform multi-physics calculations. Although graduate programs associated with computational physics are emerging, it is apparent that the pool of U.S. citizens in this multi-disciplinary field is relatively small and is typically not focused on the aspects that are of primary interest to LANL. Furthermore, more structured foundations for LANL interaction with universities in computational physics is needed; historically interactions rely heavily on individuals’ personalities and personal contacts. Thus a tertiary purpose of the Summer Workshop is to build an educational network of LANL researchers, university professors, and emerging students to advance the field and LANL’s involvement in it. This report includes both the background for the program and the reports from the students.« less
NASA Astrophysics Data System (ADS)
Zheng, Jiajia; Li, Yancheng; Li, Zhaochun; Wang, Jiong
2015-10-01
This paper presents multi-physics modeling of an MR absorber considering the magnetic hysteresis to capture the nonlinear relationship between the applied current and the generated force under impact loading. The magnetic field, temperature field, and fluid dynamics are represented by the Maxwell equations, conjugate heat transfer equations, and Navier-Stokes equations. These fields are coupled through the apparent viscosity and the magnetic force, both of which in turn depend on the magnetic flux density and the temperature. Based on a parametric study, an inverse Jiles-Atherton hysteresis model is used and implemented for the magnetic field simulation. The temperature rise of the MR fluid in the annular gap caused by core loss (i.e. eddy current loss and hysteresis loss) and fluid motion is computed to investigate the current-force behavior. A group of impulsive tests was performed for the manufactured MR absorber with step exciting currents. The numerical and experimental results showed good agreement, which validates the effectiveness of the proposed multi-physics FEA model.
AEROELASTIC SIMULATION TOOL FOR INFLATABLE BALLUTE AEROCAPTURE
NASA Technical Reports Server (NTRS)
Liever, P. A.; Sheta, E. F.; Habchi, S. D.
2006-01-01
A multidisciplinary analysis tool is under development for predicting the impact of aeroelastic effects on the functionality of inflatable ballute aeroassist vehicles in both the continuum and rarefied flow regimes. High-fidelity modules for continuum and rarefied aerodynamics, structural dynamics, heat transfer, and computational grid deformation are coupled in an integrated multi-physics, multi-disciplinary computing environment. This flexible and extensible approach allows the integration of state-of-the-art, stand-alone NASA and industry leading continuum and rarefied flow solvers and structural analysis codes into a computing environment in which the modules can run concurrently with synchronized data transfer. Coupled fluid-structure continuum flow demonstrations were conducted on a clamped ballute configuration. The feasibility of implementing a DSMC flow solver in the simulation framework was demonstrated, and loosely coupled rarefied flow aeroelastic demonstrations were performed. A NASA and industry technology survey identified CFD, DSMC and structural analysis codes capable of modeling non-linear shape and material response of thin-film inflated aeroshells. The simulation technology will find direct and immediate applications with NASA and industry in ongoing aerocapture technology development programs.
Computational electromagnetics: the physics of smooth versus oscillatory fields.
Chew, W C
2004-03-15
This paper starts by discussing the difference in the physics between solutions to Laplace's equation (static) and Maxwell's equations for dynamic problems (Helmholtz equation). Their differing physical characters are illustrated by how the two fields convey information away from their source point. The paper elucidates the fact that their differing physical characters affect the use of Laplacian field and Helmholtz field in imaging. They also affect the design of fast computational algorithms for electromagnetic scattering problems. Specifically, a comparison is made between fast algorithms developed using wavelets, the simple fast multipole method, and the multi-level fast multipole algorithm for electrodynamics. The impact of the physical characters of the dynamic field on the parallelization of the multi-level fast multipole algorithm is also discussed. The relationship of diagonalization of translators to group theory is presented. Finally, future areas of research for computational electromagnetics are described.
CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences
NASA Technical Reports Server (NTRS)
Slotnick, Jeffrey; Khodadoust, Abdollah; Alonso, Juan; Darmofal, David; Gropp, William; Lurie, Elizabeth; Mavriplis, Dimitri
2014-01-01
This report documents the results of a study to address the long range, strategic planning required by NASA's Revolutionary Computational Aerosciences (RCA) program in the area of computational fluid dynamics (CFD), including future software and hardware requirements for High Performance Computing (HPC). Specifically, the "Vision 2030" CFD study is to provide a knowledge-based forecast of the future computational capabilities required for turbulent, transitional, and reacting flow simulations across a broad Mach number regime, and to lay the foundation for the development of a future framework and/or environment where physics-based, accurate predictions of complex turbulent flows, including flow separation, can be accomplished routinely and efficiently in cooperation with other physics-based simulations to enable multi-physics analysis and design. Specific technical requirements from the aerospace industrial and scientific communities were obtained to determine critical capability gaps, anticipated technical challenges, and impediments to achieving the target CFD capability in 2030. A preliminary development plan and roadmap were created to help focus investments in technology development to help achieve the CFD vision in 2030.
AN OVERVIEW OF REDUCED ORDER MODELING TECHNIQUES FOR SAFETY APPLICATIONS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mandelli, D.; Alfonsi, A.; Talbot, P.
2016-10-01
The RISMC project is developing new advanced simulation-based tools to perform Computational Risk Analysis (CRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermal-hydraulic behavior of the reactors primary and secondary systems, but also external event temporal evolution and component/system ageing. Thus, this is not only a multi-physics problem being addressed, but also a multi-scale problem (both spatial, µm-mm-m, and temporal, seconds-hours-years). As part of the RISMC CRA approach, a large amount of computationally-expensive simulation runs may be required. An important aspect is that even though computational power is growing, themore » overall computational cost of a RISMC analysis using brute-force methods may be not viable for certain cases. A solution that is being evaluated to assist the computational issue is the use of reduced order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RISMC analysis computational cost by decreasing the number of simulation runs; for this analysis improvement we used surrogate models instead of the actual simulation codes. This article focuses on the use of reduced order modeling techniques that can be applied to RISMC analyses in order to generate, analyze, and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (microseconds instead of hours/days).« less
NASA Technical Reports Server (NTRS)
Katz, Daniel S.; Cwik, Tom; Fu, Chuigang; Imbriale, William A.; Jamnejad, Vahraz; Springer, Paul L.; Borgioli, Andrea
2000-01-01
The process of designing and analyzing a multiple-reflector system has traditionally been time-intensive, requiring large amounts of both computational and human time. At many frequencies, a discrete approximation of the radiation integral may be used to model the system. The code which implements this physical optics (PO) algorithm was developed at the Jet Propulsion Laboratory. It analyzes systems of antennas in pairs, and for each pair, the analysis can be computationally time-consuming. Additionally, the antennas must be described using a local coordinate system for each antenna, which makes it difficult to integrate the design into a multi-disciplinary framework in which there is traditionally one global coordinate system, even before considering deforming the antenna as prescribed by external structural and/or thermal factors. Finally, setting up the code to correctly analyze all the antenna pairs in the system can take a fair amount of time, and introduces possible human error. The use of parallel computing to reduce the computational time required for the analysis of a given pair of antennas has been previously discussed. This paper focuses on the other problems mentioned above. It will present a methodology and examples of use of an automated tool that performs the analysis of a complete multiple-reflector system in an integrated multi-disciplinary environment (including CAD modeling, and structural and thermal analysis) at the click of a button. This tool, named MOD Tool (Millimeter-wave Optics Design Tool), has been designed and implemented as a distributed tool, with a client that runs almost identically on Unix, Mac, and Windows platforms, and a server that runs primarily on a Unix workstation and can interact with parallel supercomputers with simple instruction from the user interacting with the client.
Physics Model-Based Scatter Correction in Multi-Source Interior Computed Tomography.
Gong, Hao; Li, Bin; Jia, Xun; Cao, Guohua
2018-02-01
Multi-source interior computed tomography (CT) has a great potential to provide ultra-fast and organ-oriented imaging at low radiation dose. However, X-ray cross scattering from multiple simultaneously activated X-ray imaging chains compromises imaging quality. Previously, we published two hardware-based scatter correction methods for multi-source interior CT. Here, we propose a software-based scatter correction method, with the benefit of no need for hardware modifications. The new method is based on a physics model and an iterative framework. The physics model was derived analytically, and was used to calculate X-ray scattering signals in both forward direction and cross directions in multi-source interior CT. The physics model was integrated to an iterative scatter correction framework to reduce scatter artifacts. The method was applied to phantom data from both Monte Carlo simulations and physical experimentation that were designed to emulate the image acquisition in a multi-source interior CT architecture recently proposed by our team. The proposed scatter correction method reduced scatter artifacts significantly, even with only one iteration. Within a few iterations, the reconstructed images fast converged toward the "scatter-free" reference images. After applying the scatter correction method, the maximum CT number error at the region-of-interests (ROIs) was reduced to 46 HU in numerical phantom dataset and 48 HU in physical phantom dataset respectively, and the contrast-noise-ratio at those ROIs increased by up to 44.3% and up to 19.7%, respectively. The proposed physics model-based iterative scatter correction method could be useful for scatter correction in dual-source or multi-source CT.
Harry Mergler with His Modified Differential Analyzer
1951-06-21
Harry Mergler stands at the control board of a differential analyzer in the new Instrument Research Laboratory at the National Advisory Committee for Aeronautics (NACA) Lewis Flight Propulsion Laboratory. The differential analyzer was a multi-variable analog computation machine devised in 1931 by Massachusetts Institute of Technology researcher and future NACA Committee member Vannevar Bush. The mechanical device could solve computations up to the sixth order, but had to be rewired before each new computation. Mergler modified Bush’s differential analyzer in the late 1940s to calculate droplet trajectories for Lewis’ icing research program. In four days Mergler’s machine could calculate what previously required weeks. NACA Lewis built the Instrument Research Laboratory in 1950 and 1951 to house the large analog computer equipment. The two-story structure also provided offices for the Mechanical Computational Analysis, and Flow Physics sections of the Physics Division. The division had previously operated from the lab’s hangar because of its icing research and flight operations activities. Mergler joined the Instrument Research Section of the Physics Division in 1948 after earning an undergraduate degree in Physics from the Case Institute of Technology. Mergler’s focus was on the synthesis of analog computers with the machine tools used to create compressor and turbine blades for jet engines.
NASA Astrophysics Data System (ADS)
Cao, Chao
2009-03-01
Nano-scale physical phenomena and processes, especially those in electronics, have drawn great attention in the past decade. Experiments have shown that electronic and transport properties of functionalized carbon nanotubes are sensitive to adsorption of gas molecules such as H2, NO2, and NH3. Similar measurements have also been performed to study adsorption of proteins on other semiconductor nano-wires. These experiments suggest that nano-scale systems can be useful for making future chemical and biological sensors. Aiming to understand the physical mechanisms underlying and governing property changes at nano-scale, we start off by investigating, via first-principles method, the electronic structure of Pd-CNT before and after hydrogen adsorption, and continue with coherent electronic transport using non-equilibrium Green’s function techniques combined with density functional theory. Once our results are fully analyzed they can be used to interpret and understand experimental data, with a few difficult issues to be addressed. Finally, we discuss a newly developed multi-scale computing architecture, OPAL, that coordinates simultaneous execution of multiple codes. Inspired by the capabilities of this computing framework, we present a scenario of future modeling and simulation of multi-scale, multi-physical processes.
Physics-Based Computational Algorithm for the Multi-Fluid Plasma Model
2014-06-30
applying it to study laser - 20 Physics-Based Multi-Fluid Plasma Algorithm Shumlak Figure 6: Blended finite element method applied to the species...separation problem in capsule implosions. Number densities and electric field are shown after the laser drive has compressed the multi-fluid plasma and...6 after the laser drive has started the compression. A separation clearly develops. The solution is found using an explicit advance (CFL=1) for the
Study of Solid State Drives performance in PROOF distributed analysis system
NASA Astrophysics Data System (ADS)
Panitkin, S. Y.; Ernst, M.; Petkus, R.; Rind, O.; Wenaus, T.
2010-04-01
Solid State Drives (SSD) is a promising storage technology for High Energy Physics parallel analysis farms. Its combination of low random access time and relatively high read speed is very well suited for situations where multiple jobs concurrently access data located on the same drive. It also has lower energy consumption and higher vibration tolerance than Hard Disk Drive (HDD) which makes it an attractive choice in many applications raging from personal laptops to large analysis farms. The Parallel ROOT Facility - PROOF is a distributed analysis system which allows to exploit inherent event level parallelism of high energy physics data. PROOF is especially efficient together with distributed local storage systems like Xrootd, when data are distributed over computing nodes. In such an architecture the local disk subsystem I/O performance becomes a critical factor, especially when computing nodes use multi-core CPUs. We will discuss our experience with SSDs in PROOF environment. We will compare performance of HDD with SSD in I/O intensive analysis scenarios. In particular we will discuss PROOF system performance scaling with a number of simultaneously running analysis jobs.
Future Directions in Medical Physics: Models, Technology, and Translation to Medicine
NASA Astrophysics Data System (ADS)
Siewerdsen, Jeffrey
The application of physics in medicine has been integral to major advances in diagnostic and therapeutic medicine. Two primary areas represent the mainstay of medical physics research in the last century: in radiation therapy, physicists have propelled advances in conformal radiation treatment and high-precision image guidance; and in diagnostic imaging, physicists have advanced an arsenal of multi-modality imaging that includes CT, MRI, ultrasound, and PET as indispensible tools for noninvasive screening, diagnosis, and assessment of treatment response. In addition to their role in building such technologically rich fields of medicine, physicists have also become integral to daily clinical practice in these areas. The future suggests new opportunities for multi-disciplinary research bridging physics, biology, engineering, and computer science, and collaboration in medical physics carries a strong capacity for identification of significant clinical needs, access to clinical data, and translation of technologies to clinical studies. In radiation therapy, for example, the extraction of knowledge from large datasets on treatment delivery, image-based phenotypes, genomic profile, and treatment outcome will require innovation in computational modeling and connection with medical physics for the curation of large datasets. Similarly in imaging physics, the demand for new imaging technology capable of measuring physical and biological processes over orders of magnitude in scale (from molecules to whole organ systems) and exploiting new contrast mechanisms for greater sensitivity to molecular agents and subtle functional / morphological change will benefit from multi-disciplinary collaboration in physics, biology, and engineering. Also in surgery and interventional radiology, where needs for increased precision and patient safety meet constraints in cost and workflow, development of new technologies for imaging, image registration, and robotic assistance can leverage collaboration in physics, biomedical engineering, and computer science. In each area, there is major opportunity for multi-disciplinary collaboration with medical physics to accelerate the translation of such technologies to clinical use. Research supported by the National Institutes of Health, Siemens Healthcare, and Carestream Health.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schaefer, Bastian; Goedecker, Stefan, E-mail: stefan.goedecker@unibas.ch
2016-07-21
An analysis of the network defined by the potential energy minima of multi-atomic systems and their connectivity via reaction pathways that go through transition states allows us to understand important characteristics like thermodynamic, dynamic, and structural properties. Unfortunately computing the transition states and reaction pathways in addition to the significant energetically low-lying local minima is a computationally demanding task. We here introduce a computationally efficient method that is based on a combination of the minima hopping global optimization method and the insight that uphill barriers tend to increase with increasing structural distances of the educt and product states. This methodmore » allows us to replace the exact connectivity information and transition state energies with alternative and approximate concepts. Without adding any significant additional cost to the minima hopping global optimization approach, this method allows us to generate an approximate network of the minima, their connectivity, and a rough measure for the energy needed for their interconversion. This can be used to obtain a first qualitative idea on important physical and chemical properties by means of a disconnectivity graph analysis. Besides the physical insight obtained by such an analysis, the gained knowledge can be used to make a decision if it is worthwhile or not to invest computational resources for an exact computation of the transition states and the reaction pathways. Furthermore it is demonstrated that the here presented method can be used for finding physically reasonable interconversion pathways that are promising input pathways for methods like transition path sampling or discrete path sampling.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Da Rio, Nicola; Robberto, Massimo, E-mail: ndario@rssd.esa.int
We present the Tool for Astrophysical Data Analysis (TA-DA), a new software aimed to greatly simplify and improve the analysis of stellar photometric data in comparison with theoretical models, and allow the derivation of stellar parameters from multi-band photometry. Its flexibility allows one to address a number of such problems: from the interpolation of stellar models, or sets of stellar physical parameters in general, to the computation of synthetic photometry in arbitrary filters or units; from the analysis of observed color-magnitude diagrams to a Bayesian derivation of stellar parameters (and extinction) based on multi-band data. TA-DA is available as amore » pre-compiled Interactive Data Language widget-based application; its graphical user interface makes it considerably user-friendly. In this paper, we describe the software and its functionalities.« less
High-resolution coupled physics solvers for analysing fine-scale nuclear reactor design problems.
Mahadevan, Vijay S; Merzari, Elia; Tautges, Timothy; Jain, Rajeev; Obabko, Aleksandr; Smith, Michael; Fischer, Paul
2014-08-06
An integrated multi-physics simulation capability for the design and analysis of current and future nuclear reactor models is being investigated, to tightly couple neutron transport and thermal-hydraulics physics under the SHARP framework. Over several years, high-fidelity, validated mono-physics solvers with proven scalability on petascale architectures have been developed independently. Based on a unified component-based architecture, these existing codes can be coupled with a mesh-data backplane and a flexible coupling-strategy-based driver suite to produce a viable tool for analysts. The goal of the SHARP framework is to perform fully resolved coupled physics analysis of a reactor on heterogeneous geometry, in order to reduce the overall numerical uncertainty while leveraging available computational resources. The coupling methodology and software interfaces of the framework are presented, along with verification studies on two representative fast sodium-cooled reactor demonstration problems to prove the usability of the SHARP framework.
High-resolution coupled physics solvers for analysing fine-scale nuclear reactor design problems
Mahadevan, Vijay S.; Merzari, Elia; Tautges, Timothy; Jain, Rajeev; Obabko, Aleksandr; Smith, Michael; Fischer, Paul
2014-01-01
An integrated multi-physics simulation capability for the design and analysis of current and future nuclear reactor models is being investigated, to tightly couple neutron transport and thermal-hydraulics physics under the SHARP framework. Over several years, high-fidelity, validated mono-physics solvers with proven scalability on petascale architectures have been developed independently. Based on a unified component-based architecture, these existing codes can be coupled with a mesh-data backplane and a flexible coupling-strategy-based driver suite to produce a viable tool for analysts. The goal of the SHARP framework is to perform fully resolved coupled physics analysis of a reactor on heterogeneous geometry, in order to reduce the overall numerical uncertainty while leveraging available computational resources. The coupling methodology and software interfaces of the framework are presented, along with verification studies on two representative fast sodium-cooled reactor demonstration problems to prove the usability of the SHARP framework. PMID:24982250
Advances in computational design and analysis of airbreathing propulsion systems
NASA Technical Reports Server (NTRS)
Klineberg, John M.
1989-01-01
The development of commercial and military aircraft depends, to a large extent, on engine manufacturers being able to achieve significant increases in propulsion capability through improved component aerodynamics, materials, and structures. The recent history of propulsion has been marked by efforts to develop computational techniques that can speed up the propulsion design process and produce superior designs. The availability of powerful supercomputers, such as the NASA Numerical Aerodynamic Simulator, and the potential for even higher performance offered by parallel computer architectures, have opened the door to the use of multi-dimensional simulations to study complex physical phenomena in propulsion systems that have previously defied analysis or experimental observation. An overview of several NASA Lewis research efforts is provided that are contributing toward the long-range goal of a numerical test-cell for the integrated, multidisciplinary design, analysis, and optimization of propulsion systems. Specific examples in Internal Computational Fluid Mechanics, Computational Structural Mechanics, Computational Materials Science, and High Performance Computing are cited and described in terms of current capabilities, technical challenges, and future research directions.
NASA Astrophysics Data System (ADS)
Bishay, Peter L.
This study presents a new family of highly accurate and efficient computational methods for modeling the multi-physics of multifunctional materials and composites in the micro-scale named "Multi-Physics Computational Grains" (MPCGs). Each "mathematical grain" has a random polygonal/polyhedral geometrical shape that resembles the natural shapes of the material grains in the micro-scale where each grain is surrounded by an arbitrary number of neighboring grains. The physics that are incorporated in this study include: Linear Elasticity, Electrostatics, Magnetostatics, Piezoelectricity, Piezomagnetism and Ferroelectricity. However, the methods proposed here can be extended to include more physics (thermo-elasticity, pyroelectricity, electric conduction, heat conduction, etc.) in their formulation, different analysis types (dynamics, fracture, fatigue, etc.), nonlinearities, different defect shapes, and some of the 2D methods can also be extended to 3D formulation. We present "Multi-Region Trefftz Collocation Grains" (MTCGs) as a simple and efficient method for direct and inverse problems, "Trefftz-Lekhnitskii Computational Gains" (TLCGs) for modeling porous and composite smart materials, "Hybrid Displacement Computational Grains" (HDCGs) as a general method for modeling multifunctional materials and composites, and finally "Radial-Basis-Functions Computational Grains" (RBFCGs) for modeling functionally-graded materials, magneto-electro-elastic (MEE) materials and the switching phenomena in ferroelectric materials. The first three proposed methods are suitable for direct numerical simulation (DNS) of the micromechanics of smart composite/porous materials with non-symmetrical arrangement of voids/inclusions, and provide minimal effort in meshing and minimal time in computations, since each grain can represent the matrix of a composite and can include a pore or an inclusion. The last three methods provide stiffness matrix in their formulation and hence can be readily implemented in a finite element routine. Several numerical examples are provided to show the ability and accuracy of the proposed methods to determine the effective material properties of different types of piezo-composites, and detect the damage-prone sites in a microstructure under certain loading types. The last method (RBFCGs) is also suitable for modeling the switching phenomena in ferro-materials (ferroelectric, ferromagnetic, etc.) after incorporating a certain nonlinear constitutive model and a switching criterion. Since the interaction between grains during loading cycles has a profound influence on the switching phenomena, it is important to simulate the grains with geometrical shapes that are similar to the real shapes of grains as seen in lab experiments. Hence the use of the 3D RBFCGs, which allow for the presence of all the six variants of the constitutive relations, together with the randomly generated crystallographic axes in each grain, as done in the present study, is considered to be the most realistic model that can be used for the direct mesoscale numerical simulation (DMNS) of polycrystalline ferro-materials.
Philip, Bobby; Berrill, Mark A.; Allu, Srikanth; ...
2015-01-26
We describe an efficient and nonlinearly consistent parallel solution methodology for solving coupled nonlinear thermal transport problems that occur in nuclear reactor applications over hundreds of individual 3D physical subdomains. Efficiency is obtained by leveraging knowledge of the physical domains, the physics on individual domains, and the couplings between them for preconditioning within a Jacobian Free Newton Krylov method. Details of the computational infrastructure that enabled this work, namely the open source Advanced Multi-Physics (AMP) package developed by the authors are described. The details of verification and validation experiments, and parallel performance analysis in weak and strong scaling studies demonstratingmore » the achieved efficiency of the algorithm are presented. Moreover, numerical experiments demonstrate that the preconditioner developed is independent of the number of fuel subdomains in a fuel rod, which is particularly important when simulating different types of fuel rods. Finally, we demonstrate the power of the coupling methodology by considering problems with couplings between surface and volume physics and coupling of nonlinear thermal transport in fuel rods to an external radiation transport code.« less
NASA Astrophysics Data System (ADS)
Avara, Mark J.; Noble, Scott; Shiokawa, Hotaka; Cheng, Roseanne; Campanelli, Manuela; Krolik, Julian H.
2017-08-01
A multi-patch approach to numerical simulations of black hole accretion flows allows one to robustly match numerical grid shape and equations solved to the natural structure of the physical system. For instance, a cartesian gridded patch can be used to cover coordinate singularities on a spherical-polar grid, increasing computational efficiency and better capturing the physical system through natural symmetries. We will present early tests, initial applications, and first results from the new MHD implementation of the PATCHWORK framework.
A Multi-Wavelength View of Planet Forming Regions: Unleashing the Full Power of ALMA
NASA Astrophysics Data System (ADS)
Tazzari, Marco
2017-11-01
Observations at sub-mm/mm wavelengths allow us to probe the solids in the interior of protoplanetary disks, where the bulk of the dust is located and planet formation is expected to occur. However, the actual size of dust grains is still largely unknown due to the limited angular resolution and sensitivity of past observations. The upgraded VLA and, especially, the ALMA observatories provide now powerful tools to resolve grain growth in disks, making the time ripe for developing a multi-wavelength analysis of sub-mm/mm observations of disks. In my contribution I will present a novel analysis method for multi-wavelength ALMA/VLA observations which, based on the self-consistent modelling of the sub-mm/mm disk continuum emission, allows us to constrain simultaneously the size distribution of dust grains and the disk's physical structure (Tazzari et al. 2016, A&A 588 A53). I will also present the recent analysis of spatially resolved ALMA Band 7 observations of a large sample of disks in the Lupus star forming region, from which we obtained a tentative evidence of a disk size-disk mass correlation (Tazzari et al. 2017, arXiv:1707.01499). Finally, I will introduce galario, a GPU Accelerated Library for the Analysis of Radio Interferometry Observations. Fitting the observed visibilities in the uv-plane is computationally demanding: with galario we solve this problem for the current as well as for the full-science ALMA capabilities by leveraging on the computing power of GPUs, providing the computational breakthrough needed to fully exploit the new wealth of information delivered by ALMA.
Plank, G; Prassl, AJ; Augustin, C
2014-01-01
Despite the evident multiphysics nature of the heart – it is an electrically controlled mechanical pump – most modeling studies considered electrophysiology and mechanics in isolation. In no small part, this is due to the formidable modeling challenges involved in building strongly coupled anatomically accurate and biophyically detailed multi-scale multi-physics models of cardiac electro-mechanics. Among the main challenges are the selection of model components and their adjustments to achieve integration into a consistent organ-scale model, dealing with technical difficulties such as the exchange of data between electro-physiological and mechanical model, particularly when using different spatio-temporal grids for discretization, and, finally, the implementation of advanced numerical techniques to deal with the substantial computational. In this study we report on progress made in developing a novel modeling framework suited to tackle these challenges. PMID:24043050
Security analysis of cyber-physical system
NASA Astrophysics Data System (ADS)
Li, Bo; Zhang, Lichen
2017-05-01
In recent years, Cyber-Physical System (CPS) has become an important research direction of academic circles and scientific and technological circles at home and abroad, is considered to be following the third wave of world information technology after the computer, the Internet. PS is a multi-dimensional, heterogeneous, deep integration of open systems, Involving the computer, communication, control and other disciplines of knowledge. As the various disciplines in the research theory and methods are significantly different, so the application of CPS has brought great challenges. This paper introduces the definition and characteristics of CPS, analyzes the current situation of CPS, analyzes the security threats faced by CPS, and gives the security solution for security threats. It also discusses CPS-specific security technology, to promote the healthy development of CPS in information security.
NASA Technical Reports Server (NTRS)
Haimes, Robert; Follen, Gregory J.
1998-01-01
CAPRI is a CAD-vendor neutral application programming interface designed for the construction of analysis and design systems. By allowing access to the geometry from within all modules (grid generators, solvers and post-processors) such tasks as meshing on the actual surfaces, node enrichment by solvers and defining which mesh faces are boundaries (for the solver and visualization system) become simpler. The overall reliance on file 'standards' is minimized. This 'Geometry Centric' approach makes multi-physics (multi-disciplinary) analysis codes much easier to build. By using the shared (coupled) surface as the foundation, CAPRI provides a single call to interpolate grid-node based data from the surface discretization in one volume to another. Finally, design systems are possible where the results can be brought back into the CAD system (and therefore manufactured) because all geometry construction and modification are performed using the CAD system's geometry kernel.
Petascale computation of multi-physics seismic simulations
NASA Astrophysics Data System (ADS)
Gabriel, Alice-Agnes; Madden, Elizabeth H.; Ulrich, Thomas; Wollherr, Stephanie; Duru, Kenneth C.
2017-04-01
Capturing the observed complexity of earthquake sources in concurrence with seismic wave propagation simulations is an inherently multi-scale, multi-physics problem. In this presentation, we present simulations of earthquake scenarios resolving high-detail dynamic rupture evolution and high frequency ground motion. The simulations combine a multitude of representations of model complexity; such as non-linear fault friction, thermal and fluid effects, heterogeneous fault stress and fault strength initial conditions, fault curvature and roughness, on- and off-fault non-elastic failure to capture dynamic rupture behavior at the source; and seismic wave attenuation, 3D subsurface structure and bathymetry impacting seismic wave propagation. Performing such scenarios at the necessary spatio-temporal resolution requires highly optimized and massively parallel simulation tools which can efficiently exploit HPC facilities. Our up to multi-PetaFLOP simulations are performed with SeisSol (www.seissol.org), an open-source software package based on an ADER-Discontinuous Galerkin (DG) scheme solving the seismic wave equations in velocity-stress formulation in elastic, viscoelastic, and viscoplastic media with high-order accuracy in time and space. Our flux-based implementation of frictional failure remains free of spurious oscillations. Tetrahedral unstructured meshes allow for complicated model geometry. SeisSol has been optimized on all software levels, including: assembler-level DG kernels which obtain 50% peak performance on some of the largest supercomputers worldwide; an overlapping MPI-OpenMP parallelization shadowing the multiphysics computations; usage of local time stepping; parallel input and output schemes and direct interfaces to community standard data formats. All these factors enable aim to minimise the time-to-solution. The results presented highlight the fact that modern numerical methods and hardware-aware optimization for modern supercomputers are essential to further our understanding of earthquake source physics and complement both physic-based ground motion research and empirical approaches in seismic hazard analysis. Lastly, we will conclude with an outlook on future exascale ADER-DG solvers for seismological applications.
NASA Technical Reports Server (NTRS)
Streett, C. L.; Lockard, D. P.; Singer, B. A.; Khorrami, M. R.; Choudhari, M. M.
2003-01-01
The LaRC investigative process for airframe noise has proven to be a useful guide for elucidation of the physics of flow-induced noise generation over the last five years. This process, relying on a close interplay between experiment and computation, is described and demonstrated here on the archetypal problem of flap-edge noise. Some detailed results from both experiment and computation are shown to illustrate the process, and a description of the multi-source physics seen in this problem is conjectured.
CPMIP: measurements of real computational performance of Earth system models in CMIP6
NASA Astrophysics Data System (ADS)
Balaji, Venkatramani; Maisonnave, Eric; Zadeh, Niki; Lawrence, Bryan N.; Biercamp, Joachim; Fladrich, Uwe; Aloisio, Giovanni; Benson, Rusty; Caubel, Arnaud; Durachta, Jeffrey; Foujols, Marie-Alice; Lister, Grenville; Mocavero, Silvia; Underwood, Seth; Wright, Garrett
2017-01-01
A climate model represents a multitude of processes on a variety of timescales and space scales: a canonical example of multi-physics multi-scale modeling. The underlying climate system is physically characterized by sensitive dependence on initial conditions, and natural stochastic variability, so very long integrations are needed to extract signals of climate change. Algorithms generally possess weak scaling and can be I/O and/or memory-bound. Such weak-scaling, I/O, and memory-bound multi-physics codes present particular challenges to computational performance. Traditional metrics of computational efficiency such as performance counters and scaling curves do not tell us enough about real sustained performance from climate models on different machines. They also do not provide a satisfactory basis for comparative information across models. codes present particular challenges to computational performance. We introduce a set of metrics that can be used for the study of computational performance of climate (and Earth system) models. These measures do not require specialized software or specific hardware counters, and should be accessible to anyone. They are independent of platform and underlying parallel programming models. We show how these metrics can be used to measure actually attained performance of Earth system models on different machines, and identify the most fruitful areas of research and development for performance engineering. codes present particular challenges to computational performance. We present results for these measures for a diverse suite of models from several modeling centers, and propose to use these measures as a basis for a CPMIP, a computational performance model intercomparison project (MIP).
Design of a Modular Monolithic Implicit Solver for Multi-Physics Applications
NASA Technical Reports Server (NTRS)
Carton De Wiart, Corentin; Diosady, Laslo T.; Garai, Anirban; Burgess, Nicholas; Blonigan, Patrick; Ekelschot, Dirk; Murman, Scott M.
2018-01-01
The design of a modular multi-physics high-order space-time finite-element framework is presented together with its extension to allow monolithic coupling of different physics. One of the main objectives of the framework is to perform efficient high- fidelity simulations of capsule/parachute systems. This problem requires simulating multiple physics including, but not limited to, the compressible Navier-Stokes equations, the dynamics of a moving body with mesh deformations and adaptation, the linear shell equations, non-re effective boundary conditions and wall modeling. The solver is based on high-order space-time - finite element methods. Continuous, discontinuous and C1-discontinuous Galerkin methods are implemented, allowing one to discretize various physical models. Tangent and adjoint sensitivity analysis are also targeted in order to conduct gradient-based optimization, error estimation, mesh adaptation, and flow control, adding another layer of complexity to the framework. The decisions made to tackle these challenges are presented. The discussion focuses first on the "single-physics" solver and later on its extension to the monolithic coupling of different physics. The implementation of different physics modules, relevant to the capsule/parachute system, are also presented. Finally, examples of coupled computations are presented, paving the way to the simulation of the full capsule/parachute system.
Progress Towards a Rad-Hydro Code for Modern Computing Architectures LA-UR-10-02825
NASA Astrophysics Data System (ADS)
Wohlbier, J. G.; Lowrie, R. B.; Bergen, B.; Calef, M.
2010-11-01
We are entering an era of high performance computing where data movement is the overwhelming bottleneck to scalable performance, as opposed to the speed of floating-point operations per processor. All multi-core hardware paradigms, whether heterogeneous or homogeneous, be it the Cell processor, GPGPU, or multi-core x86, share this common trait. In multi-physics applications such as inertial confinement fusion or astrophysics, one may be solving multi-material hydrodynamics with tabular equation of state data lookups, radiation transport, nuclear reactions, and charged particle transport in a single time cycle. The algorithms are intensely data dependent, e.g., EOS, opacity, nuclear data, and multi-core hardware memory restrictions are forcing code developers to rethink code and algorithm design. For the past two years LANL has been funding a small effort referred to as Multi-Physics on Multi-Core to explore ideas for code design as pertaining to inertial confinement fusion and astrophysics applications. The near term goals of this project are to have a multi-material radiation hydrodynamics capability, with tabular equation of state lookups, on cartesian and curvilinear block structured meshes. In the longer term we plan to add fully implicit multi-group radiation diffusion and material heat conduction, and block structured AMR. We will report on our progress to date.
Computational analysis of a multistage axial compressor
NASA Astrophysics Data System (ADS)
Mamidoju, Chaithanya
Turbomachines are used extensively in Aerospace, Power Generation, and Oil & Gas Industries. Efficiency of these machines is often an important factor and has led to the continuous effort to improve the design to achieve better efficiency. The axial flow compressor is a major component in a gas turbine with the turbine's overall performance depending strongly on compressor performance. Traditional analysis of axial compressors involves throughflow calculations, isolated blade passage analysis, Quasi-3D blade-to-blade analysis, single-stage (rotor-stator) analysis, and multi-stage analysis involving larger design cycles. In the current study, the detailed flow through a 15 stage axial compressor is analyzed using a 3-D Navier Stokes CFD solver in a parallel computing environment. Methodology is described for steady state (frozen rotor stator) analysis of one blade passage per component. Various effects such as mesh type and density, boundary conditions, tip clearance and numerical issues such as turbulence model choice, advection model choice, and parallel processing performance are analyzed. A high sensitivity of the predictions to the above was found. Physical explanation to the flow features observed in the computational study are given. The total pressure rise verses mass flow rate was computed.
A multi-scale model for geared transmission aero-thermodynamics
NASA Astrophysics Data System (ADS)
McIntyre, Sean M.
A multi-scale, multi-physics computational tool for the simulation of high-per- formance gearbox aero-thermodynamics was developed and applied to equilibrium and pathological loss-of-lubrication performance simulation. The physical processes at play in these systems include multiphase compressible ow of the air and lubricant within the gearbox, meshing kinematics and tribology, as well as heat transfer by conduction, and free and forced convection. These physics are coupled across their representative space and time scales in the computational framework developed in this dissertation. These scales span eight orders of magnitude, from the thermal response of the full gearbox O(100 m; 10 2 s), through effects at the tooth passage time scale O(10-2 m; 10-4 s), down to tribological effects on the meshing gear teeth O(10-6 m; 10-6 s). Direct numerical simulation of these coupled physics and scales is intractable. Accordingly, a scale-segregated simulation strategy was developed by partitioning and treating the contributing physical mechanisms as sub-problems, each with associated space and time scales, and appropriate coupling mechanisms. These are: (1) the long time scale thermal response of the system, (2) the multiphase (air, droplets, and film) aerodynamic flow and convective heat transfer within the gearbox, (3) the high-frequency, time-periodic thermal effects of gear tooth heating while in mesh and its subsequent cooling through the rest of rotation, (4) meshing effects including tribology and contact mechanics. The overarching goal of this dissertation was to develop software and analysis procedures for gearbox loss-of-lubrication performance. To accommodate these four physical effects and their coupling, each is treated in the CFD code as a sub problem. These physics modules are coupled algorithmically. Specifically, the high- frequency conduction analysis derives its local heat transfer coefficient and near-wall air temperature boundary conditions from a quasi-steady cyclic-symmetric simulation of the internal flow. This high-frequency conduction solution is coupled directly with a model for the meshing friction, developed by a collaborator, which was adapted for use in a finite-volume CFD code. The local surface heat flux on solid surfaces is calculated by time-averaging the heat flux in the high-frequency analysis. This serves as a fixed-flux boundary condition in the long time scale conduction module. The temperature distribution from this long time scale heat transfer calculation serves as a boundary condition for the internal convection simulation, and as the initial condition for the high-frequency heat transfer module. Using this multi-scale model, simulations were performed for equilibrium and loss-of-lubrication operation of the NASA Glenn Research Center test stand. Results were compared with experimental measurements. In addition to the multi-scale model itself, several other specific contributions were made. Eulerian models for droplets and wall-films were developed and im- plemented in the CFD code. A novel approach to retaining liquid film on the solid surfaces, and strategies for its mass exchange with droplets, were developed and verified. Models for interfacial transfer between droplets and wall-film were implemented, and include the effects of droplet deposition, splashing, bouncing, as well as film breakup. These models were validated against airfoil data. To mitigate the observed slow convergence of CFD simulations of the enclosed aerodynamic flows within gearboxes, Fourier stability analysis was applied to the SIMPLE-C fractional-step algorithm. From this, recommendations to accelerate the convergence rate through enhanced pressure-velocity coupling were made. These were shown to be effective. A fast-running finite-volume reduced-order-model of the gearbox aero-thermo- dynamics was developed, and coupled with the tribology model to investigate the sensitivity of loss-of-lubrication predictions to various model and physical param- eters. This sensitivity study was instrumental in guiding efforts toward improving the accuracy of the multi-scale model without undue increase in computational cost. In addition, the reduced-order model is now used extensively by a collaborator in tribology model development and testing. Experimental measurements of high-speed gear windage in partially and fully- shrouded configurations were performed to supplement the paucity of available validation data. This measurement program provided measurements of windage loss for a gear of design-relevant size and operating speed, as well as guidance for increasing the accuracy of future measurements.
High-resolution coupled physics solvers for analysing fine-scale nuclear reactor design problems
Mahadevan, Vijay S.; Merzari, Elia; Tautges, Timothy; ...
2014-06-30
An integrated multi-physics simulation capability for the design and analysis of current and future nuclear reactor models is being investigated, to tightly couple neutron transport and thermal-hydraulics physics under the SHARP framework. Over several years, high-fidelity, validated mono-physics solvers with proven scalability on petascale architectures have been developed independently. Based on a unified component-based architecture, these existing codes can be coupled with a mesh-data backplane and a flexible coupling-strategy-based driver suite to produce a viable tool for analysts. The goal of the SHARP framework is to perform fully resolved coupled physics analysis of a reactor on heterogeneous geometry, in ordermore » to reduce the overall numerical uncertainty while leveraging available computational resources. Finally, the coupling methodology and software interfaces of the framework are presented, along with verification studies on two representative fast sodium-cooled reactor demonstration problems to prove the usability of the SHARP framework.« less
Optimization of coupled multiphysics methodology for safety analysis of pebble bed modular reactor
NASA Astrophysics Data System (ADS)
Mkhabela, Peter Tshepo
The research conducted within the framework of this PhD thesis is devoted to the high-fidelity multi-physics (based on neutronics/thermal-hydraulics coupling) analysis of Pebble Bed Modular Reactor (PBMR), which is a High Temperature Reactor (HTR). The Next Generation Nuclear Plant (NGNP) will be a HTR design. The core design and safety analysis methods are considerably less developed and mature for HTR analysis than those currently used for Light Water Reactors (LWRs). Compared to LWRs, the HTR transient analysis is more demanding since it requires proper treatment of both slower and much longer transients (of time scale in hours and days) and fast and short transients (of time scale in minutes and seconds). There is limited operation and experimental data available for HTRs for validation of coupled multi-physics methodologies. This PhD work developed and verified reliable high fidelity coupled multi-physics models subsequently implemented in robust, efficient, and accurate computational tools to analyse the neutronics and thermal-hydraulic behaviour for design optimization and safety evaluation of PBMR concept The study provided a contribution to a greater accuracy of neutronics calculations by including the feedback from thermal hydraulics driven temperature calculation and various multi-physics effects that can influence it. Consideration of the feedback due to the influence of leakage was taken into account by development and implementation of improved buckling feedback models. Modifications were made in the calculation procedure to ensure that the xenon depletion models were accurate for proper interpolation from cross section tables. To achieve this, the NEM/THERMIX coupled code system was developed to create the system that is efficient and stable over the duration of transient calculations that last over several tens of hours. Another achievement of the PhD thesis was development and demonstration of full-physics, three-dimensional safety analysis methodology for the PBMR to provide reference solutions. Investigation of different aspects of the coupled methodology and development of efficient kinetics treatment for the PBMR were carried out, which accounts for all feedback phenomena in an efficient manner. The OECD/NEA PBMR-400 coupled code benchmark was used as a test matrix for the proposed investigations. The integrated thermal-hydraulics and neutronics (multi-physics) methods were extended to enable modeling of a wider range of transients pertinent to the PBMR. First, the effect of the spatial mapping schemes (spatial coupling) was studied and quantified for different types of transients, which resulted in implementation of improved mapping methodology based on user defined criteria. The second aspect that was studied and optimized is the temporal coupling and meshing schemes between the neutronics and thermal-hydraulics time step selection algorithms. The coupled code convergence was achieved supplemented by application of methods to accelerate it. Finally, the modeling of all feedback phenomena in PBMRs was investigated and a novel treatment of cross-section dependencies was introduced for improving the representation of cross-section variations. The added benefit was that in the process of studying and improving the coupled multi-physics methodology more insight was gained into the physics and dynamics of PBMR, which will help also to optimize the PBMR design and improve its safety. One unique contribution of the PhD research is the investigation of the importance of the correct representation of the three-dimensional (3-D) effects in the PBMR analysis. The performed studies demonstrated that explicit 3-D modeling of control rod movement is superior and removes the errors associated with the grey curtain (2-D homogenized) approximation.
Exascale computing and what it means for shock physics
NASA Astrophysics Data System (ADS)
Germann, Timothy
2015-06-01
The U.S. Department of Energy is preparing to launch an Exascale Computing Initiative, to address the myriad challenges required to deploy and effectively utilize an exascale-class supercomputer (i.e., one capable of performing 1018 operations per second) in the 2023 timeframe. Since physical (power dissipation) requirements limit clock rates to at most a few GHz, this will necessitate the coordination of on the order of a billion concurrent operations, requiring sophisticated system and application software, and underlying mathematical algorithms, that may differ radically from traditional approaches. Even at the smaller workstation or cluster level of computation, the massive concurrency and heterogeneity within each processor will impact computational scientists. Through the multi-institutional, multi-disciplinary Exascale Co-design Center for Materials in Extreme Environments (ExMatEx), we have initiated an early and deep collaboration between domain (computational materials) scientists, applied mathematicians, computer scientists, and hardware architects, in order to establish the relationships between algorithms, software stacks, and architectures needed to enable exascale-ready materials science application codes within the next decade. In my talk, I will discuss these challenges, and what it will mean for exascale-era electronic structure, molecular dynamics, and engineering-scale simulations of shock-compressed condensed matter. In particular, we anticipate that the emerging hierarchical, heterogeneous architectures can be exploited to achieve higher physical fidelity simulations using adaptive physics refinement. This work is supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research.
Reduced Order Model Implementation in the Risk-Informed Safety Margin Characterization Toolkit
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mandelli, Diego; Smith, Curtis L.; Alfonsi, Andrea
2015-09-01
The RISMC project aims to develop new advanced simulation-based tools to perform Probabilistic Risk Analysis (PRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermo-hydraulic behavior of the reactor primary and secondary systems but also external events temporal evolution and components/system ageing. Thus, this is not only a multi-physics problem but also a multi-scale problem (both spatial, µm-mm-m, and temporal, ms-s-minutes-years). As part of the RISMC PRA approach, a large amount of computationally expensive simulation runs are required. An important aspect is that even though computational power is regularly growing, themore » overall computational cost of a RISMC analysis may be not viable for certain cases. A solution that is being evaluated is the use of reduce order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RICM analysis computational cost by decreasing the number of simulations runs to perform and employ surrogate models instead of the actual simulation codes. This report focuses on the use of reduced order modeling techniques that can be applied to any RISMC analysis to generate, analyze and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (µs instead of hours/days). We apply reduced order and surrogate modeling techniques to several RISMC types of analyses using RAVEN and RELAP-7 and show the advantages that can be gained.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fu, Pengchen; Settgast, Randolph R.; Johnson, Scott M.
2014-12-17
GEOS is a massively parallel, multi-physics simulation application utilizing high performance computing (HPC) to address subsurface reservoir stimulation activities with the goal of optimizing current operations and evaluating innovative stimulation methods. GEOS enables coupling of di erent solvers associated with the various physical processes occurring during reservoir stimulation in unique and sophisticated ways, adapted to various geologic settings, materials and stimulation methods. Developed at the Lawrence Livermore National Laboratory (LLNL) as a part of a Laboratory-Directed Research and Development (LDRD) Strategic Initiative (SI) project, GEOS represents the culmination of a multi-year ongoing code development and improvement e ort that hasmore » leveraged existing code capabilities and sta expertise to design new computational geosciences software.« less
RELAP-7 Software Verification and Validation Plan
DOE Office of Scientific and Technical Information (OSTI.GOV)
Smith, Curtis L.; Choi, Yong-Joon; Zou, Ling
This INL plan comprehensively describes the software for RELAP-7 and documents the software, interface, and software design requirements for the application. The plan also describes the testing-based software verification and validation (SV&V) process—a set of specially designed software models used to test RELAP-7. The RELAP-7 (Reactor Excursion and Leak Analysis Program) code is a nuclear reactor system safety analysis code being developed at Idaho National Laboratory (INL). The code is based on the INL’s modern scientific software development framework – MOOSE (Multi-Physics Object-Oriented Simulation Environment). The overall design goal of RELAP-7 is to take advantage of the previous thirty yearsmore » of advancements in computer architecture, software design, numerical integration methods, and physical models. The end result will be a reactor systems analysis capability that retains and improves upon RELAP5’s capability and extends the analysis capability for all reactor system simulation scenarios.« less
XPATCH: a high-frequency electromagnetic scattering prediction code using shooting and bouncing rays
NASA Astrophysics Data System (ADS)
Hazlett, Michael; Andersh, Dennis J.; Lee, Shung W.; Ling, Hao; Yu, C. L.
1995-06-01
This paper describes an electromagnetic computer prediction code for generating radar cross section (RCS), time domain signatures, and synthetic aperture radar (SAR) images of realistic 3-D vehicles. The vehicle, typically an airplane or a ground vehicle, is represented by a computer-aided design (CAD) file with triangular facets, curved surfaces, or solid geometries. The computer code, XPATCH, based on the shooting and bouncing ray technique, is used to calculate the polarimetric radar return from the vehicles represented by these different CAD files. XPATCH computes the first-bounce physical optics plus the physical theory of diffraction contributions and the multi-bounce ray contributions for complex vehicles with materials. It has been found that the multi-bounce contributions are crucial for many aspect angles of all classes of vehicles. Without the multi-bounce calculations, the radar return is typically 10 to 15 dB too low. Examples of predicted range profiles, SAR imagery, and radar cross sections (RCS) for several different geometries are compared with measured data to demonstrate the quality of the predictions. The comparisons are from the UHF through the Ka frequency ranges. Recent enhancements to XPATCH for MMW applications and target Doppler predictions are also presented.
NASA Astrophysics Data System (ADS)
Harfst, S.; Portegies Zwart, S.; McMillan, S.
2008-12-01
We present MUSE, a software framework for combining existing computational tools from different astrophysical domains into a single multi-physics, multi-scale application. MUSE facilitates the coupling of existing codes written in different languages by providing inter-language tools and by specifying an interface between each module and the framework that represents a balance between generality and computational efficiency. This approach allows scientists to use combinations of codes to solve highly-coupled problems without the need to write new codes for other domains or significantly alter their existing codes. MUSE currently incorporates the domains of stellar dynamics, stellar evolution and stellar hydrodynamics for studying generalized stellar systems. We have now reached a ``Noah's Ark'' milestone, with (at least) two available numerical solvers for each domain. MUSE can treat multi-scale and multi-physics systems in which the time- and size-scales are well separated, like simulating the evolution of planetary systems, small stellar associations, dense stellar clusters, galaxies and galactic nuclei. In this paper we describe two examples calculated using MUSE: the merger of two galaxies and an N-body simulation with live stellar evolution. In addition, we demonstrate an implementation of MUSE on a distributed computer which may also include special-purpose hardware, such as GRAPEs or GPUs, to accelerate computations. The current MUSE code base is publicly available as open source at http://muse.li.
Computing Properties of Hadrons, Nuclei and Nuclear Matter from Quantum Chromodynamics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Savage, Martin J.
This project was part of a coordinated software development effort which the nuclear physics lattice QCD community pursues in order to ensure that lattice calculations can make optimal use of present, and forthcoming leadership-class and dedicated hardware, including those of the national laboratories, and prepares for the exploitation of future computational resources in the exascale era. The UW team improved and extended software libraries used in lattice QCD calculations related to multi-nucleon systems, enhanced production running codes related to load balancing multi-nucleon production on large-scale computing platforms, and developed SQLite (addressable database) interfaces to efficiently archive and analyze multi-nucleon datamore » and developed a Mathematica interface for the SQLite databases.« less
Multi-physics optimization of three-dimensional microvascular polymeric components
NASA Astrophysics Data System (ADS)
Aragón, Alejandro M.; Saksena, Rajat; Kozola, Brian D.; Geubelle, Philippe H.; Christensen, Kenneth T.; White, Scott R.
2013-01-01
This work discusses the computational design of microvascular polymeric materials, which aim at mimicking the behavior found in some living organisms that contain a vascular system. The optimization of the topology of the embedded three-dimensional microvascular network is carried out by coupling a multi-objective constrained genetic algorithm with a finite-element based physics solver, the latter validated through experiments. The optimization is carried out on multiple conflicting objective functions, namely the void volume fraction left by the network, the energy required to drive the fluid through the network and the maximum temperature when the material is subjected to thermal loads. The methodology presented in this work results in a viable alternative for the multi-physics optimization of these materials for active-cooling applications.
Han, Lei; Wulie, Buzha; Yang, Yiling; Wang, Hongqing
2015-01-05
This study investigated a novel method of fusing visible (VIS) and infrared (IR) images with the major objective of obtaining higher-resolution IR images. Most existing image fusion methods focus only on visual performance and many fail to consider the thermal physical properties of the IR images, leading to spectral distortion in the fused image. In this study, we use the IR thermal physical property to correct the VIS image directly. Specifically, the Stefan-Boltzmann Law is used as a strong constraint to modulate the VIS image, such that the fused result shows a similar level of regional thermal energy as the original IR image, while preserving the high-resolution structural features from the VIS image. This method is an improvement over our previous study, which required VIS-IR multi-wavelet fusion before the same correction method was applied. The results of experiments show that applying this correction to the VIS image directly without multi-resolution analysis (MRA) processing achieves similar results, but is considerably more computationally efficient, thereby providing a new perspective on VIS and IR image fusion.
Han, Lei; Wulie, Buzha; Yang, Yiling; Wang, Hongqing
2015-01-01
This study investigated a novel method of fusing visible (VIS) and infrared (IR) images with the major objective of obtaining higher-resolution IR images. Most existing image fusion methods focus only on visual performance and many fail to consider the thermal physical properties of the IR images, leading to spectral distortion in the fused image. In this study, we use the IR thermal physical property to correct the VIS image directly. Specifically, the Stefan-Boltzmann Law is used as a strong constraint to modulate the VIS image, such that the fused result shows a similar level of regional thermal energy as the original IR image, while preserving the high-resolution structural features from the VIS image. This method is an improvement over our previous study, which required VIS-IR multi-wavelet fusion before the same correction method was applied. The results of experiments show that applying this correction to the VIS image directly without multi-resolution analysis (MRA) processing achieves similar results, but is considerably more computationally efficient, thereby providing a new perspective on VIS and IR image fusion. PMID:25569749
Terascale Visualization: Multi-resolution Aspirin for Big-Data Headaches
NASA Astrophysics Data System (ADS)
Duchaineau, Mark
2001-06-01
Recent experience on the Accelerated Strategic Computing Initiative (ASCI) computers shows that computational physicists are successfully producing a prodigious collection of numbers on several thousand processors. But with this wealth of numbers comes an unprecedented difficulty in processing and moving them to provide useful insight and analysis. In this talk, a few simulations are highlighted where recent advancements in multiple-resolution mathematical representations and algorithms have provided some hope of seeing most of the physics of interest while keeping within the practical limits of the post-simulation storage and interactive data-exploration resources. A whole host of visualization research activities was spawned by the 1999 Gordon Bell Prize-winning computation of a shock-tube experiment showing Richtmyer-Meshkov turbulent instabilities. This includes efforts for the entire data pipeline from running simulation to interactive display: wavelet compression of field data, multi-resolution volume rendering and slice planes, out-of-core extraction and simplification of mixing-interface surfaces, shrink-wrapping to semi-regularize the surfaces, semi-structured surface wavelet compression, and view-dependent display-mesh optimization. More recently on the 12 TeraOps ASCI platform, initial results from a 5120-processor, billion-atom molecular dynamics simulation showed that 30-to-1 reductions in storage size can be achieved with no human-observable errors for the analysis required in simulations of supersonic crack propagation. This made it possible to store the 25 trillion bytes worth of simulation numbers in the available storage, which was under 1 trillion bytes. While multi-resolution methods and related systems are still in their infancy, for the largest-scale simulations there is often no other choice should the science require detailed exploration of the results.
NASA Astrophysics Data System (ADS)
Romanelli, Gherardo; Mignone, Andrea; Cervone, Angelo
2017-10-01
Pulsed fusion propulsion might finally revolutionise manned space exploration by providing an affordable and relatively fast access to interplanetary destinations. However, such systems are still in an early development phase and one of the key areas requiring further investigations is the operation of the magnetic nozzle, the device meant to exploit the fusion energy and generate thrust. One of the last pulsed fusion magnetic nozzle design is the so called multi-coil parabolic reaction chamber: the reaction is thereby ignited at the focus of an open parabolic chamber, enclosed by a series of coaxial superconducting coils that apply a magnetic field. The field, beside confining the reaction and preventing any contact between hot fusion plasma and chamber structure, is also meant to reflect the explosion and push plasma out of the rocket. Reflection is attained thanks to electric currents induced in conductive skin layers that cover each of the coils, the change of plasma axial momentum generates thrust in reaction. This working principle has yet to be extensively verified and computational Magneto-Hydro Dynamics (MHD) is a viable option to achieve that. This work is one of the first detailed ideal-MHD analysis of a multi-coil parabolic reaction chamber of this kind and has been completed employing PLUTO, a freely distributed computational code developed at the Physics Department of the University of Turin. The results are thus a preliminary verification of the chamber's performance. Nonetheless, plasma leakage through the chamber structure has been highlighted. Therefore, further investigations are required to validate the chamber design. Implementing a more accurate physical model (e.g. Hall-MHD or relativistic-MHD) is thus mandatory, and PLUTO shows the capabilities to achieve that.
NASA Astrophysics Data System (ADS)
Slaughter, A. E.; Permann, C.; Peterson, J. W.; Gaston, D.; Andrs, D.; Miller, J.
2014-12-01
The Idaho National Laboratory (INL)-developed Multiphysics Object Oriented Simulation Environment (MOOSE; www.mooseframework.org), is an open-source, parallel computational framework for enabling the solution of complex, fully implicit multiphysics systems. MOOSE provides a set of computational tools that scientists and engineers can use to create sophisticated multiphysics simulations. Applications built using MOOSE have computed solutions for chemical reaction and transport equations, computational fluid dynamics, solid mechanics, heat conduction, mesoscale materials modeling, geomechanics, and others. To facilitate the coupling of diverse and highly-coupled physical systems, MOOSE employs the Jacobian-free Newton-Krylov (JFNK) method when solving the coupled nonlinear systems of equations arising in multiphysics applications. The MOOSE framework is written in C++, and leverages other high-quality, open-source scientific software packages such as LibMesh, Hypre, and PETSc. MOOSE uses a "hybrid parallel" model which combines both shared memory (thread-based) and distributed memory (MPI-based) parallelism to ensure efficient resource utilization on a wide range of computational hardware. MOOSE-based applications are inherently modular, which allows for simulation expansion (via coupling of additional physics modules) and the creation of multi-scale simulations. Any application developed with MOOSE supports running (in parallel) any other MOOSE-based application. Each application can be developed independently, yet easily communicate with other applications (e.g., conductivity in a slope-scale model could be a constant input, or a complete phase-field micro-structure simulation) without additional code being written. This method of development has proven effective at INL and expedites the development of sophisticated, sustainable, and collaborative simulation tools.
Multi-GPU hybrid programming accelerated three-dimensional phase-field model in binary alloy
NASA Astrophysics Data System (ADS)
Zhu, Changsheng; Liu, Jieqiong; Zhu, Mingfang; Feng, Li
2018-03-01
In the process of dendritic growth simulation, the computational efficiency and the problem scales have extremely important influence on simulation efficiency of three-dimensional phase-field model. Thus, seeking for high performance calculation method to improve the computational efficiency and to expand the problem scales has a great significance to the research of microstructure of the material. A high performance calculation method based on MPI+CUDA hybrid programming model is introduced. Multi-GPU is used to implement quantitative numerical simulations of three-dimensional phase-field model in binary alloy under the condition of multi-physical processes coupling. The acceleration effect of different GPU nodes on different calculation scales is explored. On the foundation of multi-GPU calculation model that has been introduced, two optimization schemes, Non-blocking communication optimization and overlap of MPI and GPU computing optimization, are proposed. The results of two optimization schemes and basic multi-GPU model are compared. The calculation results show that the use of multi-GPU calculation model can improve the computational efficiency of three-dimensional phase-field obviously, which is 13 times to single GPU, and the problem scales have been expanded to 8193. The feasibility of two optimization schemes is shown, and the overlap of MPI and GPU computing optimization has better performance, which is 1.7 times to basic multi-GPU model, when 21 GPUs are used.
DOE Office of Scientific and Technical Information (OSTI.GOV)
DeHart, Mark D.; Mausolff, Zander; Weems, Zach
2016-08-01
One goal of the MAMMOTH M&S project is to validate the analysis capabilities within MAMMOTH. Historical data has shown limited value for validation of full three-dimensional (3D) multi-physics methods. Initial analysis considered the TREAT startup minimum critical core and one of the startup transient tests. At present, validation is focusing on measurements taken during the M8CAL test calibration series. These exercises will valuable in preliminary assessment of the ability of MAMMOTH to perform coupled multi-physics calculations; calculations performed to date are being used to validate the neutron transport solver Rattlesnake\\cite{Rattlesnake} and the fuels performance code BISON. Other validation projects outsidemore » of TREAT are available for single-physics benchmarking. Because the transient solution capability of Rattlesnake is one of the key attributes that makes it unique for TREAT transient simulations, validation of the transient solution of Rattlesnake using other time dependent kinetics benchmarks has considerable value. The Nuclear Energy Agency (NEA) of the Organization for Economic Cooperation and Development (OECD) has recently developed a computational benchmark for transient simulations. This benchmark considered both two-dimensional (2D) and 3D configurations for a total number of 26 different transients. All are negative reactivity insertions, typically returning to the critical state after some time.« less
Efficient evaluation of wireless real-time control networks.
Horvath, Peter; Yampolskiy, Mark; Koutsoukos, Xenofon
2015-02-11
In this paper, we present a system simulation framework for the design and performance evaluation of complex wireless cyber-physical systems. We describe the simulator architecture and the specific developments that are required to simulate cyber-physical systems relying on multi-channel, multihop mesh networks. We introduce realistic and efficient physical layer models and a system simulation methodology, which provides statistically significant performance evaluation results with low computational complexity. The capabilities of the proposed framework are illustrated in the example of WirelessHART, a centralized, real-time, multi-hop mesh network designed for industrial control and monitor applications.
Multi-keV x-ray sources from metal-lined cylindrical hohlraums
NASA Astrophysics Data System (ADS)
Jacquet, L.; Girard, F.; Primout, M.; Villette, B.; Stemmler, Ph.
2012-08-01
As multi-keV x-ray sources, plastic hohlraums with inner walls coated with titanium, copper, and germanium have been fired on Omega in September 2009. For all the targets, the measured and calculated multi-keV x-ray power time histories are in a good qualitative agreement. In the same irradiation conditions, measured multi-keV x-ray conversion rates are ˜6%-8% for titanium, ˜2% for copper, and ˜0.5% for germanium. For titanium and copper hohlraums, the measured conversion rates are about two times higher than those given by hydroradiative computations. Conversely, for the germanium hohlraum, a rather good agreement is found between measured and computed conversion rates. To explain these findings, multi-keV integrated emissivities calculated with RADIOM [M. Busquet, Phys. Fluids 85, 4191 (1993)], the nonlocal-thermal-equilibrium atomic physics model used in our computations, have been compared to emissivities obtained from different other models. These comparisons provide an attractive way to explain the discrepancies between experimental and calculated quantitative results.
mlCAF: Multi-Level Cross-Domain Semantic Context Fusioning for Behavior Identification.
Razzaq, Muhammad Asif; Villalonga, Claudia; Lee, Sungyoung; Akhtar, Usman; Ali, Maqbool; Kim, Eun-Soo; Khattak, Asad Masood; Seung, Hyonwoo; Hur, Taeho; Bang, Jaehun; Kim, Dohyeong; Ali Khan, Wajahat
2017-10-24
The emerging research on automatic identification of user's contexts from the cross-domain environment in ubiquitous and pervasive computing systems has proved to be successful. Monitoring the diversified user's contexts and behaviors can help in controlling lifestyle associated to chronic diseases using context-aware applications. However, availability of cross-domain heterogeneous contexts provides a challenging opportunity for their fusion to obtain abstract information for further analysis. This work demonstrates extension of our previous work from a single domain (i.e., physical activity) to multiple domains (physical activity, nutrition and clinical) for context-awareness. We propose multi-level Context-aware Framework (mlCAF), which fuses the multi-level cross-domain contexts in order to arbitrate richer behavioral contexts. This work explicitly focuses on key challenges linked to multi-level context modeling, reasoning and fusioning based on the mlCAF open-source ontology. More specifically, it addresses the interpretation of contexts from three different domains, their fusioning conforming to richer contextual information. This paper contributes in terms of ontology evolution with additional domains, context definitions, rules and inclusion of semantic queries. For the framework evaluation, multi-level cross-domain contexts collected from 20 users were used to ascertain abstract contexts, which served as basis for behavior modeling and lifestyle identification. The experimental results indicate a context recognition average accuracy of around 92.65% for the collected cross-domain contexts.
mlCAF: Multi-Level Cross-Domain Semantic Context Fusioning for Behavior Identification
Villalonga, Claudia; Lee, Sungyoung; Akhtar, Usman; Ali, Maqbool; Kim, Eun-Soo; Khattak, Asad Masood; Seung, Hyonwoo; Hur, Taeho; Kim, Dohyeong; Ali Khan, Wajahat
2017-01-01
The emerging research on automatic identification of user’s contexts from the cross-domain environment in ubiquitous and pervasive computing systems has proved to be successful. Monitoring the diversified user’s contexts and behaviors can help in controlling lifestyle associated to chronic diseases using context-aware applications. However, availability of cross-domain heterogeneous contexts provides a challenging opportunity for their fusion to obtain abstract information for further analysis. This work demonstrates extension of our previous work from a single domain (i.e., physical activity) to multiple domains (physical activity, nutrition and clinical) for context-awareness. We propose multi-level Context-aware Framework (mlCAF), which fuses the multi-level cross-domain contexts in order to arbitrate richer behavioral contexts. This work explicitly focuses on key challenges linked to multi-level context modeling, reasoning and fusioning based on the mlCAF open-source ontology. More specifically, it addresses the interpretation of contexts from three different domains, their fusioning conforming to richer contextual information. This paper contributes in terms of ontology evolution with additional domains, context definitions, rules and inclusion of semantic queries. For the framework evaluation, multi-level cross-domain contexts collected from 20 users were used to ascertain abstract contexts, which served as basis for behavior modeling and lifestyle identification. The experimental results indicate a context recognition average accuracy of around 92.65% for the collected cross-domain contexts. PMID:29064459
Lattice QCD Calculations in Nuclear Physics towards the Exascale
NASA Astrophysics Data System (ADS)
Joo, Balint
2017-01-01
The combination of algorithmic advances and new highly parallel computing architectures are enabling lattice QCD calculations to tackle ever more complex problems in nuclear physics. In this talk I will review some computational challenges that are encountered in large scale cold nuclear physics campaigns such as those in hadron spectroscopy calculations. I will discuss progress in addressing these with algorithmic improvements such as multi-grid solvers and software for recent hardware architectures such as GPUs and Intel Xeon Phi, Knights Landing. Finally, I will highlight some current topics for research and development as we head towards the Exascale era This material is funded by the U.S. Department of Energy, Office Of Science, Offices of Nuclear Physics, High Energy Physics and Advanced Scientific Computing Research, as well as the Office of Nuclear Physics under contract DE-AC05-06OR23177.
Böhnke, Frank; Bretan, Theodor; Lehner, Stefan; Strenger, Tobias
2013-10-22
The transfer characteristic of the human middle ear with an applied middle ear implant (floating mass transducer) is examined computationally with a Multi-body System approach and compared with experimental results. For this purpose, the geometry of the middle ear was reconstructed from μ-computer tomography slice data and prepared for a Multi-body System simulation. The transfer function of the floating mass transducer, which is the ratio of the input voltage and the generated force, is derived based on a physical context. The numerical results obtained with the Multi-body System approach are compared with experimental results by Laser Doppler measurements of the stapes footplate velocities of five different specimens. Although slightly differing anatomical structures were used for the calculation and the measurement, a high correspondence with respect to the course of stapes footplate displacement along the frequency was found. Notably, a notch at frequencies just below 1 kHz occurred. Additionally, phase courses of stapes footplate displacements were determined computationally if possible and compared with experimental results. The examinations were undertaken to quantify stapes footplate displacements in the clinical practice of middle ear implants and, also, to develop fitting strategies on a physical basis for hearing impaired patients aided with middle ear implants.
Design and multi-physics optimization of rotary MRF brakes
NASA Astrophysics Data System (ADS)
Topcu, Okan; Taşcıoğlu, Yiğit; Konukseven, Erhan İlhan
2018-03-01
Particle swarm optimization (PSO) is a popular method to solve the optimization problems. However, calculations for each particle will be excessive when the number of particles and complexity of the problem increases. As a result, the execution speed will be too slow to achieve the optimized solution. Thus, this paper proposes an automated design and optimization method for rotary MRF brakes and similar multi-physics problems. A modified PSO algorithm is developed for solving multi-physics engineering optimization problems. The difference between the proposed method and the conventional PSO is to split up the original single population into several subpopulations according to the division of labor. The distribution of tasks and the transfer of information to the next party have been inspired by behaviors of a hunting party. Simulation results show that the proposed modified PSO algorithm can overcome the problem of heavy computational burden of multi-physics problems while improving the accuracy. Wire type, MR fluid type, magnetic core material, and ideal current inputs have been determined by the optimization process. To the best of the authors' knowledge, this multi-physics approach is novel for optimizing rotary MRF brakes and the developed PSO algorithm is capable of solving other multi-physics engineering optimization problems. The proposed method has showed both better performance compared to the conventional PSO and also has provided small, lightweight, high impedance rotary MRF brake designs.
A novel medical image data-based multi-physics simulation platform for computational life sciences.
Neufeld, Esra; Szczerba, Dominik; Chavannes, Nicolas; Kuster, Niels
2013-04-06
Simulating and modelling complex biological systems in computational life sciences requires specialized software tools that can perform medical image data-based modelling, jointly visualize the data and computational results, and handle large, complex, realistic and often noisy anatomical models. The required novel solvers must provide the power to model the physics, biology and physiology of living tissue within the full complexity of the human anatomy (e.g. neuronal activity, perfusion and ultrasound propagation). A multi-physics simulation platform satisfying these requirements has been developed for applications including device development and optimization, safety assessment, basic research, and treatment planning. This simulation platform consists of detailed, parametrized anatomical models, a segmentation and meshing tool, a wide range of solvers and optimizers, a framework for the rapid development of specialized and parallelized finite element method solvers, a visualization toolkit-based visualization engine, a Python scripting interface for customized applications, a coupling framework, and more. Core components are cross-platform compatible and use open formats. Several examples of applications are presented: hyperthermia cancer treatment planning, tumour growth modelling, evaluating the magneto-haemodynamic effect as a biomarker and physics-based morphing of anatomical models.
TerraFERMA: Harnessing Advanced Computational Libraries in Earth Science
NASA Astrophysics Data System (ADS)
Wilson, C. R.; Spiegelman, M.; van Keken, P.
2012-12-01
Many important problems in Earth sciences can be described by non-linear coupled systems of partial differential equations. These "multi-physics" problems include thermo-chemical convection in Earth and planetary interiors, interactions of fluids and magmas with the Earth's mantle and crust and coupled flow of water and ice. These problems are of interest to a large community of researchers but are complicated to model and understand. Much of this complexity stems from the nature of multi-physics where small changes in the coupling between variables or constitutive relations can lead to radical changes in behavior, which in turn affect critical computational choices such as discretizations, solvers and preconditioners. To make progress in understanding such coupled systems requires a computational framework where multi-physics problems can be described at a high-level while maintaining the flexibility to easily modify the solution algorithm. Fortunately, recent advances in computational science provide a basis for implementing such a framework. Here we present the Transparent Finite Element Rapid Model Assembler (TerraFERMA), which leverages several advanced open-source libraries for core functionality. FEniCS (fenicsproject.org) provides a high level language for describing the weak forms of coupled systems of equations, and an automatic code generator that produces finite element assembly code. PETSc (www.mcs.anl.gov/petsc) provides a wide range of scalable linear and non-linear solvers that can be composed into effective multi-physics preconditioners. SPuD (amcg.ese.ic.ac.uk/Spud) is an application neutral options system that provides both human and machine-readable interfaces based on a single xml schema. Our software integrates these libraries and provides the user with a framework for exploring multi-physics problems. A single options file fully describes the problem, including all equations, coefficients and solver options. Custom compiled applications are generated from this file but share an infrastructure for services common to all models, e.g. diagnostics, checkpointing and global non-linear convergence monitoring. This maximizes code reusability, reliability and longevity ensuring that scientific results and the methods used to acquire them are transparent and reproducible. TerraFERMA has been tested against many published geodynamic benchmarks including 2D/3D thermal convection problems, the subduction zone benchmarks and benchmarks for magmatic solitary waves. It is currently being used in the investigation of reactive cracking phenomena with applications to carbon sequestration, but we will principally discuss its use in modeling the migration of fluids in subduction zones. Subduction zones require an understanding of the highly nonlinear interactions of fluids with solids and thus provide an excellent scientific driver for the development of multi-physics software.
Assessment of physical server reliability in multi cloud computing system
NASA Astrophysics Data System (ADS)
Kalyani, B. J. D.; Rao, Kolasani Ramchand H.
2018-04-01
Business organizations nowadays functioning with more than one cloud provider. By spreading cloud deployment across multiple service providers, it creates space for competitive prices that minimize the burden on enterprises spending budget. To assess the software reliability of multi cloud application layered software reliability assessment paradigm is considered with three levels of abstractions application layer, virtualization layer, and server layer. The reliability of each layer is assessed separately and is combined to get the reliability of multi-cloud computing application. In this paper, we focused on how to assess the reliability of server layer with required algorithms and explore the steps in the assessment of server reliability.
A multi-scale Q1/P0 approach to langrangian shock hydrodynamics.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shashkov, Mikhail; Love, Edward; Scovazzi, Guglielmo
A new multi-scale, stabilized method for Q1/P0 finite element computations of Lagrangian shock hydrodynamics is presented. Instabilities (of hourglass type) are controlled by a stabilizing operator derived using the variational multi-scale analysis paradigm. The resulting stabilizing term takes the form of a pressure correction. With respect to currently implemented hourglass control approaches, the novelty of the method resides in its residual-based character. The stabilizing residual has a definite physical meaning, since it embeds a discrete form of the Clausius-Duhem inequality. Effectively, the proposed stabilization samples and acts to counter the production of entropy due to numerical instabilities. The proposed techniquemore » is applicable to materials with no shear strength, for which there exists a caloric equation of state. The stabilization operator is incorporated into a mid-point, predictor/multi-corrector time integration algorithm, which conserves mass, momentum and total energy. Encouraging numerical results in the context of compressible gas dynamics confirm the potential of the method.« less
NASA Astrophysics Data System (ADS)
Haghnegahdar, Amin; Elshamy, Mohamed; Yassin, Fuad; Razavi, Saman; Wheater, Howard; Pietroniro, Al
2017-04-01
Complex physically-based environmental models are being increasingly used as the primary tool for watershed planning and management due to advances in computation power and data acquisition. Model sensitivity analysis plays a crucial role in understanding the behavior of these complex models and improving their performance. Due to the non-linearity and interactions within these complex models, Global sensitivity analysis (GSA) techniques should be adopted to provide a comprehensive understanding of model behavior and identify its dominant controls. In this study we adopt a multi-basin multi-criteria GSA approach to systematically assess the behavior of the Modélisation Environmentale-Surface et Hydrologie (MESH) across various hydroclimatic conditions in Canada including areas in the Great Lakes Basin, Mackenzie River Basin, and South Saskatchewan River Basin. MESH is a semi-distributed physically-based coupled land surface-hydrology modelling system developed by Environment and Climate Change Canada (ECCC) for various water resources management purposes in Canada. We use a novel method, called Variogram Analysis of Response Surfaces (VARS), to perform sensitivity analysis. VARS is a variogram-based GSA technique that can efficiently provide a spectrum of sensitivity information across a range of scales within the parameter space. We use multiple metrics to identify dominant controls of model response (e.g. streamflow) to model parameters under various conditions such as high flows, low flows, and flow volume. We also investigate the influence of initial conditions on model behavior as part of this study. Our preliminary results suggest that this type of GSA can significantly help with estimating model parameters, decreasing calibration computational burden, and reducing prediction uncertainty.
Argumentation in a Multi Party Asynchronous Computer Mediated Conference: A Generic Analysis
ERIC Educational Resources Information Center
Coffin, Caroline; Painter, Clare; Hewings, Ann
2005-01-01
This paper draws on systemic functional linguistic genre analysis to illuminate the way in which post graduate applied linguistics students structure their argumentation within a multi party asynchronous computer mediated conference. Two conference discussions within the same postgraduate course are compared in order to reveal the way in which…
NASA Astrophysics Data System (ADS)
Stainforth, D. A.; Allen, M.; Kettleborough, J.; Collins, M.; Heaps, A.; Stott, P.; Wehner, M.
2001-12-01
The climateprediction.com project is preparing to carry out the first systematic uncertainty analysis of climate forecasts using large ensembles of GCM climate simulations. This will be done by involving schools, businesses and members of the public, and utilizing the novel technology of distributed computing. Each participant will be asked to run one member of the ensemble on their PC. The model used will initially be the UK Met Office's Unified Model (UM). It will be run under Windows and software will be provided to enable those involved to view their model output as it develops. The project will use this method to carry out large perturbed physics GCM ensembles and thereby analyse the uncertainty in the forecasts from such models. Each participant/ensemble member will therefore have a version of the UM in which certain aspects of the model physics have been perturbed from their default values. Of course the non-linear nature of the system means that it will be necessary to look not just at perturbations to individual parameters in specific schemes, such as the cloud parameterization, but also to the many combinations of perturbations. This rapidly leads to the need for very large, perhaps multi-million member ensembles, which could only be undertaken using the distributed computing methodology. The status of the project will be presented and the Windows client will be demonstrated. In addition, initial results will be presented from beta test runs using a demo release for Linux PCs and Alpha workstations. Although small by comparison to the whole project, these pilot results constitute a 20-50 member perturbed physics climate ensemble with results indicating how climate sensitivity can be substantially affected by individual parameter values in the cloud scheme.
Leveraging unsupervised training sets for multi-scale compartmentalization in renal pathology
NASA Astrophysics Data System (ADS)
Lutnick, Brendon; Tomaszewski, John E.; Sarder, Pinaki
2017-03-01
Clinical pathology relies on manual compartmentalization and quantification of biological structures, which is time consuming and often error-prone. Application of computer vision segmentation algorithms to histopathological image analysis, in contrast, can offer fast, reproducible, and accurate quantitative analysis to aid pathologists. Algorithms tunable to different biologically relevant structures can allow accurate, precise, and reproducible estimates of disease states. In this direction, we have developed a fast, unsupervised computational method for simultaneously separating all biologically relevant structures from histopathological images in multi-scale. Segmentation is achieved by solving an energy optimization problem. Representing the image as a graph, nodes (pixels) are grouped by minimizing a Potts model Hamiltonian, adopted from theoretical physics, modeling interacting electron spins. Pixel relationships (modeled as edges) are used to update the energy of the partitioned graph. By iteratively improving the clustering, the optimal number of segments is revealed. To reduce computational time, the graph is simplified using a Cantor pairing function to intelligently reduce the number of included nodes. The classified nodes are then used to train a multiclass support vector machine to apply the segmentation over the full image. Accurate segmentations of images with as many as 106 pixels can be completed only in 5 sec, allowing for attainable multi-scale visualization. To establish clinical potential, we employed our method in renal biopsies to quantitatively visualize for the first time scale variant compartments of heterogeneous intra- and extraglomerular structures simultaneously. Implications of the utility of our method extend to fields such as oncology, genomics, and non-biological problems.
Computation of Thermodynamic Equilibria Pertinent to Nuclear Materials in Multi-Physics Codes
NASA Astrophysics Data System (ADS)
Piro, Markus Hans Alexander
Nuclear energy plays a vital role in supporting electrical needs and fulfilling commitments to reduce greenhouse gas emissions. Research is a continuing necessity to improve the predictive capabilities of fuel behaviour in order to reduce costs and to meet increasingly stringent safety requirements by the regulator. Moreover, a renewed interest in nuclear energy has given rise to a "nuclear renaissance" and the necessity to design the next generation of reactors. In support of this goal, significant research efforts have been dedicated to the advancement of numerical modelling and computational tools in simulating various physical and chemical phenomena associated with nuclear fuel behaviour. This undertaking in effect is collecting the experience and observations of a past generation of nuclear engineers and scientists in a meaningful way for future design purposes. There is an increasing desire to integrate thermodynamic computations directly into multi-physics nuclear fuel performance and safety codes. A new equilibrium thermodynamic solver is being developed with this matter as a primary objective. This solver is intended to provide thermodynamic material properties and boundary conditions for continuum transport calculations. There are several concerns with the use of existing commercial thermodynamic codes: computational performance; limited capabilities in handling large multi-component systems of interest to the nuclear industry; convenient incorporation into other codes with quality assurance considerations; and, licensing entanglements associated with code distribution. The development of this software in this research is aimed at addressing all of these concerns. The approach taken in this work exploits fundamental principles of equilibrium thermodynamics to simplify the numerical optimization equations. In brief, the chemical potentials of all species and phases in the system are constrained by estimates of the chemical potentials of the system components at each iterative step, and the objective is to minimize the residuals of the mass balance equations. Several numerical advantages are achieved through this simplification. In particular, computational expense is reduced and the rate of convergence is enhanced. Furthermore, the software has demonstrated the ability to solve systems involving as many as 118 component elements. An early version of the code has already been integrated into the Advanced Multi-Physics (AMP) code under development by the Oak Ridge National Laboratory, Los Alamos National Laboratory, Idaho National Laboratory and Argonne National Laboratory. Keywords: Engineering, Nuclear -- 0552, Engineering, Material Science -- 0794, Chemistry, Mathematics -- 0405, Computer Science -- 0984
DOE Office of Scientific and Technical Information (OSTI.GOV)
Arimura, Hidetaka, E-mail: arimurah@med.kyushu-u.ac.jp; Kamezawa, Hidemi; Jin, Ze
Good relationships between computational image analysis and radiological physics have been constructed for increasing the accuracy of medical diagnostic imaging and radiation therapy in radiological physics. Computational image analysis has been established based on applied mathematics, physics, and engineering. This review paper will introduce how computational image analysis is useful in radiation therapy with respect to radiological physics.
High performance MRI simulations of motion on multi-GPU systems.
Xanthis, Christos G; Venetis, Ioannis E; Aletras, Anthony H
2014-07-04
MRI physics simulators have been developed in the past for optimizing imaging protocols and for training purposes. However, these simulators have only addressed motion within a limited scope. The purpose of this study was the incorporation of realistic motion, such as cardiac motion, respiratory motion and flow, within MRI simulations in a high performance multi-GPU environment. Three different motion models were introduced in the Magnetic Resonance Imaging SIMULator (MRISIMUL) of this study: cardiac motion, respiratory motion and flow. Simulation of a simple Gradient Echo pulse sequence and a CINE pulse sequence on the corresponding anatomical model was performed. Myocardial tagging was also investigated. In pulse sequence design, software crushers were introduced to accommodate the long execution times in order to avoid spurious echoes formation. The displacement of the anatomical model isochromats was calculated within the Graphics Processing Unit (GPU) kernel for every timestep of the pulse sequence. Experiments that would allow simulation of custom anatomical and motion models were also performed. Last, simulations of motion with MRISIMUL on single-node and multi-node multi-GPU systems were examined. Gradient Echo and CINE images of the three motion models were produced and motion-related artifacts were demonstrated. The temporal evolution of the contractility of the heart was presented through the application of myocardial tagging. Better simulation performance and image quality were presented through the introduction of software crushers without the need to further increase the computational load and GPU resources. Last, MRISIMUL demonstrated an almost linear scalable performance with the increasing number of available GPU cards, in both single-node and multi-node multi-GPU computer systems. MRISIMUL is the first MR physics simulator to have implemented motion with a 3D large computational load on a single computer multi-GPU configuration. The incorporation of realistic motion models, such as cardiac motion, respiratory motion and flow may benefit the design and optimization of existing or new MR pulse sequences, protocols and algorithms, which examine motion related MR applications.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jiang, Lijian, E-mail: ljjiang@hnu.edu.cn; Li, Xinping, E-mail: exping@126.com
Stochastic multiscale modeling has become a necessary approach to quantify uncertainty and characterize multiscale phenomena for many practical problems such as flows in stochastic porous media. The numerical treatment of the stochastic multiscale models can be very challengeable as the existence of complex uncertainty and multiple physical scales in the models. To efficiently take care of the difficulty, we construct a computational reduced model. To this end, we propose a multi-element least square high-dimensional model representation (HDMR) method, through which the random domain is adaptively decomposed into a few subdomains, and a local least square HDMR is constructed in eachmore » subdomain. These local HDMRs are represented by a finite number of orthogonal basis functions defined in low-dimensional random spaces. The coefficients in the local HDMRs are determined using least square methods. We paste all the local HDMR approximations together to form a global HDMR approximation. To further reduce computational cost, we present a multi-element reduced least-square HDMR, which improves both efficiency and approximation accuracy in certain conditions. To effectively treat heterogeneity properties and multiscale features in the models, we integrate multiscale finite element methods with multi-element least-square HDMR for stochastic multiscale model reduction. This approach significantly reduces the original model's complexity in both the resolution of the physical space and the high-dimensional stochastic space. We analyze the proposed approach, and provide a set of numerical experiments to demonstrate the performance of the presented model reduction techniques. - Highlights: • Multi-element least square HDMR is proposed to treat stochastic models. • Random domain is adaptively decomposed into some subdomains to obtain adaptive multi-element HDMR. • Least-square reduced HDMR is proposed to enhance computation efficiency and approximation accuracy in certain conditions. • Integrating MsFEM and multi-element least square HDMR can significantly reduce computation complexity.« less
Huang, Chao-Tsung; Wang, Yu-Wen; Huang, Li-Ren; Chin, Jui; Chen, Liang-Gee
2017-02-01
Digital refocusing has a tradeoff between complexity and quality when using sparsely sampled light fields for low-storage applications. In this paper, we propose a fast physically correct refocusing algorithm to address this issue in a twofold way. First, view interpolation is adopted to provide photorealistic quality at infocus-defocus hybrid boundaries. Regarding its conventional high complexity, we devised a fast line-scan method specifically for refocusing, and its 1D kernel can be 30× faster than the benchmark View Synthesis Reference Software (VSRS)-1D-Fast. Second, we propose a block-based multi-rate processing flow for accelerating purely infocused or defocused regions, and a further 3- 34× speedup can be achieved for high-resolution images. All candidate blocks of variable sizes can interpolate different numbers of rendered views and perform refocusing in different subsampled layers. To avoid visible aliasing and block artifacts, we determine these parameters and the simulated aperture filter through a localized filter response analysis using defocus blur statistics. The final quadtree block partitions are then optimized in terms of computation time. Extensive experimental results are provided to show superior refocusing quality and fast computation speed. In particular, the run time is comparable with the conventional single-image blurring, which causes serious boundary artifacts.
NASA Astrophysics Data System (ADS)
Nguyen, Van-Dung; Wu, Ling; Noels, Ludovic
2017-03-01
This work provides a unified treatment of arbitrary kinds of microscopic boundary conditions usually considered in the multi-scale computational homogenization method for nonlinear multi-physics problems. An efficient procedure is developed to enforce the multi-point linear constraints arising from the microscopic boundary condition either by the direct constraint elimination or by the Lagrange multiplier elimination methods. The macroscopic tangent operators are computed in an efficient way from a multiple right hand sides linear system whose left hand side matrix is the stiffness matrix of the microscopic linearized system at the converged solution. The number of vectors at the right hand side is equal to the number of the macroscopic kinematic variables used to formulate the microscopic boundary condition. As the resolution of the microscopic linearized system often follows a direct factorization procedure, the computation of the macroscopic tangent operators is then performed using this factorized matrix at a reduced computational time.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Simunovic, Srdjan
2015-02-16
CASL's modeling and simulation technology, the Virtual Environment for Reactor Applications (VERA), incorporates coupled physics and science-based models, state-of-the-art numerical methods, modern computational science, integrated uncertainty quantification (UQ) and validation against data from operating pressurized water reactors (PWRs), single-effect experiments, and integral tests. The computational simulation component of VERA is the VERA Core Simulator (VERA-CS). The core simulator is the specific collection of multi-physics computer codes used to model and deplete a LWR core over multiple cycles. The core simulator has a single common input file that drives all of the different physics codes. The parser code, VERAIn, converts VERAmore » Input into an XML file that is used as input to different VERA codes.« less
Theoretical and experimental study of a new algorithm for factoring numbers
NASA Astrophysics Data System (ADS)
Tamma, Vincenzo
The security of codes, for example in credit card and government information, relies on the fact that the factorization of a large integer N is a rather costly process on a classical digital computer. Such a security is endangered by Shor's algorithm which employs entangled quantum systems to find, with a polynomial number of resources, the period of a function which is connected with the factors of N. We can surely expect a possible future realization of such a method for large numbers, but so far the period of Shor's function has been only computed for the number 15. Inspired by Shor's idea, our work aims to methods of factorization based on the periodicity measurement of a given continuous periodic "factoring function" which is physically implementable using an analogue computer. In particular, we have focused on both the theoretical and the experimental analysis of Gauss sums with continuous arguments leading to a new factorization algorithm. The procedure allows, for the first time, to factor several numbers by measuring the periodicity of Gauss sums performing first-order "factoring" interfer ence processes. We experimentally implemented this idea by exploiting polychromatic optical interference in the visible range with a multi-path interferometer, and achieved the factorization of seven digit numbers. The physical principle behind this "factoring" interference procedure can be potentially exploited also on entangled systems, as multi-photon entangled states, in order to achieve a polynomial scaling in the number of resources.
Diegoli, Toni Marie; Rohde, Heinrich; Borowski, Stefan; Krawczak, Michael; Coble, Michael D; Nothnagel, Michael
2016-11-01
Typing of X chromosomal short tandem repeat (X STR) markers has become a standard element of human forensic genetic analysis. Joint consideration of many X STR markers at a time increases their discriminatory power but, owing to physical linkage, requires inter-marker recombination rates to be accurately known. We estimated the recombination rates between 15 well established X STR markers using genotype data from 158 families (1041 individuals) and following a previously proposed likelihood-based approach that allows for single-step mutations. To meet the computational requirements of this family-based type of analysis, we modified a previous implementation so as to allow multi-core parallelization on a high-performance computing system. While we obtained recombination rate estimates larger than zero for all but one pair of adjacent markers within the four previously proposed linkage groups, none of the three X STR pairs defining the junctions of these groups yielded a recombination rate estimate of 0.50. Corroborating previous studies, our results therefore argue against a simple model of independent X chromosomal linkage groups. Moreover, the refined recombination fraction estimates obtained in our study will facilitate the appropriate joint consideration of all 15 investigated markers in forensic analysis. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Enabling Grid Computing resources within the KM3NeT computing model
NASA Astrophysics Data System (ADS)
Filippidis, Christos
2016-04-01
KM3NeT is a future European deep-sea research infrastructure hosting a new generation neutrino detectors that - located at the bottom of the Mediterranean Sea - will open a new window on the universe and answer fundamental questions both in particle physics and astrophysics. International collaborative scientific experiments, like KM3NeT, are generating datasets which are increasing exponentially in both complexity and volume, making their analysis, archival, and sharing one of the grand challenges of the 21st century. These experiments, in their majority, adopt computing models consisting of different Tiers with several computing centres and providing a specific set of services for the different steps of data processing such as detector calibration, simulation and data filtering, reconstruction and analysis. The computing requirements are extremely demanding and, usually, span from serial to multi-parallel or GPU-optimized jobs. The collaborative nature of these experiments demands very frequent WAN data transfers and data sharing among individuals and groups. In order to support the aforementioned demanding computing requirements we enabled Grid Computing resources, operated by EGI, within the KM3NeT computing model. In this study we describe our first advances in this field and the method for the KM3NeT users to utilize the EGI computing resources in a simulation-driven use-case.
Microphysics in the Multi-Scale Modeling Systems with Unified Physics
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.
2011-01-01
In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the microphysics developments of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the heavy precipitation processes will be presented.
Integration of Panda Workload Management System with supercomputers
NASA Astrophysics Data System (ADS)
De, K.; Jha, S.; Klimentov, A.; Maeno, T.; Mashinistov, R.; Nilsson, P.; Novikov, A.; Oleynik, D.; Panitkin, S.; Poyda, A.; Read, K. F.; Ryabinkin, E.; Teslyuk, A.; Velikhov, V.; Wells, J. C.; Wenaus, T.
2016-09-01
The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS, one of the largest collaborations ever assembled in the sciences, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Management System for managing the workflow for all data processing on over 140 data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. While PanDA currently uses more than 250000 cores with a peak performance of 0.3+ petaFLOPS, next LHC data taking runs will require more resources than Grid computing can possibly provide. To alleviate these challenges, LHC experiments are engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. We will describe a project aimed at integration of PanDA WMS with supercomputers in United States, Europe and Russia (in particular with Titan supercomputer at Oak Ridge Leadership Computing Facility (OLCF), Supercomputer at the National Research Center "Kurchatov Institute", IT4 in Ostrava, and others). The current approach utilizes a modified PanDA pilot framework for job submission to the supercomputers batch queues and local data management, with light-weight MPI wrappers to run singlethreaded workloads in parallel on Titan's multi-core worker nodes. This implementation was tested with a variety of Monte-Carlo workloads on several supercomputing platforms. We will present our current accomplishments in running PanDA WMS at supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facility's infrastructure for High Energy and Nuclear Physics, as well as other data-intensive science applications, such as bioinformatics and astro-particle physics.
Tackling some of the most intricate geophysical challenges via high-performance computing
NASA Astrophysics Data System (ADS)
Khosronejad, A.
2016-12-01
Recently, world has been witnessing significant enhancements in computing power of supercomputers. Computer clusters in conjunction with the advanced mathematical algorithms has set the stage for developing and applying powerful numerical tools to tackle some of the most intricate geophysical challenges that today`s engineers face. One such challenge is to understand how turbulent flows, in real-world settings, interact with (a) rigid and/or mobile complex bed bathymetry of waterways and sea-beds in the coastal areas; (b) objects with complex geometry that are fully or partially immersed; and (c) free-surface of waterways and water surface waves in the coastal area. This understanding is especially important because the turbulent flows in real-world environments are often bounded by geometrically complex boundaries, which dynamically deform and give rise to multi-scale and multi-physics transport phenomena, and characterized by multi-lateral interactions among various phases (e.g. air/water/sediment phases). Herein, I present some of the multi-scale and multi-physics geophysical fluid mechanics processes that I have attempted to study using an in-house high-performance computational model, the so-called VFS-Geophysics. More specifically, I will present the simulation results of turbulence/sediment/solute/turbine interactions in real-world settings. Parts of the simulations I present are performed to gain scientific insights into the processes such as sand wave formation (A. Khosronejad, and F. Sotiropoulos, (2014), Numerical simulation of sand waves in a turbulent open channel flow, Journal of Fluid Mechanics, 753:150-216), while others are carried out to predict the effects of climate change and large flood events on societal infrastructures ( A. Khosronejad, et al., (2016), Large eddy simulation of turbulence and solute transport in a forested headwater stream, Journal of Geophysical Research:, doi: 10.1002/2014JF003423).
Computers as an Instrument for Data Analysis. Technical Report No. 11.
ERIC Educational Resources Information Center
Muller, Mervin E.
A review of statistical data analysis involving computers as a multi-dimensional problem provides the perspective for consideration of the use of computers in statistical analysis and the problems associated with large data files. An overall description of STATJOB, a particular system for doing statistical data analysis on a digital computer,…
Development of a Multi-Disciplinary Computing Environment (MDICE)
NASA Technical Reports Server (NTRS)
Kingsley, Gerry; Siegel, John M., Jr.; Harrand, Vincent J.; Lawrence, Charles; Luker, Joel J.
1999-01-01
The growing need for and importance of multi-component and multi-disciplinary engineering analysis has been understood for many years. For many applications, loose (or semi-implicit) coupling is optimal, and allows the use of various legacy codes without requiring major modifications. For this purpose, CFDRC and NASA LeRC have developed a computational environment to enable coupling between various flow analysis codes at several levels of fidelity. This has been referred to as the Visual Computing Environment (VCE), and is being successfully applied to the analysis of several aircraft engine components. Recently, CFDRC and AFRL/VAAC (WL) have extended the framework and scope of VCE to enable complex multi-disciplinary simulations. The chosen initial focus is on aeroelastic aircraft applications. The developed software is referred to as MDICE-AE, an extensible system suitable for integration of several engineering analysis disciplines. This paper describes the methodology, basic architecture, chosen software technologies, salient library modules, and the current status of and plans for MDICE. A fluid-structure interaction application is described in a separate companion paper.
DOE Office of Scientific and Technical Information (OSTI.GOV)
None, None
The Second SIAM Conference on Computational Science and Engineering was held in San Diego from February 10-12, 2003. Total conference attendance was 553. This is a 23% increase in attendance over the first conference. The focus of this conference was to draw attention to the tremendous range of major computational efforts on large problems in science and engineering, to promote the interdisciplinary culture required to meet these large-scale challenges, and to encourage the training of the next generation of computational scientists. Computational Science & Engineering (CS&E) is now widely accepted, along with theory and experiment, as a crucial third modemore » of scientific investigation and engineering design. Aerospace, automotive, biological, chemical, semiconductor, and other industrial sectors now rely on simulation for technical decision support. For federal agencies also, CS&E has become an essential support for decisions on resources, transportation, and defense. CS&E is, by nature, interdisciplinary. It grows out of physical applications and it depends on computer architecture, but at its heart are powerful numerical algorithms and sophisticated computer science techniques. From an applied mathematics perspective, much of CS&E has involved analysis, but the future surely includes optimization and design, especially in the presence of uncertainty. Another mathematical frontier is the assimilation of very large data sets through such techniques as adaptive multi-resolution, automated feature search, and low-dimensional parameterization. The themes of the 2003 conference included, but were not limited to: Advanced Discretization Methods; Computational Biology and Bioinformatics; Computational Chemistry and Chemical Engineering; Computational Earth and Atmospheric Sciences; Computational Electromagnetics; Computational Fluid Dynamics; Computational Medicine and Bioengineering; Computational Physics and Astrophysics; Computational Solid Mechanics and Materials; CS&E Education; Meshing and Adaptivity; Multiscale and Multiphysics Problems; Numerical Algorithms for CS&E; Discrete and Combinatorial Algorithms for CS&E; Inverse Problems; Optimal Design, Optimal Control, and Inverse Problems; Parallel and Distributed Computing; Problem-Solving Environments; Software and Wddleware Systems; Uncertainty Estimation and Sensitivity Analysis; and Visualization and Computer Graphics.« less
Full-color large-scaled computer-generated holograms for physical and non-physical objects
NASA Astrophysics Data System (ADS)
Matsushima, Kyoji; Tsuchiyama, Yasuhiro; Sonobe, Noriaki; Masuji, Shoya; Yamaguchi, Masahiro; Sakamoto, Yuji
2017-05-01
Several full-color high-definition CGHs are created for reconstructing 3D scenes including real-existing physical objects. The field of the physical objects are generated or captured by employing three techniques; 3D scanner, synthetic aperture digital holography, and multi-viewpoint images. Full-color reconstruction of high-definition CGHs is realized by RGB color filters. The optical reconstructions are presented for verifying these techniques.
NASA Astrophysics Data System (ADS)
Karimabadi, Homa
2012-03-01
Recent advances in simulation technology and hardware are enabling breakthrough science where many longstanding problems can now be addressed for the first time. In this talk, we focus on kinetic simulations of the Earth's magnetosphere and magnetic reconnection process which is the key mechanism that breaks the protective shield of the Earth's dipole field, allowing the solar wind to enter the Earth's magnetosphere. This leads to the so-called space weather where storms on the Sun can affect space-borne and ground-based technological systems on Earth. The talk will consist of three parts: (a) overview of a new multi-scale simulation technique where each computational grid is updated based on its own unique timestep, (b) Presentation of a new approach to data analysis that we refer to as Physics Mining which entails combining data mining and computer vision algorithms with scientific visualization to extract physics from the resulting massive data sets. (c) Presentation of several recent discoveries in studies of space plasmas including the role of vortex formation and resulting turbulence in magnetized plasmas.
Quantum Computing Architectural Design
NASA Astrophysics Data System (ADS)
West, Jacob; Simms, Geoffrey; Gyure, Mark
2006-03-01
Large scale quantum computers will invariably require scalable architectures in addition to high fidelity gate operations. Quantum computing architectural design (QCAD) addresses the problems of actually implementing fault-tolerant algorithms given physical and architectural constraints beyond those of basic gate-level fidelity. Here we introduce a unified framework for QCAD that enables the scientist to study the impact of varying error correction schemes, architectural parameters including layout and scheduling, and physical operations native to a given architecture. Our software package, aptly named QCAD, provides compilation, manipulation/transformation, multi-paradigm simulation, and visualization tools. We demonstrate various features of the QCAD software package through several examples.
Towards Co-Engineering Communicating Autonomous Cyber-Physical Systems
NASA Technical Reports Server (NTRS)
Bujorianu, Marius C.; Bujorianu, Manuela L.
2009-01-01
In this paper, we sketch a framework for interdisciplinary modeling of space systems, by proposing a holistic view. We consider different system dimensions and their interaction. Specifically, we study the interactions between computation, physics, communication, uncertainty and autonomy. The most comprehensive computational paradigm that supports a holistic perspective on autonomous space systems is given by cyber-physical systems. For these, the state of art consists of collaborating multi-engineering efforts that prompt for an adequate formal foundation. To achieve this, we propose a leveraging of the traditional content of formal modeling by a co-engineering process.
Concurrent Probabilistic Simulation of High Temperature Composite Structural Response
NASA Technical Reports Server (NTRS)
Abdi, Frank
1996-01-01
A computational structural/material analysis and design tool which would meet industry's future demand for expedience and reduced cost is presented. This unique software 'GENOA' is dedicated to parallel and high speed analysis to perform probabilistic evaluation of high temperature composite response of aerospace systems. The development is based on detailed integration and modification of diverse fields of specialized analysis techniques and mathematical models to combine their latest innovative capabilities into a commercially viable software package. The technique is specifically designed to exploit the availability of processors to perform computationally intense probabilistic analysis assessing uncertainties in structural reliability analysis and composite micromechanics. The primary objectives which were achieved in performing the development were: (1) Utilization of the power of parallel processing and static/dynamic load balancing optimization to make the complex simulation of structure, material and processing of high temperature composite affordable; (2) Computational integration and synchronization of probabilistic mathematics, structural/material mechanics and parallel computing; (3) Implementation of an innovative multi-level domain decomposition technique to identify the inherent parallelism, and increasing convergence rates through high- and low-level processor assignment; (4) Creating the framework for Portable Paralleled architecture for the machine independent Multi Instruction Multi Data, (MIMD), Single Instruction Multi Data (SIMD), hybrid and distributed workstation type of computers; and (5) Market evaluation. The results of Phase-2 effort provides a good basis for continuation and warrants Phase-3 government, and industry partnership.
Application of multi-grid method on the simulation of incremental forging processes
NASA Astrophysics Data System (ADS)
Ramadan, Mohamad; Khaled, Mahmoud; Fourment, Lionel
2016-10-01
Numerical simulation becomes essential in manufacturing large part by incremental forging processes. It is a splendid tool allowing to show physical phenomena however behind the scenes, an expensive bill should be paid, that is the computational time. That is why many techniques are developed to decrease the computational time of numerical simulation. Multi-Grid method is a numerical procedure that permits to reduce computational time of numerical calculation by performing the resolution of the system of equations on several mesh of decreasing size which allows to smooth faster the low frequency of the solution as well as its high frequency. In this paper a Multi-Grid method is applied to cogging process in the software Forge 3. The study is carried out using increasing number of degrees of freedom. The results shows that calculation time is divide by two for a mesh of 39,000 nodes. The method is promising especially if coupled with Multi-Mesh method.
Progress in fast, accurate multi-scale climate simulations
Collins, W. D.; Johansen, H.; Evans, K. J.; ...
2015-06-01
We present a survey of physical and computational techniques that have the potential to contribute to the next generation of high-fidelity, multi-scale climate simulations. Examples of the climate science problems that can be investigated with more depth with these computational improvements include the capture of remote forcings of localized hydrological extreme events, an accurate representation of cloud features over a range of spatial and temporal scales, and parallel, large ensembles of simulations to more effectively explore model sensitivities and uncertainties. Numerical techniques, such as adaptive mesh refinement, implicit time integration, and separate treatment of fast physical time scales are enablingmore » improved accuracy and fidelity in simulation of dynamics and allowing more complete representations of climate features at the global scale. At the same time, partnerships with computer science teams have focused on taking advantage of evolving computer architectures such as many-core processors and GPUs. As a result, approaches which were previously considered prohibitively costly have become both more efficient and scalable. In combination, progress in these three critical areas is poised to transform climate modeling in the coming decades.« less
Simulation of multi-pulse coaxial helicity injection in the Sustained Spheromak Physics Experiment
NASA Astrophysics Data System (ADS)
O'Bryan, J. B.; Romero-Talamás, C. A.; Woodruff, S.
2018-03-01
Nonlinear, numerical computation with the NIMROD code is used to explore magnetic self-organization during multi-pulse coaxial helicity injection in the Sustained Spheromak Physics eXperiment. We describe multiple distinct phases of spheromak evolution, starting from vacuum magnetic fields and the formation of the initial magnetic flux bubble through multiple refluxing pulses and the eventual onset of the column mode instability. Experimental and computational magnetic diagnostics agree on the onset of the column mode instability, which first occurs during the second refluxing pulse of the simulated discharge. Our computations also reproduce the injector voltage traces, despite only specifying the injector current and not explicitly modeling the external capacitor bank circuit. The computations demonstrate that global magnetic evolution is fairly robust to different transport models and, therefore, that a single fluid-temperature model is sufficient for a broader, qualitative assessment of spheromak performance. Although discharges with similar traces of normalized injector current produce similar global spheromak evolution, details of the current distribution during the column mode instability impact the relative degree of poloidal flux amplification and magnetic helicity content.
NASA Astrophysics Data System (ADS)
Gao, Wei; Li, Xiang-ru
2017-07-01
The multi-task learning takes the multiple tasks together to make analysis and calculation, so as to dig out the correlations among them, and therefore to improve the accuracy of the analyzed results. This kind of methods have been widely applied to the machine learning, pattern recognition, computer vision, and other related fields. This paper investigates the application of multi-task learning in estimating the stellar atmospheric parameters, including the surface temperature (Teff), surface gravitational acceleration (lg g), and chemical abundance ([Fe/H]). Firstly, the spectral features of the three stellar atmospheric parameters are extracted by using the multi-task sparse group Lasso algorithm, then the support vector machine is used to estimate the atmospheric physical parameters. The proposed scheme is evaluated on both the Sloan stellar spectra and the theoretical spectra computed from the Kurucz's New Opacity Distribution Function (NEWODF) model. The mean absolute errors (MAEs) on the Sloan spectra are: 0.0064 for lg (Teff /K), 0.1622 for lg (g/(cm · s-2)), and 0.1221 dex for [Fe/H]; the MAEs on the synthetic spectra are 0.0006 for lg (Teff /K), 0.0098 for lg (g/(cm · s-2)), and 0.0082 dex for [Fe/H]. Experimental results show that the proposed scheme has a rather high accuracy for the estimation of stellar atmospheric parameters.
Atomistic Modeling of Nanostructures via the BFS Quantum Approximate Method
NASA Technical Reports Server (NTRS)
Bozzolo, Guillermo; Garces, Jorge E.; Noebe, Ronald D.; Farias, D.
2003-01-01
Ideally, computational modeling techniques for nanoscopic physics would be able to perform free of limitations on the type and number of elements, while providing comparable accuracy when dealing with bulk or surface problems. Computational efficiency is also desirable, if not mandatory, for properly dealing with the complexity of typical nano-strucured systems. A quantum approximate technique, the BFS method for alloys, which attempts to meet these demands, is introduced for the calculation of the energetics of nanostructures. The versatility of the technique is demonstrated through analysis of diverse systems, including multi-phase precipitation in a five element Ni-Al-Ti-Cr-Cu alloy and the formation of mixed composition Co-Cu islands on a metallic Cu(III) substrate.
Machine learning action parameters in lattice quantum chromodynamics
NASA Astrophysics Data System (ADS)
Shanahan, Phiala E.; Trewartha, Daniel; Detmold, William
2018-05-01
Numerical lattice quantum chromodynamics studies of the strong interaction are important in many aspects of particle and nuclear physics. Such studies require significant computing resources to undertake. A number of proposed methods promise improved efficiency of lattice calculations, and access to regions of parameter space that are currently computationally intractable, via multi-scale action-matching approaches that necessitate parametric regression of generated lattice datasets. The applicability of machine learning to this regression task is investigated, with deep neural networks found to provide an efficient solution even in cases where approaches such as principal component analysis fail. The high information content and complex symmetries inherent in lattice QCD datasets require custom neural network layers to be introduced and present opportunities for further development.
pyCTQW: A continuous-time quantum walk simulator on distributed memory computers
NASA Astrophysics Data System (ADS)
Izaac, Josh A.; Wang, Jingbo B.
2015-01-01
In the general field of quantum information and computation, quantum walks are playing an increasingly important role in constructing physical models and quantum algorithms. We have recently developed a distributed memory software package pyCTQW, with an object-oriented Python interface, that allows efficient simulation of large multi-particle CTQW (continuous-time quantum walk)-based systems. In this paper, we present an introduction to the Python and Fortran interfaces of pyCTQW, discuss various numerical methods of calculating the matrix exponential, and demonstrate the performance behavior of pyCTQW on a distributed memory cluster. In particular, the Chebyshev and Krylov-subspace methods for calculating the quantum walk propagation are provided, as well as methods for visualization and data analysis.
Monte Carlo Analysis of Reservoir Models Using Seismic Data and Geostatistical Models
NASA Astrophysics Data System (ADS)
Zunino, A.; Mosegaard, K.; Lange, K.; Melnikova, Y.; Hansen, T. M.
2013-12-01
We present a study on the analysis of petroleum reservoir models consistent with seismic data and geostatistical constraints performed on a synthetic reservoir model. Our aim is to invert directly for structure and rock bulk properties of the target reservoir zone. To infer the rock facies, porosity and oil saturation seismology alone is not sufficient but a rock physics model must be taken into account, which links the unknown properties to the elastic parameters. We then combine a rock physics model with a simple convolutional approach for seismic waves to invert the "measured" seismograms. To solve this inverse problem, we employ a Markov chain Monte Carlo (MCMC) method, because it offers the possibility to handle non-linearity, complex and multi-step forward models and provides realistic estimates of uncertainties. However, for large data sets the MCMC method may be impractical because of a very high computational demand. To face this challenge one strategy is to feed the algorithm with realistic models, hence relying on proper prior information. To address this problem, we utilize an algorithm drawn from geostatistics to generate geologically plausible models which represent samples of the prior distribution. The geostatistical algorithm learns the multiple-point statistics from prototype models (in the form of training images), then generates thousands of different models which are accepted or rejected by a Metropolis sampler. To further reduce the computation time we parallelize the software and run it on multi-core machines. The solution of the inverse problem is then represented by a collection of reservoir models in terms of facies, porosity and oil saturation, which constitute samples of the posterior distribution. We are finally able to produce probability maps of the properties we are interested in by performing statistical analysis on the collection of solutions.
Mariani, Alberto; Brunner, S.; Dominski, J.; ...
2018-01-17
Reducing the uncertainty on physical input parameters derived from experimental measurements is essential towards improving the reliability of gyrokinetic turbulence simulations. This can be achieved by introducing physical constraints. Amongst them, the zero particle flux condition is considered here. A first attempt is also made to match as well the experimental ion/electron heat flux ratio. This procedure is applied to the analysis of a particular Tokamak à Configuration Variable discharge. A detailed reconstruction of the zero particle flux hyper-surface in the multi-dimensional physical parameter space at fixed time of the discharge is presented, including the effect of carbon as themore » main impurity. Both collisionless and collisional regimes are considered. Hyper-surface points within the experimental error bars are found. In conclusion, the analysis is done performing gyrokinetic simulations with the local version of the GENE code, computing the fluxes with a Quasi-Linear (QL) model and validating the QL results with non-linear simulations in a subset of cases.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mariani, Alberto; Brunner, S.; Dominski, J.
Reducing the uncertainty on physical input parameters derived from experimental measurements is essential towards improving the reliability of gyrokinetic turbulence simulations. This can be achieved by introducing physical constraints. Amongst them, the zero particle flux condition is considered here. A first attempt is also made to match as well the experimental ion/electron heat flux ratio. This procedure is applied to the analysis of a particular Tokamak à Configuration Variable discharge. A detailed reconstruction of the zero particle flux hyper-surface in the multi-dimensional physical parameter space at fixed time of the discharge is presented, including the effect of carbon as themore » main impurity. Both collisionless and collisional regimes are considered. Hyper-surface points within the experimental error bars are found. In conclusion, the analysis is done performing gyrokinetic simulations with the local version of the GENE code, computing the fluxes with a Quasi-Linear (QL) model and validating the QL results with non-linear simulations in a subset of cases.« less
Multi-level tree analysis of pulmonary artery/vein trees in non-contrast CT images
NASA Astrophysics Data System (ADS)
Gao, Zhiyun; Grout, Randall W.; Hoffman, Eric A.; Saha, Punam K.
2012-02-01
Diseases like pulmonary embolism and pulmonary hypertension are associated with vascular dystrophy. Identifying such pulmonary artery/vein (A/V) tree dystrophy in terms of quantitative measures via CT imaging significantly facilitates early detection of disease or a treatment monitoring process. A tree structure, consisting of nodes and connected arcs, linked to the volumetric representation allows multi-level geometric and volumetric analysis of A/V trees. Here, a new theory and method is presented to generate multi-level A/V tree representation of volumetric data and to compute quantitative measures of A/V tree geometry and topology at various tree hierarchies. The new method is primarily designed on arc skeleton computation followed by a tree construction based topologic and geometric analysis of the skeleton. The method starts with a volumetric A/V representation as input and generates its topologic and multi-level volumetric tree representations long with different multi-level morphometric measures. A new recursive merging and pruning algorithms are introduced to detect bad junctions and noisy branches often associated with digital geometric and topologic analysis. Also, a new notion of shortest axial path is introduced to improve the skeletal arc joining two junctions. The accuracy of the multi-level tree analysis algorithm has been evaluated using computer generated phantoms and pulmonary CT images of a pig vessel cast phantom while the reproducibility of method is evaluated using multi-user A/V separation of in vivo contrast-enhanced CT images of a pig lung at different respiratory volumes.
A Novel Approach to Develop the Lower Order Model of Multi-Input Multi-Output System
NASA Astrophysics Data System (ADS)
Rajalakshmy, P.; Dharmalingam, S.; Jayakumar, J.
2017-10-01
A mathematical model is a virtual entity that uses mathematical language to describe the behavior of a system. Mathematical models are used particularly in the natural sciences and engineering disciplines like physics, biology, and electrical engineering as well as in the social sciences like economics, sociology and political science. Physicists, Engineers, Computer scientists, and Economists use mathematical models most extensively. With the advent of high performance processors and advanced mathematical computations, it is possible to develop high performing simulators for complicated Multi Input Multi Ouptut (MIMO) systems like Quadruple tank systems, Aircrafts, Boilers etc. This paper presents the development of the mathematical model of a 500 MW utility boiler which is a highly complex system. A synergistic combination of operational experience, system identification and lower order modeling philosophy has been effectively used to develop a simplified but accurate model of a circulation system of a utility boiler which is a MIMO system. The results obtained are found to be in good agreement with the physics of the process and with the results obtained through design procedure. The model obtained can be directly used for control system studies and to realize hardware simulators for boiler testing and operator training.
Symplectic multi-particle tracking on GPUs
NASA Astrophysics Data System (ADS)
Liu, Zhicong; Qiang, Ji
2018-05-01
A symplectic multi-particle tracking model is implemented on the Graphic Processing Units (GPUs) using the Compute Unified Device Architecture (CUDA) language. The symplectic tracking model can preserve phase space structure and reduce non-physical effects in long term simulation, which is important for beam property evaluation in particle accelerators. Though this model is computationally expensive, it is very suitable for parallelization and can be accelerated significantly by using GPUs. In this paper, we optimized the implementation of the symplectic tracking model on both single GPU and multiple GPUs. Using a single GPU processor, the code achieves a factor of 2-10 speedup for a range of problem sizes compared with the time on a single state-of-the-art Central Processing Unit (CPU) node with similar power consumption and semiconductor technology. It also shows good scalability on a multi-GPU cluster at Oak Ridge Leadership Computing Facility. In an application to beam dynamics simulation, the GPU implementation helps save more than a factor of two total computing time in comparison to the CPU implementation.
A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes
NASA Astrophysics Data System (ADS)
Tao, W. K.
2017-12-01
In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), and (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF). The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitation, processes and their sensitivity on model resolution and microphysics schemes will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.
A Robust Absorbing Boundary Condition for Compressible Flows
NASA Technical Reports Server (NTRS)
Loh, Ching Y.; orgenson, Philip C. E.
2005-01-01
An absorbing non-reflecting boundary condition (NRBC) for practical computations in fluid dynamics and aeroacoustics is presented with theoretical proof. This paper is a continuation and improvement of a previous paper by the author. The absorbing NRBC technique is based on a first principle of non reflecting, which contains the essential physics that a plane wave solution of the Euler equations remains intact across the boundary. The technique is theoretically shown to work for a large class of finite volume approaches. When combined with the hyperbolic conservation laws, the NRBC is simple, robust and truly multi-dimensional; no additional implementation is needed except the prescribed physical boundary conditions. Several numerical examples in multi-dimensional spaces using two different finite volume schemes are illustrated to demonstrate its robustness in practical computations. Limitations and remedies of the technique are also discussed.
NASA Astrophysics Data System (ADS)
Yamamoto, H.; Nakajima, K.; Zhang, K.; Nanai, S.
2015-12-01
Powerful numerical codes that are capable of modeling complex coupled processes of physics and chemistry have been developed for predicting the fate of CO2 in reservoirs as well as its potential impacts on groundwater and subsurface environments. However, they are often computationally demanding for solving highly non-linear models in sufficient spatial and temporal resolutions. Geological heterogeneity and uncertainties further increase the challenges in modeling works. Two-phase flow simulations in heterogeneous media usually require much longer computational time than that in homogeneous media. Uncertainties in reservoir properties may necessitate stochastic simulations with multiple realizations. Recently, massively parallel supercomputers with more than thousands of processors become available in scientific and engineering communities. Such supercomputers may attract attentions from geoscientist and reservoir engineers for solving the large and non-linear models in higher resolutions within a reasonable time. However, for making it a useful tool, it is essential to tackle several practical obstacles to utilize large number of processors effectively for general-purpose reservoir simulators. We have implemented massively-parallel versions of two TOUGH2 family codes (a multi-phase flow simulator TOUGH2 and a chemically reactive transport simulator TOUGHREACT) on two different types (vector- and scalar-type) of supercomputers with a thousand to tens of thousands of processors. After completing implementation and extensive tune-up on the supercomputers, the computational performance was measured for three simulations with multi-million grid models, including a simulation of the dissolution-diffusion-convection process that requires high spatial and temporal resolutions to simulate the growth of small convective fingers of CO2-dissolved water to larger ones in a reservoir scale. The performance measurement confirmed that the both simulators exhibit excellent scalabilities showing almost linear speedup against number of processors up to over ten thousand cores. Generally this allows us to perform coupled multi-physics (THC) simulations on high resolution geologic models with multi-million grid in a practical time (e.g., less than a second per time step).
NASA Astrophysics Data System (ADS)
Klimentov, A.; De, K.; Jha, S.; Maeno, T.; Nilsson, P.; Oleynik, D.; Panitkin, S.; Wells, J.; Wenaus, T.
2016-10-01
The.LHC, operating at CERN, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe. ATLAS, one of the largest collaborations ever assembled in the sciences, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Management System for managing the workflow for all data processing on over 150 data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. While PanDA currently uses more than 250,000 cores with a peak performance of 0.3 petaFLOPS, LHC data taking runs require more resources than grid can possibly provide. To alleviate these challenges, LHC experiments are engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. We will describe a project aimed at integration of PanDA WMS with supercomputers in United States, in particular with Titan supercomputer at Oak Ridge Leadership Computing Facility. Current approach utilizes modified PanDA pilot framework for job submission to the supercomputers batch queues and local data management, with light-weight MPI wrappers to run single threaded workloads in parallel on LCFs multi-core worker nodes. This implementation was tested with a variety of Monte-Carlo workloads on several supercomputing platforms for ALICE and ATLAS experiments and it is in full pro duction for the ATLAS since September 2015. We will present our current accomplishments with running PanDA at supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications, such as bioinformatics and astro-particle physics.
Cloud and aerosol studies using combined CPL and MAS data
NASA Astrophysics Data System (ADS)
Vaughan, Mark A.; Rodier, Sharon; Hu, Yongxiang; McGill, Matthew J.; Holz, Robert E.
2004-11-01
Current uncertainties in the role of aerosols and clouds in the Earth's climate system limit our abilities to model the climate system and predict climate change. These limitations are due primarily to difficulties of adequately measuring aerosols and clouds on a global scale. The A-train satellites (Aqua, CALIPSO, CloudSat, PARASOL, and Aura) will provide an unprecedented opportunity to address these uncertainties. The various active and passive sensors of the A-train will use a variety of measurement techniques to provide comprehensive observations of the multi-dimensional properties of clouds and aerosols. However, to fully achieve the potential of this ensemble requires a robust data analysis framework to optimally and efficiently map these individual measurements into a comprehensive set of cloud and aerosol physical properties. In this work we introduce the Multi-Instrument Data Analysis and Synthesis (MIDAS) project, whose goal is to develop a suite of physically sound and computationally efficient algorithms that will combine active and passive remote sensing data in order to produce improved assessments of aerosol and cloud radiative and microphysical properties. These algorithms include (a) the development of an intelligent feature detection algorithm that combines inputs from both active and passive sensors, and (b) identifying recognizable multi-instrument signatures related to aerosol and cloud type derived from clusters of image pixels and the associated vertical profile information. Classification of these signatures will lead to the automated identification of aerosol and cloud types. Testing of these new algorithms is done using currently existing and readily available active and passive measurements from the Cloud Physics Lidar and the MODIS Airborne Simulator, which simulate, respectively, the CALIPSO and MODIS A-train instruments.
DOE Office of Scientific and Technical Information (OSTI.GOV)
De, K; Jha, S; Klimentov, A
2016-01-01
The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS, one of the largest collaborations ever assembled in the sciences, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Managementmore » System for managing the workflow for all data processing on over 150 data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. While PanDA currently uses more than 250,000 cores with a peak performance of 0.3 petaFLOPS, LHC data taking runs require more resources than Grid computing can possibly provide. To alleviate these challenges, LHC experiments are engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. We will describe a project aimed at integration of PanDA WMS with supercomputers in United States, Europe and Russia (in particular with Titan supercomputer at Oak Ridge Leadership Computing Facility (OLCF), MIRA supercomputer at Argonne Leadership Computing Facilities (ALCF), Supercomputer at the National Research Center Kurchatov Institute , IT4 in Ostrava and others). Current approach utilizes modified PanDA pilot framework for job submission to the supercomputers batch queues and local data management, with light-weight MPI wrappers to run single threaded workloads in parallel on LCFs multi-core worker nodes. This implementation was tested with a variety of Monte-Carlo workloads on several supercomputing platforms for ALICE and ATLAS experiments and it is in full production for the ATLAS experiment since September 2015. We will present our current accomplishments with running PanDA WMS at supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications, such as bioinformatics and astro-particle physics.« less
Compensated Crystal Assemblies for Type-II Entangled Photon Generation in Quantum Cluster States
2010-03-01
in quantum computational architectures that operate by principles entirely distinct from any based on classical physics. In contrast with other...of the SPDC spectral function, to enable applications in regions that have not been accessible with other methods. Quantum Information and Computation ...Eliminating frequency and space-time correlations in multi-photon states, PRA 64, 063815, 2001 [2]A. Zeilinger et.al. Experimental One-way computing
Yamaguchi, Satoshi; Inoue, Sayuri; Sakai, Takahiko; Abe, Tomohiro; Kitagawa, Haruaki; Imazato, Satoshi
2017-05-01
The objective of this study was to assess the effect of silica nano-filler particle diameters in a computer-aided design/manufacturing (CAD/CAM) composite resin (CR) block on physical properties at the multi-scale in silico. CAD/CAM CR blocks were modeled, consisting of silica nano-filler particles (20, 40, 60, 80, and 100 nm) and matrix (Bis-GMA/TEGDMA), with filler volume contents of 55.161%. Calculation of Young's moduli and Poisson's ratios for the block at macro-scale were analyzed by homogenization. Macro-scale CAD/CAM CR blocks (3 × 3 × 3 mm) were modeled and compressive strengths were defined when the fracture loads exceeded 6075 N. MPS values of the nano-scale models were compared by localization analysis. As the filler size decreased, Young's moduli and compressive strength increased, while Poisson's ratios and MPS decreased. All parameters were significantly correlated with the diameters of the filler particles (Pearson's correlation test, r = -0.949, 0.943, -0.951, 0.976, p < 0.05). The in silico multi-scale model established in this study demonstrates that the Young's moduli, Poisson's ratios, and compressive strengths of CAD/CAM CR blocks can be enhanced by loading silica nanofiller particles of smaller diameter. CAD/CAM CR blocks by using smaller silica nano-filler particles have a potential to increase fracture resistance.
GPU accelerated dynamic functional connectivity analysis for functional MRI data.
Akgün, Devrim; Sakoğlu, Ünal; Esquivel, Johnny; Adinoff, Bryon; Mete, Mutlu
2015-07-01
Recent advances in multi-core processors and graphics card based computational technologies have paved the way for an improved and dynamic utilization of parallel computing techniques. Numerous applications have been implemented for the acceleration of computationally-intensive problems in various computational science fields including bioinformatics, in which big data problems are prevalent. In neuroimaging, dynamic functional connectivity (DFC) analysis is a computationally demanding method used to investigate dynamic functional interactions among different brain regions or networks identified with functional magnetic resonance imaging (fMRI) data. In this study, we implemented and analyzed a parallel DFC algorithm based on thread-based and block-based approaches. The thread-based approach was designed to parallelize DFC computations and was implemented in both Open Multi-Processing (OpenMP) and Compute Unified Device Architecture (CUDA) programming platforms. Another approach developed in this study to better utilize CUDA architecture is the block-based approach, where parallelization involves smaller parts of fMRI time-courses obtained by sliding-windows. Experimental results showed that the proposed parallel design solutions enabled by the GPUs significantly reduce the computation time for DFC analysis. Multicore implementation using OpenMP on 8-core processor provides up to 7.7× speed-up. GPU implementation using CUDA yielded substantial accelerations ranging from 18.5× to 157× speed-up once thread-based and block-based approaches were combined in the analysis. Proposed parallel programming solutions showed that multi-core processor and CUDA-supported GPU implementations accelerated the DFC analyses significantly. Developed algorithms make the DFC analyses more practical for multi-subject studies with more dynamic analyses. Copyright © 2015 Elsevier Ltd. All rights reserved.
SISSY: An example of a multi-threaded, networked, object-oriented databased application
DOE Office of Scientific and Technical Information (OSTI.GOV)
Scipioni, B.; Liu, D.; Song, T.
1993-05-01
The Systems Integration Support SYstem (SISSY) is presented and its capabilities and techniques are discussed. It is fully automated data collection and analysis system supporting the SSCL`s systems analysis activities as they relate to the Physics Detector and Simulation Facility (PDSF). SISSY itself is a paradigm of effective computing on the PDSF. It uses home-grown code (C++), network programming (RPC, SNMP), relational (SYBASE) and object-oriented (ObjectStore) DBMSs, UNIX operating system services (IRIX threads, cron, system utilities, shells scripts, etc.), and third party software applications (NetCentral Station, Wingz, DataLink) all of which act together as a single application to monitor andmore » analyze the PDSF.« less
High performance MRI simulations of motion on multi-GPU systems
2014-01-01
Background MRI physics simulators have been developed in the past for optimizing imaging protocols and for training purposes. However, these simulators have only addressed motion within a limited scope. The purpose of this study was the incorporation of realistic motion, such as cardiac motion, respiratory motion and flow, within MRI simulations in a high performance multi-GPU environment. Methods Three different motion models were introduced in the Magnetic Resonance Imaging SIMULator (MRISIMUL) of this study: cardiac motion, respiratory motion and flow. Simulation of a simple Gradient Echo pulse sequence and a CINE pulse sequence on the corresponding anatomical model was performed. Myocardial tagging was also investigated. In pulse sequence design, software crushers were introduced to accommodate the long execution times in order to avoid spurious echoes formation. The displacement of the anatomical model isochromats was calculated within the Graphics Processing Unit (GPU) kernel for every timestep of the pulse sequence. Experiments that would allow simulation of custom anatomical and motion models were also performed. Last, simulations of motion with MRISIMUL on single-node and multi-node multi-GPU systems were examined. Results Gradient Echo and CINE images of the three motion models were produced and motion-related artifacts were demonstrated. The temporal evolution of the contractility of the heart was presented through the application of myocardial tagging. Better simulation performance and image quality were presented through the introduction of software crushers without the need to further increase the computational load and GPU resources. Last, MRISIMUL demonstrated an almost linear scalable performance with the increasing number of available GPU cards, in both single-node and multi-node multi-GPU computer systems. Conclusions MRISIMUL is the first MR physics simulator to have implemented motion with a 3D large computational load on a single computer multi-GPU configuration. The incorporation of realistic motion models, such as cardiac motion, respiratory motion and flow may benefit the design and optimization of existing or new MR pulse sequences, protocols and algorithms, which examine motion related MR applications. PMID:24996972
NASA Technical Reports Server (NTRS)
Martinez, Andres; Benavides, Jose Victor; Ormsby, Steve L.; GuarnerosLuna, Ali
2014-01-01
Synchronized Position Hold, Engage, Reorient, Experimental Satellites (SPHERES) are bowling-ball sized satellites that provide a test bed for development and research into multi-body formation flying, multi-spacecraft control algorithms, and free-flying physical and material science investigations. Up to three self-contained free-flying satellites can fly within the cabin of the International Space Station (ISS), performing flight formations, testing of control algorithms or as a platform for investigations requiring this unique free-flying test environment. Each satellite is a self-contained unit with power, propulsion, computers, navigation equipment, and provides physical and electrical connections (via standardized expansion ports) for Principal Investigator (PI) provided hardware and sensors.
Zheng, Wei; Yan, Xiaoyong; Zhao, Wei; Qian, Chengshan
2017-12-20
A novel large-scale multi-hop localization algorithm based on regularized extreme learning is proposed in this paper. The large-scale multi-hop localization problem is formulated as a learning problem. Unlike other similar localization algorithms, the proposed algorithm overcomes the shortcoming of the traditional algorithms which are only applicable to an isotropic network, therefore has a strong adaptability to the complex deployment environment. The proposed algorithm is composed of three stages: data acquisition, modeling and location estimation. In data acquisition stage, the training information between nodes of the given network is collected. In modeling stage, the model among the hop-counts and the physical distances between nodes is constructed using regularized extreme learning. In location estimation stage, each node finds its specific location in a distributed manner. Theoretical analysis and several experiments show that the proposed algorithm can adapt to the different topological environments with low computational cost. Furthermore, high accuracy can be achieved by this method without setting complex parameters.
A blended continuous–discontinuous finite element method for solving the multi-fluid plasma model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sousa, E.M., E-mail: sousae@uw.edu; Shumlak, U., E-mail: shumlak@uw.edu
The multi-fluid plasma model represents electrons, multiple ion species, and multiple neutral species as separate fluids that interact through short-range collisions and long-range electromagnetic fields. The model spans a large range of temporal and spatial scales, which renders the model stiff and presents numerical challenges. To address the large range of timescales, a blended continuous and discontinuous Galerkin method is proposed, where the massive ion and neutral species are modeled using an explicit discontinuous Galerkin method while the electrons and electromagnetic fields are modeled using an implicit continuous Galerkin method. This approach is able to capture large-gradient ion and neutralmore » physics like shock formation, while resolving high-frequency electron dynamics in a computationally efficient manner. The details of the Blended Finite Element Method (BFEM) are presented. The numerical method is benchmarked for accuracy and tested using two-fluid one-dimensional soliton problem and electromagnetic shock problem. The results are compared to conventional finite volume and finite element methods, and demonstrate that the BFEM is particularly effective in resolving physics in stiff problems involving realistic physical parameters, including realistic electron mass and speed of light. The benefit is illustrated by computing a three-fluid plasma application that demonstrates species separation in multi-component plasmas.« less
Heat Transfer on a Film-Cooled Blade - Effect of Hole Physics
NASA Technical Reports Server (NTRS)
Garg, Vijay K.; Rigby, David L.
1998-01-01
A multi-block, three-dimensional Navier-Stokes code has been used to study the within-hole and near-hole physics in relation to heat transfer on a film-cooled blade. The flow domain consists of the coolant flow through the plenum and hole-pipes for the three staggered rows of shower-head holes on the VK1 rotor, and the main flow over the blade. A multi-block grid is generated that is nearly orthogonal to the various surfaces. It may be noted that for the VK1 rotor the shower-head holes are inclined at 30 deg. to the spanwise direction, and are normal to the streamwise direction on the blade. Wilcox's k-omega turbulence model is used. The present study provides a much better comparison for the heat transfer coefficient at the blade mid-span with the experimental data than an earlier analysis wherein coolant velocity and temperature distributions were specified at the hole exits rather than extending the computational domain into the hole-pipe and plenum. Details of the distributions of coolant velocity, temperature, k and omega at the hole exits are also presented.
Optical fibre multi-parameter sensing with secure cloud based signal capture and processing
NASA Astrophysics Data System (ADS)
Newe, Thomas; O'Connell, Eoin; Meere, Damien; Yuan, Hongwei; Leen, Gabriel; O'Keeffe, Sinead; Lewis, Elfed
2016-05-01
Recent advancements in cloud computing technologies in the context of optical and optical fibre based systems are reported. The proliferation of real time and multi-channel based sensor systems represents significant growth in data volume. This coupled with a growing need for security presents many challenges and presents a huge opportunity for an evolutionary step in the widespread application of these sensing technologies. A tiered infrastructural system approach is adopted that is designed to facilitate the delivery of Optical Fibre-based "SENsing as a Service- SENaaS". Within this infrastructure, novel optical sensing platforms, deployed within different environments, are interfaced with a Cloud-based backbone infrastructure which facilitates the secure collection, storage and analysis of real-time data. Feedback systems, which harness this data to affect a change within the monitored location/environment/condition, are also discussed. The cloud based system presented here can also be used with chemical and physical sensors that require real-time data analysis, processing and feedback.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Procassini, R.J.
1997-12-31
The fine-scale, multi-space resolution that is envisioned for accurate simulations of complex weapons systems in three spatial dimensions implies flop-rate and memory-storage requirements that will only be obtained in the near future through the use of parallel computational techniques. Since the Monte Carlo transport models in these simulations usually stress both of these computational resources, they are prime candidates for parallelization. The MONACO Monte Carlo transport package, which is currently under development at LLNL, will utilize two types of parallelism within the context of a multi-physics design code: decomposition of the spatial domain across processors (spatial parallelism) and distribution ofmore » particles in a given spatial subdomain across additional processors (particle parallelism). This implementation of the package will utilize explicit data communication between domains (message passing). Such a parallel implementation of a Monte Carlo transport model will result in non-deterministic communication patterns. The communication of particles between subdomains during a Monte Carlo time step may require a significant level of effort to achieve a high parallel efficiency.« less
2014-06-12
distribution is unlimited. Ballistic-Failure Mechanisms in Gas Metal Arc Welds of Mil A46100 Armor-Grade Steel : A Computational Investigation The views...Welds of Mil A46100 Armor-Grade Steel : A Computational Investigation Report Title In our recent work, a multi-physics computational model for the...introduction of the sixth module in the present work in recognition of the fact that in thick steel GMAW weldments, the overall ballistic performance
ERIC Educational Resources Information Center
Vieira, Rodrigo Drumond; Kelly, Gregory J.
2014-01-01
In this paper, we present and apply a multi-level method for discourse analysis in science classrooms. This method is based on the structure of human activity (activity, actions, and operations) and it was applied to study a pre-service physics teacher methods course. We argue that such an approach, based on a cultural psychological perspective,…
The Impact of Learner Characteristics on the Multi-Dimensional Construct of Social Presence
ERIC Educational Resources Information Center
Mykota, David
2017-01-01
This study explored the impact of learner characteristics on the multi-dimensional construct of social presence as measured by the computer-mediated communication questionnaire. Using Multiple Analysis of Variance findings reveal that the number of online courses taken and computer-mediated communication experience significantly affect the…
Electro-Optic Computing Architectures: Volume II. Components and System Design and Analysis
1998-02-01
The objective of the Electro - Optic Computing Architecture (EOCA) program was to develop multi-function electro - optic interfaces and optical...interconnect units to enhance the performance of parallel processor systems and form the building blocks for future electro - optic computing architectures...Specifically, three multi-function interface modules were targeted for development - an Electro - Optic Interface (EOI), an Optical Interconnection Unit
CFD Methods and Tools for Multi-Element Airfoil Analysis
NASA Technical Reports Server (NTRS)
Rogers, Stuart E.; George, Michael W. (Technical Monitor)
1995-01-01
This lecture will discuss the computational tools currently available for high-lift multi-element airfoil analysis. It will present an overview of a number of different numerical approaches, their current capabilities, short-comings, and computational costs. The lecture will be limited to viscous methods, including inviscid/boundary layer coupling methods, and incompressible and compressible Reynolds-averaged Navier-Stokes methods. Both structured and unstructured grid generation approaches will be presented. Two different structured grid procedures are outlined, one which uses multi-block patched grids, the other uses overset chimera grids. Turbulence and transition modeling will be discussed.
NASA Astrophysics Data System (ADS)
Zimoń, Małgorzata; Sawko, Robert; Emerson, David; Thompson, Christopher
2017-11-01
Uncertainty quantification (UQ) is increasingly becoming an indispensable tool for assessing the reliability of computational modelling. Efficient handling of stochastic inputs, such as boundary conditions, physical properties or geometry, increases the utility of model results significantly. We discuss the application of non-intrusive generalised polynomial chaos techniques in the context of fluid engineering simulations. Deterministic and Monte Carlo integration rules are applied to a set of problems, including ordinary differential equations and the computation of aerodynamic parameters subject to random perturbations. In particular, we analyse acoustic wave propagation in a heterogeneous medium to study the effects of mesh resolution, transients, number and variability of stochastic inputs. We consider variants of multi-level Monte Carlo and perform a novel comparison of the methods with respect to numerical and parametric errors, as well as computational cost. The results provide a comprehensive view of the necessary steps in UQ analysis and demonstrate some key features of stochastic fluid flow systems.
Machine learning action parameters in lattice quantum chromodynamics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shanahan, Phiala; Trewartha, Daneil; Detmold, William
Numerical lattice quantum chromodynamics studies of the strong interaction underpin theoretical understanding of many aspects of particle and nuclear physics. Such studies require significant computing resources to undertake. A number of proposed methods promise improved efficiency of lattice calculations, and access to regions of parameter space that are currently computationally intractable, via multi-scale action-matching approaches that necessitate parametric regression of generated lattice datasets. The applicability of machine learning to this regression task is investigated, with deep neural networks found to provide an efficient solution even in cases where approaches such as principal component analysis fail. Finally, the high information contentmore » and complex symmetries inherent in lattice QCD datasets require custom neural network layers to be introduced and present opportunities for further development.« less
Machine learning action parameters in lattice quantum chromodynamics
Shanahan, Phiala; Trewartha, Daneil; Detmold, William
2018-05-16
Numerical lattice quantum chromodynamics studies of the strong interaction underpin theoretical understanding of many aspects of particle and nuclear physics. Such studies require significant computing resources to undertake. A number of proposed methods promise improved efficiency of lattice calculations, and access to regions of parameter space that are currently computationally intractable, via multi-scale action-matching approaches that necessitate parametric regression of generated lattice datasets. The applicability of machine learning to this regression task is investigated, with deep neural networks found to provide an efficient solution even in cases where approaches such as principal component analysis fail. Finally, the high information contentmore » and complex symmetries inherent in lattice QCD datasets require custom neural network layers to be introduced and present opportunities for further development.« less
Wang, Gang; Wang, Yalin
2017-02-15
In this paper, we propose a heat kernel based regional shape descriptor that may be capable of better exploiting volumetric morphological information than other available methods, thereby improving statistical power on brain magnetic resonance imaging (MRI) analysis. The mechanism of our analysis is driven by the graph spectrum and the heat kernel theory, to capture the volumetric geometry information in the constructed tetrahedral meshes. In order to capture profound brain grey matter shape changes, we first use the volumetric Laplace-Beltrami operator to determine the point pair correspondence between white-grey matter and CSF-grey matter boundary surfaces by computing the streamlines in a tetrahedral mesh. Secondly, we propose multi-scale grey matter morphology signatures to describe the transition probability by random walk between the point pairs, which reflects the inherent geometric characteristics. Thirdly, a point distribution model is applied to reduce the dimensionality of the grey matter morphology signatures and generate the internal structure features. With the sparse linear discriminant analysis, we select a concise morphology feature set with improved classification accuracies. In our experiments, the proposed work outperformed the cortical thickness features computed by FreeSurfer software in the classification of Alzheimer's disease and its prodromal stage, i.e., mild cognitive impairment, on publicly available data from the Alzheimer's Disease Neuroimaging Initiative. The multi-scale and physics based volumetric structure feature may bring stronger statistical power than some traditional methods for MRI-based grey matter morphology analysis. Copyright © 2016 Elsevier Inc. All rights reserved.
Advanced computations in plasma physics
NASA Astrophysics Data System (ADS)
Tang, W. M.
2002-05-01
Scientific simulation in tandem with theory and experiment is an essential tool for understanding complex plasma behavior. In this paper we review recent progress and future directions for advanced simulations in magnetically confined plasmas with illustrative examples chosen from magnetic confinement research areas such as microturbulence, magnetohydrodynamics, magnetic reconnection, and others. Significant recent progress has been made in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics, giving increasingly good agreement between experimental observations and computational modeling. This was made possible by innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning widely disparate temporal and spatial scales together with access to powerful new computational resources. In particular, the fusion energy science community has made excellent progress in developing advanced codes for which computer run-time and problem size scale well with the number of processors on massively parallel machines (MPP's). A good example is the effective usage of the full power of multi-teraflop (multi-trillion floating point computations per second) MPP's to produce three-dimensional, general geometry, nonlinear particle simulations which have accelerated progress in understanding the nature of turbulence self-regulation by zonal flows. It should be emphasized that these calculations, which typically utilized billions of particles for thousands of time-steps, would not have been possible without access to powerful present generation MPP computers and the associated diagnostic and visualization capabilities. In general, results from advanced simulations provide great encouragement for being able to include increasingly realistic dynamics to enable deeper physics insights into plasmas in both natural and laboratory environments. The associated scientific excitement should serve to stimulate improved cross-cutting collaborations with other fields and also to help attract bright young talent to plasma science.
Xpatch prediction improvements to support multiple ATR applications
NASA Astrophysics Data System (ADS)
Andersh, Dennis J.; Lee, Shung W.; Moore, John T.; Sullivan, Douglas P.; Hughes, Jeff A.; Ling, Hao
1998-08-01
This paper describes an electromagnetic computer prediction code for generating radar cross section (RCS), time-domain signature sand synthetic aperture radar (SAR) images of realistic 3D vehicles. The vehicle, typically an airplane or a ground vehicle, is represented by a computer-aided design (CAD) file with triangular facets, IGES curved surfaces, or solid geometries.The computer code, Xpatch, based on the shooting-and-bouncing-ray technique, is used to calculate the polarimetric radar return from the vehicles represented by these different CAD files. Xpatch computers the first- bounce physical optics (PO) plus the physical theory of diffraction (PTD) contributions. Xpatch calculates the multi-bounce ray contributions by using geometric optics and PO for complex vehicles with materials. It has been found that the multi-bounce calculations, the radar return in typically 10 to 15 dB too low. Examples of predicted range profiles, SAR, imagery, and RCS for several different geometries are compared with measured data to demonstrate the quality of the predictions. Recent enhancements to Xpatch include improvements for millimeter wave applications and hybridization with finite element method for small geometric features and augmentation of additional IGES entities to support trimmed and untrimmed surfaces.
Multi-scale and Multi-physics Numerical Methods for Modeling Transport in Mesoscopic Systems
2014-10-13
function and wide band Fast multipole methods for Hankel waves. (2) a new linear scaling discontinuous Galerkin density functional theory, which provide a...inflow boundary condition for Wigner quantum transport equations. Also, a book titled "Computational Methods for Electromagnetic Phenomena...equationsin layered media with FMM for Bessel functions , Science China Mathematics, (12 2013): 2561. doi: TOTAL: 6 Number of Papers published in peer
NASA Astrophysics Data System (ADS)
Teodorescu, Liliana; Britton, David; Glover, Nigel; Heinrich, Gudrun; Lauret, Jérôme; Naumann, Axel; Speer, Thomas; Teixeira-Dias, Pedro
2012-06-01
ACAT2011 This volume of Journal of Physics: Conference Series is dedicated to scientific contributions presented at the 14th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2011) which took place on 5-7 September 2011 at Brunel University, UK. The workshop series, which began in 1990 in Lyon, France, brings together computer science researchers and practitioners, and researchers from particle physics and related fields in order to explore and confront the boundaries of computing and of automatic data analysis and theoretical calculation techniques. It is a forum for the exchange of ideas among the fields, exploring and promoting cutting-edge computing, data analysis and theoretical calculation techniques in fundamental physics research. This year's edition of the workshop brought together over 100 participants from all over the world. 14 invited speakers presented key topics on computing ecosystems, cloud computing, multivariate data analysis, symbolic and automatic theoretical calculations as well as computing and data analysis challenges in astrophysics, bioinformatics and musicology. Over 80 other talks and posters presented state-of-the art developments in the areas of the workshop's three tracks: Computing Technologies, Data Analysis Algorithms and Tools, and Computational Techniques in Theoretical Physics. Panel and round table discussions on data management and multivariate data analysis uncovered new ideas and collaboration opportunities in the respective areas. This edition of ACAT was generously sponsored by the Science and Technology Facility Council (STFC), the Institute for Particle Physics Phenomenology (IPPP) at Durham University, Brookhaven National Laboratory in the USA and Dell. We would like to thank all the participants of the workshop for the high level of their scientific contributions and for the enthusiastic participation in all its activities which were, ultimately, the key factors in the success of the workshop. Further information on ACAT 2011 can be found at http://acat2011.cern.ch Dr Liliana Teodorescu Brunel University ACATgroup The PDF also contains details of the workshop's committees and sponsors.
DOT National Transportation Integrated Search
1976-05-01
As part of its activity under the Rail Equipment Safety Project, computer programs for track/train dynamics analysis are being developed and modified. As part of this effort, derailment behavior of trains negotiating curves under buff or draft has be...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Simunovic, Srdjan; Piro, Markus H.A.
Thermochimica is a software library that determines a unique combination of phases and their compositions at thermochemical equilibrium. Thermochimica can be used for stand-alone calculations or it can be directly coupled to other codes. This release of the software does not have a graphical user interface (GUI) and it can be executed from the command line or from an Application Programming Interface (API). Also, it is not intended for thermodynamic model development or for constructing phase diagrams. The main purpose of the software is to be directly coupled with a multi-physics code to provide material properties and boundary conditions formore » various physical phenomena. Significant research efforts have been dedicated to enhance computational performance through advanced algorithm development, such as improved estimation techniques and non-linear solvers. Various useful parameters can be provided as output from Thermochimica, such as: determination of which phases are stable at equilibrium, the mass of solution species and phases at equilibrium, mole fractions of solution phase constituents, thermochemical activities (which are related to partial pressures for gaseous species), chemical potentials of solution species and phases, and integral Gibbs energy (referenced relative to standard state). The overall goal is to provide an open source computational tool to enhance the predictive capability of multi-physics codes without significantly impeding computational performance.« less
NASA Workshop on Computational Structural Mechanics 1987, part 3
NASA Technical Reports Server (NTRS)
Sykes, Nancy P. (Editor)
1989-01-01
Computational Structural Mechanics (CSM) topics are explored. Algorithms and software for nonlinear structural dynamics, concurrent algorithms for transient finite element analysis, computational methods and software systems for dynamics and control of large space structures, and the use of multi-grid for structural analysis are discussed.
NASA Astrophysics Data System (ADS)
Barreiro, F. H.; Borodin, M.; De, K.; Golubkov, D.; Klimentov, A.; Maeno, T.; Mashinistov, R.; Padolski, S.; Wenaus, T.; ATLAS Collaboration
2017-10-01
The second generation of the ATLAS Production System called ProdSys2 is a distributed workload manager that runs daily hundreds of thousands of jobs, from dozens of different ATLAS specific workflows, across more than hundred heterogeneous sites. It achieves high utilization by combining dynamic job definition based on many criteria, such as input and output size, memory requirements and CPU consumption, with manageable scheduling policies and by supporting different kind of computational resources, such as GRID, clouds, supercomputers and volunteer-computers. The system dynamically assigns a group of jobs (task) to a group of geographically distributed computing resources. Dynamic assignment and resources utilization is one of the major features of the system, it didn’t exist in the earliest versions of the production system where Grid resources topology was predefined using national or/and geographical pattern. Production System has a sophisticated job fault-recovery mechanism, which efficiently allows to run multi-Terabyte tasks without human intervention. We have implemented “train” model and open-ended production which allow to submit tasks automatically as soon as new set of data is available and to chain physics groups data processing and analysis with central production by the experiment. We present an overview of the ATLAS Production System and its major components features and architecture: task definition, web user interface and monitoring. We describe the important design decisions and lessons learned from an operational experience during the first year of LHC Run2. We also report the performance of the designed system and how various workflows, such as data (re)processing, Monte-Carlo and physics group production, users analysis, are scheduled and executed within one production system on heterogeneous computing resources.
Electromagnetic Physics Models for Parallel Computing Architectures
NASA Astrophysics Data System (ADS)
Amadio, G.; Ananya, A.; Apostolakis, J.; Aurora, A.; Bandieramonte, M.; Bhattacharyya, A.; Bianchini, C.; Brun, R.; Canal, P.; Carminati, F.; Duhem, L.; Elvira, D.; Gheata, A.; Gheata, M.; Goulas, I.; Iope, R.; Jun, S. Y.; Lima, G.; Mohanty, A.; Nikitina, T.; Novak, M.; Pokorski, W.; Ribon, A.; Seghal, R.; Shadura, O.; Vallecorsa, S.; Wenzel, S.; Zhang, Y.
2016-10-01
The recent emergence of hardware architectures characterized by many-core or accelerated processors has opened new opportunities for concurrent programming models taking advantage of both SIMD and SIMT architectures. GeantV, a next generation detector simulation, has been designed to exploit both the vector capability of mainstream CPUs and multi-threading capabilities of coprocessors including NVidia GPUs and Intel Xeon Phi. The characteristics of these architectures are very different in terms of the vectorization depth and type of parallelization needed to achieve optimal performance. In this paper we describe implementation of electromagnetic physics models developed for parallel computing architectures as a part of the GeantV project. Results of preliminary performance evaluation and physics validation are presented as well.
Cross-platform validation and analysis environment for particle physics
NASA Astrophysics Data System (ADS)
Chekanov, S. V.; Pogrebnyak, I.; Wilbern, D.
2017-11-01
A multi-platform validation and analysis framework for public Monte Carlo simulation for high-energy particle collisions is discussed. The front-end of this framework uses the Python programming language, while the back-end is written in Java, which provides a multi-platform environment that can be run from a web browser and can easily be deployed at the grid sites. The analysis package includes all major software tools used in high-energy physics, such as Lorentz vectors, jet algorithms, histogram packages, graphic canvases, and tools for providing data access. This multi-platform software suite, designed to minimize OS-specific maintenance and deployment time, is used for online validation of Monte Carlo event samples through a web interface.
NASA Astrophysics Data System (ADS)
Wang, Jianxiong
2014-06-01
This volume of Journal of Physics: Conference Series is dedicated to scientific contributions presented at the 15th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2013) which took place on 16-21 May 2013 at the Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China. The workshop series brings together computer science researchers and practitioners, and researchers from particle physics and related fields to explore and confront the boundaries of computing and of automatic data analysis and theoretical calculation techniques. This year's edition of the workshop brought together over 120 participants from all over the world. 18 invited speakers presented key topics on the universe in computer, Computing in Earth Sciences, multivariate data analysis, automated computation in Quantum Field Theory as well as computing and data analysis challenges in many fields. Over 70 other talks and posters presented state-of-the-art developments in the areas of the workshop's three tracks: Computing Technologies, Data Analysis Algorithms and Tools, and Computational Techniques in Theoretical Physics. The round table discussions on open-source, knowledge sharing and scientific collaboration stimulate us to think over the issue in the respective areas. ACAT 2013 was generously sponsored by the Chinese Academy of Sciences (CAS), National Natural Science Foundation of China (NFSC), Brookhaven National Laboratory in the USA (BNL), Peking University (PKU), Theoretical Physics Cernter for Science facilities of CAS (TPCSF-CAS) and Sugon. We would like to thank all the participants for their scientific contributions and for the en- thusiastic participation in all its activities of the workshop. Further information on ACAT 2013 can be found at http://acat2013.ihep.ac.cn. Professor Jianxiong Wang Institute of High Energy Physics Chinese Academy of Science Details of committees and sponsors are available in the PDF
NASA Astrophysics Data System (ADS)
Dufoyer, A.; Lecoq, N.; Massei, N.; Marechal, J. C.
2017-12-01
Physics-based modeling of karst systems remains almost impossible without enough accurate information about the inner physical characteristics. Usually, the only available hydrodynamic information is the flow rate at the karst outlet. Numerous works in the past decades have used and proven the usefulness of time-series analysis and spectral techniques applied to spring flow, precipitations or even physico-chemical parameters, for interpreting karst hydrological functioning. However, identifying or interpreting the karst systems physical features that control statistical or spectral characteristics of spring flow variations is still challenging, not to say sometimes controversial. The main objective of this work is to determine how the statistical and spectral characteristics of the hydrodynamic signal at karst springs can be related to inner physical and hydraulic properties. In order to address this issue, we undertake an empirical approach based on the use of both distributed and physics-based models, and on synthetic systems responses. The first step of the research is to conduct a sensitivity analysis of time-series/spectral methods to karst hydraulic and physical properties. For this purpose, forward modeling of flow through several simple, constrained and synthetic cases in response to precipitations is undertaken. It allows us to quantify how the statistical and spectral characteristics of flow at the outlet are sensitive to changes (i) in conduit geometries, and (ii) in hydraulic parameters of the system (matrix/conduit exchange rate, matrix hydraulic conductivity and storativity). The flow differential equations resolved by MARTHE, a computer code developed by the BRGM, allows karst conduits modeling. From signal processing on simulated spring responses, we hope to determine if specific frequencies are always modified, thanks to Fourier series and multi-resolution analysis. We also hope to quantify which parameters are the most variable with auto-correlation analysis: first results seem to show higher variations due to conduit conductivity than the ones due to matrix/conduit exchange rate. Future steps will be using another computer code, based on double-continuum approach and allowing turbulent conduit flow, and modeling a natural system.
NASA Astrophysics Data System (ADS)
Khuwaileh, Bassam
High fidelity simulation of nuclear reactors entails large scale applications characterized with high dimensionality and tremendous complexity where various physics models are integrated in the form of coupled models (e.g. neutronic with thermal-hydraulic feedback). Each of the coupled modules represents a high fidelity formulation of the first principles governing the physics of interest. Therefore, new developments in high fidelity multi-physics simulation and the corresponding sensitivity/uncertainty quantification analysis are paramount to the development and competitiveness of reactors achieved through enhanced understanding of the design and safety margins. Accordingly, this dissertation introduces efficient and scalable algorithms for performing efficient Uncertainty Quantification (UQ), Data Assimilation (DA) and Target Accuracy Assessment (TAA) for large scale, multi-physics reactor design and safety problems. This dissertation builds upon previous efforts for adaptive core simulation and reduced order modeling algorithms and extends these efforts towards coupled multi-physics models with feedback. The core idea is to recast the reactor physics analysis in terms of reduced order models. This can be achieved via identifying the important/influential degrees of freedom (DoF) via the subspace analysis, such that the required analysis can be recast by considering the important DoF only. In this dissertation, efficient algorithms for lower dimensional subspace construction have been developed for single physics and multi-physics applications with feedback. Then the reduced subspace is used to solve realistic, large scale forward (UQ) and inverse problems (DA and TAA). Once the elite set of DoF is determined, the uncertainty/sensitivity/target accuracy assessment and data assimilation analysis can be performed accurately and efficiently for large scale, high dimensional multi-physics nuclear engineering applications. Hence, in this work a Karhunen-Loeve (KL) based algorithm previously developed to quantify the uncertainty for single physics models is extended for large scale multi-physics coupled problems with feedback effect. Moreover, a non-linear surrogate based UQ approach is developed, used and compared to performance of the KL approach and brute force Monte Carlo (MC) approach. On the other hand, an efficient Data Assimilation (DA) algorithm is developed to assess information about model's parameters: nuclear data cross-sections and thermal-hydraulics parameters. Two improvements are introduced in order to perform DA on the high dimensional problems. First, a goal-oriented surrogate model can be used to replace the original models in the depletion sequence (MPACT -- COBRA-TF - ORIGEN). Second, approximating the complex and high dimensional solution space with a lower dimensional subspace makes the sampling process necessary for DA possible for high dimensional problems. Moreover, safety analysis and design optimization depend on the accurate prediction of various reactor attributes. Predictions can be enhanced by reducing the uncertainty associated with the attributes of interest. Accordingly, an inverse problem can be defined and solved to assess the contributions from sources of uncertainty; and experimental effort can be subsequently directed to further improve the uncertainty associated with these sources. In this dissertation a subspace-based gradient-free and nonlinear algorithm for inverse uncertainty quantification namely the Target Accuracy Assessment (TAA) has been developed and tested. The ideas proposed in this dissertation were first validated using lattice physics applications simulated using SCALE6.1 package (Pressurized Water Reactor (PWR) and Boiling Water Reactor (BWR) lattice models). Ultimately, the algorithms proposed her were applied to perform UQ and DA for assembly level (CASL progression problem number 6) and core wide problems representing Watts Bar Nuclear 1 (WBN1) for cycle 1 of depletion (CASL Progression Problem Number 9) modeled via simulated using VERA-CS which consists of several multi-physics coupled models. The analysis and algorithms developed in this dissertation were encoded and implemented in a newly developed tool kit algorithms for Reduced Order Modeling based Uncertainty/Sensitivity Estimator (ROMUSE).
An Integrated Nonlinear Analysis library - (INA) for solar system plasma turbulence
NASA Astrophysics Data System (ADS)
Munteanu, Costel; Kovacs, Peter; Echim, Marius; Koppan, Andras
2014-05-01
We present an integrated software library dedicated to the analysis of time series recorded in space and adapted to investigate turbulence, intermittency and multifractals. The library is written in MATLAB and provides a graphical user interface (GUI) customized for the analysis of space physics data available online like: Coordinated Data Analysis Web (CDAWeb), Automated Multi Dataset Analysis system (AMDA), Planetary Science Archive (PSA), World Data Center Kyoto (WDC), Ulysses Final Archive (UFA) and Cluster Active Archive (CAA). Three main modules are already implemented in INA : the Power Spectral Density (PSD) Analysis, the Wavelet and Intemittency Analysis and the Probability Density Functions (PDF) analysis.The layered structure of the software allows the user to easily switch between different modules/methods while retaining the same time interval for the analysis. The wavelet analysis module includes algorithms to compute and analyse the PSD, the Scalogram, the Local Intermittency Measure (LIM) or the Flatness parameter. The PDF analysis module includes algorithms for computing the PDFs for a range of scales and parameters fully customizable by the user; it also computes the Flatness parameter and enables fast comparison with standard PDF profiles like, for instance, the Gaussian PDF. The library has been already tested on Cluster and Venus Express data and we will show relevant examples. Research supported by the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement no 313038/STORM, and a grant of the Romanian Ministry of National Education, CNCS UEFISCDI, project number PN-II-ID PCE-2012-4-0418.
Software Integration in Multi-scale Simulations: the PUPIL System
NASA Astrophysics Data System (ADS)
Torras, J.; Deumens, E.; Trickey, S. B.
2006-10-01
The state of the art for computational tools in both computational chemistry and computational materials physics includes many algorithms and functionalities which are implemented again and again. Several projects aim to reduce, eliminate, or avoid this problem. Most such efforts seem to be focused within a particular specialty, either quantum chemistry or materials physics. Multi-scale simulations, by their very nature however, cannot respect that specialization. In simulation of fracture, for example, the energy gradients that drive the molecular dynamics (MD) come from a quantum mechanical treatment that most often derives from quantum chemistry. That “QM” region is linked to a surrounding “CM” region in which potentials yield the forces. The approach therefore requires the integration or at least inter-operation of quantum chemistry and materials physics algorithms. The same problem occurs in “QM/MM” simulations in computational biology. The challenge grows if pattern recognition or other analysis codes of some kind must be used as well. The most common mode of inter-operation is user intervention: codes are modified as needed and data files are managed “by hand” by the user (interactively and via shell scripts). User intervention is however inefficient by nature, difficult to transfer to the community, and prone to error. Some progress (e.g Sethna’s work at Cornell [C.R. Myers et al., Mat. Res. Soc. Symp. Proc., 538(1999) 509, C.-S. Chen et al., Poster presented at the Material Research Society Meeting (2000)]) has been made on using Python scripts to achieve a more efficient level of interoperation. In this communication we present an alternative approach to merging current working packages without the necessity of major recoding and with only a relatively light wrapper interface. The scheme supports communication among the different components required for a given multi-scale calculation and access to the functionalities of those components for the potential user. A general main program allows the management of every package with a special communication protocol between their interfaces following the directives introduced by the user which are stored in an XML structured file. The initial prototype of the PUPIL (Program for User Packages Interfacing and Linking) system has been done using Java as a fast, easy prototyping object oriented (OO) language. In order to test it, we have applied this prototype to a previously studied problem, the fracture of a silica nanorod. We did so joining two different packages to do a QM/MD calculation. The results show the potential for this software system to do different kind of simulations and its simplicity of maintenance.
Ionizing Shocks in Argon. Part 2: Transient and Multi-Dimensional Effects (Preprint)
2010-09-09
stability in ionizing monatomic gases. Part 1. Argon ,” J. Fluid Mech., 84, 55 (1978). 2M. P. F. Bristow and I. I. Glass, “ Polarizability of singly...Article 3. DATES COVERED (From - To) 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Ionizing Shocks in Argon . Part 2: Transient...Physics. 14. ABSTRACT We extend the computations of ionizing shocks in argon to unsteady and multi-dimensional, using a collisional-radiative
DOE Office of Scientific and Technical Information (OSTI.GOV)
David Andrs; Ray Berry; Derek Gaston
The document contains the simulation results of a steady state model PWR problem with the RELAP-7 code. The RELAP-7 code is the next generation nuclear reactor system safety analysis code being developed at Idaho National Laboratory (INL). The code is based on INL's modern scientific software development framework - MOOSE (Multi-Physics Object-Oriented Simulation Environment). This report summarizes the initial results of simulating a model steady-state single phase PWR problem using the current version of the RELAP-7 code. The major purpose of this demonstration simulation is to show that RELAP-7 code can be rapidly developed to simulate single-phase reactor problems. RELAP-7more » is a new project started on October 1st, 2011. It will become the main reactor systems simulation toolkit for RISMC (Risk Informed Safety Margin Characterization) and the next generation tool in the RELAP reactor safety/systems analysis application series (the replacement for RELAP5). The key to the success of RELAP-7 is the simultaneous advancement of physical models, numerical methods, and software design while maintaining a solid user perspective. Physical models include both PDEs (Partial Differential Equations) and ODEs (Ordinary Differential Equations) and experimental based closure models. RELAP-7 will eventually utilize well posed governing equations for multiphase flow, which can be strictly verified. Closure models used in RELAP5 and newly developed models will be reviewed and selected to reflect the progress made during the past three decades. RELAP-7 uses modern numerical methods, which allow implicit time integration, higher order schemes in both time and space, and strongly coupled multi-physics simulations. RELAP-7 is written with object oriented programming language C++. Its development follows modern software design paradigms. The code is easy to read, develop, maintain, and couple with other codes. Most importantly, the modern software design allows the RELAP-7 code to evolve with time. RELAP-7 is a MOOSE-based application. MOOSE (Multiphysics Object-Oriented Simulation Environment) is a framework for solving computational engineering problems in a well-planned, managed, and coordinated way. By leveraging millions of lines of open source software packages, such as PETSC (a nonlinear solver developed at Argonne National Laboratory) and LibMesh (a Finite Element Analysis package developed at University of Texas), MOOSE significantly reduces the expense and time required to develop new applications. Numerical integration methods and mesh management for parallel computation are provided by MOOSE. Therefore RELAP-7 code developers only need to focus on physics and user experiences. By using the MOOSE development environment, RELAP-7 code is developed by following the same modern software design paradigms used for other MOOSE development efforts. There are currently over 20 different MOOSE based applications ranging from 3-D transient neutron transport, detailed 3-D transient fuel performance analysis, to long-term material aging. Multi-physics and multiple dimensional analyses capabilities can be obtained by coupling RELAP-7 and other MOOSE based applications and by leveraging with capabilities developed by other DOE programs. This allows restricting the focus of RELAP-7 to systems analysis-type simulations and gives priority to retain and significantly extend RELAP5's capabilities.« less
Suzuki, Yuma; Shimizu, Tetsuhide; Yang, Ming
2017-01-01
The quantitative evaluation of the biomolecules transport with multi-physics in nano/micro scale is demanded in order to optimize the design of microfluidics device for the biomolecules detection with high detection sensitivity and rapid diagnosis. This paper aimed to investigate the effectivity of the computational simulation using the numerical model of the biomolecules transport with multi-physics near a microchannel surface on the development of biomolecules-detection devices. The biomolecules transport with fluid drag force, electric double layer (EDL) force, and van der Waals force was modeled by Newtonian Equation of motion. The model validity was verified in the influence of ion strength and flow velocity on biomolecules distribution near the surface compared with experimental results of previous studies. The influence of acting forces on its distribution near the surface was investigated by the simulation. The trend of its distribution to ion strength and flow velocity was agreement with the experimental result by the combination of all acting forces. Furthermore, EDL force dominantly influenced its distribution near its surface compared with fluid drag force except for the case of high velocity and low ion strength. The knowledges from the simulation might be useful for the design of biomolecules-detection devices and the simulation can be expected to be applied on its development as the design tool for high detection sensitivity and rapid diagnosis in the future.
MinOmics, an Integrative and Immersive Tool for Multi-Omics Analysis.
Maes, Alexandre; Martinez, Xavier; Druart, Karen; Laurent, Benoist; Guégan, Sean; Marchand, Christophe H; Lemaire, Stéphane D; Baaden, Marc
2018-06-21
Proteomic and transcriptomic technologies resulted in massive biological datasets, their interpretation requiring sophisticated computational strategies. Efficient and intuitive real-time analysis remains challenging. We use proteomic data on 1417 proteins of the green microalga Chlamydomonas reinhardtii to investigate physicochemical parameters governing selectivity of three cysteine-based redox post translational modifications (PTM): glutathionylation (SSG), nitrosylation (SNO) and disulphide bonds (SS) reduced by thioredoxins. We aim to understand underlying molecular mechanisms and structural determinants through integration of redox proteome data from gene- to structural level. Our interactive visual analytics approach on an 8.3 m2 display wall of 25 MPixel resolution features stereoscopic three dimensions (3D) representation performed by UnityMol WebGL. Virtual reality headsets complement the range of usage configurations for fully immersive tasks. Our experiments confirm that fast access to a rich cross-linked database is necessary for immersive analysis of structural data. We emphasize the possibility to display complex data structures and relationships in 3D, intrinsic to molecular structure visualization, but less common for omics-network analysis. Our setup is powered by MinOmics, an integrated analysis pipeline and visualization framework dedicated to multi-omics analysis. MinOmics integrates data from various sources into a materialized physical repository. We evaluate its performance, a design criterion for the framework.
An Investigation of the Flow Physics of Acoustic Liners by Direct Numerical Simulation
NASA Technical Reports Server (NTRS)
Watson, Willie R. (Technical Monitor); Tam, Christopher
2004-01-01
This report concentrates on reporting the effort and status of work done on three dimensional (3-D) simulation of a multi-hole resonator in an impedance tube. This work is coordinated with a parallel experimental effort to be carried out at the NASA Langley Research Center. The outline of this report is as follows : 1. Preliminary consideration. 2. Computation model. 3. Mesh design and parallel computing. 4. Visualization. 5. Status of computer code development. 1. Preliminary Consideration.
Computational Model of Secondary Palate Fusion and Disruption
Morphogenetic events are driven by cell-generated physical forces and complex cellular dynamics. To improve our capacity to predict developmental effects from cellular alterations, we built a multi-cellular agent-based model in CompuCell3D that recapitulates the cellular networks...
Cross-platform validation and analysis environment for particle physics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chekanov, S. V.; Pogrebnyak, I.; Wilbern, D.
A multi-platform validation and analysis framework for public Monte Carlo simulation for high-energy particle collisions is discussed. The front-end of this framework uses the Python programming language, while the back-end is written in Java, which provides a multi-platform environment that can be run from a web browser and can easily be deployed at the grid sites. The analysis package includes all major software tools used in high-energy physics, such as Lorentz vectors, jet algorithms, histogram packages, graphic canvases, and tools for providing data access. This multi-platform software suite, designed to minimize OS-specific maintenance and deployment time, is used for onlinemore » validation of Monte Carlo event samples through a web interface.« less
A Stratified Acoustic Model Accounting for Phase Shifts for Underwater Acoustic Networks
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.
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.
Multi-body Dynamic Contact Analysis Tool for Transmission Design
2003-04-01
frequencies were computed in COSMIC NASTRAN, and were validated against the published experimental modal analysis [17]. • Using assumed time domain... modal superposition. • Results from the structural analysis (mode shapes or forced response) were converted into IDEAS universal format (dataset 55...ARMY RESEARCH LABORATORY Multi-body Dynamic Contact Analysis Tool for Transmission Design SBIR Phase II Final Report by
gpuSPHASE-A shared memory caching implementation for 2D SPH using CUDA
NASA Astrophysics Data System (ADS)
Winkler, Daniel; Meister, Michael; Rezavand, Massoud; Rauch, Wolfgang
2017-04-01
Smoothed particle hydrodynamics (SPH) is a meshless Lagrangian method that has been successfully applied to computational fluid dynamics (CFD), solid mechanics and many other multi-physics problems. Using the method to solve transport phenomena in process engineering requires the simulation of several days to weeks of physical time. Based on the high computational demand of CFD such simulations in 3D need a computation time of years so that a reduction to a 2D domain is inevitable. In this paper gpuSPHASE, a new open-source 2D SPH solver implementation for graphics devices, is developed. It is optimized for simulations that must be executed with thousands of frames per second to be computed in reasonable time. A novel caching algorithm for Compute Unified Device Architecture (CUDA) shared memory is proposed and implemented. The software is validated and the performance is evaluated for the well established dambreak test case.
Advances in Geologic Disposal System Modeling and Application to Crystalline Rock
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mariner, Paul E.; Stein, Emily R.; Frederick, Jennifer M.
The Used Fuel Disposition Campaign (UFDC) of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Fuel Cycle Technology (OFCT) is conducting research and development (R&D) on geologic disposal of used nuclear fuel (UNF) and high-level nuclear waste (HLW). Two of the high priorities for UFDC disposal R&D are design concept development and disposal system modeling (DOE 2011). These priorities are directly addressed in the UFDC Generic Disposal Systems Analysis (GDSA) work package, which is charged with developing a disposal system modeling and analysis capability for evaluating disposal system performance for nuclear waste in geologic mediamore » (e.g., salt, granite, clay, and deep borehole disposal). This report describes specific GDSA activities in fiscal year 2016 (FY 2016) toward the development of the enhanced disposal system modeling and analysis capability for geologic disposal of nuclear waste. The GDSA framework employs the PFLOTRAN thermal-hydrologic-chemical multi-physics code and the Dakota uncertainty sampling and propagation code. Each code is designed for massively-parallel processing in a high-performance computing (HPC) environment. Multi-physics representations in PFLOTRAN are used to simulate various coupled processes including heat flow, fluid flow, waste dissolution, radionuclide release, radionuclide decay and ingrowth, precipitation and dissolution of secondary phases, and radionuclide transport through engineered barriers and natural geologic barriers to the biosphere. Dakota is used to generate sets of representative realizations and to analyze parameter sensitivity.« less
INTEGRATION OF PANDA WORKLOAD MANAGEMENT SYSTEM WITH SUPERCOMPUTERS
DOE Office of Scientific and Technical Information (OSTI.GOV)
De, K; Jha, S; Maeno, T
Abstract The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the funda- mental nature of matter and the basic forces that shape our universe, and were recently credited for the dis- covery of a Higgs boson. ATLAS, one of the largest collaborations ever assembled in the sciences, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Datamore » Analysis) Workload Management System for managing the workflow for all data processing on over 140 data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data cen- ters are physically scattered all over the world. While PanDA currently uses more than 250000 cores with a peak performance of 0.3+ petaFLOPS, next LHC data taking runs will require more resources than Grid computing can possibly provide. To alleviate these challenges, LHC experiments are engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. We will describe a project aimed at integration of PanDA WMS with supercomputers in United States, Europe and Russia (in particular with Titan supercomputer at Oak Ridge Leadership Com- puting Facility (OLCF), Supercomputer at the National Research Center Kurchatov Institute , IT4 in Ostrava, and others). The current approach utilizes a modified PanDA pilot framework for job submission to the supercomputers batch queues and local data management, with light-weight MPI wrappers to run single- threaded workloads in parallel on Titan s multi-core worker nodes. This implementation was tested with a variety of Monte-Carlo workloads on several supercomputing platforms. We will present our current accom- plishments in running PanDA WMS at supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facility s infrastructure for High Energy and Nuclear Physics, as well as other data-intensive science applications, such as bioinformatics and astro-particle physics.« less
Modeling of Multi-Tube Pulse Detonation Engine Operation
NASA Technical Reports Server (NTRS)
Ebrahimi, Houshang B.; Mohanraj, Rajendran; Merkle, Charles L.
2001-01-01
The present paper explores some preliminary issues concerning the operational characteristics of multiple-tube pulsed detonation engines (PDEs). The study is based on a two-dimensional analysis of the first-pulse operation of two detonation tubes exhausting through a common nozzle. Computations are first performed to assess isolated tube behavior followed by results for multi-tube flow phenomena. The computations are based on an eight-species, finite-rate transient flow-field model. The results serve as an important precursor to understanding appropriate propellant fill procedures and shock wave propagation in multi-tube, multi-dimensional simulations. Differences in behavior between single and multi-tube PDE models are discussed, The influence of multi-tube geometry and the preferred times for injecting the fresh propellant mixture during multi-tube PDE operation are studied.
Electromagnetic physics models for parallel computing architectures
Amadio, G.; Ananya, A.; Apostolakis, J.; ...
2016-11-21
The recent emergence of hardware architectures characterized by many-core or accelerated processors has opened new opportunities for concurrent programming models taking advantage of both SIMD and SIMT architectures. GeantV, a next generation detector simulation, has been designed to exploit both the vector capability of mainstream CPUs and multi-threading capabilities of coprocessors including NVidia GPUs and Intel Xeon Phi. The characteristics of these architectures are very different in terms of the vectorization depth and type of parallelization needed to achieve optimal performance. In this paper we describe implementation of electromagnetic physics models developed for parallel computing architectures as a part ofmore » the GeantV project. Finally, the results of preliminary performance evaluation and physics validation are presented as well.« less
Li-ion synaptic transistor for low power analog computing
Fuller, Elliot J.; Gabaly, Farid El; Leonard, Francois; ...
2016-11-22
Nonvolatile redox transistors (NVRTs) based upon Li-ion battery materials are demonstrated as memory elements for neuromorphic computer architectures with multi-level analog states, “write” linearity, low-voltage switching, and low power dissipation. Simulations of back propagation using the device properties reach ideal classification accuracy. Finally, physics-based simulations predict energy costs per “write” operation of <10 aJ when scaled to 200 nm × 200 nm.
Computationally efficient optimization of radiation drives
NASA Astrophysics Data System (ADS)
Zimmerman, George; Swift, Damian
2017-06-01
For many applications of pulsed radiation, the temporal pulse shape is designed to induce a desired time-history of conditions. This optimization is normally performed using multi-physics simulations of the system, adjusting the shape until the desired response is induced. These simulations may be computationally intensive, and iterative forward optimization is then expensive and slow. In principle, a simulation program could be modified to adjust the radiation drive automatically until the desired instantaneous response is achieved, but this may be impracticable in a complicated multi-physics program. However, the computational time increment is typically much shorter than the time scale of changes in the desired response, so the radiation intensity can be adjusted so that the response tends toward the desired value. This relaxed in-situ optimization method can give an adequate design for a pulse shape in a single forward simulation, giving a typical gain in computational efficiency of tens to thousands. This approach was demonstrated for the design of laser pulse shapes to induce ramp loading to high pressure in target assemblies where different components had significantly different mechanical impedance, requiring careful pulse shaping. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
An efficient dynamic load balancing algorithm
NASA Astrophysics Data System (ADS)
Lagaros, Nikos D.
2014-01-01
In engineering problems, randomness and uncertainties are inherent. Robust design procedures, formulated in the framework of multi-objective optimization, have been proposed in order to take into account sources of randomness and uncertainty. These design procedures require orders of magnitude more computational effort than conventional analysis or optimum design processes since a very large number of finite element analyses is required to be dealt. It is therefore an imperative need to exploit the capabilities of computing resources in order to deal with this kind of problems. In particular, parallel computing can be implemented at the level of metaheuristic optimization, by exploiting the physical parallelization feature of the nondominated sorting evolution strategies method, as well as at the level of repeated structural analyses required for assessing the behavioural constraints and for calculating the objective functions. In this study an efficient dynamic load balancing algorithm for optimum exploitation of available computing resources is proposed and, without loss of generality, is applied for computing the desired Pareto front. In such problems the computation of the complete Pareto front with feasible designs only, constitutes a very challenging task. The proposed algorithm achieves linear speedup factors and almost 100% speedup factor values with reference to the sequential procedure.
NASA Astrophysics Data System (ADS)
Klein, R.; Woodward, C. S.; Johannesson, G.; Domyancic, D.; Covey, C. C.; Lucas, D. D.
2012-12-01
Uncertainty Quantification (UQ) is a critical field within 21st century simulation science that resides at the very center of the web of emerging predictive capabilities. The science of UQ holds the promise of giving much greater meaning to the results of complex large-scale simulations, allowing for quantifying and bounding uncertainties. This powerful capability will yield new insights into scientific predictions (e.g. Climate) of great impact on both national and international arenas, allow informed decisions on the design of critical experiments (e.g. ICF capsule design, MFE, NE) in many scientific fields, and assign confidence bounds to scientifically predictable outcomes (e.g. nuclear weapons design). In this talk I will discuss a major new strategic initiative (SI) we have developed at Lawrence Livermore National Laboratory to advance the science of Uncertainty Quantification at LLNL focusing in particular on (a) the research and development of new algorithms and methodologies of UQ as applied to multi-physics multi-scale codes, (b) incorporation of these advancements into a global UQ Pipeline (i.e. a computational superstructure) that will simplify user access to sophisticated tools for UQ studies as well as act as a self-guided, self-adapting UQ engine for UQ studies on extreme computing platforms and (c) use laboratory applications as a test bed for new algorithms and methodologies. The initial SI focus has been on applications for the quantification of uncertainty associated with Climate prediction, but the validated UQ methodologies we have developed are now being fed back into Science Based Stockpile Stewardship (SSS) and ICF UQ efforts. To make advancements in several of these UQ grand challenges, I will focus in talk on the following three research areas in our Strategic Initiative: Error Estimation in multi-physics and multi-scale codes ; Tackling the "Curse of High Dimensionality"; and development of an advanced UQ Computational Pipeline to enable complete UQ workflow and analysis for ensemble runs at the extreme scale (e.g. exascale) with self-guiding adaptation in the UQ Pipeline engine. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and was funded by the Uncertainty Quantification Strategic Initiative Laboratory Directed Research and Development Project at LLNL under project tracking code 10-SI-013 (UCRL LLNL-ABS-569112).
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ghrayeb, S. Z.; Ouisloumen, M.; Ougouag, A. M.
2012-07-01
A multi-group formulation for the exact neutron elastic scattering kernel is developed. This formulation is intended for implementation into a lattice physics code. The correct accounting for the crystal lattice effects influences the estimated values for the probability of neutron absorption and scattering, which in turn affect the estimation of core reactivity and burnup characteristics. A computer program has been written to test the formulation for various nuclides. Results of the multi-group code have been verified against the correct analytic scattering kernel. In both cases neutrons were started at various energies and temperatures and the corresponding scattering kernels were tallied.more » (authors)« less
Multi-Core Processor Memory Contention Benchmark Analysis Case Study
NASA Technical Reports Server (NTRS)
Simon, Tyler; McGalliard, James
2009-01-01
Multi-core processors dominate current mainframe, server, and high performance computing (HPC) systems. This paper provides synthetic kernel and natural benchmark results from an HPC system at the NASA Goddard Space Flight Center that illustrate the performance impacts of multi-core (dual- and quad-core) vs. single core processor systems. Analysis of processor design, application source code, and synthetic and natural test results all indicate that multi-core processors can suffer from significant memory subsystem contention compared to similar single-core processors.
Multi-GPU implementation of a VMAT treatment plan optimization algorithm.
Tian, Zhen; Peng, Fei; Folkerts, Michael; Tan, Jun; Jia, Xun; Jiang, Steve B
2015-06-01
Volumetric modulated arc therapy (VMAT) optimization is a computationally challenging problem due to its large data size, high degrees of freedom, and many hardware constraints. High-performance graphics processing units (GPUs) have been used to speed up the computations. However, GPU's relatively small memory size cannot handle cases with a large dose-deposition coefficient (DDC) matrix in cases of, e.g., those with a large target size, multiple targets, multiple arcs, and/or small beamlet size. The main purpose of this paper is to report an implementation of a column-generation-based VMAT algorithm, previously developed in the authors' group, on a multi-GPU platform to solve the memory limitation problem. While the column-generation-based VMAT algorithm has been previously developed, the GPU implementation details have not been reported. Hence, another purpose is to present detailed techniques employed for GPU implementation. The authors also would like to utilize this particular problem as an example problem to study the feasibility of using a multi-GPU platform to solve large-scale problems in medical physics. The column-generation approach generates VMAT apertures sequentially by solving a pricing problem (PP) and a master problem (MP) iteratively. In the authors' method, the sparse DDC matrix is first stored on a CPU in coordinate list format (COO). On the GPU side, this matrix is split into four submatrices according to beam angles, which are stored on four GPUs in compressed sparse row format. Computation of beamlet price, the first step in PP, is accomplished using multi-GPUs. A fast inter-GPU data transfer scheme is accomplished using peer-to-peer access. The remaining steps of PP and MP problems are implemented on CPU or a single GPU due to their modest problem scale and computational loads. Barzilai and Borwein algorithm with a subspace step scheme is adopted here to solve the MP problem. A head and neck (H&N) cancer case is then used to validate the authors' method. The authors also compare their multi-GPU implementation with three different single GPU implementation strategies, i.e., truncating DDC matrix (S1), repeatedly transferring DDC matrix between CPU and GPU (S2), and porting computations involving DDC matrix to CPU (S3), in terms of both plan quality and computational efficiency. Two more H&N patient cases and three prostate cases are used to demonstrate the advantages of the authors' method. The authors' multi-GPU implementation can finish the optimization process within ∼ 1 min for the H&N patient case. S1 leads to an inferior plan quality although its total time was 10 s shorter than the multi-GPU implementation due to the reduced matrix size. S2 and S3 yield the same plan quality as the multi-GPU implementation but take ∼4 and ∼6 min, respectively. High computational efficiency was consistently achieved for the other five patient cases tested, with VMAT plans of clinically acceptable quality obtained within 23-46 s. Conversely, to obtain clinically comparable or acceptable plans for all six of these VMAT cases that the authors have tested in this paper, the optimization time needed in a commercial TPS system on CPU was found to be in an order of several minutes. The results demonstrate that the multi-GPU implementation of the authors' column-generation-based VMAT optimization can handle the large-scale VMAT optimization problem efficiently without sacrificing plan quality. The authors' study may serve as an example to shed some light on other large-scale medical physics problems that require multi-GPU techniques.
Development of a Renormalization Group Approach to Multi-Scale Plasma Physics Computation
2012-03-28
with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1...NUMBER(S) 12. DISTRIBUTION/AVAILABILITY STATEMENT 13. SUPPLEMENTARY NOTES 14. ABSTRACT 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: a . REPORT...code) 29-12-2008 Final Technical Report From 29-12-2008 To 16-95-2011 (STTR PHASE II) DEVELOPMENT OF A RENORMALIZATION GROUP APPROACH TO MULTI-SCALE
SU-F-I-10: Spatially Local Statistics for Adaptive Image Filtering
DOE Office of Scientific and Technical Information (OSTI.GOV)
Iliopoulos, AS; Sun, X; Floros, D
Purpose: To facilitate adaptive image filtering operations, addressing spatial variations in both noise and signal. Such issues are prevalent in cone-beam projections, where physical effects such as X-ray scattering result in spatially variant noise, violating common assumptions of homogeneous noise and challenging conventional filtering approaches to signal extraction and noise suppression. Methods: We present a computational mechanism for probing into and quantifying the spatial variance of noise throughout an image. The mechanism builds a pyramid of local statistics at multiple spatial scales; local statistical information at each scale includes (weighted) mean, median, standard deviation, median absolute deviation, as well asmore » histogram or dynamic range after local mean/median shifting. Based on inter-scale differences of local statistics, the spatial scope of distinguishable noise variation is detected in a semi- or un-supervised manner. Additionally, we propose and demonstrate the incorporation of such information in globally parametrized (i.e., non-adaptive) filters, effectively transforming the latter into spatially adaptive filters. The multi-scale mechanism is materialized by efficient algorithms and implemented in parallel CPU/GPU architectures. Results: We demonstrate the impact of local statistics for adaptive image processing and analysis using cone-beam projections of a Catphan phantom, fitted within an annulus to increase X-ray scattering. The effective spatial scope of local statistics calculations is shown to vary throughout the image domain, necessitating multi-scale noise and signal structure analysis. Filtering results with and without spatial filter adaptation are compared visually, illustrating improvements in imaging signal extraction and noise suppression, and in preserving information in low-contrast regions. Conclusion: Local image statistics can be incorporated in filtering operations to equip them with spatial adaptivity to spatial signal/noise variations. An efficient multi-scale computational mechanism is developed to curtail processing latency. Spatially adaptive filtering may impact subsequent processing tasks such as reconstruction and numerical gradient computations for deformable registration. NIH Grant No. R01-184173.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ely, Geoffrey P.
2013-10-31
This project uses dynamic rupture simulations to investigate high-frequency seismic energy generation. The relevant phenomena (frictional breakdown, shear heating, effective normal-stress fluctuations, material damage, etc.) controlling rupture are strongly interacting and span many orders of magnitude in spatial scale, requiring highresolution simulations that couple disparate physical processes (e.g., elastodynamics, thermal weakening, pore-fluid transport, and heat conduction). Compounding the computational challenge, we know that natural faults are not planar, but instead have roughness that can be approximated by power laws potentially leading to large, multiscale fluctuations in normal stress. The capacity to perform 3D rupture simulations that couple these processes willmore » provide guidance for constructing appropriate source models for high-frequency ground motion simulations. The improved rupture models from our multi-scale dynamic rupture simulations will be used to conduct physicsbased (3D waveform modeling-based) probabilistic seismic hazard analysis (PSHA) for California. These calculation will provide numerous important seismic hazard results, including a state-wide extended earthquake rupture forecast with rupture variations for all significant events, a synthetic seismogram catalog for thousands of scenario events and more than 5000 physics-based seismic hazard curves for California.« less
NASA Astrophysics Data System (ADS)
Bhardwaj, Jyotirmoy; Gupta, Karunesh K.; Gupta, Rajiv
2018-02-01
New concepts and techniques are replacing traditional methods of water quality parameter measurement systems. This paper introduces a cyber-physical system (CPS) approach for water quality assessment in a distribution network. Cyber-physical systems with embedded sensors, processors and actuators can be designed to sense and interact with the water environment. The proposed CPS is comprised of sensing framework integrated with five different water quality parameter sensor nodes and soft computing framework for computational modelling. Soft computing framework utilizes the applications of Python for user interface and fuzzy sciences for decision making. Introduction of multiple sensors in a water distribution network generates a huge number of data matrices, which are sometimes highly complex, difficult to understand and convoluted for effective decision making. Therefore, the proposed system framework also intends to simplify the complexity of obtained sensor data matrices and to support decision making for water engineers through a soft computing framework. The target of this proposed research is to provide a simple and efficient method to identify and detect presence of contamination in a water distribution network using applications of CPS.
Experimental Mathematics and Mathematical Physics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bailey, David H.; Borwein, Jonathan M.; Broadhurst, David
2009-06-26
One of the most effective techniques of experimental mathematics is to compute mathematical entities such as integrals, series or limits to high precision, then attempt to recognize the resulting numerical values. Recently these techniques have been applied with great success to problems in mathematical physics. Notable among these applications are the identification of some key multi-dimensional integrals that arise in Ising theory, quantum field theory and in magnetic spin theory.
Energy and time determine scaling in biological and computer designs
Bezerra, George; Edwards, Benjamin; Brown, James; Forrest, Stephanie
2016-01-01
Metabolic rate in animals and power consumption in computers are analogous quantities that scale similarly with size. We analyse vascular systems of mammals and on-chip networks of microprocessors, where natural selection and human engineering, respectively, have produced systems that minimize both energy dissipation and delivery times. Using a simple network model that simultaneously minimizes energy and time, our analysis explains empirically observed trends in the scaling of metabolic rate in mammals and power consumption and performance in microprocessors across several orders of magnitude in size. Just as the evolutionary transitions from unicellular to multicellular animals in biology are associated with shifts in metabolic scaling, our model suggests that the scaling of power and performance will change as computer designs transition to decentralized multi-core and distributed cyber-physical systems. More generally, a single energy–time minimization principle may govern the design of many complex systems that process energy, materials and information. This article is part of the themed issue ‘The major synthetic evolutionary transitions’. PMID:27431524
Energy and time determine scaling in biological and computer designs.
Moses, Melanie; Bezerra, George; Edwards, Benjamin; Brown, James; Forrest, Stephanie
2016-08-19
Metabolic rate in animals and power consumption in computers are analogous quantities that scale similarly with size. We analyse vascular systems of mammals and on-chip networks of microprocessors, where natural selection and human engineering, respectively, have produced systems that minimize both energy dissipation and delivery times. Using a simple network model that simultaneously minimizes energy and time, our analysis explains empirically observed trends in the scaling of metabolic rate in mammals and power consumption and performance in microprocessors across several orders of magnitude in size. Just as the evolutionary transitions from unicellular to multicellular animals in biology are associated with shifts in metabolic scaling, our model suggests that the scaling of power and performance will change as computer designs transition to decentralized multi-core and distributed cyber-physical systems. More generally, a single energy-time minimization principle may govern the design of many complex systems that process energy, materials and information.This article is part of the themed issue 'The major synthetic evolutionary transitions'. © 2016 The Author(s).
DOE Office of Scientific and Technical Information (OSTI.GOV)
Khawli, Toufik Al; Eppelt, Urs; Hermanns, Torsten
2016-06-08
In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part ismore » to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels. In the third part, the metamodel is used to provide the two global sensitivity measures: i) the Elementary Effect for screening the parameters, and ii) the variance decomposition method for calculating the Sobol indices that quantify both the main and interaction effects. The application of the proposed approach is illustrated with an industrial application with the goal of optimizing a drilling process using a Gaussian laser beam.« less
NASA Astrophysics Data System (ADS)
Khawli, Toufik Al; Gebhardt, Sascha; Eppelt, Urs; Hermanns, Torsten; Kuhlen, Torsten; Schulz, Wolfgang
2016-06-01
In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part is to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels. In the third part, the metamodel is used to provide the two global sensitivity measures: i) the Elementary Effect for screening the parameters, and ii) the variance decomposition method for calculating the Sobol indices that quantify both the main and interaction effects. The application of the proposed approach is illustrated with an industrial application with the goal of optimizing a drilling process using a Gaussian laser beam.
Integration of Advanced Probabilistic Analysis Techniques with Multi-Physics Models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cetiner, Mustafa Sacit; none,; Flanagan, George F.
2014-07-30
An integrated simulation platform that couples probabilistic analysis-based tools with model-based simulation tools can provide valuable insights for reactive and proactive responses to plant operating conditions. The objective of this work is to demonstrate the benefits of a partial implementation of the Small Modular Reactor (SMR) Probabilistic Risk Assessment (PRA) Detailed Framework Specification through the coupling of advanced PRA capabilities and accurate multi-physics plant models. Coupling a probabilistic model with a multi-physics model will aid in design, operations, and safety by providing a more accurate understanding of plant behavior. This represents the first attempt at actually integrating these two typesmore » of analyses for a control system used for operations, on a faster than real-time basis. This report documents the development of the basic communication capability to exchange data with the probabilistic model using Reliability Workbench (RWB) and the multi-physics model using Dymola. The communication pathways from injecting a fault (i.e., failing a component) to the probabilistic and multi-physics models were successfully completed. This first version was tested with prototypic models represented in both RWB and Modelica. First, a simple event tree/fault tree (ET/FT) model was created to develop the software code to implement the communication capabilities between the dynamic-link library (dll) and RWB. A program, written in C#, successfully communicates faults to the probabilistic model through the dll. A systems model of the Advanced Liquid-Metal Reactor–Power Reactor Inherently Safe Module (ALMR-PRISM) design developed under another DOE project was upgraded using Dymola to include proper interfaces to allow data exchange with the control application (ConApp). A program, written in C+, successfully communicates faults to the multi-physics model. The results of the example simulation were successfully plotted.« less
NASA Astrophysics Data System (ADS)
Hoang, Tuan L.; Nazarov, Roman; Kang, Changwoo; Fan, Jiangyuan
2018-07-01
Under the multi-ion irradiation conditions present in accelerated material-testing facilities or fission/fusion nuclear reactors, the combined effects of atomic displacements with radiation products may induce complex synergies in the structural materials. However, limited access to multi-ion irradiation facilities and the lack of computational models capable of simulating the evolution of complex defects and their synergies make it difficult to understand the actual physical processes taking place in the materials under these extreme conditions. In this paper, we propose the application of pulsed single/dual-beam irradiation as replacements for the expensive steady triple-beam irradiation to study radiation damages in materials under multi-ion irradiation.
NASA Astrophysics Data System (ADS)
Song, Lu-Kai; Wen, Jie; Fei, Cheng-Wei; Bai, Guang-Chen
2018-05-01
To improve the computing efficiency and precision of probabilistic design for multi-failure structure, a distributed collaborative probabilistic design method-based fuzzy neural network of regression (FR) (called as DCFRM) is proposed with the integration of distributed collaborative response surface method and fuzzy neural network regression model. The mathematical model of DCFRM is established and the probabilistic design idea with DCFRM is introduced. The probabilistic analysis of turbine blisk involving multi-failure modes (deformation failure, stress failure and strain failure) was investigated by considering fluid-structure interaction with the proposed method. The distribution characteristics, reliability degree, and sensitivity degree of each failure mode and overall failure mode on turbine blisk are obtained, which provides a useful reference for improving the performance and reliability of aeroengine. Through the comparison of methods shows that the DCFRM reshapes the probability of probabilistic analysis for multi-failure structure and improves the computing efficiency while keeping acceptable computational precision. Moreover, the proposed method offers a useful insight for reliability-based design optimization of multi-failure structure and thereby also enriches the theory and method of mechanical reliability design.
FRR: fair remote retrieval of outsourced private medical records in electronic health networks.
Wang, Huaqun; Wu, Qianhong; Qin, Bo; Domingo-Ferrer, Josep
2014-08-01
Cloud computing is emerging as the next-generation IT architecture. However, cloud computing also raises security and privacy concerns since the users have no physical control over the outsourced data. This paper focuses on fairly retrieving encrypted private medical records outsourced to remote untrusted cloud servers in the case of medical accidents and disputes. Our goal is to enable an independent committee to fairly recover the original private medical records so that medical investigation can be carried out in a convincing way. We achieve this goal with a fair remote retrieval (FRR) model in which either t investigation committee members cooperatively retrieve the original medical data or none of them can get any information on the medical records. We realize the first FRR scheme by exploiting fair multi-member key exchange and homomorphic privately verifiable tags. Based on the standard computational Diffie-Hellman (CDH) assumption, our scheme is provably secure in the random oracle model (ROM). A detailed performance analysis and experimental results show that our scheme is efficient in terms of communication and computation. Copyright © 2014 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Chu, J.; Zhang, C.; Fu, G.; Li, Y.; Zhou, H.
2015-08-01
This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce computational demands. Sobol's method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed method dramatically reduces the computational demands required for attaining high-quality approximations of optimal trade-off relationships between conflicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed dimension reduction and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform dimension reduction of optimization problems when solving complex multi-objective reservoir operation problems.
NASA Astrophysics Data System (ADS)
Chu, J. G.; Zhang, C.; Fu, G. T.; Li, Y.; Zhou, H. C.
2015-04-01
This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce the computational demands. Sobol's method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed problem decomposition dramatically reduces the computational demands required for attaining high quality approximations of optimal tradeoff relationships between conflicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed problem decomposition and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform problem decomposition when solving the complex multi-objective reservoir operation problems.
Interactive multi-mode blade impact analysis
NASA Technical Reports Server (NTRS)
Alexander, A.; Cornell, R. W.
1978-01-01
The theoretical methodology used in developing an analysis for the response of turbine engine fan blades subjected to soft-body (bird) impacts is reported, and the computer program developed using this methodology as its basis is described. This computer program is an outgrowth of two programs that were previously developed for the purpose of studying problems of a similar nature (a 3-mode beam impact analysis and a multi-mode beam impact analysis). The present program utilizes an improved missile model that is interactively coupled with blade motion which is more consistent with actual observations. It takes into account local deformation at the impact area, blade camber effects, and the spreading of the impacted missile mass on the blade surface. In addition, it accommodates plate-type mode shapes. The analysis capability in this computer program represents a significant improvement in the development of the methodology for evaluating potential fan blade materials and designs with regard to foreign object impact resistance.
Physics Computing '92: Proceedings of the 4th International Conference
NASA Astrophysics Data System (ADS)
de Groot, Robert A.; Nadrchal, Jaroslav
1993-04-01
The Table of Contents for the book is as follows: * Preface * INVITED PAPERS * Ab Initio Theoretical Approaches to the Structural, Electronic and Vibrational Properties of Small Clusters and Fullerenes: The State of the Art * Neural Multigrid Methods for Gauge Theories and Other Disordered Systems * Multicanonical Monte Carlo Simulations * On the Use of the Symbolic Language Maple in Physics and Chemistry: Several Examples * Nonequilibrium Phase Transitions in Catalysis and Population Models * Computer Algebra, Symmetry Analysis and Integrability of Nonlinear Evolution Equations * The Path-Integral Quantum Simulation of Hydrogen in Metals * Digital Optical Computing: A New Approach of Systolic Arrays Based on Coherence Modulation of Light and Integrated Optics Technology * Molecular Dynamics Simulations of Granular Materials * Numerical Implementation of a K.A.M. Algorithm * Quasi-Monte Carlo, Quasi-Random Numbers and Quasi-Error Estimates * What Can We Learn from QMC Simulations * Physics of Fluctuating Membranes * Plato, Apollonius, and Klein: Playing with Spheres * Steady States in Nonequilibrium Lattice Systems * CONVODE: A REDUCE Package for Differential Equations * Chaos in Coupled Rotators * Symplectic Numerical Methods for Hamiltonian Problems * Computer Simulations of Surfactant Self Assembly * High-dimensional and Very Large Cellular Automata for Immunological Shape Space * A Review of the Lattice Boltzmann Method * Electronic Structure of Solids in the Self-interaction Corrected Local-spin-density Approximation * Dedicated Computers for Lattice Gauge Theory Simulations * Physics Education: A Survey of Problems and Possible Solutions * Parallel Computing and Electronic-Structure Theory * High Precision Simulation Techniques for Lattice Field Theory * CONTRIBUTED PAPERS * Case Study of Microscale Hydrodynamics Using Molecular Dynamics and Lattice Gas Methods * Computer Modelling of the Structural and Electronic Properties of the Supported Metal Catalysis * Ordered Particle Simulations for Serial and MIMD Parallel Computers * "NOLP" -- Program Package for Laser Plasma Nonlinear Optics * Algorithms to Solve Nonlinear Least Square Problems * Distribution of Hydrogen Atoms in Pd-H Computed by Molecular Dynamics * A Ray Tracing of Optical System for Protein Crystallography Beamline at Storage Ring-SIBERIA-2 * Vibrational Properties of a Pseudobinary Linear Chain with Correlated Substitutional Disorder * Application of the Software Package Mathematica in Generalized Master Equation Method * Linelist: An Interactive Program for Analysing Beam-foil Spectra * GROMACS: A Parallel Computer for Molecular Dynamics Simulations * GROMACS Method of Virial Calculation Using a Single Sum * The Interactive Program for the Solution of the Laplace Equation with the Elimination of Singularities for Boundary Functions * Random-Number Generators: Testing Procedures and Comparison of RNG Algorithms * Micro-TOPIC: A Tokamak Plasma Impurities Code * Rotational Molecular Scattering Calculations * Orthonormal Polynomial Method for Calibrating of Cryogenic Temperature Sensors * Frame-based System Representing Basis of Physics * The Role of Massively Data-parallel Computers in Large Scale Molecular Dynamics Simulations * Short-range Molecular Dynamics on a Network of Processors and Workstations * An Algorithm for Higher-order Perturbation Theory in Radiative Transfer Computations * Hydrostochastics: The Master Equation Formulation of Fluid Dynamics * HPP Lattice Gas on Transputers and Networked Workstations * Study on the Hysteresis Cycle Simulation Using Modeling with Different Functions on Intervals * Refined Pruning Techniques for Feed-forward Neural Networks * Random Walk Simulation of the Motion of Transient Charges in Photoconductors * The Optical Hysteresis in Hydrogenated Amorphous Silicon * Diffusion Monte Carlo Analysis of Modern Interatomic Potentials for He * A Parallel Strategy for Molecular Dynamics Simulations of Polar Liquids on Transputer Arrays * Distribution of Ions Reflected on Rough Surfaces * The Study of Step Density Distribution During Molecular Beam Epitaxy Growth: Monte Carlo Computer Simulation * Towards a Formal Approach to the Construction of Large-scale Scientific Applications Software * Correlated Random Walk and Discrete Modelling of Propagation through Inhomogeneous Media * Teaching Plasma Physics Simulation * A Theoretical Determination of the Au-Ni Phase Diagram * Boson and Fermion Kinetics in One-dimensional Lattices * Computational Physics Course on the Technical University * Symbolic Computations in Simulation Code Development and Femtosecond-pulse Laser-plasma Interaction Studies * Computer Algebra and Integrated Computing Systems in Education of Physical Sciences * Coordinated System of Programs for Undergraduate Physics Instruction * Program Package MIRIAM and Atomic Physics of Extreme Systems * High Energy Physics Simulation on the T_Node * The Chapman-Kolmogorov Equation as Representation of Huygens' Principle and the Monolithic Self-consistent Numerical Modelling of Lasers * Authoring System for Simulation Developments * Molecular Dynamics Study of Ion Charge Effects in the Structure of Ionic Crystals * A Computational Physics Introductory Course * Computer Calculation of Substrate Temperature Field in MBE System * Multimagnetical Simulation of the Ising Model in Two and Three Dimensions * Failure of the CTRW Treatment of the Quasicoherent Excitation Transfer * Implementation of a Parallel Conjugate Gradient Method for Simulation of Elastic Light Scattering * Algorithms for Study of Thin Film Growth * Algorithms and Programs for Physics Teaching in Romanian Technical Universities * Multicanonical Simulation of 1st order Transitions: Interface Tension of the 2D 7-State Potts Model * Two Numerical Methods for the Calculation of Periodic Orbits in Hamiltonian Systems * Chaotic Behavior in a Probabilistic Cellular Automata? * Wave Optics Computing by a Networked-based Vector Wave Automaton * Tensor Manipulation Package in REDUCE * Propagation of Electromagnetic Pulses in Stratified Media * The Simple Molecular Dynamics Model for the Study of Thermalization of the Hot Nucleon Gas * Electron Spin Polarization in PdCo Alloys Calculated by KKR-CPA-LSD Method * Simulation Studies of Microscopic Droplet Spreading * A Vectorizable Algorithm for the Multicolor Successive Overrelaxation Method * Tetragonality of the CuAu I Lattice and Its Relation to Electronic Specific Heat and Spin Susceptibility * Computer Simulation of the Formation of Metallic Aggregates Produced by Chemical Reactions in Aqueous Solution * Scaling in Growth Models with Diffusion: A Monte Carlo Study * The Nucleus as the Mesoscopic System * Neural Network Computation as Dynamic System Simulation * First-principles Theory of Surface Segregation in Binary Alloys * Data Smooth Approximation Algorithm for Estimating the Temperature Dependence of the Ice Nucleation Rate * Genetic Algorithms in Optical Design * Application of 2D-FFT in the Study of Molecular Exchange Processes by NMR * Advanced Mobility Model for Electron Transport in P-Si Inversion Layers * Computer Simulation for Film Surfaces and its Fractal Dimension * Parallel Computation Techniques and the Structure of Catalyst Surfaces * Educational SW to Teach Digital Electronics and the Corresponding Text Book * Primitive Trinomials (Mod 2) Whose Degree is a Mersenne Exponent * Stochastic Modelisation and Parallel Computing * Remarks on the Hybrid Monte Carlo Algorithm for the ∫4 Model * An Experimental Computer Assisted Workbench for Physics Teaching * A Fully Implicit Code to Model Tokamak Plasma Edge Transport * EXPFIT: An Interactive Program for Automatic Beam-foil Decay Curve Analysis * Mapping Technique for Solving General, 1-D Hamiltonian Systems * Freeway Traffic, Cellular Automata, and Some (Self-Organizing) Criticality * Photonuclear Yield Analysis by Dynamic Programming * Incremental Representation of the Simply Connected Planar Curves * Self-convergence in Monte Carlo Methods * Adaptive Mesh Technique for Shock Wave Propagation * Simulation of Supersonic Coronal Streams and Their Interaction with the Solar Wind * The Nature of Chaos in Two Systems of Ordinary Nonlinear Differential Equations * Considerations of a Window-shopper * Interpretation of Data Obtained by RTP 4-Channel Pulsed Radar Reflectometer Using a Multi Layer Perceptron * Statistics of Lattice Bosons for Finite Systems * Fractal Based Image Compression with Affine Transformations * Algorithmic Studies on Simulation Codes for Heavy-ion Reactions * An Energy-Wise Computer Simulation of DNA-Ion-Water Interactions Explains the Abnormal Structure of Poly[d(A)]:Poly[d(T)] * Computer Simulation Study of Kosterlitz-Thouless-Like Transitions * Problem-oriented Software Package GUN-EBT for Computer Simulation of Beam Formation and Transport in Technological Electron-Optical Systems * Parallelization of a Boundary Value Solver and its Application in Nonlinear Dynamics * The Symbolic Classification of Real Four-dimensional Lie Algebras * Short, Singular Pulses Generation by a Dye Laser at Two Wavelengths Simultaneously * Quantum Monte Carlo Simulations of the Apex-Oxygen-Model * Approximation Procedures for the Axial Symmetric Static Einstein-Maxwell-Higgs Theory * Crystallization on a Sphere: Parallel Simulation on a Transputer Network * FAMULUS: A Software Product (also) for Physics Education * MathCAD vs. FAMULUS -- A Brief Comparison * First-principles Dynamics Used to Study Dissociative Chemisorption * A Computer Controlled System for Crystal Growth from Melt * A Time Resolved Spectroscopic Method for Short Pulsed Particle Emission * Green's Function Computation in Radiative Transfer Theory * Random Search Optimization Technique for One-criteria and Multi-criteria Problems * Hartley Transform Applications to Thermal Drift Elimination in Scanning Tunneling Microscopy * Algorithms of Measuring, Processing and Interpretation of Experimental Data Obtained with Scanning Tunneling Microscope * Time-dependent Atom-surface Interactions * Local and Global Minima on Molecular Potential Energy Surfaces: An Example of N3 Radical * Computation of Bifurcation Surfaces * Symbolic Computations in Quantum Mechanics: Energies in Next-to-solvable Systems * A Tool for RTP Reactor and Lamp Field Design * Modelling of Particle Spectra for the Analysis of Solid State Surface * List of Participants
Multi-Body Dynamic Contact Analysis. Tool for Transmission Design SBIR Phase II Final Report
2003-04-01
shapes and natural frequencies were computed in COSMIC NASTRAN, and were validated against the published experimental modal analysis [17]. • Using...COSMIC NASTRAN via modal superposition. • Results from the structural analysis (mode shapes or forced response) were converted into IDEAS universal...ARMY RESEARCH LABORATORY Multi-body Dynamic Contact Analysis Tool for Transmission Design SBIR Phase II Final Report by
Wong, Kelvin K L; Wang, Defeng; Ko, Jacky K L; Mazumdar, Jagannath; Le, Thu-Thao; Ghista, Dhanjoo
2017-03-21
Cardiac dysfunction constitutes common cardiovascular health issues in the society, and has been an investigation topic of strong focus by researchers in the medical imaging community. Diagnostic modalities based on echocardiography, magnetic resonance imaging, chest radiography and computed tomography are common techniques that provide cardiovascular structural information to diagnose heart defects. However, functional information of cardiovascular flow, which can in fact be used to support the diagnosis of many cardiovascular diseases with a myriad of hemodynamics performance indicators, remains unexplored to its full potential. Some of these indicators constitute important cardiac functional parameters affecting the cardiovascular abnormalities. With the advancement of computer technology that facilitates high speed computational fluid dynamics, the realization of a support diagnostic platform of hemodynamics quantification and analysis can be achieved. This article reviews the state-of-the-art medical imaging and high fidelity multi-physics computational analyses that together enable reconstruction of cardiovascular structures and hemodynamic flow patterns within them, such as of the left ventricle (LV) and carotid bifurcations. The combined medical imaging and hemodynamic analysis enables us to study the mechanisms of cardiovascular disease-causing dysfunctions, such as how (1) cardiomyopathy causes left ventricular remodeling and loss of contractility leading to heart failure, and (2) modeling of LV construction and simulation of intra-LV hemodynamics can enable us to determine the optimum procedure of surgical ventriculation to restore its contractility and health This combined medical imaging and hemodynamics framework can potentially extend medical knowledge of cardiovascular defects and associated hemodynamic behavior and their surgical restoration, by means of an integrated medical image diagnostics and hemodynamic performance analysis framework.
Tetherless ergonomics workstation to assess nurses' physical workload in a clinical setting.
Smith, Warren D; Nave, Michael E; Hreljac, Alan P
2011-01-01
Nurses are at risk of physical injury when moving immobile patients. This paper describes the development and testing of a tetherless ergonomics workstation that is suitable for studying nurses' physical workload in a clinical setting. The workstation uses wearable sensors to record multiple channels of body orientation and muscle activity and wirelessly transmits them to a base station laptop computer for display, storage, and analysis. In preparation for use in a clinical setting, the workstation was tested in a laboratory equipped for multi-camera video motion analysis. The testing included a pilot study of the effect of bed height on student nurses' physical workload while they repositioned a volunteer posing as a bedridden patient toward the head of the bed. Each nurse subject chose a preferred bed height, and data were recorded, in randomized order, with the bed at this height, at 0.1 m below this height, and at 0.1 m above this height. The testing showed that the body orientation recordings made by the wearable sensors agreed closely with those obtained from the video motion analysis system. The pilot study showed the following trends: As the bed height was raised, the nurses' trunk flexion at both thoracic and lumbar sites and lumbar muscle effort decreased, whereas trapezius and deltoid muscle effort increased. These trends will be evaluated by further studies of practicing nurses in the clinical setting.
Analysis Commons, A Team Approach to Discovery in a Big-Data Environment for Genetic Epidemiology
Brody, Jennifer A.; Morrison, Alanna C.; Bis, Joshua C.; O'Connell, Jeffrey R.; Brown, Michael R.; Huffman, Jennifer E.; Ames, Darren C.; Carroll, Andrew; Conomos, Matthew P.; Gabriel, Stacey; Gibbs, Richard A.; Gogarten, Stephanie M.; Gupta, Namrata; Jaquish, Cashell E.; Johnson, Andrew D.; Lewis, Joshua P.; Liu, Xiaoming; Manning, Alisa K.; Papanicolaou, George J.; Pitsillides, Achilleas N.; Rice, Kenneth M.; Salerno, William; Sitlani, Colleen M.; Smith, Nicholas L.; Heckbert, Susan R.; Laurie, Cathy C.; Mitchell, Braxton D.; Vasan, Ramachandran S.; Rich, Stephen S.; Rotter, Jerome I.; Wilson, James G.; Boerwinkle, Eric; Psaty, Bruce M.; Cupples, L. Adrienne
2017-01-01
Summary paragraph The exploding volume of whole-genome sequence (WGS) and multi-omics data requires new approaches for analysis. As one solution, we have created a cloud-based Analysis Commons, which brings together genotype and phenotype data from multiple studies in a setting that is accessible by multiple investigators. This framework addresses many of the challenges of multi-center WGS analyses, including data sharing mechanisms, phenotype harmonization, integrated multi-omics analyses, annotation, and computational flexibility. In this setting, the computational pipeline facilitates a sequence-to-discovery analysis workflow illustrated here by an analysis of plasma fibrinogen levels in 3996 individuals from the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) WGS program. The Analysis Commons represents a novel model for transforming WGS resources from a massive quantity of phenotypic and genomic data into knowledge of the determinants of health and disease risk in diverse human populations. PMID:29074945
Path integral molecular dynamics for exact quantum statistics of multi-electronic-state systems.
Liu, Xinzijian; Liu, Jian
2018-03-14
An exact approach to compute physical properties for general multi-electronic-state (MES) systems in thermal equilibrium is presented. The approach is extended from our recent progress on path integral molecular dynamics (PIMD), Liu et al. [J. Chem. Phys. 145, 024103 (2016)] and Zhang et al. [J. Chem. Phys. 147, 034109 (2017)], for quantum statistical mechanics when a single potential energy surface is involved. We first define an effective potential function that is numerically favorable for MES-PIMD and then derive corresponding estimators in MES-PIMD for evaluating various physical properties. Its application to several representative one-dimensional and multi-dimensional models demonstrates that MES-PIMD in principle offers a practical tool in either of the diabatic and adiabatic representations for studying exact quantum statistics of complex/large MES systems when the Born-Oppenheimer approximation, Condon approximation, and harmonic bath approximation are broken.
Path integral molecular dynamics for exact quantum statistics of multi-electronic-state systems
NASA Astrophysics Data System (ADS)
Liu, Xinzijian; Liu, Jian
2018-03-01
An exact approach to compute physical properties for general multi-electronic-state (MES) systems in thermal equilibrium is presented. The approach is extended from our recent progress on path integral molecular dynamics (PIMD), Liu et al. [J. Chem. Phys. 145, 024103 (2016)] and Zhang et al. [J. Chem. Phys. 147, 034109 (2017)], for quantum statistical mechanics when a single potential energy surface is involved. We first define an effective potential function that is numerically favorable for MES-PIMD and then derive corresponding estimators in MES-PIMD for evaluating various physical properties. Its application to several representative one-dimensional and multi-dimensional models demonstrates that MES-PIMD in principle offers a practical tool in either of the diabatic and adiabatic representations for studying exact quantum statistics of complex/large MES systems when the Born-Oppenheimer approximation, Condon approximation, and harmonic bath approximation are broken.
NASA Astrophysics Data System (ADS)
Huang, J. H.; Wang, X. J.; Wang, J.
2016-02-01
The primary purpose of this paper is to propose a mathematical model of PLZT ceramic with coupled multi-physics fields, e.g. thermal, electric, mechanical and light field. To this end, the coupling relationships of multi-physics fields and the mechanism of some effects resulting in the photostrictive effect are analyzed theoretically, based on which a mathematical model considering coupled multi-physics fields is established. According to the analysis and experimental results, the mathematical model can explain the hysteresis phenomenon and the variation trend of the photo-induced voltage very well and is in agreement with the experimental curves. In addition, the PLZT bimorph is applied as an energy transducer for a photovoltaic-electrostatic hybrid actuated micromirror, and the relation of the rotation angle and the photo-induced voltage is discussed based on the novel photostrictive mathematical model.
Transportation Research and Analysis Computing Center (TRACC) Year 6 Quarter 4 Progress Report
DOT National Transportation Integrated Search
2013-03-01
Argonne National Laboratory initiated a FY2006-FY2009 multi-year program with the US Department of Transportation (USDOT) on October 1, 2006, to establish the Transportation Research and Analysis Computing Center (TRACC). As part of the TRACC project...
Developing affordable multi-touch technologies for use in physics
NASA Astrophysics Data System (ADS)
Potter, Mark; Ilie, Carolina; Schofield, Damian; Vampola, David
2012-02-01
Physics is one of many areas which has the ability to benefit from a number of different teaching styles and sophisticated instructional tools due to it having both theoretical and practical applications which can be explored. The purpose of this research is to develop affordable large scale multi-touch interfaces which can be used within and outside of the classroom as both an instruction technology and a computer supported collaborative learning tool. Not only can this technology be implemented at university levels, but also at the K-12 level of education. Pedagogical research indicates that kinesthetic learning is a fundamental, powerful, and ubiquitous learning style [1]. Through the use of these types of multi-touch tools and teaching methods which incorporate them, the classroom can be enriched to allow for better comprehension and retention of information. This is due in part to a wider range of learning styles, such as kinesthetic learning, which are being catered to within the classroom. [4pt] [1] Wieman, C.E, Perkins, K.K., Adams, W.K., ``Oersted Medal Lecture 2007: Interactive Simulations for teaching physics: What works, what doesn't and why,'' American Journal of Physics. 76 393-99.
Efficient and robust relaxation procedures for multi-component mixtures including phase transition
DOE Office of Scientific and Technical Information (OSTI.GOV)
Han, Ee, E-mail: eehan@math.uni-bremen.de; Hantke, Maren, E-mail: maren.hantke@ovgu.de; Müller, Siegfried, E-mail: mueller@igpm.rwth-aachen.de
We consider a thermodynamic consistent multi-component model in multi-dimensions that is a generalization of the classical two-phase flow model of Baer and Nunziato. The exchange of mass, momentum and energy between the phases is described by additional source terms. Typically these terms are handled by relaxation procedures. Available relaxation procedures suffer from efficiency and robustness resulting in very costly computations that in general only allow for one-dimensional computations. Therefore we focus on the development of new efficient and robust numerical methods for relaxation processes. We derive exact procedures to determine mechanical and thermal equilibrium states. Further we introduce a novelmore » iterative method to treat the mass transfer for a three component mixture. All new procedures can be extended to an arbitrary number of inert ideal gases. We prove existence, uniqueness and physical admissibility of the resulting states and convergence of our new procedures. Efficiency and robustness of the procedures are verified by means of numerical computations in one and two space dimensions. - Highlights: • We develop novel relaxation procedures for a generalized, thermodynamically consistent Baer–Nunziato type model. • Exact procedures for mechanical and thermal relaxation procedures avoid artificial parameters. • Existence, uniqueness and physical admissibility of the equilibrium states are proven for special mixtures. • A novel iterative method for mass transfer is introduced for a three component mixture providing a unique and admissible equilibrium state.« less
2014-01-01
Background Network-based learning algorithms for automated function prediction (AFP) are negatively affected by the limited coverage of experimental data and limited a priori known functional annotations. As a consequence their application to model organisms is often restricted to well characterized biological processes and pathways, and their effectiveness with poorly annotated species is relatively limited. A possible solution to this problem might consist in the construction of big networks including multiple species, but this in turn poses challenging computational problems, due to the scalability limitations of existing algorithms and the main memory requirements induced by the construction of big networks. Distributed computation or the usage of big computers could in principle respond to these issues, but raises further algorithmic problems and require resources not satisfiable with simple off-the-shelf computers. Results We propose a novel framework for scalable network-based learning of multi-species protein functions based on both a local implementation of existing algorithms and the adoption of innovative technologies: we solve “locally” the AFP problem, by designing “vertex-centric” implementations of network-based algorithms, but we do not give up thinking “globally” by exploiting the overall topology of the network. This is made possible by the adoption of secondary memory-based technologies that allow the efficient use of the large memory available on disks, thus overcoming the main memory limitations of modern off-the-shelf computers. This approach has been applied to the analysis of a large multi-species network including more than 300 species of bacteria and to a network with more than 200,000 proteins belonging to 13 Eukaryotic species. To our knowledge this is the first work where secondary-memory based network analysis has been applied to multi-species function prediction using biological networks with hundreds of thousands of proteins. Conclusions The combination of these algorithmic and technological approaches makes feasible the analysis of large multi-species networks using ordinary computers with limited speed and primary memory, and in perspective could enable the analysis of huge networks (e.g. the whole proteomes available in SwissProt), using well-equipped stand-alone machines. PMID:24843788
Collider Physics Cosmic Frontier Cosmic Frontier Theory & Computing Detector R&D Electronic Design Theory Seminar Argonne >High Energy Physics Cosmic Frontier Theory & Computing Homepage General Cosmic Frontier Theory & Computing Group led the analysis to begin mapping dark matter. There have
Space Station Common Berthing Mechanism, a multi-body simulation application
NASA Technical Reports Server (NTRS)
Searle, Ian
1993-01-01
This paper discusses an application of multi-body dynamic analysis conducted at the Boeing Company in connection with the Space Station (SS) Common Berthing Mechanism (CBM). After introducing the hardware and analytical objectives we will focus on some of the day-to-day computational issues associated with this type of analysis.
Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.
2011-01-01
In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to use of the multi-satellite simulator tqimproy precipitation processes will be discussed.
Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes
NASA Technical Reports Server (NTRS)
Tao, Wei--Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.
2010-01-01
In recent years, exponentially increasing computer power extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 sq km in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale models can be run in grid size similar to cloud resolving models through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model). (2) a regional scale model (a NASA unified weather research and forecast, W8F). (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling systems to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use the multi-satellite simulator to improve precipitation processes will be discussed.
Using Multi-Scale Modeling Systems to Study the Precipitation Processes
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2010-01-01
In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.
Implicit time-integration method for simultaneous solution of a coupled non-linear system
NASA Astrophysics Data System (ADS)
Watson, Justin Kyle
Historically large physical problems have been divided into smaller problems based on the physics involved. This is no different in reactor safety analysis. The problem of analyzing a nuclear reactor for design basis accidents is performed by a handful of computer codes each solving a portion of the problem. The reactor thermal hydraulic response to an event is determined using a system code like TRAC RELAP Advanced Computational Engine (TRACE). The core power response to the same accident scenario is determined using a core physics code like Purdue Advanced Core Simulator (PARCS). Containment response to the reactor depressurization in a Loss Of Coolant Accident (LOCA) type event is calculated by a separate code. Sub-channel analysis is performed with yet another computer code. This is just a sample of the computer codes used to solve the overall problems of nuclear reactor design basis accidents. Traditionally each of these codes operates independently from each other using only the global results from one calculation as boundary conditions to another. Industry's drive to uprate power for reactors has motivated analysts to move from a conservative approach to design basis accident towards a best estimate method. To achieve a best estimate calculation efforts have been aimed at coupling the individual physics models to improve the accuracy of the analysis and reduce margins. The current coupling techniques are sequential in nature. During a calculation time-step data is passed between the two codes. The individual codes solve their portion of the calculation and converge to a solution before the calculation is allowed to proceed to the next time-step. This thesis presents a fully implicit method of simultaneous solving the neutron balance equations, heat conduction equations and the constitutive fluid dynamics equations. It discusses the problems involved in coupling different physics phenomena within multi-physics codes and presents a solution to these problems. The thesis also outlines the basic concepts behind the nodal balance equations, heat transfer equations and the thermal hydraulic equations, which will be coupled to form a fully implicit nonlinear system of equations. The coupling of separate physics models to solve a larger problem and improve accuracy and efficiency of a calculation is not a new idea, however implementing them in an implicit manner and solving the system simultaneously is. Also the application to reactor safety codes is new and has not be done with thermal hydraulics and neutronics codes on realistic applications in the past. The coupling technique described in this thesis is applicable to other similar coupled thermal hydraulic and core physics reactor safety codes. This technique is demonstrated using coupled input decks to show that the system is solved correctly and then verified by using two derivative test problems based on international benchmark problems the OECD/NRC Three mile Island (TMI) Main Steam Line Break (MSLB) problem (representative of pressurized water reactor analysis) and the OECD/NRC Peach Bottom (PB) Turbine Trip (TT) benchmark (representative of boiling water reactor analysis).
Coupled multi-disciplinary simulation of composite engine structures in propulsion environment
NASA Technical Reports Server (NTRS)
Chamis, Christos C.; Singhal, Surendra N.
1992-01-01
A computational simulation procedure is described for the coupled response of multi-layered multi-material composite engine structural components which are subjected to simultaneous multi-disciplinary thermal, structural, vibration, and acoustic loadings including the effect of hostile environments. The simulation is based on a three dimensional finite element analysis technique in conjunction with structural mechanics codes and with acoustic analysis methods. The composite material behavior is assessed at the various composite scales, i.e., the laminate/ply/constituents (fiber/matrix), via a nonlinear material characterization model. Sample cases exhibiting nonlinear geometrical, material, loading, and environmental behavior of aircraft engine fan blades, are presented. Results for deformed shape, vibration frequency, mode shapes, and acoustic noise emitted from the fan blade, are discussed for their coupled effect in hot and humid environments. Results such as acoustic noise for coupled composite-mechanics/heat transfer/structural/vibration/acoustic analyses demonstrate the effectiveness of coupled multi-disciplinary computational simulation and the various advantages of composite materials compared to metals.
Empirical Determination of Competence Areas to Computer Science Education
ERIC Educational Resources Information Center
Zendler, Andreas; Klaudt, Dieter; Seitz, Cornelia
2014-01-01
The authors discuss empirically determined competence areas to K-12 computer science education, emphasizing the cognitive level of competence. The results of a questionnaire with 120 professors of computer science serve as a database. By using multi-dimensional scaling and cluster analysis, four competence areas to computer science education…
New modalities for scientific engagement in Africa - the case for computational physics
NASA Astrophysics Data System (ADS)
Chetty, N.
2011-09-01
Computational physics as a mode of studying the mathematical and physical sciences has grown world-wide over the past two decades, but this trend is yet to fully develop in Africa. The essential ingredients are there for this to happen: increasing internet connectivity, cheaper computing resources and the widespread availability of open source and freeware. The missing ingredients centre on intellectual isolation and the low levels of quality international collaborations. Low level of funding for research from local governments remains a critical issue. This paper gives a motivation for the importance of developing computational physics at the university undergraduate level, graduate level and research levels and gives suggestions on how this may be achieved within the African context. It is argued that students develop a more intuitive feel for the mathematical and physical sciences, that they learn useful, transferable skills that make our graduates well-sought after in the industrial and commercial environments, and that such graduates are better prepared to tackle research problems at the masters and doctoral levels. At the research level, the case of the African School Series on Electronic Structure Methods and Applications (ASESMA) is presented as a new multi-national modality for engaging with African scientists. There are many novel aspects to this School series, which are discussed.
Analysis of Multi-State Systems with Multi-State Components Using EVMDDs
2012-05-01
Fault-Tolerant Computing (FTCS), pp. 249– 258, June 1995. [5] T. Kam, T. Villa, R. K. Brayton , and A. L. Sangiovanni- Vincentelli, “Multi-valued...Shmerko, and R. S. Stankovic, Decision Diagram Techniques for Micro- and Nanoelectronic Design, CRC Press, Taylor & Francis Group, 2006. [16] X. Zang, D
Arbabi, Vahid; Pouran, Behdad; Weinans, Harrie; Zadpoor, Amir A
2016-09-06
Analytical and numerical methods have been used to extract essential engineering parameters such as elastic modulus, Poisson׳s ratio, permeability and diffusion coefficient from experimental data in various types of biological tissues. The major limitation associated with analytical techniques is that they are often only applicable to problems with simplified assumptions. Numerical multi-physics methods, on the other hand, enable minimizing the simplified assumptions but require substantial computational expertise, which is not always available. In this paper, we propose a novel approach that combines inverse and forward artificial neural networks (ANNs) which enables fast and accurate estimation of the diffusion coefficient of cartilage without any need for computational modeling. In this approach, an inverse ANN is trained using our multi-zone biphasic-solute finite-bath computational model of diffusion in cartilage to estimate the diffusion coefficient of the various zones of cartilage given the concentration-time curves. Robust estimation of the diffusion coefficients, however, requires introducing certain levels of stochastic variations during the training process. Determining the required level of stochastic variation is performed by coupling the inverse ANN with a forward ANN that receives the diffusion coefficient as input and returns the concentration-time curve as output. Combined together, forward-inverse ANNs enable computationally inexperienced users to obtain accurate and fast estimation of the diffusion coefficients of cartilage zones. The diffusion coefficients estimated using the proposed approach are compared with those determined using direct scanning of the parameter space as the optimization approach. It has been shown that both approaches yield comparable results. Copyright © 2016 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
Venkatapathy, Ethiraj; Gulhan, Ali; Aftosmis, Michael; Brock, Joseph; Mathias, Donovan; Need, Dominic; Rodriguez, David; Seltner, Patrick; Stern, Eric; Wiles, Sebastian
2017-01-01
An airburst from a large asteroid during entry can cause significant ground damage. The damage depends on the energy and the altitude of airburst. Breakup of asteroids into fragments and their lateral spread have been observed. Modeling the underlying physics of fragmented bodies interacting at hypersonic speeds and the spread of fragments is needed for a true predictive capability. Current models use heuristic arguments and assumptions such as pancaking or point source explosive energy release at pre-determined altitude or an assumed fragmentation spread rate to predict airburst damage. A multi-year collaboration between German Aerospace Center (DLR) and NASA has been established to develop validated computational tools to address the above challenge.
Next Generation Workload Management System For Big Data on Heterogeneous Distributed Computing
NASA Astrophysics Data System (ADS)
Klimentov, A.; Buncic, P.; De, K.; Jha, S.; Maeno, T.; Mount, R.; Nilsson, P.; Oleynik, D.; Panitkin, S.; Petrosyan, A.; Porter, R. J.; Read, K. F.; Vaniachine, A.; Wells, J. C.; Wenaus, T.
2015-05-01
The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS and ALICE are the largest collaborations ever assembled in the sciences and are at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, both experiments rely on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Management System (WMS) for managing the workflow for all data processing on hundreds of data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. The scale is demonstrated by the following numbers: PanDA manages O(102) sites, O(105) cores, O(108) jobs per year, O(103) users, and ATLAS data volume is O(1017) bytes. In 2013 we started an ambitious program to expand PanDA to all available computing resources, including opportunistic use of commercial and academic clouds and Leadership Computing Facilities (LCF). The project titled ‘Next Generation Workload Management and Analysis System for Big Data’ (BigPanDA) is funded by DOE ASCR and HEP. Extending PanDA to clouds and LCF presents new challenges in managing heterogeneity and supporting workflow. The BigPanDA project is underway to setup and tailor PanDA at the Oak Ridge Leadership Computing Facility (OLCF) and at the National Research Center "Kurchatov Institute" together with ALICE distributed computing and ORNL computing professionals. Our approach to integration of HPC platforms at the OLCF and elsewhere is to reuse, as much as possible, existing components of the PanDA system. We will present our current accomplishments with running the PanDA WMS at OLCF and other supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications.
Computing Properties of Hadrons, Nuclei and Nuclear Matter from Quantum Chromodynamics (LQCD)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Negele, John W.
Building on the success of two preceding generations of Scientific Discovery through Advanced Computing (SciDAC) projects, this grant supported the MIT component (P.I. John Negele) of a multi-institutional SciDAC-3 project that also included Brookhaven National Laboratory, the lead laboratory with P. I. Frithjof Karsch serving as Project Director, Thomas Jefferson National Accelerator Facility with P. I. David Richards serving as Co-director, University of Washington with P. I. Martin Savage, University of North Carolina with P. I. Rob Fowler, and College of William and Mary with P. I. Andreas Stathopoulos. Nationally, this multi-institutional project coordinated the software development effort that themore » nuclear physics lattice QCD community needs to ensure that lattice calculations can make optimal use of forthcoming leadership-class and dedicated hardware, including that at the national laboratories, and to exploit future computational resources in the Exascale era.« less
Optimization and Control of Cyber-Physical Vehicle Systems
Bradley, Justin M.; Atkins, Ella M.
2015-01-01
A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined. PMID:26378541
Optimization and Control of Cyber-Physical Vehicle Systems.
Bradley, Justin M; Atkins, Ella M
2015-09-11
A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined.
Preparing CAM-SE for Multi-Tracer Applications: CAM-SE-Cslam
NASA Astrophysics Data System (ADS)
Lauritzen, P. H.; Taylor, M.; Goldhaber, S.
2014-12-01
The NCAR-DOE spectral element (SE) dynamical core comes from the HOMME (High-Order Modeling Environment; Dennis et al., 2012) and it is available in CAM. The CAM-SE dynamical core is designed with intrinsic mimetic properties guaranteeing total energy conservation (to time-truncation errors) and mass-conservation, and has demonstrated excellent scalability on massively parallel compute platforms (Taylor, 2011). For applications involving many tracers such as chemistry and biochemistry modeling, CAM-SE has been found to be significantly more computationally costly than the current "workhorse" model CAM-FV (Finite-Volume; Lin 2004). Hence a multi-tracer efficient scheme, called the CSLAM (Conservative Semi-Lagrangian Multi-tracer; Lauritzen et al., 2011) scheme, has been implemented in the HOMME (Erath et al., 2012). The CSLAM scheme has recently been cast in flux-form in HOMME so that it can be coupled to the SE dynamical core through conventional flux-coupling methods where the SE dynamical core provides background air mass fluxes to CSLAM. Since the CSLAM scheme makes use of a finite-volume gnomonic cubed-sphere grid and hence does not operate on the SE quadrature grid, the capability of running tracer advection, the physical parameterization suite and dynamics on separate grids has been implemented in CAM-SE. The default CAM-SE-CSLAM setup is to run physics on the quasi-equal area CSLAM grid. The capability of running physics on a different grid than the SE dynamical core may provide a more consistent coupling since the physics grid option operates with quasi-equal-area cell average values rather than non-equi-distant grid-point (SE quadrature point) values. Preliminary results on the performance of CAM-SE-CSLAM will be presented.
NASA Astrophysics Data System (ADS)
Shou, Y.; Combi, M.; Toth, G.; Tenishev, V.; Fougere, N.; Jia, X.; Rubin, M.; Huang, Z.; Hansen, K.; Gombosi, T.; Bieler, A.
2016-12-01
Physics-based numerical coma models are desirable whether to interpret the spacecraft observations of the inner coma or to compare with the ground-based observations of the outer coma. In this work, we develop a multi-neutral-fluid model based on the BATS-R-US code of the University of Michigan, which is capable of computing both the inner and outer coma and simulating time-variable phenomena. It treats H2O, OH, H2, O, and H as separate fluids and each fluid has its own velocity and temperature, with collisions coupling all fluids together. The self-consistent collisional interactions decrease the velocity differences, re-distribute the excess energy deposited by chemical reactions among all species, and account for the varying heating efficiency under various physical conditions. Recognizing that the fluid approach has limitations in capturing all of the correct physics for certain applications, especially for very low density environment, we applied our multi-fluid coma model to comet 67P/Churyumov-Gerasimenko at various heliocentric distances and demonstrated that it yields comparable results to the Direct Simulation Monte Carlo (DSMC) model, which is based on a kinetic approach that is valid under these conditions. Therefore, our model may be a powerful alternative to the particle-based model, especially for some computationally intensive simulations. In addition, by running the model with several combinations of production rates and heliocentric distances, we characterize the cometary H2O expansion speeds and demonstrate the nonlinear dependencies of production rate and heliocentric distance. Our results are also compared to previous modeling work and remote observations, which serve as further validation of our model.
Assembling Large, Multi-Sensor Climate Datasets Using the SciFlo Grid Workflow System
NASA Astrophysics Data System (ADS)
Wilson, B.; Manipon, G.; Xing, Z.; Fetzer, E.
2009-04-01
NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time "matchups" between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, assemble merged datasets, and compute fused products for further scientific and statistical analysis. To meet these large-scale challenges, we are utilizing a Grid computing and dataflow framework, named SciFlo, in which we are deploying a set of versatile and reusable operators for data query, access, subsetting, co-registration, mining, fusion, and advanced statistical analysis. SciFlo is a semantically-enabled ("smart") Grid Workflow system that ties together a peer-to-peer network of computers into an efficient engine for distributed computation. The SciFlo workflow engine enables scientists to do multi-instrument Earth Science by assembling remotely-invokable Web Services (SOAP or http GET URLs), native executables, command-line scripts, and Python codes into a distributed computing flow. A scientist visually authors the graph of operation in the VizFlow GUI, or uses a text editor to modify the simple XML workflow documents. The SciFlo client & server engines optimize the execution of such distributed workflows and allow the user to transparently find and use datasets and operators without worrying about the actual location of the Grid resources. The engine transparently moves data to the operators, and moves operators to the data (on the dozen trusted SciFlo nodes). SciFlo also deploys a variety of Data Grid services to: query datasets in space and time, locate & retrieve on-line data granules, provide on-the-fly variable and spatial subsetting, perform pairwise instrument matchups for A-Train datasets, and compute fused products. These services are combined into efficient workflows to assemble the desired large-scale, merged climate datasets. SciFlo is currently being applied in several large climate studies: comparisons of aerosol optical depth between MODIS, MISR, AERONET ground network, and U. Michigan's IMPACT aerosol transport model; characterization of long-term biases in microwave and infrared instruments (AIRS, MLS) by comparisons to GPS temperature retrievals accurate to 0.1 degrees Kelvin; and construction of a decade-long, multi-sensor water vapor climatology stratified by classified cloud scene by bringing together datasets from AIRS/AMSU, AMSR-E, MLS, MODIS, and CloudSat (NASA MEASUREs grant, Fetzer PI). The presentation will discuss the SciFlo technologies, their application in these distributed workflows, and the many challenges encountered in assembling and analyzing these massive datasets.
Automated analysis and classification of melanocytic tumor on skin whole slide images.
Xu, Hongming; Lu, Cheng; Berendt, Richard; Jha, Naresh; Mandal, Mrinal
2018-06-01
This paper presents a computer-aided technique for automated analysis and classification of melanocytic tumor on skin whole slide biopsy images. The proposed technique consists of four main modules. First, skin epidermis and dermis regions are segmented by a multi-resolution framework. Next, epidermis analysis is performed, where a set of epidermis features reflecting nuclear morphologies and spatial distributions is computed. In parallel with epidermis analysis, dermis analysis is also performed, where dermal cell nuclei are segmented and a set of textural and cytological features are computed. Finally, the skin melanocytic image is classified into different categories such as melanoma, nevus or normal tissue by using a multi-class support vector machine (mSVM) with extracted epidermis and dermis features. Experimental results on 66 skin whole slide images indicate that the proposed technique achieves more than 95% classification accuracy, which suggests that the technique has the potential to be used for assisting pathologists on skin biopsy image analysis and classification. Copyright © 2018 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Erfanian, A.; Fomenko, L.; Wang, G.
2016-12-01
Multi-model ensemble (MME) average is considered the most reliable for simulating both present-day and future climates. It has been a primary reference for making conclusions in major coordinated studies i.e. IPCC Assessment Reports and CORDEX. The biases of individual models cancel out each other in MME average, enabling the ensemble mean to outperform individual members in simulating the mean climate. This enhancement however comes with tremendous computational cost, which is especially inhibiting for regional climate modeling as model uncertainties can originate from both RCMs and the driving GCMs. Here we propose the Ensemble-based Reconstructed Forcings (ERF) approach to regional climate modeling that achieves a similar level of bias reduction at a fraction of cost compared with the conventional MME approach. The new method constructs a single set of initial and boundary conditions (IBCs) by averaging the IBCs of multiple GCMs, and drives the RCM with this ensemble average of IBCs to conduct a single run. Using a regional climate model (RegCM4.3.4-CLM4.5), we tested the method over West Africa for multiple combination of (up to six) GCMs. Our results indicate that the performance of the ERF method is comparable to that of the MME average in simulating the mean climate. The bias reduction seen in ERF simulations is achieved by using more realistic IBCs in solving the system of equations underlying the RCM physics and dynamics. This endows the new method with a theoretical advantage in addition to reducing computational cost. The ERF output is an unaltered solution of the RCM as opposed to a climate state that might not be physically plausible due to the averaging of multiple solutions with the conventional MME approach. The ERF approach should be considered for use in major international efforts such as CORDEX. Key words: Multi-model ensemble, ensemble analysis, ERF, regional climate modeling
NASA Astrophysics Data System (ADS)
Zheng, Xu; Hao, Zhiyong; Wang, Xu; Mao, Jie
2016-06-01
High-speed-railway-train interior noise at low, medium, and high frequencies could be simulated by finite element analysis (FEA) or boundary element analysis (BEA), hybrid finite element analysis-statistical energy analysis (FEA-SEA) and statistical energy analysis (SEA), respectively. First, a new method named statistical acoustic energy flow (SAEF) is proposed, which can be applied to the full-spectrum HST interior noise simulation (including low, medium, and high frequencies) with only one model. In an SAEF model, the corresponding multi-physical-field coupling excitations are firstly fully considered and coupled to excite the interior noise. The interior noise attenuated by sound insulation panels of carriage is simulated through modeling the inflow acoustic energy from the exterior excitations into the interior acoustic cavities. Rigid multi-body dynamics, fast multi-pole BEA, and large-eddy simulation with indirect boundary element analysis are first employed to extract the multi-physical-field excitations, which include the wheel-rail interaction forces/secondary suspension forces, the wheel-rail rolling noise, and aerodynamic noise, respectively. All the peak values and their frequency bands of the simulated acoustic excitations are validated with those from the noise source identification test. Besides, the measured equipment noise inside equipment compartment is used as one of the excitation sources which contribute to the interior noise. Second, a full-trimmed FE carriage model is firstly constructed, and the simulated modal shapes and frequencies agree well with the measured ones, which has validated the global FE carriage model as well as the local FE models of the aluminum alloy-trim composite panel. Thus, the sound transmission loss model of any composite panel has indirectly been validated. Finally, the SAEF model of the carriage is constructed based on the accurate FE model and stimulated by the multi-physical-field excitations. The results show that the trend of the simulated 1/3 octave band sound pressure spectrum agrees well with that of the on-site-measured one. The deviation between the simulated and measured overall sound pressure level (SPL) is 2.6 dB(A) and well controlled below the engineering tolerance limit, which has validated the SAEF model in the full-spectrum analysis of the high speed train interior noise.
Using multi-criteria analysis of simulation models to understand complex biological systems
Maureen C. Kennedy; E. David Ford
2011-01-01
Scientists frequently use computer-simulation models to help solve complex biological problems. Typically, such models are highly integrated, they produce multiple outputs, and standard methods of model analysis are ill suited for evaluating them. We show how multi-criteria optimization with Pareto optimality allows for model outputs to be compared to multiple system...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bryan, Frank; Dennis, John; MacCready, Parker
This project aimed to improve long term global climate simulations by resolving and enhancing the representation of the processes involved in the cycling of freshwater through estuaries and coastal regions. This was a collaborative multi-institution project consisting of physical oceanographers, climate model developers, and computational scientists. It specifically targeted the DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation. The main computational objectives were: 1. To develop computationally efficient, but physically based, parameterizations of estuary and continental shelf mixing processes for use in an Earth System Model (CESM). 2. Tomore » develop a two-way nested regional modeling framework in order to dynamically downscale the climate response of particular coastal ocean regions and to upscale the impact of the regional coastal processes to the global climate in an Earth System Model (CESM). 3. To develop computational infrastructure to enhance the efficiency of data transfer between specific sources and destinations, i.e., a point-to-point communication capability, (used in objective 1) within POP, the ocean component of CESM.« less
The Secret Life of Quarks, Final Report for the University of North Carolina at Chapel Hill
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fowler, Robert J.
This final report summarizes activities and results at the University of North Carolina as part of the the SciDAC-2 Project The Secret Life of Quarks: National Computational Infrastructure for Lattice Quantum Chromodynamics. The overall objective of the project is to construct the software needed to study quantum chromo- dynamics (QCD), the theory of the strong interactions of subatomic physics, and similar strongly coupled gauge theories anticipated to be of importance in the LHC era. It built upon the successful efforts of the SciDAC-1 project National Computational Infrastructure for Lattice Gauge Theory, in which a QCD Applications Programming Interface (QCD API)more » was developed that enables lat- tice gauge theorists to make effective use of a wide variety of massively parallel computers. In the SciDAC-2 project, optimized versions of the QCD API were being created for the IBM Blue- Gene/L (BG/L) and BlueGene/P (BG/P), the Cray XT3/XT4 and its successors, and clusters based on multi-core processors and Infiniband communications networks. The QCD API is being used to enhance the performance of the major QCD community codes and to create new applications. Software libraries of physics tools have been expanded to contain sharable building blocks for inclusion in application codes, performance analysis and visualization tools, and software for au- tomation of physics work flow. New software tools were designed for managing the large data sets generated in lattice QCD simulations, and for sharing them through the International Lattice Data Grid consortium. As part of the overall project, researchers at UNC were funded through ASCR to work in three general areas. The main thrust has been performance instrumentation and analysis in support of the SciDAC QCD code base as it evolved and as it moved to new computation platforms. In support of the performance activities, performance data was to be collected in a database for the purpose of broader analysis. Third, the UNC work was done at RENCI (Renaissance Computing Institute), which has extensive expertise and facilities for scientific data visualization, so we acted in an ongoing consulting and support role in that area.« less
Interactive Multi-Instrument Database of Solar Flares (IMIDSF)
NASA Astrophysics Data System (ADS)
Sadykov, Viacheslav M.; Nita, Gelu M.; Oria, Vincent; Kosovichev, Alexander G.
2017-08-01
Solar flares represent a complicated physical phenomenon observed in a broad range of the electromagnetic spectrum, from radiowaves to gamma-rays. For a complete understanding of the flares it is necessary to perform a combined multi-wavelength analysis using observations from many satellites and ground-based observatories. For efficient data search, integration of different flare lists and representation of observational data, we have developed the Interactive Multi-Instrument Database of Solar Flares (https://solarflare.njit.edu/). The web database is fully functional and allows the user to search for uniquely-identified flare events based on their physical descriptors and availability of observations of a particular set of instruments. Currently, data from three primary flare lists (GOES, RHESSI and HEK) and a variety of other event catalogs (Hinode, Fermi GBM, Konus-Wind, OVSA flare catalogs, CACTus CME catalog, Filament eruption catalog) and observing logs (IRIS and Nobeyama coverage), are integrated. An additional set of physical descriptors (temperature and emission measure) along with observing summary, data links and multi-wavelength light curves is provided for each flare event since January 2002. Results of an initial statistical analysis will be presented.
A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis.
Tervonen, Tommi; van Valkenhoef, Gert; Buskens, Erik; Hillege, Hans L; Postmus, Douwe
2011-05-30
Drug benefit-risk (BR) analysis is based on firm clinical evidence regarding various safety and efficacy outcomes. In this paper, we propose a new and more formal approach for constructing a supporting multi-criteria model that fully takes into account the evidence on efficacy and adverse drug reactions. Our approach is based on the stochastic multi-criteria acceptability analysis methodology, which allows us to compute the typical value judgments that support a decision, to quantify decision uncertainty, and to compute a comprehensive BR profile. We construct a multi-criteria model for the therapeutic group of second-generation antidepressants. We assess fluoxetine and venlafaxine together with placebo according to incidence of treatment response and three common adverse drug reactions by using data from a published study. Our model shows that there are clear trade-offs among the treatment alternatives. Copyright © 2011 John Wiley & Sons, Ltd.
High-Productivity Computing in Computational Physics Education
NASA Astrophysics Data System (ADS)
Tel-Zur, Guy
2011-03-01
We describe the development of a new course in Computational Physics at the Ben-Gurion University. This elective course for 3rd year undergraduates and MSc. students is being taught during one semester. Computational Physics is by now well accepted as the Third Pillar of Science. This paper's claim is that modern Computational Physics education should deal also with High-Productivity Computing. The traditional approach of teaching Computational Physics emphasizes ``Correctness'' and then ``Accuracy'' and we add also ``Performance.'' Along with topics in Mathematical Methods and case studies in Physics the course deals a significant amount of time with ``Mini-Courses'' in topics such as: High-Throughput Computing - Condor, Parallel Programming - MPI and OpenMP, How to build a Beowulf, Visualization and Grid and Cloud Computing. The course does not intend to teach neither new physics nor new mathematics but it is focused on an integrated approach for solving problems starting from the physics problem, the corresponding mathematical solution, the numerical scheme, writing an efficient computer code and finally analysis and visualization.
NASA Astrophysics Data System (ADS)
Lu, Meilian; Yang, Dong; Zhou, Xing
2013-03-01
Based on the analysis of the requirements of conversation history storage in CPM (Converged IP Messaging) system, a Multi-views storage model and access methods of conversation history are proposed. The storage model separates logical views from physical storage and divides the storage into system managed region and user managed region. It simultaneously supports conversation view, system pre-defined view and user-defined view of storage. The rationality and feasibility of multi-view presentation, the physical storage model and access methods are validated through the implemented prototype. It proves that, this proposal has good scalability, which will help to optimize the physical data storage structure and improve storage performance.
NASA Technical Reports Server (NTRS)
Majumdar, Alok; Schallhorn, Paul
1998-01-01
This paper describes a finite volume computational thermo-fluid dynamics method to solve for Navier-Stokes equations in conjunction with energy equation and thermodynamic equation of state in an unstructured coordinate system. The system of equations have been solved by a simultaneous Newton-Raphson method and compared with several benchmark solutions. Excellent agreements have been obtained in each case and the method has been found to be significantly faster than conventional Computational Fluid Dynamic(CFD) methods and therefore has the potential for implementation in Multi-Disciplinary analysis and design optimization in fluid and thermal systems. The paper also describes an algorithm of design optimization based on Newton-Raphson method which has been recently tested in a turbomachinery application.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bryan, Frank; Dennis, John; MacCready, Parker
This project aimed to improve long term global climate simulations by resolving and enhancing the representation of the processes involved in the cycling of freshwater through estuaries and coastal regions. This was a collaborative multi-institution project consisting of physical oceanographers, climate model developers, and computational scientists. It specifically targeted the DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bryan, Frank; Dennis, John; MacCready, Parker
This project aimed to improve long term global climate simulations by resolving and enhancing the representation of the processes involved in the cycling of freshwater through estuaries and coastal regions. This was a collaborative multi-institution project consisting of physical oceanographers, climate model developers, and computational scientists. It specifically targeted the DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation.
STAMPS: Software Tool for Automated MRI Post-processing on a supercomputer.
Bigler, Don C; Aksu, Yaman; Miller, David J; Yang, Qing X
2009-08-01
This paper describes a Software Tool for Automated MRI Post-processing (STAMP) of multiple types of brain MRIs on a workstation and for parallel processing on a supercomputer (STAMPS). This software tool enables the automation of nonlinear registration for a large image set and for multiple MR image types. The tool uses standard brain MRI post-processing tools (such as SPM, FSL, and HAMMER) for multiple MR image types in a pipeline fashion. It also contains novel MRI post-processing features. The STAMP image outputs can be used to perform brain analysis using Statistical Parametric Mapping (SPM) or single-/multi-image modality brain analysis using Support Vector Machines (SVMs). Since STAMPS is PBS-based, the supercomputer may be a multi-node computer cluster or one of the latest multi-core computers.
Scholarly literature and the press: scientific impact and social perception of physics computing
NASA Astrophysics Data System (ADS)
Pia, M. G.; Basaglia, T.; Bell, Z. W.; Dressendorfer, P. V.
2014-06-01
The broad coverage of the search for the Higgs boson in the mainstream media is a relative novelty for high energy physics (HEP) research, whose achievements have traditionally been limited to scholarly literature. This paper illustrates the results of a scientometric analysis of HEP computing in scientific literature, institutional media and the press, and a comparative overview of similar metrics concerning representative particle physics measurements. The picture emerging from these scientometric data documents the relationship between the scientific impact and the social perception of HEP physics research versus that of HEP computing. The results of this analysis suggest that improved communication of the scientific and social role of HEP computing via press releases from the major HEP laboratories would be beneficial to the high energy physics community.
Combination of Multi-Agent Systems and Wireless Sensor Networks for the Monitoring of Cattle
Barriuso, Alberto L.; De Paz, Juan F.; Lozano, Álvaro
2018-01-01
Precision breeding techniques have been widely used to optimize expenses and increase livestock yields. Notwithstanding, the joint use of heterogeneous sensors and artificial intelligence techniques for the simultaneous analysis or detection of different problems that cattle may present has not been addressed. This study arises from the necessity to obtain a technological tool that faces this state of the art limitation. As novelty, this work presents a multi-agent architecture based on virtual organizations which allows to deploy a new embedded agent model in computationally limited autonomous sensors, making use of the Platform for Automatic coNstruction of orGanizations of intElligent Agents (PANGEA). To validate the proposed platform, different studies have been performed, where parameters specific to each animal are studied, such as physical activity, temperature, estrus cycle state and the moment in which the animal goes into labor. In addition, a set of applications that allow farmers to remotely monitor the livestock have been developed. PMID:29301310
Combination of Multi-Agent Systems and Wireless Sensor Networks for the Monitoring of Cattle.
Barriuso, Alberto L; Villarrubia González, Gabriel; De Paz, Juan F; Lozano, Álvaro; Bajo, Javier
2018-01-02
Precision breeding techniques have been widely used to optimize expenses and increase livestock yields. Notwithstanding, the joint use of heterogeneous sensors and artificial intelligence techniques for the simultaneous analysis or detection of different problems that cattle may present has not been addressed. This study arises from the necessity to obtain a technological tool that faces this state of the art limitation. As novelty, this work presents a multi-agent architecture based on virtual organizations which allows to deploy a new embedded agent model in computationally limited autonomous sensors, making use of the Platform for Automatic coNstruction of orGanizations of intElligent Agents (PANGEA). To validate the proposed platform, different studies have been performed, where parameters specific to each animal are studied, such as physical activity, temperature, estrus cycle state and the moment in which the animal goes into labor. In addition, a set of applications that allow farmers to remotely monitor the livestock have been developed.
NASA Astrophysics Data System (ADS)
Schmidt, M.; Hugentobler, U.; Jakowski, N.; Dettmering, D.; Liang, W.; Limberger, M.; Wilken, V.; Gerzen, T.; Hoque, M.; Berdermann, J.
2012-04-01
Near real-time high resolution and high precision ionosphere models are needed for a large number of applications, e.g. in navigation, positioning, telecommunications or astronautics. Today these ionosphere models are mostly empirical, i.e., based purely on mathematical approaches. In the DFG project 'Multi-scale model of the ionosphere from the combination of modern space-geodetic satellite techniques (MuSIK)' the complex phenomena within the ionosphere are described vertically by combining the Chapman electron density profile with a plasmasphere layer. In order to consider the horizontal and temporal behaviour the fundamental target parameters of this physics-motivated approach are modelled by series expansions in terms of tensor products of localizing B-spline functions depending on longitude, latitude and time. For testing the procedure the model will be applied to an appropriate region in South America, which covers relevant ionospheric processes and phenomena such as the Equatorial Anomaly. The project connects the expertise of the three project partners, namely Deutsches Geodätisches Forschungsinstitut (DGFI) Munich, the Institute of Astronomical and Physical Geodesy (IAPG) of the Technical University Munich (TUM) and the German Aerospace Center (DLR), Neustrelitz. In this presentation we focus on the current status of the project. In the first year of the project we studied the behaviour of the ionosphere in the test region, we setup appropriate test periods covering high and low solar activity as well as winter and summer and started the data collection, analysis, pre-processing and archiving. We developed partly the mathematical-physical modelling approach and performed first computations based on simulated input data. Here we present information on the data coverage for the area and the time periods of our investigations and we outline challenges of the multi-dimensional mathematical-physical modelling approach. We show first results, discuss problems in modelling and possible solution strategies and finally, we address open questions.
NASA Astrophysics Data System (ADS)
Ryu, Hoon; Jeong, Yosang; Kang, Ji-Hoon; Cho, Kyu Nam
2016-12-01
Modelling of multi-million atomic semiconductor structures is important as it not only predicts properties of physically realizable novel materials, but can accelerate advanced device designs. This work elaborates a new Technology-Computer-Aided-Design (TCAD) tool for nanoelectronics modelling, which uses a sp3d5s∗ tight-binding approach to describe multi-million atomic structures, and simulate electronic structures with high performance computing (HPC), including atomic effects such as alloy and dopant disorders. Being named as Quantum simulation tool for Advanced Nanoscale Devices (Q-AND), the tool shows nice scalability on traditional multi-core HPC clusters implying the strong capability of large-scale electronic structure simulations, particularly with remarkable performance enhancement on latest clusters of Intel Xeon PhiTM coprocessors. A review of the recent modelling study conducted to understand an experimental work of highly phosphorus-doped silicon nanowires, is presented to demonstrate the utility of Q-AND. Having been developed via Intel Parallel Computing Center project, Q-AND will be open to public to establish a sound framework of nanoelectronics modelling with advanced HPC clusters of a many-core base. With details of the development methodology and exemplary study of dopant electronics, this work will present a practical guideline for TCAD development to researchers in the field of computational nanoelectronics.
NASA Astrophysics Data System (ADS)
Spiegelman, M. W.; Wilson, C. R.; Van Keken, P. E.
2013-12-01
We announce the release of a new software infrastructure, TerraFERMA, the Transparent Finite Element Rapid Model Assembler for the exploration and solution of coupled multi-physics problems. The design of TerraFERMA is driven by two overarching computational needs in Earth sciences. The first is the need for increased flexibility in both problem description and solution strategies for coupled problems where small changes in model assumptions can often lead to dramatic changes in physical behavior. The second is the need for software and models that are more transparent so that results can be verified, reproduced and modified in a manner such that the best ideas in computation and earth science can be more easily shared and reused. TerraFERMA leverages three advanced open-source libraries for scientific computation that provide high level problem description (FEniCS), composable solvers for coupled multi-physics problems (PETSc) and a science neutral options handling system (SPuD) that allows the hierarchical management of all model options. TerraFERMA integrates these libraries into an easier to use interface that organizes the scientific and computational choices required in a model into a single options file, from which a custom compiled application is generated and run. Because all models share the same infrastructure, models become more reusable and reproducible. TerraFERMA inherits much of its functionality from the underlying libraries. It currently solves partial differential equations (PDE) using finite element methods on simplicial meshes of triangles (2D) and tetrahedra (3D). The software is particularly well suited for non-linear problems with complex coupling between components. We demonstrate the design and utility of TerraFERMA through examples of thermal convection and magma dynamics. TerraFERMA has been tested successfully against over 45 benchmark problems from 7 publications in incompressible and compressible convection, magmatic solitary waves and Stokes flow with free surfaces. We have been using it extensively for research in basic magma dynamics, fluid flow in subduction zones and reactive cracking in poro-elastic materials. TerraFERMA is open-source and available as a git repository at bitbucket.org/tferma/tferma and through CIG. Instability of a 1-D magmatic solitary wave to spherical 3D waves calculated using TerraFERMA
NASA Technical Reports Server (NTRS)
Gnoffo, Peter A.; Johnston, Christopher O.; Kleb, Bil
2010-01-01
Challenges to computational aerothermodynamic (CA) simulation and validation of hypersonic flow over planetary entry vehicles are discussed. Entry, descent, and landing (EDL) of high mass to Mars is a significant driver of new simulation requirements. These requirements include simulation of large deployable, flexible structures and interactions with reaction control system (RCS) and retro-thruster jets. Simulation of radiation and ablation coupled to the flow solver continues to be a high priority for planetary entry analyses, especially for return to Earth and outer planet missions. Three research areas addressing these challenges are emphasized. The first addresses the need to obtain accurate heating on unstructured tetrahedral grid systems to take advantage of flexibility in grid generation and grid adaptation. A multi-dimensional inviscid flux reconstruction algorithm is defined that is oriented with local flow topology as opposed to grid. The second addresses coupling of radiation and ablation to the hypersonic flow solver - flight- and ground-based data are used to provide limited validation of these multi-physics simulations. The third addresses the challenges of retro-propulsion simulation and the criticality of grid adaptation in this application. The evolution of CA to become a tool for innovation of EDL systems requires a successful resolution of these challenges.
HEPDOOP: High-Energy Physics Analysis using Hadoop
NASA Astrophysics Data System (ADS)
Bhimji, W.; Bristow, T.; Washbrook, A.
2014-06-01
We perform a LHC data analysis workflow using tools and data formats that are commonly used in the "Big Data" community outside High Energy Physics (HEP). These include Apache Avro for serialisation to binary files, Pig and Hadoop for mass data processing and Python Scikit-Learn for multi-variate analysis. Comparison is made with the same analysis performed with current HEP tools in ROOT.
Multi-terabyte EIDE disk arrays running Linux RAID5
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sanders, D.A.; Cremaldi, L.M.; Eschenburg, V.
2004-11-01
High-energy physics experiments are currently recording large amounts of data and in a few years will be recording prodigious quantities of data. New methods must be developed to handle this data and make analysis at universities possible. Grid Computing is one method; however, the data must be cached at the various Grid nodes. We examine some storage techniques that exploit recent developments in commodity hardware. Disk arrays using RAID level 5 (RAID-5) include both parity and striping. The striping improves access speed. The parity protects data in the event of a single disk failure, but not in the case ofmore » multiple disk failures. We report on tests of dual-processor Linux Software RAID-5 arrays and Hardware RAID-5 arrays using a 12-disk 3ware controller, in conjunction with 250 and 300 GB disks, for use in offline high-energy physics data analysis. The price of IDE disks is now less than $1/GB. These RAID-5 disk arrays can be scaled to sizes affordable to small institutions and used when fast random access at low cost is important.« less
Algorithm Development for the Multi-Fluid Plasma Model
2011-05-30
392, Sep 1995. [13] L Chacon , DC Barnes, DA Knoll, and GH Miley. An implicit energy- conservative 2D Fokker-Planck algorithm. Journal of Computational...Physics, 157(2):618–653, 2000. [14] L Chacon , DC Barnes, DA Knoll, and GH Miley. An implicit energy- conservative 2D Fokker-Planck algorithm - II
Large calculation of the flow over a hypersonic vehicle using a GPU
NASA Astrophysics Data System (ADS)
Elsen, Erich; LeGresley, Patrick; Darve, Eric
2008-12-01
Graphics processing units are capable of impressive computing performance up to 518 Gflops peak performance. Various groups have been using these processors for general purpose computing; most efforts have focussed on demonstrating relatively basic calculations, e.g. numerical linear algebra, or physical simulations for visualization purposes with limited accuracy. This paper describes the simulation of a hypersonic vehicle configuration with detailed geometry and accurate boundary conditions using the compressible Euler equations. To the authors' knowledge, this is the most sophisticated calculation of this kind in terms of complexity of the geometry, the physical model, the numerical methods employed, and the accuracy of the solution. The Navier-Stokes Stanford University Solver (NSSUS) was used for this purpose. NSSUS is a multi-block structured code with a provably stable and accurate numerical discretization which uses a vertex-based finite-difference method. A multi-grid scheme is used to accelerate the solution of the system. Based on a comparison of the Intel Core 2 Duo and NVIDIA 8800GTX, speed-ups of over 40× were demonstrated for simple test geometries and 20× for complex geometries.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zou, Ling; Berry, R. A.; Martineau, R. C.
The RELAP-7 code is the next generation nuclear reactor system safety analysis code being developed at the Idaho National Laboratory (INL). The code is based on the INL’s modern scientific software development framework, MOOSE (Multi-Physics Object Oriented Simulation Environment). The overall design goal of RELAP-7 is to take advantage of the previous thirty years of advancements in computer architecture, software design, numerical integration methods, and physical models. The end result will be a reactor systems analysis capability that retains and improves upon RELAP5’s and TRACE’s capabilities and extends their analysis capabilities for all reactor system simulation scenarios. The RELAP-7 codemore » utilizes the well-posed 7-equation two-phase flow model for compressible two-phase flow. Closure models used in the TRACE code has been reviewed and selected to reflect the progress made during the past decades and provide a basis for the colure correlations implemented in the RELAP-7 code. This document provides a summary on the closure correlations that are currently implemented in the RELAP-7 code. The closure correlations include sub-grid models that describe interactions between the fluids and the flow channel, and interactions between the two phases.« less
Uncertainty in Operational Atmospheric Analyses and Re-Analyses
NASA Astrophysics Data System (ADS)
Langland, R.; Maue, R. N.
2016-12-01
This talk will describe uncertainty in atmospheric analyses of wind and temperature produced by operational forecast models and in re-analysis products. Because the "true" atmospheric state cannot be precisely quantified, there is necessarily error in every atmospheric analysis, and this error can be estimated by computing differences ( variance and bias) between analysis products produced at various centers (e.g., ECMWF, NCEP, U.S Navy, etc.) that use independent data assimilation procedures, somewhat different sets of atmospheric observations and forecast models with different resolutions, dynamical equations, and physical parameterizations. These estimates of analysis uncertainty provide a useful proxy to actual analysis error. For this study, we use a unique multi-year and multi-model data archive developed at NRL-Monterey. It will be shown that current uncertainty in atmospheric analyses is closely correlated with the geographic distribution of assimilated in-situ atmospheric observations, especially those provided by high-accuracy radiosonde and commercial aircraft observations. The lowest atmospheric analysis uncertainty is found over North America, Europe and Eastern Asia, which have the largest numbers of radiosonde and commercial aircraft observations. Analysis uncertainty is substantially larger (by factors of two to three times) in most of the Southern hemisphere, the North Pacific ocean, and under-developed nations of Africa and South America where there are few radiosonde or commercial aircraft data. It appears that in regions where atmospheric analyses depend primarily on satellite radiance observations, analysis uncertainty of both temperature and wind remains relatively high compared to values found over North America and Europe.
Coupled Aerodynamic and Structural Sensitivity Analysis of a High-Speed Civil Transport
NASA Technical Reports Server (NTRS)
Mason, B. H.; Walsh, J. L.
2001-01-01
An objective of the High Performance Computing and Communication Program at the NASA Langley Research Center is to demonstrate multidisciplinary shape and sizing optimization of a complete aerospace vehicle configuration by using high-fidelity, finite-element structural analysis and computational fluid dynamics aerodynamic analysis. In a previous study, a multi-disciplinary analysis system for a high-speed civil transport was formulated to integrate a set of existing discipline analysis codes, some of them computationally intensive, This paper is an extension of the previous study, in which the sensitivity analysis for the coupled aerodynamic and structural analysis problem is formulated and implemented. Uncoupled stress sensitivities computed with a constant load vector in a commercial finite element analysis code are compared to coupled aeroelastic sensitivities computed by finite differences. The computational expense of these sensitivity calculation methods is discussed.
A multi-resolution approach for optimal mass transport
NASA Astrophysics Data System (ADS)
Dominitz, Ayelet; Angenent, Sigurd; Tannenbaum, Allen
2007-09-01
Optimal mass transport is an important technique with numerous applications in econometrics, fluid dynamics, automatic control, statistical physics, shape optimization, expert systems, and meteorology. Motivated by certain problems in image registration and medical image visualization, in this note, we describe a simple gradient descent methodology for computing the optimal L2 transport mapping which may be easily implemented using a multiresolution scheme. We also indicate how the optimal transport map may be computed on the sphere. A numerical example is presented illustrating our ideas.
2006-09-01
required directional control for each thruster due to their high precision and equivalent power and computer interface requirements to those for the...Universal Serial Bus) ports, LPT (Line Printing Terminal) and KVM (Keyboard-Video- Mouse) interfaces. Additionally, power is supplied to the computer through...of the IDE cable to the Prometheus Development Kit ACC-IDEEXT. Connect a small drive power connector from the desktop ATX power supply to the ACC
Spatial data analytics on heterogeneous multi- and many-core parallel architectures using python
Laura, Jason R.; Rey, Sergio J.
2017-01-01
Parallel vector spatial analysis concerns the application of parallel computational methods to facilitate vector-based spatial analysis. The history of parallel computation in spatial analysis is reviewed, and this work is placed into the broader context of high-performance computing (HPC) and parallelization research. The rise of cyber infrastructure and its manifestation in spatial analysis as CyberGIScience is seen as a main driver of renewed interest in parallel computation in the spatial sciences. Key problems in spatial analysis that have been the focus of parallel computing are covered. Chief among these are spatial optimization problems, computational geometric problems including polygonization and spatial contiguity detection, the use of Monte Carlo Markov chain simulation in spatial statistics, and parallel implementations of spatial econometric methods. Future directions for research on parallelization in computational spatial analysis are outlined.
Users matter : multi-agent systems model of high performance computing cluster users.
DOE Office of Scientific and Technical Information (OSTI.GOV)
North, M. J.; Hood, C. S.; Decision and Information Sciences
2005-01-01
High performance computing clusters have been a critical resource for computational science for over a decade and have more recently become integral to large-scale industrial analysis. Despite their well-specified components, the aggregate behavior of clusters is poorly understood. The difficulties arise from complicated interactions between cluster components during operation. These interactions have been studied by many researchers, some of whom have identified the need for holistic multi-scale modeling that simultaneously includes network level, operating system level, process level, and user level behaviors. Each of these levels presents its own modeling challenges, but the user level is the most complex duemore » to the adaptability of human beings. In this vein, there are several major user modeling goals, namely descriptive modeling, predictive modeling and automated weakness discovery. This study shows how multi-agent techniques were used to simulate a large-scale computing cluster at each of these levels.« less
Multi-Scale Surface Descriptors
Cipriano, Gregory; Phillips, George N.; Gleicher, Michael
2010-01-01
Local shape descriptors compactly characterize regions of a surface, and have been applied to tasks in visualization, shape matching, and analysis. Classically, curvature has be used as a shape descriptor; however, this differential property characterizes only an infinitesimal neighborhood. In this paper, we provide shape descriptors for surface meshes designed to be multi-scale, that is, capable of characterizing regions of varying size. These descriptors capture statistically the shape of a neighborhood around a central point by fitting a quadratic surface. They therefore mimic differential curvature, are efficient to compute, and encode anisotropy. We show how simple variants of mesh operations can be used to compute the descriptors without resorting to expensive parameterizations, and additionally provide a statistical approximation for reduced computational cost. We show how these descriptors apply to a number of uses in visualization, analysis, and matching of surfaces, particularly to tasks in protein surface analysis. PMID:19834190
Zhai, Peng-Wang; Hu, Yongxiang; Trepte, Charles R; Lucker, Patricia L
2009-02-16
A vector radiative transfer model has been developed for coupled atmosphere and ocean systems based on the Successive Order of Scattering (SOS) Method. The emphasis of this study is to make the model easy-to-use and computationally efficient. This model provides the full Stokes vector at arbitrary locations which can be conveniently specified by users. The model is capable of tracking and labeling different sources of the photons that are measured, e.g. water leaving radiances and reflected sky lights. This model also has the capability to separate florescence from multi-scattered sunlight. The delta - fit technique has been adopted to reduce computational time associated with the strongly forward-peaked scattering phase matrices. The exponential - linear approximation has been used to reduce the number of discretized vertical layers while maintaining the accuracy. This model is developed to serve the remote sensing community in harvesting physical parameters from multi-platform, multi-sensor measurements that target different components of the atmosphere-oceanic system.
Multi-Physics Analysis of the Fermilab Booster RF Cavity
DOE Office of Scientific and Technical Information (OSTI.GOV)
Awida, M.; Reid, J.; Yakovlev, V.
After about 40 years of operation the RF accelerating cavities in Fermilab Booster need an upgrade to improve their reliability and to increase the repetition rate in order to support a future experimental program. An increase in the repetitio n rate from 7 to 15 Hz entails increasing the power dissipation in the RF cavities, their ferrite loaded tuners, and HOM dampers. The increased duty factor requires careful modelling for the RF heating effects in the cavity. A multi-physic analysis invest igating both the RF and thermal properties of Booster cavity under various operating conditions is presented in this paper.
Multi-Physics Analysis of the Fermilab Booster RF Cavity
DOE Office of Scientific and Technical Information (OSTI.GOV)
Awida, M.; Reid, J.; Yakovlev, V.
After about 40 years of operation the RF accelerating cavities in Fermilab Booster need an upgrade to improve their reliability and to increase the repetition rate in order to support a future experimental program. An increase in the repetition rate from 7 to 15 Hz entails increasing the power dissipation in the RF cavities, their ferrite loaded tuners, and HOM dampers. The increased duty factor requires careful modelling for the RF heating effects in the cavity. A multi-physic analysis investigating both the RF and thermal properties of Booster cavity under various operating conditions is presented in this paper.
LIBS data analysis using a predictor-corrector based digital signal processor algorithm
NASA Astrophysics Data System (ADS)
Sanders, Alex; Griffin, Steven T.; Robinson, Aaron
2012-06-01
There are many accepted sensor technologies for generating spectra for material classification. Once the spectra are generated, communication bandwidth limitations favor local material classification with its attendant reduction in data transfer rates and power consumption. Transferring sensor technologies such as Cavity Ring-Down Spectroscopy (CRDS) and Laser Induced Breakdown Spectroscopy (LIBS) require effective material classifiers. A result of recent efforts has been emphasis on Partial Least Squares - Discriminant Analysis (PLS-DA) and Principle Component Analysis (PCA). Implementation of these via general purpose computers is difficult in small portable sensor configurations. This paper addresses the creation of a low mass, low power, robust hardware spectra classifier for a limited set of predetermined materials in an atmospheric matrix. Crucial to this is the incorporation of PCA or PLS-DA classifiers into a predictor-corrector style implementation. The system configuration guarantees rapid convergence. Software running on multi-core Digital Signal Processor (DSPs) simulates a stream-lined plasma physics model estimator, reducing Analog-to-Digital (ADC) power requirements. This paper presents the results of a predictorcorrector model implemented on a low power multi-core DSP to perform substance classification. This configuration emphasizes the hardware system and software design via a predictor corrector model that simultaneously decreases the sample rate while performing the classification.
NASA Technical Reports Server (NTRS)
Mazaheri, Alireza; Gnoffo, Peter A.; Johnston, Chirstopher O.; Kleb, Bil
2010-01-01
This users manual provides in-depth information concerning installation and execution of LAURA, version 5. LAURA is a structured, multi-block, computational aerothermodynamic simulation code. Version 5 represents a major refactoring of the original Fortran 77 LAURA code toward a modular structure afforded by Fortran 95. The refactoring improved usability and maintainability by eliminating the requirement for problem-dependent re-compilations, providing more intuitive distribution of functionality, and simplifying interfaces required for multi-physics coupling. As a result, LAURA now shares gas-physics modules, MPI modules, and other low-level modules with the FUN3D unstructured-grid code. In addition to internal refactoring, several new features and capabilities have been added, e.g., a GNU-standard installation process, parallel load balancing, automatic trajectory point sequencing, free-energy minimization, and coupled ablation and flowfield radiation.
NASA Technical Reports Server (NTRS)
Mazaheri, Alireza; Gnoffo, Peter A.; Johnston, Christopher O.; Kleb, William L.
2013-01-01
This users manual provides in-depth information concerning installation and execution of LAURA, version 5. LAURA is a structured, multi-block, computational aerothermodynamic simulation code. Version 5 represents a major refactoring of the original Fortran 77 LAURA code toward a modular structure afforded by Fortran 95. The refactoring improved usability and maintain ability by eliminating the requirement for problem dependent recompilations, providing more intuitive distribution of functionality, and simplifying interfaces required for multi-physics coupling. As a result, LAURA now shares gas-physics modules, MPI modules, and other low-level modules with the Fun3D unstructured-grid code. In addition to internal refactoring, several new features and capabilities have been added, e.g., a GNU standard installation process, parallel load balancing, automatic trajectory point sequencing, free-energy minimization, and coupled ablation and flowfield radiation.
NASA Technical Reports Server (NTRS)
Mazaheri, Alireza; Gnoffo, Peter A.; Johnston, Christopher O.; Kleb, Bil
2011-01-01
This users manual provides in-depth information concerning installation and execution of Laura, version 5. Laura is a structured, multi-block, computational aerothermodynamic simulation code. Version 5 represents a major refactoring of the original Fortran 77 Laura code toward a modular structure afforded by Fortran 95. The refactoring improved usability and maintainability by eliminating the requirement for problem dependent re-compilations, providing more intuitive distribution of functionality, and simplifying interfaces required for multi-physics coupling. As a result, Laura now shares gas-physics modules, MPI modules, and other low-level modules with the Fun3D unstructured-grid code. In addition to internal refactoring, several new features and capabilities have been added, e.g., a GNU-standard installation process, parallel load balancing, automatic trajectory point sequencing, free-energy minimization, and coupled ablation and flowfield radiation.
Chung, Dongjun; Kuan, Pei Fen; Li, Bo; Sanalkumar, Rajendran; Liang, Kun; Bresnick, Emery H; Dewey, Colin; Keleş, Sündüz
2011-07-01
Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is rapidly replacing chromatin immunoprecipitation combined with genome-wide tiling array analysis (ChIP-chip) as the preferred approach for mapping transcription-factor binding sites and chromatin modifications. The state of the art for analyzing ChIP-seq data relies on using only reads that map uniquely to a relevant reference genome (uni-reads). This can lead to the omission of up to 30% of alignable reads. We describe a general approach for utilizing reads that map to multiple locations on the reference genome (multi-reads). Our approach is based on allocating multi-reads as fractional counts using a weighted alignment scheme. Using human STAT1 and mouse GATA1 ChIP-seq datasets, we illustrate that incorporation of multi-reads significantly increases sequencing depths, leads to detection of novel peaks that are not otherwise identifiable with uni-reads, and improves detection of peaks in mappable regions. We investigate various genome-wide characteristics of peaks detected only by utilization of multi-reads via computational experiments. Overall, peaks from multi-read analysis have similar characteristics to peaks that are identified by uni-reads except that the majority of them reside in segmental duplications. We further validate a number of GATA1 multi-read only peaks by independent quantitative real-time ChIP analysis and identify novel target genes of GATA1. These computational and experimental results establish that multi-reads can be of critical importance for studying transcription factor binding in highly repetitive regions of genomes with ChIP-seq experiments.
Jali - Unstructured Mesh Infrastructure for Multi-Physics Applications
DOE Office of Scientific and Technical Information (OSTI.GOV)
Garimella, Rao V; Berndt, Markus; Coon, Ethan
2017-04-13
Jali is a parallel unstructured mesh infrastructure library designed for use by multi-physics simulations. It supports 2D and 3D arbitrary polyhedral meshes distributed over hundreds to thousands of nodes. Jali can read write Exodus II meshes along with fields and sets on the mesh and support for other formats is partially implemented or is (https://github.com/MeshToolkit/MSTK), an open source general purpose unstructured mesh infrastructure library from Los Alamos National Laboratory. While it has been made to work with other mesh frameworks such as MOAB and STKmesh in the past, support for maintaining the interface to these frameworks has been suspended formore » now. Jali supports distributed as well as on-node parallelism. Support of on-node parallelism is through direct use of the the mesh in multi-threaded constructs or through the use of "tiles" which are submeshes or sub-partitions of a partition destined for a compute node.« less
Mapping University Students' Epistemic Framing of Computational Physics Using Network Analysis
ERIC Educational Resources Information Center
Bodin, Madelen
2012-01-01
Solving physics problem in university physics education using a computational approach requires knowledge and skills in several domains, for example, physics, mathematics, programming, and modeling. These competences are in turn related to students' beliefs about the domains as well as about learning. These knowledge and beliefs components are…
Multi-GPU implementation of a VMAT treatment plan optimization algorithm
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tian, Zhen, E-mail: Zhen.Tian@UTSouthwestern.edu, E-mail: Xun.Jia@UTSouthwestern.edu, E-mail: Steve.Jiang@UTSouthwestern.edu; Folkerts, Michael; Tan, Jun
Purpose: Volumetric modulated arc therapy (VMAT) optimization is a computationally challenging problem due to its large data size, high degrees of freedom, and many hardware constraints. High-performance graphics processing units (GPUs) have been used to speed up the computations. However, GPU’s relatively small memory size cannot handle cases with a large dose-deposition coefficient (DDC) matrix in cases of, e.g., those with a large target size, multiple targets, multiple arcs, and/or small beamlet size. The main purpose of this paper is to report an implementation of a column-generation-based VMAT algorithm, previously developed in the authors’ group, on a multi-GPU platform tomore » solve the memory limitation problem. While the column-generation-based VMAT algorithm has been previously developed, the GPU implementation details have not been reported. Hence, another purpose is to present detailed techniques employed for GPU implementation. The authors also would like to utilize this particular problem as an example problem to study the feasibility of using a multi-GPU platform to solve large-scale problems in medical physics. Methods: The column-generation approach generates VMAT apertures sequentially by solving a pricing problem (PP) and a master problem (MP) iteratively. In the authors’ method, the sparse DDC matrix is first stored on a CPU in coordinate list format (COO). On the GPU side, this matrix is split into four submatrices according to beam angles, which are stored on four GPUs in compressed sparse row format. Computation of beamlet price, the first step in PP, is accomplished using multi-GPUs. A fast inter-GPU data transfer scheme is accomplished using peer-to-peer access. The remaining steps of PP and MP problems are implemented on CPU or a single GPU due to their modest problem scale and computational loads. Barzilai and Borwein algorithm with a subspace step scheme is adopted here to solve the MP problem. A head and neck (H and N) cancer case is then used to validate the authors’ method. The authors also compare their multi-GPU implementation with three different single GPU implementation strategies, i.e., truncating DDC matrix (S1), repeatedly transferring DDC matrix between CPU and GPU (S2), and porting computations involving DDC matrix to CPU (S3), in terms of both plan quality and computational efficiency. Two more H and N patient cases and three prostate cases are used to demonstrate the advantages of the authors’ method. Results: The authors’ multi-GPU implementation can finish the optimization process within ∼1 min for the H and N patient case. S1 leads to an inferior plan quality although its total time was 10 s shorter than the multi-GPU implementation due to the reduced matrix size. S2 and S3 yield the same plan quality as the multi-GPU implementation but take ∼4 and ∼6 min, respectively. High computational efficiency was consistently achieved for the other five patient cases tested, with VMAT plans of clinically acceptable quality obtained within 23–46 s. Conversely, to obtain clinically comparable or acceptable plans for all six of these VMAT cases that the authors have tested in this paper, the optimization time needed in a commercial TPS system on CPU was found to be in an order of several minutes. Conclusions: The results demonstrate that the multi-GPU implementation of the authors’ column-generation-based VMAT optimization can handle the large-scale VMAT optimization problem efficiently without sacrificing plan quality. The authors’ study may serve as an example to shed some light on other large-scale medical physics problems that require multi-GPU techniques.« less
Predicting the valley physics of silicon quantum dots directly from a device layout
NASA Astrophysics Data System (ADS)
Gamble, John King; Harvey-Collard, Patrick; Jacobson, N. Tobias; Bacewski, Andrew D.; Nielsen, Erik; Montaño, Inès; Rudolph, Martin; Carroll, Malcolm S.; Muller, Richard P.
Qubits made from electrostatically-defined quantum dots in Si-based systems are excellent candidates for quantum information processing applications. However, the multi-valley structure of silicon's band structure provides additional challenges for the few-electron physics critical to qubit manipulation. Here, we present a theory for valley physics that is predictive, in that we take as input the real physical device geometry and experimental voltage operation schedule, and with minimal approximation compute the resulting valley physics. We present both effective mass theory and atomistic tight-binding calculations for two distinct metal-oxide-semiconductor (MOS) quantum dot systems, directly comparing them to experimental measurements of the valley splitting. We conclude by assessing these detailed simulations' utility for engineering desired valley physics in future devices. Sandia is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the US Department of Energy's National Nuclear Security Administration under Contract No. DE-AC04-94AL85000. The authors gratefully acknowledge support from the Sandia National Laboratories Truman Fellowship Program, which is funded by the Laboratory Directed Research and Development (LDRD) Program.
Data-driven train set crash dynamics simulation
NASA Astrophysics Data System (ADS)
Tang, Zhao; Zhu, Yunrui; Nie, Yinyu; Guo, Shihui; Liu, Fengjia; Chang, Jian; Zhang, Jianjun
2017-02-01
Traditional finite element (FE) methods are arguably expensive in computation/simulation of the train crash. High computational cost limits their direct applications in investigating dynamic behaviours of an entire train set for crashworthiness design and structural optimisation. On the contrary, multi-body modelling is widely used because of its low computational cost with the trade-off in accuracy. In this study, a data-driven train crash modelling method is proposed to improve the performance of a multi-body dynamics simulation of train set crash without increasing the computational burden. This is achieved by the parallel random forest algorithm, which is a machine learning approach that extracts useful patterns of force-displacement curves and predicts a force-displacement relation in a given collision condition from a collection of offline FE simulation data on various collision conditions, namely different crash velocities in our analysis. Using the FE simulation results as a benchmark, we compared our method with traditional multi-body modelling methods and the result shows that our data-driven method improves the accuracy over traditional multi-body models in train crash simulation and runs at the same level of efficiency.
A highly efficient multi-core algorithm for clustering extremely large datasets
2010-01-01
Background In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput technologies. This demand is likely to increase. Standard algorithms for analyzing data, such as cluster algorithms, need to be parallelized for fast processing. Unfortunately, most approaches for parallelizing algorithms largely rely on network communication protocols connecting and requiring multiple computers. One answer to this problem is to utilize the intrinsic capabilities in current multi-core hardware to distribute the tasks among the different cores of one computer. Results We introduce a multi-core parallelization of the k-means and k-modes cluster algorithms based on the design principles of transactional memory for clustering gene expression microarray type data and categorial SNP data. Our new shared memory parallel algorithms show to be highly efficient. We demonstrate their computational power and show their utility in cluster stability and sensitivity analysis employing repeated runs with slightly changed parameters. Computation speed of our Java based algorithm was increased by a factor of 10 for large data sets while preserving computational accuracy compared to single-core implementations and a recently published network based parallelization. Conclusions Most desktop computers and even notebooks provide at least dual-core processors. Our multi-core algorithms show that using modern algorithmic concepts, parallelization makes it possible to perform even such laborious tasks as cluster sensitivity and cluster number estimation on the laboratory computer. PMID:20370922
Multi-GPU and multi-CPU accelerated FDTD scheme for vibroacoustic applications
NASA Astrophysics Data System (ADS)
Francés, J.; Otero, B.; Bleda, S.; Gallego, S.; Neipp, C.; Márquez, A.; Beléndez, A.
2015-06-01
The Finite-Difference Time-Domain (FDTD) method is applied to the analysis of vibroacoustic problems and to study the propagation of longitudinal and transversal waves in a stratified media. The potential of the scheme and the relevance of each acceleration strategy for massively computations in FDTD are demonstrated in this work. In this paper, we propose two new specific implementations of the bi-dimensional scheme of the FDTD method using multi-CPU and multi-GPU, respectively. In the first implementation, an open source message passing interface (OMPI) has been included in order to massively exploit the resources of a biprocessor station with two Intel Xeon processors. Moreover, regarding CPU code version, the streaming SIMD extensions (SSE) and also the advanced vectorial extensions (AVX) have been included with shared memory approaches that take advantage of the multi-core platforms. On the other hand, the second implementation called the multi-GPU code version is based on Peer-to-Peer communications available in CUDA on two GPUs (NVIDIA GTX 670). Subsequently, this paper presents an accurate analysis of the influence of the different code versions including shared memory approaches, vector instructions and multi-processors (both CPU and GPU) and compares them in order to delimit the degree of improvement of using distributed solutions based on multi-CPU and multi-GPU. The performance of both approaches was analysed and it has been demonstrated that the addition of shared memory schemes to CPU computing improves substantially the performance of vector instructions enlarging the simulation sizes that use efficiently the cache memory of CPUs. In this case GPU computing is slightly twice times faster than the fine tuned CPU version in both cases one and two nodes. However, for massively computations explicit vector instructions do not worth it since the memory bandwidth is the limiting factor and the performance tends to be the same than the sequential version with auto-vectorisation and also shared memory approach. In this scenario GPU computing is the best option since it provides a homogeneous behaviour. More specifically, the speedup of GPU computing achieves an upper limit of 12 for both one and two GPUs, whereas the performance reaches peak values of 80 GFlops and 146 GFlops for the performance for one GPU and two GPUs respectively. Finally, the method is applied to an earth crust profile in order to demonstrate the potential of our approach and the necessity of applying acceleration strategies in these type of applications.
NASA Astrophysics Data System (ADS)
Ahn, Sul-Ah; Jung, Youngim
2016-10-01
The research activities of the computational physicists utilizing high performance computing are analyzed by bibliometirc approaches. This study aims at providing the computational physicists utilizing high-performance computing and policy planners with useful bibliometric results for an assessment of research activities. In order to achieve this purpose, we carried out a co-authorship network analysis of journal articles to assess the research activities of researchers for high-performance computational physics as a case study. For this study, we used journal articles of the Scopus database from Elsevier covering the time period of 2004-2013. We extracted the author rank in the physics field utilizing high-performance computing by the number of papers published during ten years from 2004. Finally, we drew the co-authorship network for 45 top-authors and their coauthors, and described some features of the co-authorship network in relation to the author rank. Suggestions for further studies are discussed.
The Australian Computational Earth Systems Simulator
NASA Astrophysics Data System (ADS)
Mora, P.; Muhlhaus, H.; Lister, G.; Dyskin, A.; Place, D.; Appelbe, B.; Nimmervoll, N.; Abramson, D.
2001-12-01
Numerical simulation of the physics and dynamics of the entire earth system offers an outstanding opportunity for advancing earth system science and technology but represents a major challenge due to the range of scales and physical processes involved, as well as the magnitude of the software engineering effort required. However, new simulation and computer technologies are bringing this objective within reach. Under a special competitive national funding scheme to establish new Major National Research Facilities (MNRF), the Australian government together with a consortium of Universities and research institutions have funded construction of the Australian Computational Earth Systems Simulator (ACcESS). The Simulator or computational virtual earth will provide the research infrastructure to the Australian earth systems science community required for simulations of dynamical earth processes at scales ranging from microscopic to global. It will consist of thematic supercomputer infrastructure and an earth systems simulation software system. The Simulator models and software will be constructed over a five year period by a multi-disciplinary team of computational scientists, mathematicians, earth scientists, civil engineers and software engineers. The construction team will integrate numerical simulation models (3D discrete elements/lattice solid model, particle-in-cell large deformation finite-element method, stress reconstruction models, multi-scale continuum models etc) with geophysical, geological and tectonic models, through advanced software engineering and visualization technologies. When fully constructed, the Simulator aims to provide the software and hardware infrastructure needed to model solid earth phenomena including global scale dynamics and mineralisation processes, crustal scale processes including plate tectonics, mountain building, interacting fault system dynamics, and micro-scale processes that control the geological, physical and dynamic behaviour of earth systems. ACcESS represents a part of Australia's contribution to the APEC Cooperation for Earthquake Simulation (ACES) international initiative. Together with other national earth systems science initiatives including the Japanese Earth Simulator and US General Earthquake Model projects, ACcESS aims to provide a driver for scientific advancement and technological breakthroughs including: quantum leaps in understanding of earth evolution at global, crustal, regional and microscopic scales; new knowledge of the physics of crustal fault systems required to underpin the grand challenge of earthquake prediction; new understanding and predictive capabilities of geological processes such as tectonics and mineralisation.
Generalized Advanced Propeller Analysis System (GAPAS). Volume 2: Computer program user manual
NASA Technical Reports Server (NTRS)
Glatt, L.; Crawford, D. R.; Kosmatka, J. B.; Swigart, R. J.; Wong, E. W.
1986-01-01
The Generalized Advanced Propeller Analysis System (GAPAS) computer code is described. GAPAS was developed to analyze advanced technology multi-bladed propellers which operate on aircraft with speeds up to Mach 0.8 and altitudes up to 40,000 feet. GAPAS includes technology for analyzing aerodynamic, structural, and acoustic performance of propellers. The computer code was developed for the CDC 7600 computer and is currently available for industrial use on the NASA Langley computer. A description of all the analytical models incorporated in GAPAS is included. Sample calculations are also described as well as users requirements for modifying the analysis system. Computer system core requirements and running times are also discussed.
Toward Transparent Data Management in Multi-layer Storage Hierarchy for HPC Systems
Wadhwa, Bharti; Byna, Suren; Butt, Ali R.
2018-04-17
Upcoming exascale high performance computing (HPC) systems are expected to comprise multi-tier storage hierarchy, and thus will necessitate innovative storage and I/O mechanisms. Traditional disk and block-based interfaces and file systems face severe challenges in utilizing capabilities of storage hierarchies due to the lack of hierarchy support and semantic interfaces. Object-based and semantically-rich data abstractions for scientific data management on large scale systems offer a sustainable solution to these challenges. Such data abstractions can also simplify users involvement in data movement. Here, we take the first steps of realizing such an object abstraction and explore storage mechanisms for these objectsmore » to enhance I/O performance, especially for scientific applications. We explore how an object-based interface can facilitate next generation scalable computing systems by presenting the mapping of data I/O from two real world HPC scientific use cases: a plasma physics simulation code (VPIC) and a cosmology simulation code (HACC). Our storage model stores data objects in different physical organizations to support data movement across layers of memory/storage hierarchy. Our implementation sclaes well to 16K parallel processes, and compared to the state of the art, such as MPI-IO and HDF5, our object-based data abstractions and data placement strategy in multi-level storage hierarchy achieves up to 7 X I/O performance improvement for scientific data.« less
Multi-scale image segmentation and numerical modeling in carbonate rocks
NASA Astrophysics Data System (ADS)
Alves, G. C.; Vanorio, T.
2016-12-01
Numerical methods based on computational simulations can be an important tool in estimating physical properties of rocks. These can complement experimental results, especially when time constraints and sample availability are a problem. However, computational models created at different scales can yield conflicting results with respect to the physical laboratory. This problem is exacerbated in carbonate rocks due to their heterogeneity at all scales. We developed a multi-scale approach performing segmentation of the rock images and numerical modeling across several scales, accounting for those heterogeneities. As a first step, we measured the porosity and the elastic properties of a group of carbonate samples with varying micrite content. Then, samples were imaged by Scanning Electron Microscope (SEM) as well as optical microscope at different magnifications. We applied three different image segmentation techniques to create numerical models from the SEM images and performed numerical simulations of the elastic wave-equation. Our results show that a multi-scale approach can efficiently account for micro-porosities in tight micrite-supported samples, yielding acoustic velocities comparable to those obtained experimentally. Nevertheless, in high-porosity samples characterized by larger grain/micrite ratio, results show that SEM scale images tend to overestimate velocities, mostly due to their inability to capture macro- and/or intragranular- porosity. This suggests that, for high-porosity carbonate samples, optical microscope images would be more suited for numerical simulations.
Toward Transparent Data Management in Multi-layer Storage Hierarchy for HPC Systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wadhwa, Bharti; Byna, Suren; Butt, Ali R.
Upcoming exascale high performance computing (HPC) systems are expected to comprise multi-tier storage hierarchy, and thus will necessitate innovative storage and I/O mechanisms. Traditional disk and block-based interfaces and file systems face severe challenges in utilizing capabilities of storage hierarchies due to the lack of hierarchy support and semantic interfaces. Object-based and semantically-rich data abstractions for scientific data management on large scale systems offer a sustainable solution to these challenges. Such data abstractions can also simplify users involvement in data movement. Here, we take the first steps of realizing such an object abstraction and explore storage mechanisms for these objectsmore » to enhance I/O performance, especially for scientific applications. We explore how an object-based interface can facilitate next generation scalable computing systems by presenting the mapping of data I/O from two real world HPC scientific use cases: a plasma physics simulation code (VPIC) and a cosmology simulation code (HACC). Our storage model stores data objects in different physical organizations to support data movement across layers of memory/storage hierarchy. Our implementation sclaes well to 16K parallel processes, and compared to the state of the art, such as MPI-IO and HDF5, our object-based data abstractions and data placement strategy in multi-level storage hierarchy achieves up to 7 X I/O performance improvement for scientific data.« less
Model of a programmable quantum processing unit based on a quantum transistor effect
NASA Astrophysics Data System (ADS)
Ablayev, Farid; Andrianov, Sergey; Fetisov, Danila; Moiseev, Sergey; Terentyev, Alexandr; Urmanchev, Andrey; Vasiliev, Alexander
2018-02-01
In this paper we propose a model of a programmable quantum processing device realizable with existing nano-photonic technologies. It can be viewed as a basis for new high performance hardware architectures. Protocols for physical implementation of device on the controlled photon transfer and atomic transitions are presented. These protocols are designed for executing basic single-qubit and multi-qubit gates forming a universal set. We analyze the possible operation of this quantum computer scheme. Then we formalize the physical architecture by a mathematical model of a Quantum Processing Unit (QPU), which we use as a basis for the Quantum Programming Framework. This framework makes it possible to perform universal quantum computations in a multitasking environment.
TOPICAL REVIEW: Advances and challenges in computational plasma science
NASA Astrophysics Data System (ADS)
Tang, W. M.; Chan, V. S.
2005-02-01
Scientific simulation, which provides a natural bridge between theory and experiment, is an essential tool for understanding complex plasma behaviour. Recent advances in simulations of magnetically confined plasmas are reviewed in this paper, with illustrative examples, chosen from associated research areas such as microturbulence, magnetohydrodynamics and other topics. Progress has been stimulated, in particular, by the exponential growth of computer speed along with significant improvements in computer technology. The advances in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics have produced increasingly good agreement between experimental observations and computational modelling. This was enabled by two key factors: (a) innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning widely disparate temporal and spatial scales and (b) access to powerful new computational resources. Excellent progress has been made in developing codes for which computer run-time and problem-size scale well with the number of processors on massively parallel processors (MPPs). Examples include the effective usage of the full power of multi-teraflop (multi-trillion floating point computations per second) MPPs to produce three-dimensional, general geometry, nonlinear particle simulations that have accelerated advances in understanding the nature of turbulence self-regulation by zonal flows. These calculations, which typically utilized billions of particles for thousands of time-steps, would not have been possible without access to powerful present generation MPP computers and the associated diagnostic and visualization capabilities. In looking towards the future, the current results from advanced simulations provide great encouragement for being able to include increasingly realistic dynamics to enable deeper physics insights into plasmas in both natural and laboratory environments. This should produce the scientific excitement which will help to (a) stimulate enhanced cross-cutting collaborations with other fields and (b) attract the bright young talent needed for the future health of the field of plasma science.
Advances and challenges in computational plasma science
NASA Astrophysics Data System (ADS)
Tang, W. M.
2005-02-01
Scientific simulation, which provides a natural bridge between theory and experiment, is an essential tool for understanding complex plasma behaviour. Recent advances in simulations of magnetically confined plasmas are reviewed in this paper, with illustrative examples, chosen from associated research areas such as microturbulence, magnetohydrodynamics and other topics. Progress has been stimulated, in particular, by the exponential growth of computer speed along with significant improvements in computer technology. The advances in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics have produced increasingly good agreement between experimental observations and computational modelling. This was enabled by two key factors: (a) innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning widely disparate temporal and spatial scales and (b) access to powerful new computational resources. Excellent progress has been made in developing codes for which computer run-time and problem-size scale well with the number of processors on massively parallel processors (MPPs). Examples include the effective usage of the full power of multi-teraflop (multi-trillion floating point computations per second) MPPs to produce three-dimensional, general geometry, nonlinear particle simulations that have accelerated advances in understanding the nature of turbulence self-regulation by zonal flows. These calculations, which typically utilized billions of particles for thousands of time-steps, would not have been possible without access to powerful present generation MPP computers and the associated diagnostic and visualization capabilities. In looking towards the future, the current results from advanced simulations provide great encouragement for being able to include increasingly realistic dynamics to enable deeper physics insights into plasmas in both natural and laboratory environments. This should produce the scientific excitement which will help to (a) stimulate enhanced cross-cutting collaborations with other fields and (b) attract the bright young talent needed for the future health of the field of plasma science.
Provenance-aware optimization of workload for distributed data production
NASA Astrophysics Data System (ADS)
Makatun, Dzmitry; Lauret, Jérôme; Rudová, Hana; Šumbera, Michal
2017-10-01
Distributed data processing in High Energy and Nuclear Physics (HENP) is a prominent example of big data analysis. Having petabytes of data being processed at tens of computational sites with thousands of CPUs, standard job scheduling approaches either do not address well the problem complexity or are dedicated to one specific aspect of the problem only (CPU, network or storage). Previously we have developed a new job scheduling approach dedicated to distributed data production - an essential part of data processing in HENP (preprocessing in big data terminology). In this contribution, we discuss the load balancing with multiple data sources and data replication, present recent improvements made to our planner and provide results of simulations which demonstrate the advantage against standard scheduling policies for the new use case. Multi-source or provenance is common in computing models of many applications whereas the data may be copied to several destinations. The initial input data set would hence be already partially replicated to multiple locations and the task of the scheduler is to maximize overall computational throughput considering possible data movements and CPU allocation. The studies have shown that our approach can provide a significant gain in overall computational performance in a wide scope of simulations considering realistic size of computational Grid and various input data distribution.
Rosetta:MSF: a modular framework for multi-state computational protein design.
Löffler, Patrick; Schmitz, Samuel; Hupfeld, Enrico; Sterner, Reinhard; Merkl, Rainer
2017-06-01
Computational protein design (CPD) is a powerful technique to engineer existing proteins or to design novel ones that display desired properties. Rosetta is a software suite including algorithms for computational modeling and analysis of protein structures and offers many elaborate protocols created to solve highly specific tasks of protein engineering. Most of Rosetta's protocols optimize sequences based on a single conformation (i. e. design state). However, challenging CPD objectives like multi-specificity design or the concurrent consideration of positive and negative design goals demand the simultaneous assessment of multiple states. This is why we have developed the multi-state framework MSF that facilitates the implementation of Rosetta's single-state protocols in a multi-state environment and made available two frequently used protocols. Utilizing MSF, we demonstrated for one of these protocols that multi-state design yields a 15% higher performance than single-state design on a ligand-binding benchmark consisting of structural conformations. With this protocol, we designed de novo nine retro-aldolases on a conformational ensemble deduced from a (βα)8-barrel protein. All variants displayed measurable catalytic activity, testifying to a high success rate for this concept of multi-state enzyme design.
Rosetta:MSF: a modular framework for multi-state computational protein design
Hupfeld, Enrico; Sterner, Reinhard
2017-01-01
Computational protein design (CPD) is a powerful technique to engineer existing proteins or to design novel ones that display desired properties. Rosetta is a software suite including algorithms for computational modeling and analysis of protein structures and offers many elaborate protocols created to solve highly specific tasks of protein engineering. Most of Rosetta’s protocols optimize sequences based on a single conformation (i. e. design state). However, challenging CPD objectives like multi-specificity design or the concurrent consideration of positive and negative design goals demand the simultaneous assessment of multiple states. This is why we have developed the multi-state framework MSF that facilitates the implementation of Rosetta’s single-state protocols in a multi-state environment and made available two frequently used protocols. Utilizing MSF, we demonstrated for one of these protocols that multi-state design yields a 15% higher performance than single-state design on a ligand-binding benchmark consisting of structural conformations. With this protocol, we designed de novo nine retro-aldolases on a conformational ensemble deduced from a (βα)8-barrel protein. All variants displayed measurable catalytic activity, testifying to a high success rate for this concept of multi-state enzyme design. PMID:28604768
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
Computer aided design environment for the analysis and design of multi-body flexible structures
NASA Technical Reports Server (NTRS)
Ramakrishnan, Jayant V.; Singh, Ramen P.
1989-01-01
A computer aided design environment consisting of the programs NASTRAN, TREETOPS and MATLAB is presented in this paper. With links for data transfer between these programs, the integrated design of multi-body flexible structures is significantly enhanced. The CAD environment is used to model the Space Shuttle/Pinhole Occulater Facility. Then a controller is designed and evaluated in the nonlinear time history sense. Recent enhancements and ongoing research to add more capabilities are also described.
Grid-Enabled Quantitative Analysis of Breast Cancer
2010-10-01
large-scale, multi-modality computerized image analysis . The central hypothesis of this research is that large-scale image analysis for breast cancer...research, we designed a pilot study utilizing large scale parallel Grid computing harnessing nationwide infrastructure for medical image analysis . Also
Multi-Fluid Moment Simulations of Ganymede using the Next-Generation OpenGGCM
NASA Astrophysics Data System (ADS)
Wang, L.; Germaschewski, K.; Hakim, A.; Bhattacharjee, A.; Raeder, J.
2015-12-01
We coupled the multi-fluid moment code Gkeyll[1,2] to the next-generation OpenGGCM[3], and studied the reconnection dynamics at the Ganymede. This work is part of our effort to tackle the grand challenge of integrating kinetic effects into global fluid models. The multi-fluid moment model integrates kinetic effects in that it can capture crucial kinetic physics like pressure tensor effects by evolving moments of the Vlasov equations for each species. This approach has advantages over previous models: desired kinetic effects, together with other important effects like the Hall effect, are self-consistently embedded in the moment equations, and can be efficiently implemented, while not suffering from severe time-step restriction due to plasma oscillation nor artificial whistler modes. This model also handles multiple ion species naturally, which opens up opportunties in investigating the role of oxygen in magnetospheric reconnection and improved coupling to ionosphere models. In this work, the multi-fluid moment solver in Gkeyll was wrapped as a time-stepping module for the high performance, highly flexible next-generation OpenGGCM. Gkeyll is only used to provide the local plasma solver, while computational aspects like parallelization and boundary conditions are handled entirely by OpenGGCM, including interfacing to other models like ionospheric boundary conditions provided by coupling with CTIM [3]. The coupled code is used to study the dynamics near Ganymede, and the results are compared with MHD and Hall MHD results by Dorelli et al. [4]. Hakim, A. (2008). Journal of Fusion Energy, 27, 36-43. Hakim, A., Loverich, J., & Shumlak, U. (2006). Journal of Computational Physics, 219, 418-442. Raeder, J., Larson, D., Li, W., Kepko, E. L., & Fuller-Rowell, T. (2008). Space Science Reviews, 141(1-4), 535-555. Dorelli, J. C., Glocer, A., Collinson, G., & Tóth, G. (2015). Journal of Geophysical Research: Space Physics, 120.
NASA Astrophysics Data System (ADS)
El-Wardany, Tahany; Lynch, Mathew; Gu, Wenjiong; Hsu, Arthur; Klecka, Michael; Nardi, Aaron; Viens, Daniel
This paper proposes an optimization framework enabling the integration of multi-scale / multi-physics simulation codes to perform structural optimization design for additively manufactured components. Cold spray was selected as the additive manufacturing (AM) process and its constraints were identified and included in the optimization scheme. The developed framework first utilizes topology optimization to maximize stiffness for conceptual design. The subsequent step applies shape optimization to refine the design for stress-life fatigue. The component weight was reduced by 20% while stresses were reduced by 75% and the rigidity was improved by 37%. The framework and analysis codes were implemented using Altair software as well as an in-house loading code. The optimized design was subsequently produced by the cold spray process.
CLINICAL SURFACES - Activity-Based Computing for Distributed Multi-Display Environments in Hospitals
NASA Astrophysics Data System (ADS)
Bardram, Jakob E.; Bunde-Pedersen, Jonathan; Doryab, Afsaneh; Sørensen, Steffen
A multi-display environment (MDE) is made up of co-located and networked personal and public devices that form an integrated workspace enabling co-located group work. Traditionally, MDEs have, however, mainly been designed to support a single “smart room”, and have had little sense of the tasks and activities that the MDE is being used for. This paper presents a novel approach to support activity-based computing in distributed MDEs, where displays are physically distributed across a large building. CLINICAL SURFACES was designed for clinical work in hospitals, and enables context-sensitive retrieval and browsing of patient data on public displays. We present the design and implementation of CLINICAL SURFACES, and report from an evaluation of the system at a large hospital. The evaluation shows that using distributed public displays to support activity-based computing inside a hospital is very useful for clinical work, and that the apparent contradiction between maintaining privacy of medical data in a public display environment can be mitigated by the use of CLINICAL SURFACES.
Benchmarking NWP Kernels on Multi- and Many-core Processors
NASA Astrophysics Data System (ADS)
Michalakes, J.; Vachharajani, M.
2008-12-01
Increased computing power for weather, climate, and atmospheric science has provided direct benefits for defense, agriculture, the economy, the environment, and public welfare and convenience. Today, very large clusters with many thousands of processors are allowing scientists to move forward with simulations of unprecedented size. But time-critical applications such as real-time forecasting or climate prediction need strong scaling: faster nodes and processors, not more of them. Moreover, the need for good cost- performance has never been greater, both in terms of performance per watt and per dollar. For these reasons, the new generations of multi- and many-core processors being mass produced for commercial IT and "graphical computing" (video games) are being scrutinized for their ability to exploit the abundant fine- grain parallelism in atmospheric models. We present results of our work to date identifying key computational kernels within the dynamics and physics of a large community NWP model, the Weather Research and Forecast (WRF) model. We benchmark and optimize these kernels on several different multi- and many-core processors. The goals are to (1) characterize and model performance of the kernels in terms of computational intensity, data parallelism, memory bandwidth pressure, memory footprint, etc. (2) enumerate and classify effective strategies for coding and optimizing for these new processors, (3) assess difficulties and opportunities for tool or higher-level language support, and (4) establish a continuing set of kernel benchmarks that can be used to measure and compare effectiveness of current and future designs of multi- and many-core processors for weather and climate applications.
NASA Astrophysics Data System (ADS)
Fiala, L.; Lokajicek, M.; Tumova, N.
2015-05-01
This volume of the IOP Conference Series is dedicated to scientific contributions presented at the 16th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2014), this year the motto was ''bridging disciplines''. The conference took place on September 1-5, 2014, at the Faculty of Civil Engineering, Czech Technical University in Prague, Czech Republic. The 16th edition of ACAT explored the boundaries of computing system architectures, data analysis algorithmics, automatic calculations, and theoretical calculation technologies. It provided a forum for confronting and exchanging ideas among these fields, where new approaches in computing technologies for scientific research were explored and promoted. This year's edition of the workshop brought together over 140 participants from all over the world. The workshop's 16 invited speakers presented key topics on advanced computing and analysis techniques in physics. During the workshop, 60 talks and 40 posters were presented in three tracks: Computing Technology for Physics Research, Data Analysis - Algorithms and Tools, and Computations in Theoretical Physics: Techniques and Methods. The round table enabled discussions on expanding software, knowledge sharing and scientific collaboration in the respective areas. ACAT 2014 was generously sponsored by Western Digital, Brookhaven National Laboratory, Hewlett Packard, DataDirect Networks, M Computers, Bright Computing, Huawei and PDV-Systemhaus. Special appreciations go to the track liaisons Lorenzo Moneta, Axel Naumann and Grigory Rubtsov for their work on the scientific program and the publication preparation. ACAT's IACC would also like to express its gratitude to all referees for their work on making sure the contributions are published in the proceedings. Our thanks extend to the conference liaisons Andrei Kataev and Jerome Lauret who worked with the local contacts and made this conference possible as well as to the program coordinator Federico Carminati and the conference chair Denis Perret-Gallix for their global supervision. Further information on ACAT 2014 can be found at http://www.particle.cz/acat2014
NASA Technical Reports Server (NTRS)
Martin, William G.; Cairns, Brian; Bal, Guillaume
2014-01-01
This paper derives an efficient procedure for using the three-dimensional (3D) vector radiative transfer equation (VRTE) to adjust atmosphere and surface properties and improve their fit with multi-angle/multi-pixel radiometric and polarimetric measurements of scattered sunlight. The proposed adjoint method uses the 3D VRTE to compute the measurement misfit function and the adjoint 3D VRTE to compute its gradient with respect to all unknown parameters. In the remote sensing problems of interest, the scalar-valued misfit function quantifies agreement with data as a function of atmosphere and surface properties, and its gradient guides the search through this parameter space. Remote sensing of the atmosphere and surface in a three-dimensional region may require thousands of unknown parameters and millions of data points. Many approaches would require calls to the 3D VRTE solver in proportion to the number of unknown parameters or measurements. To avoid this issue of scale, we focus on computing the gradient of the misfit function as an alternative to the Jacobian of the measurement operator. The resulting adjoint method provides a way to adjust 3D atmosphere and surface properties with only two calls to the 3D VRTE solver for each spectral channel, regardless of the number of retrieval parameters, measurement view angles or pixels. This gives a procedure for adjusting atmosphere and surface parameters that will scale to the large problems of 3D remote sensing. For certain types of multi-angle/multi-pixel polarimetric measurements, this encourages the development of a new class of three-dimensional retrieval algorithms with more flexible parametrizations of spatial heterogeneity, less reliance on data screening procedures, and improved coverage in terms of the resolved physical processes in the Earth?s atmosphere.
A non-oscillatory energy-splitting method for the computation of compressible multi-fluid flows
NASA Astrophysics Data System (ADS)
Lei, Xin; Li, Jiequan
2018-04-01
This paper proposes a new non-oscillatory energy-splitting conservative algorithm for computing multi-fluid flows in the Eulerian framework. In comparison with existing multi-fluid algorithms in the literature, it is shown that the mass fraction model with isobaric hypothesis is a plausible choice for designing numerical methods for multi-fluid flows. Then we construct a conservative Godunov-based scheme with the high order accurate extension by using the generalized Riemann problem solver, through the detailed analysis of kinetic energy exchange when fluids are mixed under the hypothesis of isobaric equilibrium. Numerical experiments are carried out for the shock-interface interaction and shock-bubble interaction problems, which display the excellent performance of this type of schemes and demonstrate that nonphysical oscillations are suppressed around material interfaces substantially.
Multi-Scale Computational Modeling of Two-Phased Metal Using GMC Method
NASA Technical Reports Server (NTRS)
Moghaddam, Masoud Ghorbani; Achuthan, A.; Bednacyk, B. A.; Arnold, S. M.; Pineda, E. J.
2014-01-01
A multi-scale computational model for determining plastic behavior in two-phased CMSX-4 Ni-based superalloys is developed on a finite element analysis (FEA) framework employing crystal plasticity constitutive model that can capture the microstructural scale stress field. The generalized method of cells (GMC) micromechanics model is used for homogenizing the local field quantities. At first, GMC as stand-alone is validated by analyzing a repeating unit cell (RUC) as a two-phased sample with 72.9% volume fraction of gamma'-precipitate in the gamma-matrix phase and comparing the results with those predicted by finite element analysis (FEA) models incorporating the same crystal plasticity constitutive model. The global stress-strain behavior and the local field quantity distributions predicted by GMC demonstrated good agreement with FEA. High computational saving, at the expense of some accuracy in the components of local tensor field quantities, was obtained with GMC. Finally, the capability of the developed multi-scale model linking FEA and GMC to solve real life sized structures is demonstrated by analyzing an engine disc component and determining the microstructural scale details of the field quantities.
Development of the US3D Code for Advanced Compressible and Reacting Flow Simulations
NASA Technical Reports Server (NTRS)
Candler, Graham V.; Johnson, Heath B.; Nompelis, Ioannis; Subbareddy, Pramod K.; Drayna, Travis W.; Gidzak, Vladimyr; Barnhardt, Michael D.
2015-01-01
Aerothermodynamics and hypersonic flows involve complex multi-disciplinary physics, including finite-rate gas-phase kinetics, finite-rate internal energy relaxation, gas-surface interactions with finite-rate oxidation and sublimation, transition to turbulence, large-scale unsteadiness, shock-boundary layer interactions, fluid-structure interactions, and thermal protection system ablation and thermal response. Many of the flows have a large range of length and time scales, requiring large computational grids, implicit time integration, and large solution run times. The University of Minnesota NASA US3D code was designed for the simulation of these complex, highly-coupled flows. It has many of the features of the well-established DPLR code, but uses unstructured grids and has many advanced numerical capabilities and physical models for multi-physics problems. The main capabilities of the code are described, the physical modeling approaches are discussed, the different types of numerical flux functions and time integration approaches are outlined, and the parallelization strategy is overviewed. Comparisons between US3D and the NASA DPLR code are presented, and several advanced simulations are presented to illustrate some of novel features of the code.
Grid-converged solution and analysis of the unsteady viscous flow in a two-dimensional shock tube
NASA Astrophysics Data System (ADS)
Zhou, Guangzhao; Xu, Kun; Liu, Feng
2018-01-01
The flow in a shock tube is extremely complex with dynamic multi-scale structures of sharp fronts, flow separation, and vortices due to the interaction of the shock wave, the contact surface, and the boundary layer over the side wall of the tube. Prediction and understanding of the complex fluid dynamics are of theoretical and practical importance. It is also an extremely challenging problem for numerical simulation, especially at relatively high Reynolds numbers. Daru and Tenaud ["Evaluation of TVD high resolution schemes for unsteady viscous shocked flows," Comput. Fluids 30, 89-113 (2001)] proposed a two-dimensional model problem as a numerical test case for high-resolution schemes to simulate the flow field in a square closed shock tube. Though many researchers attempted this problem using a variety of computational methods, there is not yet an agreed-upon grid-converged solution of the problem at the Reynolds number of 1000. This paper presents a rigorous grid-convergence study and the resulting grid-converged solutions for this problem by using a newly developed, efficient, and high-order gas-kinetic scheme. Critical data extracted from the converged solutions are documented as benchmark data. The complex fluid dynamics of the flow at Re = 1000 are discussed and analyzed in detail. Major phenomena revealed by the numerical computations include the downward concentration of the fluid through the curved shock, the formation of the vortices, the mechanism of the shock wave bifurcation, the structure of the jet along the bottom wall, and the Kelvin-Helmholtz instability near the contact surface. Presentation and analysis of those flow processes provide important physical insight into the complex flow physics occurring in a shock tube.
The space physics analysis network
NASA Astrophysics Data System (ADS)
Green, James L.
1988-04-01
The Space Physics Analysis Network, or SPAN, is emerging as a viable method for solving an immediate communication problem for space and Earth scientists and has been operational for nearly 7 years. SPAN and its extension into Europe, utilizes computer-to-computer communications allowing mail, binary and text file transfer, and remote logon capability to over 1000 space science computer systems. The network has been used to successfully transfer real-time data to remote researchers for rapid data analysis but its primary function is for non-real-time applications. One of the major advantages for using SPAN is its spacecraft mission independence. Space science researchers using SPAN are located in universities, industries and government institutions all across the United States and Europe. These researchers are in such fields as magnetospheric physics, astrophysics, ionosperic physics, atmospheric physics, climatology, meteorology, oceanography, planetary physics and solar physics. SPAN users have access to space and Earth science data bases, mission planning and information systems, and computational facilities for the purposes of facilitating correlative space data exchange, data analysis and space research. For example, the National Space Science Data Center (NSSDC), which manages the network, is providing facilities on SPAN such as the Network Information Center (SPAN NIC). SPAN has interconnections with several national and international networks such as HEPNET and TEXNET forming a transparent DECnet network. The combined total number of computers now reachable over these combined networks is about 2000. In addition, SPAN supports full function capabilities over the international public packet switched networks (e.g. TELENET) and has mail gateways to ARPANET, BITNET and JANET.
Thermal Analysis of Magnetically-Coupled Pump for Cryogenic Applications
NASA Technical Reports Server (NTRS)
Senocak, Inanc; Udaykumar, H. S.; Ndri, Narcisse; Francois, Marianne; Shyy, Wei
1999-01-01
Magnetically-coupled pump is under evaluation at Kennedy Space Center for possible cryogenic applications. A major concern is the impact of low temperature fluid flows on the pump performance. As a first step toward addressing this and related issues, a computational fluid dynamics and heat transfer tool has been adopted in a pump geometry. The computational tool includes (i) a commercial grid generator to handle multiple grid blocks and complicated geometric definitions, and (ii) an in-house computational fluid dynamics and heat transfer software developed in the Principal Investigator's group at the University of Florida. Both pure-conduction and combined convection-conduction computations have been conducted. A pure-conduction analysis gives insufficient information about the overall thermal distribution. Combined convection-conduction analysis indicates the significant influence of the coolant over the entire flow path. Since 2-D simulation is of limited help, future work on full 3-D modeling of the pump using multi-materials is needed. A comprehensive and accurate model can be developed to take into account the effect of multi-phase flow in the cooling flow loop, and the magnetic interactions.
Yang, Chaowei; Wu, Huayi; Huang, Qunying; Li, Zhenlong; Li, Jing
2011-01-01
Contemporary physical science studies rely on the effective analyses of geographically dispersed spatial data and simulations of physical phenomena. Single computers and generic high-end computing are not sufficient to process the data for complex physical science analysis and simulations, which can be successfully supported only through distributed computing, best optimized through the application of spatial principles. Spatial computing, the computing aspect of a spatial cyberinfrastructure, refers to a computing paradigm that utilizes spatial principles to optimize distributed computers to catalyze advancements in the physical sciences. Spatial principles govern the interactions between scientific parameters across space and time by providing the spatial connections and constraints to drive the progression of the phenomena. Therefore, spatial computing studies could better position us to leverage spatial principles in simulating physical phenomena and, by extension, advance the physical sciences. Using geospatial science as an example, this paper illustrates through three research examples how spatial computing could (i) enable data intensive science with efficient data/services search, access, and utilization, (ii) facilitate physical science studies with enabling high-performance computing capabilities, and (iii) empower scientists with multidimensional visualization tools to understand observations and simulations. The research examples demonstrate that spatial computing is of critical importance to design computing methods to catalyze physical science studies with better data access, phenomena simulation, and analytical visualization. We envision that spatial computing will become a core technology that drives fundamental physical science advancements in the 21st century. PMID:21444779
Yang, Chaowei; Wu, Huayi; Huang, Qunying; Li, Zhenlong; Li, Jing
2011-04-05
Contemporary physical science studies rely on the effective analyses of geographically dispersed spatial data and simulations of physical phenomena. Single computers and generic high-end computing are not sufficient to process the data for complex physical science analysis and simulations, which can be successfully supported only through distributed computing, best optimized through the application of spatial principles. Spatial computing, the computing aspect of a spatial cyberinfrastructure, refers to a computing paradigm that utilizes spatial principles to optimize distributed computers to catalyze advancements in the physical sciences. Spatial principles govern the interactions between scientific parameters across space and time by providing the spatial connections and constraints to drive the progression of the phenomena. Therefore, spatial computing studies could better position us to leverage spatial principles in simulating physical phenomena and, by extension, advance the physical sciences. Using geospatial science as an example, this paper illustrates through three research examples how spatial computing could (i) enable data intensive science with efficient data/services search, access, and utilization, (ii) facilitate physical science studies with enabling high-performance computing capabilities, and (iii) empower scientists with multidimensional visualization tools to understand observations and simulations. The research examples demonstrate that spatial computing is of critical importance to design computing methods to catalyze physical science studies with better data access, phenomena simulation, and analytical visualization. We envision that spatial computing will become a core technology that drives fundamental physical science advancements in the 21st century.
A multi-physics analysis for the actuation of the SSS in opal reactor
NASA Astrophysics Data System (ADS)
Ferraro, Diego; Alberto, Patricio; Villarino, Eduardo; Doval, Alicia
2018-05-01
OPAL is a 20 MWth multi-purpose open-pool type Research Reactor located at Lucas Heights, Australia. It was designed, built and commissioned by INVAP between 2000 and 2006 and it has been operated by the Australia Nuclear Science and Technology Organization (ANSTO) showing a very good overall performance. On November 2016, OPAL reached 10 years of continuous operation, becoming one of the most reliable and available in its kind worldwide, with an unbeaten record of being fully operational 307 days a year. One of the enhanced safety features present in this state-of-art reactor is the availability of an independent, diverse and redundant Second Shutdown System (SSS), which consists in the drainage of the heavy water reflector contained in the Reflector Vessel. As far as high quality experimental data is available from reactor commissioning and operation stages and even from early component design validation stages, several models both regarding neutronic and thermo-hydraulic approaches have been developed during recent years using advanced calculations tools and the novel capabilities to couple them. These advanced models were developed in order to assess the capability of such codes to simulate and predict complex behaviours and develop highly detail analysis. In this framework, INVAP developed a three-dimensional CFD model that represents the detailed hydraulic behaviour of the Second Shutdown System for an actuation scenario, where the heavy water drainage 3D temporal profiles inside the Reflector Vessel can be obtained. This model was validated, comparing the computational results with experimental measurements performed in a real-size physical model built by INVAP during early OPAL design engineering stages. Furthermore, detailed 3D Serpent Monte Carlo models are also available, which have been already validated with experimental data from reactor commissioning and operating cycles. In the present work the neutronic and thermohydraulic models, available for OPAL reactor, are coupled by means of a shared unstructured mesh geometry definition of relevant zones inside the Reflector Vessel. Several scenarios, both regarding coupled and uncoupled neutronic & thermohydraulic behavior, are presented and analyzed, showing the capabilities to develop and manage advanced modelling that allows to predict multi-physics variables observed when an in-depth performance analysis of a Research Reactor like OPAL is carried out.
Programmable multi-zone furnace for microgravity research
NASA Technical Reports Server (NTRS)
Rosenthal, Bruce N.; Krolikowski, Cathryn R.
1991-01-01
In order to provide new furnace technology to accommodate microgravity research studies and commercial applications in material processes, research has been initiated on the development of the Programmable-Multi-zone Furnace (PMZF). The PMZF is described as a multi-user materials processing furnace facility that is composed of thirty or more heater elements in series on a muffle tube or in a stacked ring-type configuration and independently controlled by a computer. One of the aims of the PMZF project is to allow furnace thermal gradient profiles to be reconfigured without physical modification of the hardware by creating the capability of reconfiguring thermal profiles in response to investigators' requests. The future location of the PMZF facility is discussed; the preliminary science survey results and preliminary conceptual designs for the PMZF are presented; and a review of multi-zone furnace technology is given.
NASA Astrophysics Data System (ADS)
Pokhrel, A.; El Hannach, M.; Orfino, F. P.; Dutta, M.; Kjeang, E.
2016-10-01
X-ray computed tomography (XCT), a non-destructive technique, is proposed for three-dimensional, multi-length scale characterization of complex failure modes in fuel cell electrodes. Comparative tomography data sets are acquired for a conditioned beginning of life (BOL) and a degraded end of life (EOL) membrane electrode assembly subjected to cathode degradation by voltage cycling. Micro length scale analysis shows a five-fold increase in crack size and 57% thickness reduction in the EOL cathode catalyst layer, indicating widespread action of carbon corrosion. Complementary nano length scale analysis shows a significant reduction in porosity, increased pore size, and dramatically reduced effective diffusivity within the remaining porous structure of the catalyst layer at EOL. Collapsing of the structure is evident from the combination of thinning and reduced porosity, as uniquely determined by the multi-length scale approach. Additionally, a novel image processing based technique developed for nano scale segregation of pore, ionomer, and Pt/C dominated voxels shows an increase in ionomer volume fraction, Pt/C agglomerates, and severe carbon corrosion at the catalyst layer/membrane interface at EOL. In summary, XCT based multi-length scale analysis enables detailed information needed for comprehensive understanding of the complex failure modes observed in fuel cell electrodes.
NASA Astrophysics Data System (ADS)
Abdeljabbar Kharrat, Nourhene; Plateaux, Régis; Miladi Chaabane, Mariem; Choley, Jean-Yves; Karra, Chafik; Haddar, Mohamed
2018-05-01
The present work tackles the modeling of multi-physics systems applying a topological approach while proceeding with a new methodology using a topological modification to the structure of systems. Then the comparison with the Magos' methodology is made. Their common ground is the use of connectivity within systems. The comparison and analysis of the different types of modeling show the importance of the topological methodology through the integration of the topological modification to the topological structure of a multi-physics system. In order to validate this methodology, the case of Pogo-stick is studied. The first step consists in generating a topological graph of the system. Then the connectivity step takes into account the contact with the ground. During the last step of this research; the MGS language (Modeling of General System) is used to model the system through equations. Finally, the results are compared to those obtained by MODELICA. Therefore, this proposed methodology may be generalized to model multi-physics systems that can be considered as a set of local elements.
BESIU Physical Analysis on Hadoop Platform
NASA Astrophysics Data System (ADS)
Huo, Jing; Zang, Dongsong; Lei, Xiaofeng; Li, Qiang; Sun, Gongxing
2014-06-01
In the past 20 years, computing cluster has been widely used for High Energy Physics data processing. The jobs running on the traditional cluster with a Data-to-Computing structure, have to read large volumes of data via the network to the computing nodes for analysis, thereby making the I/O latency become a bottleneck of the whole system. The new distributed computing technology based on the MapReduce programming model has many advantages, such as high concurrency, high scalability and high fault tolerance, and it can benefit us in dealing with Big Data. This paper brings the idea of using MapReduce model to do BESIII physical analysis, and presents a new data analysis system structure based on Hadoop platform, which not only greatly improve the efficiency of data analysis, but also reduces the cost of system building. Moreover, this paper establishes an event pre-selection system based on the event level metadata(TAGs) database to optimize the data analyzing procedure.
Kanbar, Lara J; Shalish, Wissam; Precup, Doina; Brown, Karen; Sant'Anna, Guilherme M; Kearney, Robert E
2017-07-01
In multi-disciplinary studies, different forms of data are often collected for analysis. For example, APEX, a study on the automated prediction of extubation readiness in extremely preterm infants, collects clinical parameters and cardiorespiratory signals. A variety of cardiorespiratory metrics are computed from these signals and used to assign a cardiorespiratory pattern at each time. In such a situation, exploratory analysis requires a visualization tool capable of displaying these different types of acquired and computed signals in an integrated environment. Thus, we developed APEX_SCOPE, a graphical tool for the visualization of multi-modal data comprising cardiorespiratory signals, automated cardiorespiratory metrics, automated respiratory patterns, manually classified respiratory patterns, and manual annotations by clinicians during data acquisition. This MATLAB-based application provides a means for collaborators to view combinations of signals to promote discussion, generate hypotheses and develop features.
Development of an extensible dual-core wireless sensing node for cyber-physical systems
NASA Astrophysics Data System (ADS)
Kane, Michael; Zhu, Dapeng; Hirose, Mitsuhito; Dong, Xinjun; Winter, Benjamin; Häckell, Mortiz; Lynch, Jerome P.; Wang, Yang; Swartz, A.
2014-04-01
The introduction of wireless telemetry into the design of monitoring and control systems has been shown to reduce system costs while simplifying installations. To date, wireless nodes proposed for sensing and actuation in cyberphysical systems have been designed using microcontrollers with one computational pipeline (i.e., single-core microcontrollers). While concurrent code execution can be implemented on single-core microcontrollers, concurrency is emulated by splitting the pipeline's resources to support multiple threads of code execution. For many applications, this approach to multi-threading is acceptable in terms of speed and function. However, some applications such as feedback controls demand deterministic timing of code execution and maximum computational throughput. For these applications, the adoption of multi-core processor architectures represents one effective solution. Multi-core microcontrollers have multiple computational pipelines that can execute embedded code in parallel and can be interrupted independent of one another. In this study, a new wireless platform named Martlet is introduced with a dual-core microcontroller adopted in its design. The dual-core microcontroller design allows Martlet to dedicate one core to standard wireless sensor operations while the other core is reserved for embedded data processing and real-time feedback control law execution. Another distinct feature of Martlet is a standardized hardware interface that allows specialized daughter boards (termed wing boards) to be interfaced to the Martlet baseboard. This extensibility opens opportunity to encapsulate specialized sensing and actuation functions in a wing board without altering the design of Martlet. In addition to describing the design of Martlet, a few example wings are detailed, along with experiments showing the Martlet's ability to monitor and control physical systems such as wind turbines and buildings.
Multi-representation based on scientific investigation for enhancing students’ representation skills
NASA Astrophysics Data System (ADS)
Siswanto, J.; Susantini, E.; Jatmiko, B.
2018-03-01
This research aims to implementation learning physics with multi-representation based on the scientific investigation for enhancing students’ representation skills, especially on the magnetic field subject. The research design is one group pretest-posttest. This research was conducted in the department of mathematics education, Universitas PGRI Semarang, with the sample is students of class 2F who take basic physics courses. The data were obtained by representation skills test and documentation of multi-representation worksheet. The Results show gain analysis
Next Generation Workload Management System For Big Data on Heterogeneous Distributed Computing
Klimentov, A.; Buncic, P.; De, K.; ...
2015-05-22
The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS and ALICE are the largest collaborations ever assembled in the sciences and are at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, both experiments rely on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Managementmore » System (WMS) for managing the workflow for all data processing on hundreds of data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. The scale is demonstrated by the following numbers: PanDA manages O(10 2) sites, O(10 5) cores, O(10 8) jobs per year, O(10 3) users, and ATLAS data volume is O(10 17) bytes. In 2013 we started an ambitious program to expand PanDA to all available computing resources, including opportunistic use of commercial and academic clouds and Leadership Computing Facilities (LCF). The project titled 'Next Generation Workload Management and Analysis System for Big Data' (BigPanDA) is funded by DOE ASCR and HEP. Extending PanDA to clouds and LCF presents new challenges in managing heterogeneity and supporting workflow. The BigPanDA project is underway to setup and tailor PanDA at the Oak Ridge Leadership Computing Facility (OLCF) and at the National Research Center "Kurchatov Institute" together with ALICE distributed computing and ORNL computing professionals. Our approach to integration of HPC platforms at the OLCF and elsewhere is to reuse, as much as possible, existing components of the PanDA system. Finally, we will present our current accomplishments with running the PanDA WMS at OLCF and other supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications.« less
Next Generation Workload Management System For Big Data on Heterogeneous Distributed Computing
DOE Office of Scientific and Technical Information (OSTI.GOV)
Klimentov, A.; Buncic, P.; De, K.
The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS and ALICE are the largest collaborations ever assembled in the sciences and are at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, both experiments rely on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Managementmore » System (WMS) for managing the workflow for all data processing on hundreds of data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. The scale is demonstrated by the following numbers: PanDA manages O(10 2) sites, O(10 5) cores, O(10 8) jobs per year, O(10 3) users, and ATLAS data volume is O(10 17) bytes. In 2013 we started an ambitious program to expand PanDA to all available computing resources, including opportunistic use of commercial and academic clouds and Leadership Computing Facilities (LCF). The project titled 'Next Generation Workload Management and Analysis System for Big Data' (BigPanDA) is funded by DOE ASCR and HEP. Extending PanDA to clouds and LCF presents new challenges in managing heterogeneity and supporting workflow. The BigPanDA project is underway to setup and tailor PanDA at the Oak Ridge Leadership Computing Facility (OLCF) and at the National Research Center "Kurchatov Institute" together with ALICE distributed computing and ORNL computing professionals. Our approach to integration of HPC platforms at the OLCF and elsewhere is to reuse, as much as possible, existing components of the PanDA system. Finally, we will present our current accomplishments with running the PanDA WMS at OLCF and other supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications.« less
NASA Astrophysics Data System (ADS)
Zunino, Andrea; Mosegaard, Klaus
2017-04-01
Sought-after reservoir properties of interest are linked only indirectly to the observable geophysical data which are recorded at the earth's surface. In this framework, seismic data represent one of the most reliable tool to study the structure and properties of the subsurface for natural resources. Nonetheless, seismic analysis is not an end in itself, as physical properties such as porosity are often of more interest for reservoir characterization. As such, inference of those properties implies taking into account also rock physics models linking porosity and other physical properties to elastic parameters. In the framework of seismic reflection data, we address this challenge for a reservoir target zone employing a probabilistic method characterized by a multi-step complex nonlinear forward modeling that combines: 1) a rock physics model with 2) the solution of full Zoeppritz equations and 3) a convolutional seismic forward modeling. The target property of this work is porosity, which is inferred using a Monte Carlo approach where porosity models, i.e., solutions to the inverse problem, are directly sampled from the posterior distribution. From a theoretical point of view, the Monte Carlo strategy can be particularly useful in the presence of nonlinear forward models, which is often the case when employing sophisticated rock physics models and full Zoeppritz equations and to estimate related uncertainty. However, the resulting computational challenge is huge. We propose to alleviate this computational burden by assuming some smoothness of the subsurface parameters and consequently parameterizing the model in terms of spline bases. This allows us a certain flexibility in that the number of spline bases and hence the resolution in each spatial direction can be controlled. The method is tested on a 3-D synthetic case and on a 2-D real data set.
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
NASA Astrophysics Data System (ADS)
Rahman, M. S.; Pota, H. R.; Mahmud, M. A.; Hossain, M. J.
2016-05-01
This paper presents the impact of large penetration of wind power on the transient stability through a dynamic evaluation of the critical clearing times (CCTs) by using intelligent agent-based approach. A decentralised multi-agent-based framework is developed, where agents represent a number of physical device models to form a complex infrastructure for computation and communication. They enable the dynamic flow of information and energy for the interaction between the physical processes and their activities. These agents dynamically adapt online measurements and use the CCT information for relay coordination to improve the transient stability of power systems. Simulations are carried out on a smart microgrid system for faults at increasing wind power penetration levels and the improvement in transient stability using the proposed agent-based framework is demonstrated.
A Browser-Based Multi-User Working Environment for Physicists
NASA Astrophysics Data System (ADS)
Erdmann, M.; Fischer, R.; Glaser, C.; Klingebiel, D.; Komm, M.; Müller, G.; Rieger, M.; Steggemann, J.; Urban, M.; Winchen, T.
2014-06-01
Many programs in experimental particle physics do not yet have a graphical interface, or demand strong platform and software requirements. With the most recent development of the VISPA project, we provide graphical interfaces to existing software programs and access to multiple computing clusters through standard web browsers. The scalable clientserver system allows analyses to be performed in sizable teams, and disburdens the individual physicist from installing and maintaining a software environment. The VISPA graphical interfaces are implemented in HTML, JavaScript and extensions to the Python webserver. The webserver uses SSH and RPC to access user data, code and processes on remote sites. As example applications we present graphical interfaces for steering the reconstruction framework OFFLINE of the Pierre-Auger experiment, and the analysis development toolkit PXL. The browser based VISPA system was field-tested in biweekly homework of a third year physics course by more than 100 students. We discuss the system deployment and the evaluation by the students.
Multi-disciplinary coupling effects for integrated design of propulsion systems
NASA Technical Reports Server (NTRS)
Chamis, C. C.; Singhal, S. N.
1993-01-01
Effective computational simulation procedures are described for modeling the inherent multi-disciplinary interactions which govern the accurate response of propulsion systems. Results are presented for propulsion system responses including multi-disciplinary coupling effects using coupled multi-discipline thermal, structural, and acoustic tailoring; an integrated system of multi-disciplinary simulators; coupled material behavior/fabrication process tailoring; sensitivities using a probabilistic simulator; and coupled materials, structures, fracture, and probabilistic behavior simulator. The results demonstrate that superior designs can be achieved if the analysis/tailoring methods account for the multi-disciplinary coupling effects. The coupling across disciplines can be used to develop an integrated coupled multi-discipline numerical propulsion system simulator.
Structure identification methods for atomistic simulations of crystalline materials
Stukowski, Alexander
2012-05-28
Here, we discuss existing and new computational analysis techniques to classify local atomic arrangements in large-scale atomistic computer simulations of crystalline solids. This article includes a performance comparison of typical analysis algorithms such as common neighbor analysis (CNA), centrosymmetry analysis, bond angle analysis, bond order analysis and Voronoi analysis. In addition we propose a simple extension to the CNA method that makes it suitable for multi-phase systems. Finally, we introduce a new structure identification algorithm, the neighbor distance analysis, which is designed to identify atomic structure units in grain boundaries.
Scientific Discovery through Advanced Computing in Plasma Science
NASA Astrophysics Data System (ADS)
Tang, William
2005-03-01
Advanced computing is generally recognized to be an increasingly vital tool for accelerating progress in scientific research during the 21st Century. For example, the Department of Energy's ``Scientific Discovery through Advanced Computing'' (SciDAC) Program was motivated in large measure by the fact that formidable scientific challenges in its research portfolio could best be addressed by utilizing the combination of the rapid advances in super-computing technology together with the emergence of effective new algorithms and computational methodologies. The imperative is to translate such progress into corresponding increases in the performance of the scientific codes used to model complex physical systems such as those encountered in high temperature plasma research. If properly validated against experimental measurements and analytic benchmarks, these codes can provide reliable predictive capability for the behavior of a broad range of complex natural and engineered systems. This talk reviews recent progress and future directions for advanced simulations with some illustrative examples taken from the plasma science applications area. Significant recent progress has been made in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics, giving increasingly good agreement between experimental observations and computational modeling. This was made possible by the combination of access to powerful new computational resources together with innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning a huge range in time and space scales. In particular, the plasma science community has made excellent progress in developing advanced codes for which computer run-time and problem size scale well with the number of processors on massively parallel machines (MPP's). A good example is the effective usage of the full power of multi-teraflop (multi-trillion floating point computations per second) MPP's to produce three-dimensional, general geometry, nonlinear particle simulations which have accelerated progress in understanding the nature of plasma turbulence in magnetically-confined high temperature plasmas. These calculations, which typically utilized billions of particles for thousands of time-steps, would not have been possible without access to powerful present generation MPP computers and the associated diagnostic and visualization capabilities. In general, results from advanced simulations provide great encouragement for being able to include increasingly realistic dynamics to enable deeper physics insights into plasmas in both natural and laboratory environments. The associated scientific excitement should serve to stimulate improved cross-cutting collaborations with other fields and also to help attract bright young talent to the computational science area.
Cytobank: providing an analytics platform for community cytometry data analysis and collaboration.
Chen, Tiffany J; Kotecha, Nikesh
2014-01-01
Cytometry is used extensively in clinical and laboratory settings to diagnose and track cell subsets in blood and tissue. High-throughput, single-cell approaches leveraging cytometry are developed and applied in the computational and systems biology communities by researchers, who seek to improve the diagnosis of human diseases, map the structures of cell signaling networks, and identify new cell types. Data analysis and management present a bottleneck in the flow of knowledge from bench to clinic. Multi-parameter flow and mass cytometry enable identification of signaling profiles of patient cell samples. Currently, this process is manual, requiring hours of work to summarize multi-dimensional data and translate these data for input into other analysis programs. In addition, the increase in the number and size of collaborative cytometry studies as well as the computational complexity of analytical tools require the ability to assemble sufficient and appropriately configured computing capacity on demand. There is a critical need for platforms that can be used by both clinical and basic researchers who routinely rely on cytometry. Recent advances provide a unique opportunity to facilitate collaboration and analysis and management of cytometry data. Specifically, advances in cloud computing and virtualization are enabling efficient use of large computing resources for analysis and backup. An example is Cytobank, a platform that allows researchers to annotate, analyze, and share results along with the underlying single-cell data.
Coupled Physics Environment (CouPE) library - Design, Implementation, and Release
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mahadevan, Vijay S.
Over several years, high fidelity, validated mono-physics solvers with proven scalability on peta-scale architectures have been developed independently. Based on a unified component-based architecture, these existing codes can be coupled with a unified mesh-data backplane and a flexible coupling-strategy-based driver suite to produce a viable tool for analysts. In this report, we present details on the design decisions and developments on CouPE, an acronym that stands for Coupled Physics Environment that orchestrates a coupled physics solver through the interfaces exposed by MOAB array-based unstructured mesh, both of which are part of SIGMA (Scalable Interfaces for Geometry and Mesh-Based Applications) toolkit.more » The SIGMA toolkit contains libraries that enable scalable geometry and unstructured mesh creation and handling in a memory and computationally efficient implementation. The CouPE version being prepared for a full open-source release along with updated documentation will contain several useful examples that will enable users to start developing their applications natively using the native MOAB mesh and couple their models to existing physics applications to analyze and solve real world problems of interest. An integrated multi-physics simulation capability for the design and analysis of current and future nuclear reactor models is also being investigated as part of the NEAMS RPL, to tightly couple neutron transport, thermal-hydraulics and structural mechanics physics under the SHARP framework. This report summarizes the efforts that have been invested in CouPE to bring together several existing physics applications namely PROTEUS (neutron transport code), Nek5000 (computational fluid-dynamics code) and Diablo (structural mechanics code). The goal of the SHARP framework is to perform fully resolved coupled physics analysis of a reactor on heterogeneous geometry, in order to reduce the overall numerical uncertainty while leveraging available computational resources. The design of CouPE along with motivations that led to implementation choices are also discussed. The first release of the library will be different from the current version of the code that integrates the components in SHARP and explanation on the need for forking the source base will also be provided. Enhancements in the functionality and improved user guides will be available as part of the release. CouPE v0.1 is scheduled for an open-source release in December 2014 along with SIGMA v1.1 components that provide support for language-agnostic mesh loading, traversal and query interfaces along with scalable solution transfer of fields between different physics codes. The coupling methodology and software interfaces of the library are presented, along with verification studies on two representative fast sodium-cooled reactor demonstration problems to prove the usability of the CouPE library.« less
Problems Related to Parallelization of CFD Algorithms on GPU, Multi-GPU and Hybrid Architectures
NASA Astrophysics Data System (ADS)
Biazewicz, Marek; Kurowski, Krzysztof; Ludwiczak, Bogdan; Napieraia, Krystyna
2010-09-01
Computational Fluid Dynamics (CFD) is one of the branches of fluid mechanics, which uses numerical methods and algorithms to solve and analyze fluid flows. CFD is used in various domains, such as oil and gas reservoir uncertainty analysis, aerodynamic body shapes optimization (e.g. planes, cars, ships, sport helmets, skis), natural phenomena analysis, numerical simulation for weather forecasting or realistic visualizations. CFD problem is very complex and needs a lot of computational power to obtain the results in a reasonable time. We have implemented a parallel application for two-dimensional CFD simulation with a free surface approximation (MAC method) using new hardware architectures, in particular multi-GPU and hybrid computing environments. For this purpose we decided to use NVIDIA graphic cards with CUDA environment due to its simplicity of programming and good computations performance. We used finite difference discretization of Navier-Stokes equations, where fluid is propagated over an Eulerian Grid. In this model, the behavior of the fluid inside the cell depends only on the properties of local, surrounding cells, therefore it is well suited for the GPU-based architecture. In this paper we demonstrate how to use efficiently the computing power of GPUs for CFD. Additionally, we present some best practices to help users analyze and improve the performance of CFD applications executed on GPU. Finally, we discuss various challenges around the multi-GPU implementation on the example of matrix multiplication.
Physical activity and asthma: A longitudinal and multi-country study.
Russell, Melissa A; Janson, Christer; Real, Francisco Gómez; Johannessen, Ane; Waatevik, Marie; Benediktsdóttir, Bryndis; Holm, Mathias; Lindberg, Eva; Schlünssen, Vivi; Raza, Wasif; Dharmage, Shyamali C; Svanes, Cecilie
2017-11-01
To investigate the impact of physical activity on asthma in middle-aged adults, in one longitudinal analysis, and one multi-centre cross-sectional analysis. The Respiratory Health in Northern Europe (RHINE) is a population-based postal questionnaire cohort study. Physical activity, height and weight were self-reported in Bergen, Norway, at RHINE II (1999-2001) and all centres at RHINE III (2010-2012). A longitudinal analysis of Bergen data investigated the association of baseline physical activity with follow-up asthma, incident asthma and symptoms, using logistic and zero-inflated Poisson regression (n = 1782). A cross-sectional analysis of all RHINE III centres investigated the association of physical activity with concurrent asthma and symptoms (n = 13,542) using mixed-effects models. Body mass index (BMI) was categorised (<20, 20-24.99, 25-29.99, 30+ kg/m 2 ) and physical activity grouped by amount and frequency of lighter (no sweating/heavy breathing) and vigorous (sweating/heavy breathing) activity. In the Bergen longitudinal analysis, undertaking light activity 3+ times/week at baseline was associated with less follow-up asthma (odds ratio [OR] 0.44, 95% confidence interval [CI] 0.22, 0.89), whilst an effect from undertaking vigorous activity 3+ times/week was not detected (OR 1.22, 95% CI 0.44, 2.76). The associations were attenuated with BMI adjustment. In the all-centre cross-sectional analysis an interaction was found, with the association between physical activity and asthma varying across BMI categories. These findings suggest potential longer-term benefit from lighter physical activity, whilst improvement in asthma outcomes from increasing activity intensity was not evident. Additionally, it appears the benefit from physical activity may differ according to BMI.
FAST: A multi-processed environment for visualization of computational fluid dynamics
NASA Technical Reports Server (NTRS)
Bancroft, Gordon V.; Merritt, Fergus J.; Plessel, Todd C.; Kelaita, Paul G.; Mccabe, R. Kevin
1991-01-01
Three-dimensional, unsteady, multi-zoned fluid dynamics simulations over full scale aircraft are typical of the problems being investigated at NASA Ames' Numerical Aerodynamic Simulation (NAS) facility on CRAY2 and CRAY-YMP supercomputers. With multiple processor workstations available in the 10-30 Mflop range, we feel that these new developments in scientific computing warrant a new approach to the design and implementation of analysis tools. These larger, more complex problems create a need for new visualization techniques not possible with the existing software or systems available as of this writing. The visualization techniques will change as the supercomputing environment, and hence the scientific methods employed, evolves even further. The Flow Analysis Software Toolkit (FAST), an implementation of a software system for fluid mechanics analysis, is discussed.
A Quantum Multi-proxy Blind Signature Scheme Based on Genuine Four-Qubit Entangled State
NASA Astrophysics Data System (ADS)
Tian, Juan-Hong; Zhang, Jian-Zhong; Li, Yan-Ping
2016-02-01
In this paper, we propose a multi-proxy blind signature scheme based on controlled teleportation. Genuine four-qubit entangled state functions as quantum channel. The scheme uses the physical characteristics of quantum mechanics to implement delegation, signature and verification. The security analysis shows the scheme satisfies the security features of multi-proxy signature, unforgeability, undeniability, blindness and unconditional security.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Crossno, Patricia J.; Gittinger, Jaxon; Hunt, Warren L.
Slycat™ is a web-based system for performing data analysis and visualization of potentially large quantities of remote, high-dimensional data. Slycat™ specializes in working with ensemble data. An ensemble is a group of related data sets, which typically consists of a set of simulation runs exploring the same problem space. An ensemble can be thought of as a set of samples within a multi-variate domain, where each sample is a vector whose value defines a point in high-dimensional space. To understand and describe the underlying problem being modeled in the simulations, ensemble analysis looks for shared behaviors and common features acrossmore » the group of runs. Additionally, ensemble analysis tries to quantify differences found in any members that deviate from the rest of the group. The Slycat™ system integrates data management, scalable analysis, and visualization. Results are viewed remotely on a user’s desktop via commodity web clients using a multi-tiered hierarchy of computation and data storage, as shown in Figure 1. Our goal is to operate on data as close to the source as possible, thereby reducing time and storage costs associated with data movement. Consequently, we are working to develop parallel analysis capabilities that operate on High Performance Computing (HPC) platforms, to explore approaches for reducing data size, and to implement strategies for staging computation across the Slycat™ hierarchy. Within Slycat™, data and visual analysis are organized around projects, which are shared by a project team. Project members are explicitly added, each with a designated set of permissions. Although users sign-in to access Slycat™, individual accounts are not maintained. Instead, authentication is used to determine project access. Within projects, Slycat™ models capture analysis results and enable data exploration through various visual representations. Although for scientists each simulation run is a model of real-world phenomena given certain conditions, we use the term model to refer to our modeling of the ensemble data, not the physics. Different model types often provide complementary perspectives on data features when analyzing the same data set. Each model visualizes data at several levels of abstraction, allowing the user to range from viewing the ensemble holistically to accessing numeric parameter values for a single run. Bookmarks provide a mechanism for sharing results, enabling interesting model states to be labeled and saved.« less
Extracting transient Rayleigh wave and its application in detecting quality of highway roadbed
Liu, J.; Xia, J.; Luo, Y.; Li, X.; Xu, S.; ,
2004-01-01
This paper first explains the tau-p mapping method of extracting Rayleigh waves (LR waves) from field shot gathers. It also explains a mathematical model of physical character parameters of quality of high-grade roads. This paper then discusses an algorithm of computing dispersion curves using adjacent channels. Shear velocity and physical character parameters are obtained by inversion of dispersion curves. The algorithm using adjacent channels to calculating dispersion curves eliminates average effects that exist by using multi-channels to obtain dispersion curves so that it improves longitudinal and transverse resolution of LR waves and precision of non-invasive detection, and also broadens its application fields. By analysis of modeling results of detached computation of the ground roll and real examples of detecting density and pressure strength of a high-grade roadbed, and by comparison of shallow seismic image method with borehole cores, we concluded that: 1 the abnormal scale and configuration obtained by LR waves are mostly the same as the result of shallow seismic image method; 2 an average relative error of density obtained from LR waves inversion is 1.6% comparing with borehole coring; 3 transient LR waves in detecting density and pressure strength of a high-grade roadbed is feasible and effective.
Towards a Multi-Mission, Airborne Science Data System Environment
NASA Astrophysics Data System (ADS)
Crichton, D. J.; Hardman, S.; Law, E.; Freeborn, D.; Kay-Im, E.; Lau, G.; Oswald, J.
2011-12-01
NASA earth science instruments are increasingly relying on airborne missions. However, traditionally, there has been limited common infrastructure support available to principal investigators in the area of science data systems. As a result, each investigator has been required to develop their own computing infrastructures for the science data system. Typically there is little software reuse and many projects lack sufficient resources to provide a robust infrastructure to capture, process, distribute and archive the observations acquired from airborne flights. At NASA's Jet Propulsion Laboratory (JPL), we have been developing a multi-mission data system infrastructure for airborne instruments called the Airborne Cloud Computing Environment (ACCE). ACCE encompasses the end-to-end lifecycle covering planning, provisioning of data system capabilities, and support for scientific analysis in order to improve the quality, cost effectiveness, and capabilities to enable new scientific discovery and research in earth observation. This includes improving data system interoperability across each instrument. A principal characteristic is being able to provide an agile infrastructure that is architected to allow for a variety of configurations of the infrastructure from locally installed compute and storage services to provisioning those services via the "cloud" from cloud computer vendors such as Amazon.com. Investigators often have different needs that require a flexible configuration. The data system infrastructure is built on the Apache's Object Oriented Data Technology (OODT) suite of components which has been used for a number of spaceborne missions and provides a rich set of open source software components and services for constructing science processing and data management systems. In 2010, a partnership was formed between the ACCE team and the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) mission to support the data processing and data management needs. A principal goal is to provide support for the Fourier Transform Spectrometer (FTS) instrument which will produce over 700,000 soundings over the life of their three-year mission. The cost to purchase and operate a cluster-based system in order to generate Level 2 Full Physics products from this data was prohibitive. Through an evaluation of cloud computing solutions, Amazon's Elastic Compute Cloud (EC2) was selected for the CARVE deployment. As the ACCE infrastructure is developed and extended to form an infrastructure for airborne missions, the experience of working with CARVE has provided a number of lessons learned and has proven to be important in reinforcing the unique aspects of airborne missions and the importance of the ACCE infrastructure in developing a cost effective, flexible multi-mission capability that leverages emerging capabilities in cloud computing, workflow management, and distributed computing.
NASA Astrophysics Data System (ADS)
Shou, Yinsi; Combi, Michael R.; Toth, Gabor; Huang, Zhenguang; Jia, Xianzhe; Fougere, Nicolas; Tenishev, Valeriy; Gombosi, T. I.; Hansen, Kenneth C.; Bieler, Andre
2016-10-01
Physics-based numerical coma models are desirable whether to interpret the spacecraft observations of the inner coma or to compare with the ground-based observations of the outer coma. In this work, we develop a multi-neutral-fluid model based on BATS-R-US in the University of Michigan's SWMF (Space Weather Modeling Framework), which is capable of computing both the inner and the outer coma and simulating time-variable phenomena. It treats H2O, OH, H2, O, and H as separate fluids and each fluid has its own velocity and temperature, with collisions coupling all fluids together. The self-consistent collisional interactions decrease the velocity differences, re-distribute the excess energy deposited by chemical reactions among all species, and account for the varying heating efficiency under various physical conditions. Recognizing that the fluid approach has limitations in capturing all of the correct physics for certain applications, especially for very low density environment, we applied our multi-fluid coma model to comet 67P/Churyumov-Gerasimenko (CG) at various heliocentric distances and demonstrated that it is able to yield comparable results as the Direct Simulation Monte Carlo (DSMC) model, which is based on a kinetic approach that is valid under these conditions. Therefore, our model may be a powerful alternative to the particle-based model, especially for some computationally intensive simulations. In addition, by running the model with several combinations of production rates and heliocentric distances, we can characterize the cometary H2O expansion speeds and demonstrate the nonlinear effect of production rates or photochemical heating. Our results are also compared to previous modeling work (e.g., Bockelee-Morvan & Crovisier 1987) and remote observations (e.g., Tseng et al. 2007), which serve as further validation of our model. This work has been partially supported by grant NNX14AG84G from the NASA Planetary Atmospheres Program, and US Rosetta contracts JPL #1266313, JPL #1266314 and JPL #1286489.
Simulating and mapping spatial complexity using multi-scale techniques
De Cola, L.
1994-01-01
A central problem in spatial analysis is the mapping of data for complex spatial fields using relatively simple data structures, such as those of a conventional GIS. This complexity can be measured using such indices as multi-scale variance, which reflects spatial autocorrelation, and multi-fractal dimension, which characterizes the values of fields. These indices are computed for three spatial processes: Gaussian noise, a simple mathematical function, and data for a random walk. Fractal analysis is then used to produce a vegetation map of the central region of California based on a satellite image. This analysis suggests that real world data lie on a continuum between the simple and the random, and that a major GIS challenge is the scientific representation and understanding of rapidly changing multi-scale fields. -Author
Multi-core processing and scheduling performance in CMS
NASA Astrophysics Data System (ADS)
Hernández, J. M.; Evans, D.; Foulkes, S.
2012-12-01
Commodity hardware is going many-core. We might soon not be able to satisfy the job memory needs per core in the current single-core processing model in High Energy Physics. In addition, an ever increasing number of independent and incoherent jobs running on the same physical hardware not sharing resources might significantly affect processing performance. It will be essential to effectively utilize the multi-core architecture. CMS has incorporated support for multi-core processing in the event processing framework and the workload management system. Multi-core processing jobs share common data in memory, such us the code libraries, detector geometry and conditions data, resulting in a much lower memory usage than standard single-core independent jobs. Exploiting this new processing model requires a new model in computing resource allocation, departing from the standard single-core allocation for a job. The experiment job management system needs to have control over a larger quantum of resource since multi-core aware jobs require the scheduling of multiples cores simultaneously. CMS is exploring the approach of using whole nodes as unit in the workload management system where all cores of a node are allocated to a multi-core job. Whole-node scheduling allows for optimization of the data/workflow management (e.g. I/O caching, local merging) but efficient utilization of all scheduled cores is challenging. Dedicated whole-node queues have been setup at all Tier-1 centers for exploring multi-core processing workflows in CMS. We present the evaluation of the performance scheduling and executing multi-core workflows in whole-node queues compared to the standard single-core processing workflows.
A Multi-Level Parallelization Concept for High-Fidelity Multi-Block Solvers
NASA Technical Reports Server (NTRS)
Hatay, Ferhat F.; Jespersen, Dennis C.; Guruswamy, Guru P.; Rizk, Yehia M.; Byun, Chansup; Gee, Ken; VanDalsem, William R. (Technical Monitor)
1997-01-01
The integration of high-fidelity Computational Fluid Dynamics (CFD) analysis tools with the industrial design process benefits greatly from the robust implementations that are transportable across a wide range of computer architectures. In the present work, a hybrid domain-decomposition and parallelization concept was developed and implemented into the widely-used NASA multi-block Computational Fluid Dynamics (CFD) packages implemented in ENSAERO and OVERFLOW. The new parallel solver concept, PENS (Parallel Euler Navier-Stokes Solver), employs both fine and coarse granularity in data partitioning as well as data coalescing to obtain the desired load-balance characteristics on the available computer platforms. This multi-level parallelism implementation itself introduces no changes to the numerical results, hence the original fidelity of the packages are identically preserved. The present implementation uses the Message Passing Interface (MPI) library for interprocessor message passing and memory accessing. By choosing an appropriate combination of the available partitioning and coalescing capabilities only during the execution stage, the PENS solver becomes adaptable to different computer architectures from shared-memory to distributed-memory platforms with varying degrees of parallelism. The PENS implementation on the IBM SP2 distributed memory environment at the NASA Ames Research Center obtains 85 percent scalable parallel performance using fine-grain partitioning of single-block CFD domains using up to 128 wide computational nodes. Multi-block CFD simulations of complete aircraft simulations achieve 75 percent perfect load-balanced executions using data coalescing and the two levels of parallelism. SGI PowerChallenge, SGI Origin 2000, and a cluster of workstations are the other platforms where the robustness of the implementation is tested. The performance behavior on the other computer platforms with a variety of realistic problems will be included as this on-going study progresses.
Teodoro, George; Kurc, Tahsin; Andrade, Guilherme; Kong, Jun; Ferreira, Renato; Saltz, Joel
2015-01-01
We carry out a comparative performance study of multi-core CPUs, GPUs and Intel Xeon Phi (Many Integrated Core-MIC) with a microscopy image analysis application. We experimentally evaluate the performance of computing devices on core operations of the application. We correlate the observed performance with the characteristics of computing devices and data access patterns, computation complexities, and parallelization forms of the operations. The results show a significant variability in the performance of operations with respect to the device used. The performances of operations with regular data access are comparable or sometimes better on a MIC than that on a GPU. GPUs are more efficient than MICs for operations that access data irregularly, because of the lower bandwidth of the MIC for random data accesses. We propose new performance-aware scheduling strategies that consider variabilities in operation speedups. Our scheduling strategies significantly improve application performance compared to classic strategies in hybrid configurations. PMID:28239253
NASA Technical Reports Server (NTRS)
Hoff, Claus; Cady, Eric; Chainyk, Mike; Kissil, Andrew; Levine, Marie; Moore, Greg
2011-01-01
The efficient simulation of multidisciplinary thermo-opto-mechanical effects in precision deployable systems has for years been limited by numerical toolsets that do not necessarily share the same finite element basis, level of mesh discretization, data formats, or compute platforms. Cielo, a general purpose integrated modeling tool funded by the Jet Propulsion Laboratory and the Exoplanet Exploration Program, addresses shortcomings in the current state of the art via features that enable the use of a single, common model for thermal, structural and optical aberration analysis, producing results of greater accuracy, without the need for results interpolation or mapping. This paper will highlight some of these advances, and will demonstrate them within the context of detailed external occulter analyses, focusing on in-plane deformations of the petal edges for both steady-state and transient conditions, with subsequent optical performance metrics including intensity distributions at the pupil and image plane.
Goscinski, Wojtek J.; McIntosh, Paul; Felzmann, Ulrich; Maksimenko, Anton; Hall, Christopher J.; Gureyev, Timur; Thompson, Darren; Janke, Andrew; Galloway, Graham; Killeen, Neil E. B.; Raniga, Parnesh; Kaluza, Owen; Ng, Amanda; Poudel, Govinda; Barnes, David G.; Nguyen, Toan; Bonnington, Paul; Egan, Gary F.
2014-01-01
The Multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) is a national imaging and visualization facility established by Monash University, the Australian Synchrotron, the Commonwealth Scientific Industrial Research Organization (CSIRO), and the Victorian Partnership for Advanced Computing (VPAC), with funding from the National Computational Infrastructure and the Victorian Government. The MASSIVE facility provides hardware, software, and expertise to drive research in the biomedical sciences, particularly advanced brain imaging research using synchrotron x-ray and infrared imaging, functional and structural magnetic resonance imaging (MRI), x-ray computer tomography (CT), electron microscopy and optical microscopy. The development of MASSIVE has been based on best practice in system integration methodologies, frameworks, and architectures. The facility has: (i) integrated multiple different neuroimaging analysis software components, (ii) enabled cross-platform and cross-modality integration of neuroinformatics tools, and (iii) brought together neuroimaging databases and analysis workflows. MASSIVE is now operational as a nationally distributed and integrated facility for neuroinfomatics and brain imaging research. PMID:24734019
Development of a Scale Measuring Trait Anxiety in Physical Education
ERIC Educational Resources Information Center
Barkoukis, Vassilis; Rodafinos, Angelos; Koidou, Eirini; Tsorbatzoudis, Haralambos
2012-01-01
The aim of the present study was to examine the validity and reliability of a multi-dimensional measure of trait anxiety specifically designed for the physical education lesson. The Physical Education Trait Anxiety Scale was initially completed by 774 high school students during regular school classes. A confirmatory factor analysis supported the…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yu, Y. Q.; Shemon, E. R.; Thomas, J. W.
SHARP is an advanced modeling and simulation toolkit for the analysis of nuclear reactors. It is comprised of several components including physical modeling tools, tools to integrate the physics codes for multi-physics analyses, and a set of tools to couple the codes within the MOAB framework. Physics modules currently include the neutronics code PROTEUS, the thermal-hydraulics code Nek5000, and the structural mechanics code Diablo. This manual focuses on performing multi-physics calculations with the SHARP ToolKit. Manuals for the three individual physics modules are available with the SHARP distribution to help the user to either carry out the primary multi-physics calculationmore » with basic knowledge or perform further advanced development with in-depth knowledge of these codes. This manual provides step-by-step instructions on employing SHARP, including how to download and install the code, how to build the drivers for a test case, how to perform a calculation and how to visualize the results. Since SHARP has some specific library and environment dependencies, it is highly recommended that the user read this manual prior to installing SHARP. Verification tests cases are included to check proper installation of each module. It is suggested that the new user should first follow the step-by-step instructions provided for a test problem in this manual to understand the basic procedure of using SHARP before using SHARP for his/her own analysis. Both reference output and scripts are provided along with the test cases in order to verify correct installation and execution of the SHARP package. At the end of this manual, detailed instructions are provided on how to create a new test case so that user can perform novel multi-physics calculations with SHARP. Frequently asked questions are listed at the end of this manual to help the user to troubleshoot issues.« less
Novel Fast Pyrolysis/Catalytic Technology for the Production of Stable Upgraded Liquids
DOE Office of Scientific and Technical Information (OSTI.GOV)
Oyama, Ted; Agblevor, Foster; Battaglia, Francine
The objective of the proposed research is the demonstration and development of a novel biomass pyrolysis technology for the production of a stable bio-oil. The approach is to carry out catalytic hydrodeoxygenation (HDO) and upgrading together with pyrolysis in a single fluidized bed reactor with a unique two-level design that permits the physical separation of the two processes. The hydrogen required for the HDO will be generated in the catalytic section by the water-gas shift reaction employing recycled CO produced from the pyrolysis reaction itself. Thus, the use of a reactive recycle stream is another innovation in this technology. Themore » catalysts will be designed in collaboration with BASF Catalysts LLC (formerly Engelhard Corporation), a leader in the manufacture of attrition-resistant cracking catalysts. The proposed work will include reactor modeling with state-of-the-art computational fluid dynamics in a supercomputer, and advanced kinetic analysis for optimization of bio-oil production. The stability of the bio-oil will be determined by viscosity, oxygen content, and acidity determinations in real and accelerated measurements. A multi-faceted team has been assembled to handle laboratory demonstration studies and computational analysis for optimization and scaleup.« less
Multi-Parameter Linear Least-Squares Fitting to Poisson Data One Count at a Time
NASA Technical Reports Server (NTRS)
Wheaton, W.; Dunklee, A.; Jacobson, A.; Ling, J.; Mahoney, W.; Radocinski, R.
1993-01-01
A standard problem in gamma-ray astronomy data analysis is the decomposition of a set of observed counts, described by Poisson statistics, according to a given multi-component linear model, with underlying physical count rates or fluxes which are to be estimated from the data.
Principal polynomial analysis.
Laparra, Valero; Jiménez, Sandra; Tuia, Devis; Camps-Valls, Gustau; Malo, Jesus
2014-11-01
This paper presents a new framework for manifold learning based on a sequence of principal polynomials that capture the possibly nonlinear nature of the data. The proposed Principal Polynomial Analysis (PPA) generalizes PCA by modeling the directions of maximal variance by means of curves, instead of straight lines. Contrarily to previous approaches, PPA reduces to performing simple univariate regressions, which makes it computationally feasible and robust. Moreover, PPA shows a number of interesting analytical properties. First, PPA is a volume-preserving map, which in turn guarantees the existence of the inverse. Second, such an inverse can be obtained in closed form. Invertibility is an important advantage over other learning methods, because it permits to understand the identified features in the input domain where the data has physical meaning. Moreover, it allows to evaluate the performance of dimensionality reduction in sensible (input-domain) units. Volume preservation also allows an easy computation of information theoretic quantities, such as the reduction in multi-information after the transform. Third, the analytical nature of PPA leads to a clear geometrical interpretation of the manifold: it allows the computation of Frenet-Serret frames (local features) and of generalized curvatures at any point of the space. And fourth, the analytical Jacobian allows the computation of the metric induced by the data, thus generalizing the Mahalanobis distance. These properties are demonstrated theoretically and illustrated experimentally. The performance of PPA is evaluated in dimensionality and redundancy reduction, in both synthetic and real datasets from the UCI repository.
Limits to the Extraction of Information from Multi-Hop Skywave Radar Signals
2005-04-14
equations to compute the eikonal rays gh a model ionosphere, plotting the resulting tories in the range-height plane. oes received via these multi...kilometres. This extensive database is ideally suited to the sta- tistical analysis of the directional, diurnal, seasonal 0 0 500 1000 1500 2000 2500
Parallel satellite orbital situational problems solver for space missions design and control
NASA Astrophysics Data System (ADS)
Atanassov, Atanas Marinov
2016-11-01
Solving different scientific problems for space applications demands implementation of observations, measurements or realization of active experiments during time intervals in which specific geometric and physical conditions are fulfilled. The solving of situational problems for determination of these time intervals when the satellite instruments work optimally is a very important part of all activities on every stage of preparation and realization of space missions. The elaboration of universal, flexible and robust approach for situation analysis, which is easily portable toward new satellite missions, is significant for reduction of missions' preparation times and costs. Every situation problem could be based on one or more situation conditions. Simultaneously solving different kinds of situation problems based on different number and types of situational conditions, each one of them satisfied on different segments of satellite orbit requires irregular calculations. Three formal approaches are presented. First one is related to situation problems description that allows achieving flexibility in situation problem assembling and presentation in computer memory. The second formal approach is connected with developing of situation problem solver organized as processor that executes specific code for every particular situational condition. The third formal approach is related to solver parallelization utilizing threads and dynamic scheduling based on "pool of threads" abstraction and ensures a good load balance. The developed situation problems solver is intended for incorporation in the frames of multi-physics multi-satellite space mission's design and simulation tools.
A web portal for hydrodynamical, cosmological simulations
NASA Astrophysics Data System (ADS)
Ragagnin, A.; Dolag, K.; Biffi, V.; Cadolle Bel, M.; Hammer, N. J.; Krukau, A.; Petkova, M.; Steinborn, D.
2017-07-01
This article describes a data centre hosting a web portal for accessing and sharing the output of large, cosmological, hydro-dynamical simulations with a broad scientific community. It also allows users to receive related scientific data products by directly processing the raw simulation data on a remote computing cluster. The data centre has a multi-layer structure: a web portal, a job control layer, a computing cluster and a HPC storage system. The outer layer enables users to choose an object from the simulations. Objects can be selected by visually inspecting 2D maps of the simulation data, by performing highly compounded and elaborated queries or graphically by plotting arbitrary combinations of properties. The user can run analysis tools on a chosen object. These services allow users to run analysis tools on the raw simulation data. The job control layer is responsible for handling and performing the analysis jobs, which are executed on a computing cluster. The innermost layer is formed by a HPC storage system which hosts the large, raw simulation data. The following services are available for the users: (I) CLUSTERINSPECT visualizes properties of member galaxies of a selected galaxy cluster; (II) SIMCUT returns the raw data of a sub-volume around a selected object from a simulation, containing all the original, hydro-dynamical quantities; (III) SMAC creates idealized 2D maps of various, physical quantities and observables of a selected object; (IV) PHOX generates virtual X-ray observations with specifications of various current and upcoming instruments.
Zhao, Jin; Li, Yan; Yang, Zhi-Wei; Wang, Wei; Meng, Yan
2011-10-01
We present a case of a patient with rare anatomy of a maxillary second molar with three mesiobuccal root canals and a maxillary third molar with four separate roots, identified using multi-slice computed topography (CT) and three-dimensional reconstruction techniques. The described case enriched/might enrich our knowledge about possible anatomical aberrations of maxillary molars. In addition, we demonstrate the role of multi-slice CT as an objective tool for confirmatory diagnosis and successful endodontic management.
Multi-GPU Jacobian accelerated computing for soft-field tomography.
Borsic, A; Attardo, E A; Halter, R J
2012-10-01
Image reconstruction in soft-field tomography is based on an inverse problem formulation, where a forward model is fitted to the data. In medical applications, where the anatomy presents complex shapes, it is common to use finite element models (FEMs) to represent the volume of interest and solve a partial differential equation that models the physics of the system. Over the last decade, there has been a shifting interest from 2D modeling to 3D modeling, as the underlying physics of most problems are 3D. Although the increased computational power of modern computers allows working with much larger FEM models, the computational time required to reconstruct 3D images on a fine 3D FEM model can be significant, on the order of hours. For example, in electrical impedance tomography (EIT) applications using a dense 3D FEM mesh with half a million elements, a single reconstruction iteration takes approximately 15-20 min with optimized routines running on a modern multi-core PC. It is desirable to accelerate image reconstruction to enable researchers to more easily and rapidly explore data and reconstruction parameters. Furthermore, providing high-speed reconstructions is essential for some promising clinical application of EIT. For 3D problems, 70% of the computing time is spent building the Jacobian matrix, and 25% of the time in forward solving. In this work, we focus on accelerating the Jacobian computation by using single and multiple GPUs. First, we discuss an optimized implementation on a modern multi-core PC architecture and show how computing time is bounded by the CPU-to-memory bandwidth; this factor limits the rate at which data can be fetched by the CPU. Gains associated with the use of multiple CPU cores are minimal, since data operands cannot be fetched fast enough to saturate the processing power of even a single CPU core. GPUs have much faster memory bandwidths compared to CPUs and better parallelism. We are able to obtain acceleration factors of 20 times on a single NVIDIA S1070 GPU, and of 50 times on four GPUs, bringing the Jacobian computing time for a fine 3D mesh from 12 min to 14 s. We regard this as an important step toward gaining interactive reconstruction times in 3D imaging, particularly when coupled in the future with acceleration of the forward problem. While we demonstrate results for EIT, these results apply to any soft-field imaging modality where the Jacobian matrix is computed with the adjoint method.
Multi-GPU Jacobian Accelerated Computing for Soft Field Tomography
Borsic, A.; Attardo, E. A.; Halter, R. J.
2012-01-01
Image reconstruction in soft-field tomography is based on an inverse problem formulation, where a forward model is fitted to the data. In medical applications, where the anatomy presents complex shapes, it is common to use Finite Element Models to represent the volume of interest and to solve a partial differential equation that models the physics of the system. Over the last decade, there has been a shifting interest from 2D modeling to 3D modeling, as the underlying physics of most problems are three-dimensional. Though the increased computational power of modern computers allows working with much larger FEM models, the computational time required to reconstruct 3D images on a fine 3D FEM model can be significant, on the order of hours. For example, in Electrical Impedance Tomography applications using a dense 3D FEM mesh with half a million elements, a single reconstruction iteration takes approximately 15 to 20 minutes with optimized routines running on a modern multi-core PC. It is desirable to accelerate image reconstruction to enable researchers to more easily and rapidly explore data and reconstruction parameters. Further, providing high-speed reconstructions are essential for some promising clinical application of EIT. For 3D problems 70% of the computing time is spent building the Jacobian matrix, and 25% of the time in forward solving. In the present work, we focus on accelerating the Jacobian computation by using single and multiple GPUs. First, we discuss an optimized implementation on a modern multi-core PC architecture and show how computing time is bounded by the CPU-to-memory bandwidth; this factor limits the rate at which data can be fetched by the CPU. Gains associated with use of multiple CPU cores are minimal, since data operands cannot be fetched fast enough to saturate the processing power of even a single CPU core. GPUs have a much faster memory bandwidths compared to CPUs and better parallelism. We are able to obtain acceleration factors of 20 times on a single NVIDIA S1070 GPU, and of 50 times on 4 GPUs, bringing the Jacobian computing time for a fine 3D mesh from 12 minutes to 14 seconds. We regard this as an important step towards gaining interactive reconstruction times in 3D imaging, particularly when coupled in the future with acceleration of the forward problem. While we demonstrate results for Electrical Impedance Tomography, these results apply to any soft-field imaging modality where the Jacobian matrix is computed with the Adjoint Method. PMID:23010857
Thermal stress analysis of reusable surface insulation for shuttle
NASA Technical Reports Server (NTRS)
Ojalvo, I. U.; Levy, A.; Austin, F.
1974-01-01
An iterative procedure for accurately determining tile stresses associated with static mechanical and thermally induced internal loads is presented. The necessary conditions for convergence of the method are derived. An user-oriented computer program based upon the present method of analysis was developed. The program is capable of analyzing multi-tiled panels and determining the associated stresses. Typical numerical results from this computer program are presented.
Visualization of multi-INT fusion data using Java Viewer (JVIEW)
NASA Astrophysics Data System (ADS)
Blasch, Erik; Aved, Alex; Nagy, James; Scott, Stephen
2014-05-01
Visualization is important for multi-intelligence fusion and we demonstrate issues for presenting physics-derived (i.e., hard) and human-derived (i.e., soft) fusion results. Physics-derived solutions (e.g., imagery) typically involve sensor measurements that are objective, while human-derived (e.g., text) typically involve language processing. Both results can be geographically displayed for user-machine fusion. Attributes of an effective and efficient display are not well understood, so we demonstrate issues and results for filtering, correlation, and association of data for users - be they operators or analysts. Operators require near-real time solutions while analysts have the opportunities of non-real time solutions for forensic analysis. In a use case, we demonstrate examples using the JVIEW concept that has been applied to piloting, space situation awareness, and cyber analysis. Using the open-source JVIEW software, we showcase a big data solution for multi-intelligence fusion application for context-enhanced information fusion.
Kel, AlexanderE
2017-02-01
Computational analysis of master regulators through the search for transcription factor binding sites followed by analysis of signal transduction networks of a cell is a new approach of causal analysis of multi-omics data. This paper contains results on analysis of multi-omics data that include transcriptomics, proteomics and epigenomics data of methotrexate (MTX) resistant colon cancer cell line. The data were used for analysis of mechanisms of resistance and for prediction of potential drug targets and promising compounds for reverting the MTX resistance of these cancer cells. We present all results of the analysis including the lists of identified transcription factors and their binding sites in genome and the list of predicted master regulators - potential drug targets. This data was generated in the study recently published in the article "Multi-omics "Upstream Analysis" of regulatory genomic regions helps identifying targets against methotrexate resistance of colon cancer" (Kel et al., 2016) [4]. These data are of interest for researchers from the field of multi-omics data analysis and for biologists who are interested in identification of novel drug targets against NTX resistance.
Research in applied mathematics, numerical analysis, and computer science
NASA Technical Reports Server (NTRS)
1984-01-01
Research conducted at the Institute for Computer Applications in Science and Engineering (ICASE) in applied mathematics, numerical analysis, and computer science is summarized and abstracts of published reports are presented. The major categories of the ICASE research program are: (1) numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; (2) control and parameter identification; (3) computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and (4) computer systems and software, especially vector and parallel computers.
NASA Astrophysics Data System (ADS)
Vieira, Rodrigo Drumond; Kelly, Gregory J.
2014-11-01
In this paper, we present and apply a multi-level method for discourse analysis in science classrooms. This method is based on the structure of human activity (activity, actions, and operations) and it was applied to study a pre-service physics teacher methods course. We argue that such an approach, based on a cultural psychological perspective, affords opportunities for analysts to perform a theoretically based detailed analysis of discourse events. Along with the presentation of analysis, we show and discuss how the articulation of different levels offers interpretative criteria for analyzing instructional conversations. We synthesize the results into a model for a teacher's practice and discuss the implications and possibilities of this approach for the field of discourse analysis in science classrooms. Finally, we reflect on how the development of teachers' understanding of their activity structures can contribute to forms of progressive discourse of science education.
Modelling of the Thermo-Physical and Physical Properties for Solidification of Al-Alloys
NASA Astrophysics Data System (ADS)
Saunders, N.; Li, X.; Miodownik, A. P.; Schillé, J.-P.
The thermo-physical and physical properties of the liquid and solid phases are critical components in casting simulations. Such properties include the fraction solid transformed, enthalpy release, thermal conductivity, volume and density, all as a function of temperature. Due to the difficulty in experimentally determining such properties at solidification temperatures, little information exists for multi-component alloys. As part of the development of a new computer program for modelling of materials properties (JMatPro) extensive work has been carried out on the development of sound, physically based models for these properties. Wide ranging results will presented for Al-based alloys, which will include more detailed information concerning the density change of the liquid that intrinsically occurs during solidification due to its change in composition.
NASA Astrophysics Data System (ADS)
Hou, Zhenlong; Huang, Danian
2017-09-01
In this paper, we make a study on the inversion of probability tomography (IPT) with gravity gradiometry data at first. The space resolution of the results is improved by multi-tensor joint inversion, depth weighting matrix and the other methods. Aiming at solving the problems brought by the big data in the exploration, we present the parallel algorithm and the performance analysis combining Compute Unified Device Architecture (CUDA) with Open Multi-Processing (OpenMP) based on Graphics Processing Unit (GPU) accelerating. In the test of the synthetic model and real data from Vinton Dome, we get the improved results. It is also proved that the improved inversion algorithm is effective and feasible. The performance of parallel algorithm we designed is better than the other ones with CUDA. The maximum speedup could be more than 200. In the performance analysis, multi-GPU speedup and multi-GPU efficiency are applied to analyze the scalability of the multi-GPU programs. The designed parallel algorithm is demonstrated to be able to process larger scale of data and the new analysis method is practical.
Multi-disciplinary coupling for integrated design of propulsion systems
NASA Technical Reports Server (NTRS)
Chamis, C. C.; Singhal, S. N.
1993-01-01
Effective computational simulation procedures are described for modeling the inherent multi-disciplinary interactions for determining the true response of propulsion systems. Results are presented for propulsion system responses including multi-discipline coupling effects via (1) coupled multi-discipline tailoring, (2) an integrated system of multidisciplinary simulators, (3) coupled material-behavior/fabrication-process tailoring, (4) sensitivities using a probabilistic simulator, and (5) coupled materials/structures/fracture/probabilistic behavior simulator. The results show that the best designs can be determined if the analysis/tailoring methods account for the multi-disciplinary coupling effects. The coupling across disciplines can be used to develop an integrated interactive multi-discipline numerical propulsion system simulator.
Rey-Villamizar, Nicolas; Somasundar, Vinay; Megjhani, Murad; Xu, Yan; Lu, Yanbin; Padmanabhan, Raghav; Trett, Kristen; Shain, William; Roysam, Badri
2014-01-01
In this article, we describe the use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes, including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis tasks, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral images of brain tissue surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels. Each channel consists of 6000 × 10,000 × 500 voxels with 16 bits/voxel, implying image sizes exceeding 250 GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analysis for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN) capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment. Our Python script enables efficient data storage and movement between computers and storage servers, logs all the processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.
NUMERICAL METHODS FOR SOLVING THE MULTI-TERM TIME-FRACTIONAL WAVE-DIFFUSION EQUATION.
Liu, F; Meerschaert, M M; McGough, R J; Zhuang, P; Liu, Q
2013-03-01
In this paper, the multi-term time-fractional wave-diffusion equations are considered. The multi-term time fractional derivatives are defined in the Caputo sense, whose orders belong to the intervals [0,1], [1,2), [0,2), [0,3), [2,3) and [2,4), respectively. Some computationally effective numerical methods are proposed for simulating the multi-term time-fractional wave-diffusion equations. The numerical results demonstrate the effectiveness of theoretical analysis. These methods and techniques can also be extended to other kinds of the multi-term fractional time-space models with fractional Laplacian.
NUMERICAL METHODS FOR SOLVING THE MULTI-TERM TIME-FRACTIONAL WAVE-DIFFUSION EQUATION
Liu, F.; Meerschaert, M.M.; McGough, R.J.; Zhuang, P.; Liu, Q.
2013-01-01
In this paper, the multi-term time-fractional wave-diffusion equations are considered. The multi-term time fractional derivatives are defined in the Caputo sense, whose orders belong to the intervals [0,1], [1,2), [0,2), [0,3), [2,3) and [2,4), respectively. Some computationally effective numerical methods are proposed for simulating the multi-term time-fractional wave-diffusion equations. The numerical results demonstrate the effectiveness of theoretical analysis. These methods and techniques can also be extended to other kinds of the multi-term fractional time-space models with fractional Laplacian. PMID:23772179
NASA Technical Reports Server (NTRS)
Chang, Chau-Lyan; Venkatachari, Balaji Shankar; Cheng, Gary
2013-01-01
With the wide availability of affordable multiple-core parallel supercomputers, next generation numerical simulations of flow physics are being focused on unsteady computations for problems involving multiple time scales and multiple physics. These simulations require higher solution accuracy than most algorithms and computational fluid dynamics codes currently available. This paper focuses on the developmental effort for high-fidelity multi-dimensional, unstructured-mesh flow solvers using the space-time conservation element, solution element (CESE) framework. Two approaches have been investigated in this research in order to provide high-accuracy, cross-cutting numerical simulations for a variety of flow regimes: 1) time-accurate local time stepping and 2) highorder CESE method. The first approach utilizes consistent numerical formulations in the space-time flux integration to preserve temporal conservation across the cells with different marching time steps. Such approach relieves the stringent time step constraint associated with the smallest time step in the computational domain while preserving temporal accuracy for all the cells. For flows involving multiple scales, both numerical accuracy and efficiency can be significantly enhanced. The second approach extends the current CESE solver to higher-order accuracy. Unlike other existing explicit high-order methods for unstructured meshes, the CESE framework maintains a CFL condition of one for arbitrarily high-order formulations while retaining the same compact stencil as its second-order counterpart. For large-scale unsteady computations, this feature substantially enhances numerical efficiency. Numerical formulations and validations using benchmark problems are discussed in this paper along with realistic examples.
2nd Generation QUATARA Flight Computer Project
NASA Technical Reports Server (NTRS)
Falker, Jay; Keys, Andrew; Fraticelli, Jose Molina; Capo-Iugo, Pedro; Peeples, Steven
2015-01-01
Single core flight computer boards have been designed, developed, and tested (DD&T) to be flown in small satellites for the last few years. In this project, a prototype flight computer will be designed as a distributed multi-core system containing four microprocessors running code in parallel. This flight computer will be capable of performing multiple computationally intensive tasks such as processing digital and/or analog data, controlling actuator systems, managing cameras, operating robotic manipulators and transmitting/receiving from/to a ground station. In addition, this flight computer will be designed to be fault tolerant by creating both a robust physical hardware connection and by using a software voting scheme to determine the processor's performance. This voting scheme will leverage on the work done for the Space Launch System (SLS) flight software. The prototype flight computer will be constructed with Commercial Off-The-Shelf (COTS) components which are estimated to survive for two years in a low-Earth orbit.
Verification of low-Mach number combustion codes using the method of manufactured solutions
NASA Astrophysics Data System (ADS)
Shunn, Lee; Ham, Frank; Knupp, Patrick; Moin, Parviz
2007-11-01
Many computational combustion models rely on tabulated constitutive relations to close the system of equations. As these reactive state-equations are typically multi-dimensional and highly non-linear, their implications on the convergence and accuracy of simulation codes are not well understood. In this presentation, the effects of tabulated state-relationships on the computational performance of low-Mach number combustion codes are explored using the method of manufactured solutions (MMS). Several MMS examples are developed and applied, progressing from simple one-dimensional configurations to problems involving higher dimensionality and solution-complexity. The manufactured solutions are implemented in two multi-physics hydrodynamics codes: CDP developed at Stanford University and FUEGO developed at Sandia National Laboratories. In addition to verifying the order-of-accuracy of the codes, the MMS problems help highlight certain robustness issues in existing variable-density flow-solvers. Strategies to overcome these issues are briefly discussed.
Dong, Ming-Xin; Zhang, Wei; Hou, Zhi-Bo; Yu, Yi-Chen; Shi, Shuai; Ding, Dong-Sheng; Shi, Bao-Sen
2017-11-15
Multi-photon entangled states not only play a crucial role in research on quantum physics but also have many applications in quantum information fields such as quantum computation, quantum communication, and quantum metrology. To fully exploit the multi-photon entangled states, it is important to establish the interaction between entangled photons and matter, which requires that photons have narrow bandwidth. Here, we report on the experimental generation of a narrowband four-photon Greenberger-Horne-Zeilinger state with a fidelity of 64.9% through multiplexing two spontaneous four-wave mixings in a cold Rb85 atomic ensemble. The full bandwidth of the generated GHZ state is about 19.5 MHz. Thus, the generated photons can effectively match the atoms, which are very suitable for building a quantum computation and quantum communication network based on atomic ensembles.
Summary of research in applied mathematics, numerical analysis, and computer sciences
NASA Technical Reports Server (NTRS)
1986-01-01
The major categories of current ICASE research programs addressed include: numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; control and parameter identification problems, with emphasis on effective numerical methods; computational problems in engineering and physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and computer systems and software, especially vector and parallel computers.
Multi-source Geospatial Data Analysis with Google Earth Engine
NASA Astrophysics Data System (ADS)
Erickson, T.
2014-12-01
The Google Earth Engine platform is a cloud computing environment for data analysis that combines a public data catalog with a large-scale computational facility optimized for parallel processing of geospatial data. The data catalog is a multi-petabyte archive of georeferenced datasets that include images from Earth observing satellite and airborne sensors (examples: USGS Landsat, NASA MODIS, USDA NAIP), weather and climate datasets, and digital elevation models. Earth Engine supports both a just-in-time computation model that enables real-time preview and debugging during algorithm development for open-ended data exploration, and a batch computation mode for applying algorithms over large spatial and temporal extents. The platform automatically handles many traditionally-onerous data management tasks, such as data format conversion, reprojection, and resampling, which facilitates writing algorithms that combine data from multiple sensors and/or models. Although the primary use of Earth Engine, to date, has been the analysis of large Earth observing satellite datasets, the computational platform is generally applicable to a wide variety of use cases that require large-scale geospatial data analyses. This presentation will focus on how Earth Engine facilitates the analysis of geospatial data streams that originate from multiple separate sources (and often communities) and how it enables collaboration during algorithm development and data exploration. The talk will highlight current projects/analyses that are enabled by this functionality.https://earthengine.google.org
Audigier, Chloé; Mansi, Tommaso; Delingette, Hervé; Rapaka, Saikiran; Passerini, Tiziano; Mihalef, Viorel; Jolly, Marie-Pierre; Pop, Raoul; Diana, Michele; Soler, Luc; Kamen, Ali; Comaniciu, Dorin; Ayache, Nicholas
2017-09-01
We aim at developing a framework for the validation of a subject-specific multi-physics model of liver tumor radiofrequency ablation (RFA). The RFA computation becomes subject specific after several levels of personalization: geometrical and biophysical (hemodynamics, heat transfer and an extended cellular necrosis model). We present a comprehensive experimental setup combining multimodal, pre- and postoperative anatomical and functional images, as well as the interventional monitoring of intra-operative signals: the temperature and delivered power. To exploit this dataset, an efficient processing pipeline is introduced, which copes with image noise, variable resolution and anisotropy. The validation study includes twelve ablations from five healthy pig livers: a mean point-to-mesh error between predicted and actual ablation extent of 5.3 ± 3.6 mm is achieved. This enables an end-to-end preclinical validation framework that considers the available dataset.
NASA Technical Reports Server (NTRS)
Davis, Brynmor; Kim, Edward; Piepmeier, Jeffrey; Hildebrand, Peter H. (Technical Monitor)
2001-01-01
Many new Earth remote-sensing instruments are embracing both the advantages and added complexity that result from interferometric or fully polarimetric operation. To increase instrument understanding and functionality a model of the signals these instruments measure is presented. A stochastic model is used as it recognizes the non-deterministic nature of any real-world measurements while also providing a tractable mathematical framework. A stationary, Gaussian-distributed model structure is proposed. Temporal and spectral correlation measures provide a statistical description of the physical properties of coherence and polarization-state. From this relationship the model is mathematically defined. The model is shown to be unique for any set of physical parameters. A method of realizing the model (necessary for applications such as synthetic calibration-signal generation) is given and computer simulation results are presented. The signals are constructed using the output of a multi-input multi-output linear filter system, driven with white noise.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rutland, Christopher J.
2009-04-26
The Terascale High-Fidelity Simulations of Turbulent Combustion (TSTC) project is a multi-university collaborative effort to develop a high-fidelity turbulent reacting flow simulation capability utilizing terascale, massively parallel computer technology. The main paradigm of the approach is direct numerical simulation (DNS) featuring the highest temporal and spatial accuracy, allowing quantitative observations of the fine-scale physics found in turbulent reacting flows as well as providing a useful tool for development of sub-models needed in device-level simulations. Under this component of the TSTC program the simulation code named S3D, developed and shared with coworkers at Sandia National Laboratories, has been enhanced with newmore » numerical algorithms and physical models to provide predictive capabilities for turbulent liquid fuel spray dynamics. Major accomplishments include improved fundamental understanding of mixing and auto-ignition in multi-phase turbulent reactant mixtures and turbulent fuel injection spray jets.« less
"Analysis of the multi-layered cloud radiative effects at the surface using A-train data"
NASA Astrophysics Data System (ADS)
Viudez-Mora, A.; Smith, W. L., Jr.; Kato, S.
2017-12-01
Clouds cover about 74% of the planet and they are an important part of the climate system and strongly influence the surface energy budget. The cloud vertical distribution has important implications in the atmospheric heating and cooling rates. Based on observations by active sensors in the A-train satellite constellation, CALIPSO [Winker et. al, 2010] and CloudSat [Stephens et. al, 2002], more than 1/3 of all clouds are multi-layered. Detection and retrieval of multi-layer cloud physical properties are needed in understanding their effects on the surface radiation budget. This study examines the sensitivity of surface irradiances to cloud properties derived from satellite sensors. Surface irradiances were computed in two different ways, one using cloud properties solely from MODerate resolution Imaging Spectroradiometer (MODIS), and the other using MODIS data supplemented with CALIPSO and CloudSat (hereafter CLCS) cloud vertical structure information [Kato et. al, 2010]. Results reveal that incorporating more precise and realistic cloud properties from CLCS into radiative transfer calculations yields improved estimates of cloud radiative effects (CRE) at the surface (CREsfc). The calculations using only MODIS cloud properties, comparisons of the computed CREsfc for 2-layer (2L) overcast CERES footprints, CLCS reduces the SW CRE by 1.5±26.7 Wm-2, increases the LW CRE by 4.1±12.7 Wm-2, and increases the net CREsfc by 0.9±46.7 Wm-2. In a subsequent analysis, we classified up to 6 different combinations of multi-layered clouds depending on the cloud top height as: High-high (HH), high-middle (HM), high-low (HL), middle-middle (MM), middle-low (ML) and low-low (LL). The 3 most frequent 2L cloud systems were: HL (56.1%), HM (22.3%) and HH (12.1%). For these cases, the computed CREsfc estimated using CLCS data presented the most significant differences when compared using only MODIS data. For example, the differences for the SW and Net CRE in the case HH was 12.3±47.3 Wm-2 and 16.0±48.45 Wm-2, respectively. For the case of HM, the LW CRE difference was -9.9±14.0 Wm-2. Kato, S., et al. (2010), J. Geophys. Res., 115. Stephens, G. L., et al. (2002), Bull. Am. Meteorol. Soc., 83. Winker, D. M., et al., (2010),Bull. Amer. Meteor. Soc., 91.
Parallel and Portable Monte Carlo Particle Transport
NASA Astrophysics Data System (ADS)
Lee, S. R.; Cummings, J. C.; Nolen, S. D.; Keen, N. D.
1997-08-01
We have developed a multi-group, Monte Carlo neutron transport code in C++ using object-oriented methods and the Parallel Object-Oriented Methods and Applications (POOMA) class library. This transport code, called MC++, currently computes k and α eigenvalues of the neutron transport equation on a rectilinear computational mesh. It is portable to and runs in parallel on a wide variety of platforms, including MPPs, clustered SMPs, and individual workstations. It contains appropriate classes and abstractions for particle transport and, through the use of POOMA, for portable parallelism. Current capabilities are discussed, along with physics and performance results for several test problems on a variety of hardware, including all three Accelerated Strategic Computing Initiative (ASCI) platforms. Current parallel performance indicates the ability to compute α-eigenvalues in seconds or minutes rather than days or weeks. Current and future work on the implementation of a general transport physics framework (TPF) is also described. This TPF employs modern C++ programming techniques to provide simplified user interfaces, generic STL-style programming, and compile-time performance optimization. Physics capabilities of the TPF will be extended to include continuous energy treatments, implicit Monte Carlo algorithms, and a variety of convergence acceleration techniques such as importance combing.
Yu, Zhicong; Leng, Shuai; Li, Zhoubo; McCollough, Cynthia H.
2016-01-01
Photon-counting computed tomography (PCCT) is an emerging imaging technique that enables multi-energy imaging with only a single scan acquisition. To enable multi-energy imaging, the detected photons corresponding to the full x-ray spectrum are divided into several subgroups of bin data that correspond to narrower energy windows. Consequently, noise in each energy bin increases compared to the full-spectrum data. This work proposes an iterative reconstruction algorithm for noise suppression in the narrower energy bins used in PCCT imaging. The algorithm is based on the framework of prior image constrained compressed sensing (PICCS) and is called spectral PICCS; it uses the full-spectrum image reconstructed using conventional filtered back-projection as the prior image. The spectral PICCS algorithm is implemented using a constrained optimization scheme with adaptive iterative step sizes such that only two tuning parameters are required in most cases. The algorithm was first evaluated using computer simulations, and then validated by both physical phantoms and in-vivo swine studies using a research PCCT system. Results from both computer-simulation and experimental studies showed substantial image noise reduction in narrow energy bins (43~73%) without sacrificing CT number accuracy or spatial resolution. PMID:27551878
NASA Astrophysics Data System (ADS)
Yu, Zhicong; Leng, Shuai; Li, Zhoubo; McCollough, Cynthia H.
2016-09-01
Photon-counting computed tomography (PCCT) is an emerging imaging technique that enables multi-energy imaging with only a single scan acquisition. To enable multi-energy imaging, the detected photons corresponding to the full x-ray spectrum are divided into several subgroups of bin data that correspond to narrower energy windows. Consequently, noise in each energy bin increases compared to the full-spectrum data. This work proposes an iterative reconstruction algorithm for noise suppression in the narrower energy bins used in PCCT imaging. The algorithm is based on the framework of prior image constrained compressed sensing (PICCS) and is called spectral PICCS; it uses the full-spectrum image reconstructed using conventional filtered back-projection as the prior image. The spectral PICCS algorithm is implemented using a constrained optimization scheme with adaptive iterative step sizes such that only two tuning parameters are required in most cases. The algorithm was first evaluated using computer simulations, and then validated by both physical phantoms and in vivo swine studies using a research PCCT system. Results from both computer-simulation and experimental studies showed substantial image noise reduction in narrow energy bins (43-73%) without sacrificing CT number accuracy or spatial resolution.
A FRAMEWORK FOR FINE-SCALE COMPUTATIONAL FLUID DYNAMICS AIR QUALITY MODELING AND ANALYSIS
This paper discusses a framework for fine-scale CFD modeling that may be developed to complement the present Community Multi-scale Air Quality (CMAQ) modeling system which itself is a computational fluid dynamics model. A goal of this presentation is to stimulate discussions on w...
DigOut: viewing differential expression genes as outliers.
Yu, Hui; Tu, Kang; Xie, Lu; Li, Yuan-Yuan
2010-12-01
With regards to well-replicated two-conditional microarray datasets, the selection of differentially expressed (DE) genes is a well-studied computational topic, but for multi-conditional microarray datasets with limited or no replication, the same task is not properly addressed by previous studies. This paper adopts multivariate outlier analysis to analyze replication-lacking multi-conditional microarray datasets, finding that it performs significantly better than the widely used limit fold change (LFC) model in a simulated comparative experiment. Compared with the LFC model, the multivariate outlier analysis also demonstrates improved stability against sample variations in a series of manipulated real expression datasets. The reanalysis of a real non-replicated multi-conditional expression dataset series leads to satisfactory results. In conclusion, a multivariate outlier analysis algorithm, like DigOut, is particularly useful for selecting DE genes from non-replicated multi-conditional gene expression dataset.
Evaluation of accelerometer based multi-sensor versus single-sensor activity recognition systems.
Gao, Lei; Bourke, A K; Nelson, John
2014-06-01
Physical activity has a positive impact on people's well-being and it had been shown to decrease the occurrence of chronic diseases in the older adult population. To date, a substantial amount of research studies exist, which focus on activity recognition using inertial sensors. Many of these studies adopt a single sensor approach and focus on proposing novel features combined with complex classifiers to improve the overall recognition accuracy. In addition, the implementation of the advanced feature extraction algorithms and the complex classifiers exceed the computing ability of most current wearable sensor platforms. This paper proposes a method to adopt multiple sensors on distributed body locations to overcome this problem. The objective of the proposed system is to achieve higher recognition accuracy with "light-weight" signal processing algorithms, which run on a distributed computing based sensor system comprised of computationally efficient nodes. For analysing and evaluating the multi-sensor system, eight subjects were recruited to perform eight normal scripted activities in different life scenarios, each repeated three times. Thus a total of 192 activities were recorded resulting in 864 separate annotated activity states. The methods for designing such a multi-sensor system required consideration of the following: signal pre-processing algorithms, sampling rate, feature selection and classifier selection. Each has been investigated and the most appropriate approach is selected to achieve a trade-off between recognition accuracy and computing execution time. A comparison of six different systems, which employ single or multiple sensors, is presented. The experimental results illustrate that the proposed multi-sensor system can achieve an overall recognition accuracy of 96.4% by adopting the mean and variance features, using the Decision Tree classifier. The results demonstrate that elaborate classifiers and feature sets are not required to achieve high recognition accuracies on a multi-sensor system. Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.
Baseline process description for simulating plutonium oxide production for precalc project
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pike, J. A.
Savannah River National Laboratory (SRNL) started a multi-year project, the PreCalc Project, to develop a computational simulation of a plutonium oxide (PuO 2) production facility with the objective to study the fundamental relationships between morphological and physicochemical properties. This report provides a detailed baseline process description to be used by SRNL personnel and collaborators to facilitate the initial design and construction of the simulation. The PreCalc Project team selected the HB-Line Plutonium Finishing Facility as the basis for a nominal baseline process since the facility is operational and significant model validation data can be obtained. The process boundary as wellmore » as process and facility design details necessary for multi-scale, multi-physics models are provided.« less
Yang, Tao; Sezer, Hayri; Celik, Ismail B.; ...
2015-06-02
In the present paper, a physics-based procedure combining experiments and multi-physics numerical simulations is developed for overall analysis of SOFCs operational diagnostics and performance predictions. In this procedure, essential information for the fuel cell is extracted first by utilizing empirical polarization analysis in conjunction with experiments and refined by multi-physics numerical simulations via simultaneous analysis and calibration of polarization curve and impedance behavior. The performance at different utilization cases and operating currents is also predicted to confirm the accuracy of the proposed model. It is demonstrated that, with the present electrochemical model, three air/fuel flow conditions are needed to producemore » a set of complete data for better understanding of the processes occurring within SOFCs. After calibration against button cell experiments, the methodology can be used to assess performance of planar cell without further calibration. The proposed methodology would accelerate the calibration process and improve the efficiency of design and diagnostics.« less
The Use of Multi-Criteria Evaluation and Network Analysis in the Area Development Planning Process
2013-03-01
layouts. The alternative layout scoring process, base in multi-criteria evaluation, returns a quantitative score for each alternative layout and a...The purpose of this research was to develop improvements to the area development planning process. These plans are used to improve operations within...an installation sub-section by altering the physical layout of facilities. One methodology was developed based on apply network analysis concepts to
Heterogeneous scalable framework for multiphase flows
DOE Office of Scientific and Technical Information (OSTI.GOV)
Morris, Karla Vanessa
2013-09-01
Two categories of challenges confront the developer of computational spray models: those related to the computation and those related to the physics. Regarding the computation, the trend towards heterogeneous, multi- and many-core platforms will require considerable re-engineering of codes written for the current supercomputing platforms. Regarding the physics, accurate methods for transferring mass, momentum and energy from the dispersed phase onto the carrier fluid grid have so far eluded modelers. Significant challenges also lie at the intersection between these two categories. To be competitive, any physics model must be expressible in a parallel algorithm that performs well on evolving computermore » platforms. This work created an application based on a software architecture where the physics and software concerns are separated in a way that adds flexibility to both. The develop spray-tracking package includes an application programming interface (API) that abstracts away the platform-dependent parallelization concerns, enabling the scientific programmer to write serial code that the API resolves into parallel processes and threads of execution. The project also developed the infrastructure required to provide similar APIs to other application. The API allow object-oriented Fortran applications direct interaction with Trilinos to support memory management of distributed objects in central processing units (CPU) and graphic processing units (GPU) nodes for applications using C++.« less
Performance implications from sizing a VM on multi-core systems: A Data analytic application s view
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lim, Seung-Hwan; Horey, James L; Begoli, Edmon
In this paper, we present a quantitative performance analysis of data analytics applications running on multi-core virtual machines. Such environments form the core of cloud computing. In addition, data analytics applications, such as Cassandra and Hadoop, are becoming increasingly popular on cloud computing platforms. This convergence necessitates a better understanding of the performance and cost implications of such hybrid systems. For example, the very rst step in hosting applications in virtualized environments, requires the user to con gure the number of virtual processors and the size of memory. To understand performance implications of this step, we benchmarked three Yahoo Cloudmore » Serving Benchmark (YCSB) workloads in a virtualized multi-core environment. Our measurements indicate that the performance of Cassandra for YCSB workloads does not heavily depend on the processing capacity of a system, while the size of the data set is critical to performance relative to allocated memory. We also identi ed a strong relationship between the running time of workloads and various hardware events (last level cache loads, misses, and CPU migrations). From this analysis, we provide several suggestions to improve the performance of data analytics applications running on cloud computing environments.« less
NASA Astrophysics Data System (ADS)
Liu, Jiping; Kang, Xiaochen; Dong, Chun; Xu, Shenghua
2017-12-01
Surface area estimation is a widely used tool for resource evaluation in the physical world. When processing large scale spatial data, the input/output (I/O) can easily become the bottleneck in parallelizing the algorithm due to the limited physical memory resources and the very slow disk transfer rate. In this paper, we proposed a stream tilling approach to surface area estimation that first decomposed a spatial data set into tiles with topological expansions. With these tiles, the one-to-one mapping relationship between the input and the computing process was broken. Then, we realized a streaming framework towards the scheduling of the I/O processes and computing units. Herein, each computing unit encapsulated a same copy of the estimation algorithm, and multiple asynchronous computing units could work individually in parallel. Finally, the performed experiment demonstrated that our stream tilling estimation can efficiently alleviate the heavy pressures from the I/O-bound work, and the measured speedup after being optimized have greatly outperformed the directly parallel versions in shared memory systems with multi-core processors.
TCW: Transcriptome Computational Workbench
Soderlund, Carol; Nelson, William; Willer, Mark; Gang, David R.
2013-01-01
Background The analysis of transcriptome data involves many steps and various programs, along with organization of large amounts of data and results. Without a methodical approach for storage, analysis and query, the resulting ad hoc analysis can lead to human error, loss of data and results, inefficient use of time, and lack of verifiability, repeatability, and extensibility. Methodology The Transcriptome Computational Workbench (TCW) provides Java graphical interfaces for methodical analysis for both single and comparative transcriptome data without the use of a reference genome (e.g. for non-model organisms). The singleTCW interface steps the user through importing transcript sequences (e.g. Illumina) or assembling long sequences (e.g. Sanger, 454, transcripts), annotating the sequences, and performing differential expression analysis using published statistical programs in R. The data, metadata, and results are stored in a MySQL database. The multiTCW interface builds a comparison database by importing sequence and annotation from one or more single TCW databases, executes the ESTscan program to translate the sequences into proteins, and then incorporates one or more clusterings, where the clustering options are to execute the orthoMCL program, compute transitive closure, or import clusters. Both singleTCW and multiTCW allow extensive query and display of the results, where singleTCW displays the alignment of annotation hits to transcript sequences, and multiTCW displays multiple transcript alignments with MUSCLE or pairwise alignments. The query programs can be executed on the desktop for fastest analysis, or from the web for sharing the results. Conclusion It is now affordable to buy a multi-processor machine, and easy to install Java and MySQL. By simply downloading the TCW, the user can interactively analyze, query and view their data. The TCW allows in-depth data mining of the results, which can lead to a better understanding of the transcriptome. TCW is freely available from www.agcol.arizona.edu/software/tcw. PMID:23874959
TCW: transcriptome computational workbench.
Soderlund, Carol; Nelson, William; Willer, Mark; Gang, David R
2013-01-01
The analysis of transcriptome data involves many steps and various programs, along with organization of large amounts of data and results. Without a methodical approach for storage, analysis and query, the resulting ad hoc analysis can lead to human error, loss of data and results, inefficient use of time, and lack of verifiability, repeatability, and extensibility. The Transcriptome Computational Workbench (TCW) provides Java graphical interfaces for methodical analysis for both single and comparative transcriptome data without the use of a reference genome (e.g. for non-model organisms). The singleTCW interface steps the user through importing transcript sequences (e.g. Illumina) or assembling long sequences (e.g. Sanger, 454, transcripts), annotating the sequences, and performing differential expression analysis using published statistical programs in R. The data, metadata, and results are stored in a MySQL database. The multiTCW interface builds a comparison database by importing sequence and annotation from one or more single TCW databases, executes the ESTscan program to translate the sequences into proteins, and then incorporates one or more clusterings, where the clustering options are to execute the orthoMCL program, compute transitive closure, or import clusters. Both singleTCW and multiTCW allow extensive query and display of the results, where singleTCW displays the alignment of annotation hits to transcript sequences, and multiTCW displays multiple transcript alignments with MUSCLE or pairwise alignments. The query programs can be executed on the desktop for fastest analysis, or from the web for sharing the results. It is now affordable to buy a multi-processor machine, and easy to install Java and MySQL. By simply downloading the TCW, the user can interactively analyze, query and view their data. The TCW allows in-depth data mining of the results, which can lead to a better understanding of the transcriptome. TCW is freely available from www.agcol.arizona.edu/software/tcw.
Fast multi-core based multimodal registration of 2D cross-sections and 3D datasets.
Scharfe, Michael; Pielot, Rainer; Schreiber, Falk
2010-01-11
Solving bioinformatics tasks often requires extensive computational power. Recent trends in processor architecture combine multiple cores into a single chip to improve overall performance. The Cell Broadband Engine (CBE), a heterogeneous multi-core processor, provides power-efficient and cost-effective high-performance computing. One application area is image analysis and visualisation, in particular registration of 2D cross-sections into 3D image datasets. Such techniques can be used to put different image modalities into spatial correspondence, for example, 2D images of histological cuts into morphological 3D frameworks. We evaluate the CBE-driven PlayStation 3 as a high performance, cost-effective computing platform by adapting a multimodal alignment procedure to several characteristic hardware properties. The optimisations are based on partitioning, vectorisation, branch reducing and loop unrolling techniques with special attention to 32-bit multiplies and limited local storage on the computing units. We show how a typical image analysis and visualisation problem, the multimodal registration of 2D cross-sections and 3D datasets, benefits from the multi-core based implementation of the alignment algorithm. We discuss several CBE-based optimisation methods and compare our results to standard solutions. More information and the source code are available from http://cbe.ipk-gatersleben.de. The results demonstrate that the CBE processor in a PlayStation 3 accelerates computational intensive multimodal registration, which is of great importance in biological/medical image processing. The PlayStation 3 as a low cost CBE-based platform offers an efficient option to conventional hardware to solve computational problems in image processing and bioinformatics.
Bicen, A Ozan; Lehtomaki, Janne J; Akyildiz, Ian F
2018-03-01
Molecular communication (MC) over a microfluidic channel with flow is investigated based on Shannon's channel capacity theorem and Fick's laws of diffusion. Specifically, the sum capacity for MC between a single transmitter and multiple receivers (broadcast MC) is studied. The transmitter communicates by using different types of signaling molecules with each receiver over the microfluidic channel. The transmitted molecules propagate through microfluidic channel until reaching the corresponding receiver. Although the use of different types of molecules provides orthogonal signaling, the sum broadcast capacity may not scale with the number of the receivers due to physics of the propagation (interplay between convection and diffusion based on distance). In this paper, the performance of broadcast MC on a microfluidic chip is characterized by studying the physical geometry of the microfluidic channel and leveraging the information theory. The convergence of the sum capacity for microfluidic broadcast channel is analytically investigated based on the physical system parameters with respect to the increasing number of molecular receivers. The analysis presented here can be useful to predict the achievable information rate in microfluidic interconnects for the biochemical computation and microfluidic multi-sample assays.
Miao, Yinbin; Ma, Jianfeng; Liu, Ximeng; Wei, Fushan; Liu, Zhiquan; Wang, Xu An
2016-11-01
Online personal health record (PHR) is more inclined to shift data storage and search operations to cloud server so as to enjoy the elastic resources and lessen computational burden in cloud storage. As multiple patients' data is always stored in the cloud server simultaneously, it is a challenge to guarantee the confidentiality of PHR data and allow data users to search encrypted data in an efficient and privacy-preserving way. To this end, we design a secure cryptographic primitive called as attribute-based multi-keyword search over encrypted personal health records in multi-owner setting to support both fine-grained access control and multi-keyword search via Ciphertext-Policy Attribute-Based Encryption. Formal security analysis proves our scheme is selectively secure against chosen-keyword attack. As a further contribution, we conduct empirical experiments over real-world dataset to show its feasibility and practicality in a broad range of actual scenarios without incurring additional computational burden.
Computational method for multi-modal microscopy based on transport of intensity equation
NASA Astrophysics Data System (ADS)
Li, Jiaji; Chen, Qian; Sun, Jiasong; Zhang, Jialin; Zuo, Chao
2017-02-01
In this paper, we develop the requisite theory to describe a hybrid virtual-physical multi-modal imaging system which yields quantitative phase, Zernike phase contrast, differential interference contrast (DIC), and light field moment imaging simultaneously based on transport of intensity equation(TIE). We then give the experimental demonstration of these ideas by time-lapse imaging of live HeLa cell mitosis. Experimental results verify that a tunable lens based TIE system, combined with the appropriate post-processing algorithm, can achieve a variety of promising imaging modalities in parallel with the quantitative phase images for the dynamic study of cellular processes.
Assembling Large, Multi-Sensor Climate Datasets Using the SciFlo Grid Workflow System
NASA Astrophysics Data System (ADS)
Wilson, B. D.; Manipon, G.; Xing, Z.; Fetzer, E.
2008-12-01
NASA's Earth Observing System (EOS) is the world's most ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the A-Train platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the cloud scenes from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time matchups between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, and assemble merged datasets for further scientific and statistical analysis. To meet these large-scale challenges, we are utilizing a Grid computing and dataflow framework, named SciFlo, in which we are deploying a set of versatile and reusable operators for data query, access, subsetting, co-registration, mining, fusion, and advanced statistical analysis. SciFlo is a semantically-enabled ("smart") Grid Workflow system that ties together a peer-to-peer network of computers into an efficient engine for distributed computation. The SciFlo workflow engine enables scientists to do multi-instrument Earth Science by assembling remotely-invokable Web Services (SOAP or http GET URLs), native executables, command-line scripts, and Python codes into a distributed computing flow. A scientist visually authors the graph of operation in the VizFlow GUI, or uses a text editor to modify the simple XML workflow documents. The SciFlo client & server engines optimize the execution of such distributed workflows and allow the user to transparently find and use datasets and operators without worrying about the actual location of the Grid resources. The engine transparently moves data to the operators, and moves operators to the data (on the dozen trusted SciFlo nodes). SciFlo also deploys a variety of Data Grid services to: query datasets in space and time, locate & retrieve on-line data granules, provide on-the-fly variable and spatial subsetting, and perform pairwise instrument matchups for A-Train datasets. These services are combined into efficient workflows to assemble the desired large-scale, merged climate datasets. SciFlo is currently being applied in several large climate studies: comparisons of aerosol optical depth between MODIS, MISR, AERONET ground network, and U. Michigan's IMPACT aerosol transport model; characterization of long-term biases in microwave and infrared instruments (AIRS, MLS) by comparisons to GPS temperature retrievals accurate to 0.1 degrees Kelvin; and construction of a decade-long, multi-sensor water vapor climatology stratified by classified cloud scene by bringing together datasets from AIRS/AMSU, AMSR-E, MLS, MODIS, and CloudSat (NASA MEASUREs grant, Fetzer PI). The presentation will discuss the SciFlo technologies, their application in these distributed workflows, and the many challenges encountered in assembling and analyzing these massive datasets.
Multi-community command and control systems in law enforcement: An introductory planning guide
NASA Technical Reports Server (NTRS)
Sohn, R. L.; Garcia, E. A.; Kennedy, R. D.
1976-01-01
A set of planning guidelines for multi-community command and control systems in law enforcement is presented. Essential characteristics and applications of these systems are outlined. Requirements analysis, system concept design, implementation planning, and performance and cost modeling are described and demonstrated with numerous examples. Program management techniques and joint powers agreements for multicommunity programs are discussed in detail. A description of a typical multi-community computer-aided dispatch system is appended.
Computational mechanics and physics at NASA Langley Research Center
NASA Technical Reports Server (NTRS)
South, Jerry C., Jr.
1987-01-01
An overview is given of computational mechanics and physics at NASA Langley Research Center. Computational analysis is a major component and tool in many of Langley's diverse research disciplines, as well as in the interdisciplinary research. Examples are given for algorithm development and advanced applications in aerodynamics, transition to turbulence and turbulence simulation, hypersonics, structures, and interdisciplinary optimization.
Development of computer-based analytical tool for assessing physical protection system
NASA Astrophysics Data System (ADS)
Mardhi, Alim; Pengvanich, Phongphaeth
2016-01-01
Assessment of physical protection system effectiveness is the priority for ensuring the optimum protection caused by unlawful acts against a nuclear facility, such as unauthorized removal of nuclear materials and sabotage of the facility itself. Since an assessment based on real exercise scenarios is costly and time-consuming, the computer-based analytical tool can offer the solution for approaching the likelihood threat scenario. There are several currently available tools that can be used instantly such as EASI and SAPE, however for our research purpose it is more suitable to have the tool that can be customized and enhanced further. In this work, we have developed a computer-based analytical tool by utilizing the network methodological approach for modelling the adversary paths. The inputs are multi-elements in security used for evaluate the effectiveness of the system's detection, delay, and response. The tool has capability to analyze the most critical path and quantify the probability of effectiveness of the system as performance measure.
Multi-scale simulations of space problems with iPIC3D
NASA Astrophysics Data System (ADS)
Lapenta, Giovanni; Bettarini, Lapo; Markidis, Stefano
The implicit Particle-in-Cell method for the computer simulation of space plasma, and its im-plementation in a three-dimensional parallel code, called iPIC3D, are presented. The implicit integration in time of the Vlasov-Maxwell system removes the numerical stability constraints and enables kinetic plasma simulations at magnetohydrodynamics scales. Simulations of mag-netic reconnection in plasma are presented to show the effectiveness of the algorithm. In particular we will show a number of simulations done for large scale 3D systems using the physical mass ratio for Hydrogen. Most notably one simulation treats kinetically a box of tens of Earth radii in each direction and was conducted using about 16000 processors of the Pleiades NASA computer. The work is conducted in collaboration with the MMS-IDS theory team from University of Colorado (M. Goldman, D. Newman and L. Andersson). Reference: Stefano Markidis, Giovanni Lapenta, Rizwan-uddin Multi-scale simulations of plasma with iPIC3D Mathematics and Computers in Simulation, Available online 17 October 2009, http://dx.doi.org/10.1016/j.matcom.2009.08.038
NASA Astrophysics Data System (ADS)
Terzopoulos, Demetri; Qureshi, Faisal Z.
Computer vision and sensor networks researchers are increasingly motivated to investigate complex multi-camera sensing and control issues that arise in the automatic visual surveillance of extensive, highly populated public spaces such as airports and train stations. However, they often encounter serious impediments to deploying and experimenting with large-scale physical camera networks in such real-world environments. We propose an alternative approach called "Virtual Vision", which facilitates this type of research through the virtual reality simulation of populated urban spaces, camera sensor networks, and computer vision on commodity computers. We demonstrate the usefulness of our approach by developing two highly automated surveillance systems comprising passive and active pan/tilt/zoom cameras that are deployed in a virtual train station environment populated by autonomous, lifelike virtual pedestrians. The easily reconfigurable virtual cameras distributed in this environment generate synthetic video feeds that emulate those acquired by real surveillance cameras monitoring public spaces. The novel multi-camera control strategies that we describe enable the cameras to collaborate in persistently observing pedestrians of interest and in acquiring close-up videos of pedestrians in designated areas.
Multi-core processing and scheduling performance in CMS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hernandez, J. M.; Evans, D.; Foulkes, S.
2012-01-01
Commodity hardware is going many-core. We might soon not be able to satisfy the job memory needs per core in the current single-core processing model in High Energy Physics. In addition, an ever increasing number of independent and incoherent jobs running on the same physical hardware not sharing resources might significantly affect processing performance. It will be essential to effectively utilize the multi-core architecture. CMS has incorporated support for multi-core processing in the event processing framework and the workload management system. Multi-core processing jobs share common data in memory, such us the code libraries, detector geometry and conditions data, resultingmore » in a much lower memory usage than standard single-core independent jobs. Exploiting this new processing model requires a new model in computing resource allocation, departing from the standard single-core allocation for a job. The experiment job management system needs to have control over a larger quantum of resource since multi-core aware jobs require the scheduling of multiples cores simultaneously. CMS is exploring the approach of using whole nodes as unit in the workload management system where all cores of a node are allocated to a multi-core job. Whole-node scheduling allows for optimization of the data/workflow management (e.g. I/O caching, local merging) but efficient utilization of all scheduled cores is challenging. Dedicated whole-node queues have been setup at all Tier-1 centers for exploring multi-core processing workflows in CMS. We present the evaluation of the performance scheduling and executing multi-core workflows in whole-node queues compared to the standard single-core processing workflows.« less
Data management and analysis for the Earth System Grid
NASA Astrophysics Data System (ADS)
Williams, D. N.; Ananthakrishnan, R.; Bernholdt, D. E.; Bharathi, S.; Brown, D.; Chen, M.; Chervenak, A. L.; Cinquini, L.; Drach, R.; Foster, I. T.; Fox, P.; Hankin, S.; Henson, V. E.; Jones, P.; Middleton, D. E.; Schwidder, J.; Schweitzer, R.; Schuler, R.; Shoshani, A.; Siebenlist, F.; Sim, A.; Strand, W. G.; Wilhelmi, N.; Su, M.
2008-07-01
The international climate community is expected to generate hundreds of petabytes of simulation data within the next five to seven years. This data must be accessed and analyzed by thousands of analysts worldwide in order to provide accurate and timely estimates of the likely impact of climate change on physical, biological, and human systems. Climate change is thus not only a scientific challenge of the first order but also a major technological challenge. In order to address this technological challenge, the Earth System Grid Center for Enabling Technologies (ESG-CET) has been established within the U.S. Department of Energy's Scientific Discovery through Advanced Computing (SciDAC)-2 program, with support from the offices of Advanced Scientific Computing Research and Biological and Environmental Research. ESG-CET's mission is to provide climate researchers worldwide with access to the data, information, models, analysis tools, and computational capabilities required to make sense of enormous climate simulation datasets. Its specific goals are to (1) make data more useful to climate researchers by developing Grid technology that enhances data usability; (2) meet specific distributed database, data access, and data movement needs of national and international climate projects; (3) provide a universal and secure web-based data access portal for broad multi-model data collections; and (4) provide a wide-range of Grid-enabled climate data analysis tools and diagnostic methods to international climate centers and U.S. government agencies. Building on the successes of the previous Earth System Grid (ESG) project, which has enabled thousands of researchers to access tens of terabytes of data from a small number of ESG sites, ESG-CET is working to integrate a far larger number of distributed data providers, high-bandwidth wide-area networks, and remote computers in a highly collaborative problem-solving environment.
Implementing a Loosely Coupled Fluid Structure Interaction Finite Element Model in PHASTA
NASA Astrophysics Data System (ADS)
Pope, David
Fluid Structure Interaction problems are an important multi-physics phenomenon in the design of aerospace vehicles and other engineering applications. A variety of computational fluid dynamics solvers capable of resolving the fluid dynamics exist. PHASTA is one such computational fluid dynamics solver. Enhancing the capability of PHASTA to resolve Fluid-Structure Interaction first requires implementing a structural dynamics solver. The implementation also requires a correction of the mesh used to solve the fluid equations to account for the deformation of the structure. This results in mesh motion and causes the need for an Arbitrary Lagrangian-Eulerian modification to the fluid dynamics equations currently implemented in PHASTA. With the implementation of both structural dynamics physics, mesh correction, and the Arbitrary Lagrangian-Eulerian modification of the fluid dynamics equations, PHASTA is made capable of solving Fluid-Structure Interaction problems.
Visual comparison testing of automotive paint simulation
NASA Astrophysics Data System (ADS)
Meyer, Gary; Fan, Hua-Tzu; Seubert, Christopher; Evey, Curtis; Meseth, Jan; Schnackenberg, Ryan
2015-03-01
An experiment was performed to determine whether typical industrial automotive color paint comparisons made using real physical samples could also be carried out using a digital simulation displayed on a calibrated color television monitor. A special light booth, designed to facilitate evaluation of the car paint color with reflectance angle, was employed in both the real and virtual color comparisons. Paint samples were measured using a multi-angle spectrophotometer and were simulated using a commercially available software package. Subjects performed the test quicker using the computer graphic simulation, and results indicate that there is only a small difference between the decisions made using the light booth and the computer monitor. This outcome demonstrates the potential of employing simulations to replace some of the time consuming work with real physical samples that still characterizes material appearance work in industry.
NASA Astrophysics Data System (ADS)
Moore, Linda A.; Ferreira, Jannie T.
2003-03-01
Sports vision encompasses the visual assessment and provision of sports-specific visual performance enhancement and ocular protection for athletes of all ages, genders and levels of participation. In recent years, sports vision has been identified as one of the key performance indicators in sport. It is built on four main cornerstones: corrective eyewear, protective eyewear, visual skills enhancement and performance enhancement. Although clinically well established in the US, it is still a relatively new area of optometric specialisation elsewhere in the world and is gaining increasing popularity with eyecare practitioners and researchers. This research is often multi-disciplinary and involves input from a variety of subject disciplines, mainly those of optometry, medicine, physiology, psychology, physics, chemistry, computer science and engineering. Collaborative research projects are currently underway between staff of the Schools of Physics and Computing (DIT) and the Academy of Sports Vision (RAU).
Computational Aerodynamic Modeling of Small Quadcopter Vehicles
NASA Technical Reports Server (NTRS)
Yoon, Seokkwan; Ventura Diaz, Patricia; Boyd, D. Douglas; Chan, William M.; Theodore, Colin R.
2017-01-01
High-fidelity computational simulations have been performed which focus on rotor-fuselage and rotor-rotor aerodynamic interactions of small quad-rotor vehicle systems. The three-dimensional unsteady Navier-Stokes equations are solved on overset grids using high-order accurate schemes, dual-time stepping, low Mach number preconditioning, and hybrid turbulence modeling. Computational results for isolated rotors are shown to compare well with available experimental data. Computational results in hover reveal the differences between a conventional configuration where the rotors are mounted above the fuselage and an unconventional configuration where the rotors are mounted below the fuselage. Complex flow physics in forward flight is investigated. The goal of this work is to demonstrate that understanding of interactional aerodynamics can be an important factor in design decisions regarding rotor and fuselage placement for next-generation multi-rotor drones.
A self-taught artificial agent for multi-physics computational model personalization.
Neumann, Dominik; Mansi, Tommaso; Itu, Lucian; Georgescu, Bogdan; Kayvanpour, Elham; Sedaghat-Hamedani, Farbod; Amr, Ali; Haas, Jan; Katus, Hugo; Meder, Benjamin; Steidl, Stefan; Hornegger, Joachim; Comaniciu, Dorin
2016-12-01
Personalization is the process of fitting a model to patient data, a critical step towards application of multi-physics computational models in clinical practice. Designing robust personalization algorithms is often a tedious, time-consuming, model- and data-specific process. We propose to use artificial intelligence concepts to learn this task, inspired by how human experts manually perform it. The problem is reformulated in terms of reinforcement learning. In an off-line phase, Vito, our self-taught artificial agent, learns a representative decision process model through exploration of the computational model: it learns how the model behaves under change of parameters. The agent then automatically learns an optimal strategy for on-line personalization. The algorithm is model-independent; applying it to a new model requires only adjusting few hyper-parameters of the agent and defining the observations to match. The full knowledge of the model itself is not required. Vito was tested in a synthetic scenario, showing that it could learn how to optimize cost functions generically. Then Vito was applied to the inverse problem of cardiac electrophysiology and the personalization of a whole-body circulation model. The obtained results suggested that Vito could achieve equivalent, if not better goodness of fit than standard methods, while being more robust (up to 11% higher success rates) and with faster (up to seven times) convergence rate. Our artificial intelligence approach could thus make personalization algorithms generalizable and self-adaptable to any patient and any model. Copyright © 2016. Published by Elsevier B.V.
2013-01-01
Background Screen-based media (SBM) occupy a considerable portion of young peoples’ discretionary leisure time. The aim of this paper was to investigate whether distinct clusters of SBM use exist, and if so, to examine the relationship of any identified clusters with other activity/sedentary behaviours and physical and mental health indicators. Methods The data for this study come from 643 adolescents, aged 14 years, who were participating in the longitudinal Western Australian Pregnancy Cohort (Raine) Study through May 2003 to June 2006. Time spent on SBM, phone use and reading was assessed using the Multimedia Activity Recall for Children and Adults. Height, weight, muscle strength were measured at a clinic visit and the adolescents also completed questionnaires on their physical activity and psychosocial health. Latent class analysis (LCA) was used to analyse groupings of SBM use. Results Three clusters of SBM use were found; C1 ‘instrumental computer users’ (high email use, general computer use), C2 ‘multi-modal e-gamers’ (both high console and computer game use) and C3 ‘computer e-gamers’ (high computer game use only). Television viewing was moderately high amongst all the clusters. C2 males took fewer steps than their male peers in C1 and C3 (-13,787/week, 95% CI: -4619 to -22957, p = 0.003 and -14,806, 95% CI: -5,306 to -24,305, p = 0.002) and recorded less MVPA than the C1 males (-3.5 h, 95% CI: -1.0 to -5.9, p = 0.005). There was no difference in activity levels between females in clusters C1 and C3. Conclusion SBM use by adolescents did cluster and these clusters related differently to activity/sedentary behaviours and both physical and psychosocial health indicators. It is clear that SBM use is not a single construct and future research needs to take consideration of this if it intends to understand the impact SBM has on health. PMID:24330626
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shemon, Emily R.; Smith, Micheal A.; Lee, Changho
2016-02-16
PROTEUS-SN is a three-dimensional, highly scalable, high-fidelity neutron transport code developed at Argonne National Laboratory. The code is applicable to all spectrum reactor transport calculations, particularly those in which a high degree of fidelity is needed either to represent spatial detail or to resolve solution gradients. PROTEUS-SN solves the second order formulation of the transport equation using the continuous Galerkin finite element method in space, the discrete ordinates approximation in angle, and the multigroup approximation in energy. PROTEUS-SN’s parallel methodology permits the efficient decomposition of the problem by both space and angle, permitting large problems to run efficiently on hundredsmore » of thousands of cores. PROTEUS-SN can also be used in serial or on smaller compute clusters (10’s to 100’s of cores) for smaller homogenized problems, although it is generally more computationally expensive than traditional homogenized methodology codes. PROTEUS-SN has been used to model partially homogenized systems, where regions of interest are represented explicitly and other regions are homogenized to reduce the problem size and required computational resources. PROTEUS-SN solves forward and adjoint eigenvalue problems and permits both neutron upscattering and downscattering. An adiabatic kinetics option has recently been included for performing simple time-dependent calculations in addition to standard steady state calculations. PROTEUS-SN handles void and reflective boundary conditions. Multigroup cross sections can be generated externally using the MC2-3 fast reactor multigroup cross section generation code or internally using the cross section application programming interface (API) which can treat the subgroup or resonance table libraries. PROTEUS-SN is written in Fortran 90 and also includes C preprocessor definitions. The code links against the PETSc, METIS, HDF5, and MPICH libraries. It optionally links against the MOAB library and is a part of the SHARP multi-physics suite for coupled multi-physics analysis of nuclear reactors. This user manual describes how to set up a neutron transport simulation with the PROTEUS-SN code. A companion methodology manual describes the theory and algorithms within PROTEUS-SN.« less
NASA Astrophysics Data System (ADS)
Vikram, K. Arun; Ratnam, Ch; Lakshmi, VVK; Kumar, A. Sunny; Ramakanth, RT
2018-02-01
Meta-heuristic multi-response optimization methods are widely in use to solve multi-objective problems to obtain Pareto optimal solutions during optimization. This work focuses on optimal multi-response evaluation of process parameters in generating responses like surface roughness (Ra), surface hardness (H) and tool vibration displacement amplitude (Vib) while performing operations like tangential and orthogonal turn-mill processes on A-axis Computer Numerical Control vertical milling center. Process parameters like tool speed, feed rate and depth of cut are considered as process parameters machined over brass material under dry condition with high speed steel end milling cutters using Taguchi design of experiments (DOE). Meta-heuristic like Dragonfly algorithm is used to optimize the multi-objectives like ‘Ra’, ‘H’ and ‘Vib’ to identify the optimal multi-response process parameters combination. Later, the results thus obtained from multi-objective dragonfly algorithm (MODA) are compared with another multi-response optimization technique Viz. Grey relational analysis (GRA).
Physical properties of the HAT-P-23 and WASP-48 planetary systems from multi-colour photometry
NASA Astrophysics Data System (ADS)
Ciceri, S.; Mancini, L.; Southworth, J.; Bruni, I.; Nikolov, N.; D'Ago, G.; Schröder, T.; Bozza, V.; Tregloan-Reed, J.; Henning, Th.
2015-05-01
Context. Accurate and repeated photometric follow-up observations of planetary transit events are important to precisely characterize the physical properties of exoplanets. A good knowledge of the main characteristics of the exoplanets is fundamental in order to trace their origin and evolution. Multi-band photometric observations play an important role in this process. Aims: By using new photometric data, we computed precise estimates of the physical properties of two transiting planetary systems at equilibrium temperatures of ~2000 K. Methods: We present new broadband, multi-colour photometric observations obtained using three small class telescopes and the telescope-defocussing technique. In particular we obtained 11 and 10 light curves covering 8 and 7 transits of HAT-P-23 and WASP-48, respectively. For each of the two targets, one transit event was simultaneously observed through four optical filters. One transit of WASP-48 b was monitored with two telescopes from the same observatory. The physical parameters of the systems were obtained by fitting the transit light curves with jktebop and from published spectroscopic measurements. Results: We have revised the physical parameters of the two planetary systems, finding a smaller radius for both HAT-P-23 b and WASP-48 b, Rb = 1.224 ± 0.037 RJup and Rb = 1.396 ± 0.051 RJup, respectively, than those measured in the discovery papers (Rb = 1.368 ± 0.090 RJup and Rb = 1.67 ± 0.10 RJup). The density of the two planets are higher than those previously published (ρb ~ 1.1 and ~0.3 ρjup for HAT-P-23 and WASP-48, respectively) hence the two hot Jupiters are no longer located in a parameter space region of highly inflated planets. An analysis of the variation of the planet's measured radius as a function of optical wavelength reveals flat transmission spectra within the experimental uncertainties. We also confirm the presence of the eclipsing contact binary NSVS-3071474 in the same field of view of WASP-48, for which we refine the value of the period to be 0.459 d. The photometric light curves are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/577/A54
Collaborative Science Using Web Services and the SciFlo Grid Dataflow Engine
NASA Astrophysics Data System (ADS)
Wilson, B. D.; Manipon, G.; Xing, Z.; Yunck, T.
2006-12-01
The General Earth Science Investigation Suite (GENESIS) project is a NASA-sponsored partnership between the Jet Propulsion Laboratory, academia, and NASA data centers to develop a new suite of Web Services tools to facilitate multi-sensor investigations in Earth System Science. The goal of GENESIS is to enable large-scale, multi-instrument atmospheric science using combined datasets from the AIRS, MODIS, MISR, and GPS sensors. Investigations include cross-comparison of spaceborne climate sensors, cloud spectral analysis, study of upper troposphere-stratosphere water transport, study of the aerosol indirect cloud effect, and global climate model validation. The challenges are to bring together very large datasets, reformat and understand the individual instrument retrievals, co-register or re-grid the retrieved physical parameters, perform computationally-intensive data fusion and data mining operations, and accumulate complex statistics over months to years of data. To meet these challenges, we have developed a Grid computing and dataflow framework, named SciFlo, in which we are deploying a set of versatile and reusable operators for data access, subsetting, registration, mining, fusion, compression, and advanced statistical analysis. SciFlo leverages remote Web Services, called via Simple Object Access Protocol (SOAP) or REST (one-line) URLs, and the Grid Computing standards (WS-* &Globus Alliance toolkits), and enables scientists to do multi-instrument Earth Science by assembling reusable Web Services and native executables into a distributed computing flow (tree of operators). The SciFlo client &server engines optimize the execution of such distributed data flows and allow the user to transparently find and use datasets and operators without worrying about the actual location of the Grid resources. In particular, SciFlo exploits the wealth of datasets accessible by OpenGIS Consortium (OGC) Web Mapping Servers & Web Coverage Servers (WMS/WCS), and by Open Data Access Protocol (OpenDAP) servers. The scientist injects a distributed computation into the Grid by simply filling out an HTML form or directly authoring the underlying XML dataflow document, and results are returned directly to the scientist's desktop. Once an analysis has been specified for a chunk or day of data, it can be easily repeated with different control parameters or over months of data. Recently, the Earth Science Information Partners (ESIP) Federation sponsored a collaborative activity in which several ESIP members advertised their respective WMS/WCS and SOAP services, developed some collaborative science scenarios for atmospheric and aerosol science, and then choreographed services from multiple groups into demonstration workflows using the SciFlo engine and a Business Process Execution Language (BPEL) workflow engine. For several scenarios, the same collaborative workflow was executed in three ways: using hand-coded scripts, by executing a SciFlo document, and by executing a BPEL workflow document. We will discuss the lessons learned from this activity, the need for standardized interfaces (like WMS/WCS), the difficulty in agreeing on even simple XML formats and interfaces, and further collaborations that are being pursued.
Multi-scale and multi-domain computational astrophysics.
van Elteren, Arjen; Pelupessy, Inti; Zwart, Simon Portegies
2014-08-06
Astronomical phenomena are governed by processes on all spatial and temporal scales, ranging from days to the age of the Universe (13.8 Gyr) as well as from kilometre size up to the size of the Universe. This enormous range in scales is contrived, but as long as there is a physical connection between the smallest and largest scales it is important to be able to resolve them all, and for the study of many astronomical phenomena this governance is present. Although covering all these scales is a challenge for numerical modellers, the most challenging aspect is the equally broad and complex range in physics, and the way in which these processes propagate through all scales. In our recent effort to cover all scales and all relevant physical processes on these scales, we have designed the Astrophysics Multipurpose Software Environment (AMUSE). AMUSE is a Python-based framework with production quality community codes and provides a specialized environment to connect this plethora of solvers to a homogeneous problem-solving environment. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
NASA Astrophysics Data System (ADS)
Xue, ShiChuan; Wu, JunJie; Xu, Ping; Yang, XueJun
2018-02-01
Quantum computing is a significant computing capability which is superior to classical computing because of its superposition feature. Distinguishing several quantum states from quantum algorithm outputs is often a vital computational task. In most cases, the quantum states tend to be non-orthogonal due to superposition; quantum mechanics has proved that perfect outcomes could not be achieved by measurements, forcing repetitive measurement. Hence, it is important to determine the optimum measuring method which requires fewer repetitions and a lower error rate. However, extending current measurement approaches mainly aiming at quantum cryptography to multi-qubit situations for quantum computing confronts challenges, such as conducting global operations which has considerable costs in the experimental realm. Therefore, in this study, we have proposed an optimum subsystem method to avoid these difficulties. We have provided an analysis of the comparison between the reduced subsystem method and the global minimum error method for two-qubit problems; the conclusions have been verified experimentally. The results showed that the subsystem method could effectively discriminate non-orthogonal two-qubit states, such as separable states, entangled pure states, and mixed states; the cost of the experimental process had been significantly reduced, in most circumstances, with acceptable error rate. We believe the optimal subsystem method is the most valuable and promising approach for multi-qubit quantum computing applications.
[Automobile versus pedestrian accidents analysis by fixed-parameters computer simulation].
Mao, Ming-Yuan; Chen, Yi-Jiu; Liu, Ning-Guo; Zou, Dong-Hua; Liu, Jun-Yong; Jin, Xian-Long
2008-04-01
Using computer simulation to analyze the effects of speed, type of automobile and impacted position on crash-course and injuries of pedestrians in automobile vs. pedestrian accidents. Automobiles (bus, minibus, car and truck) and pedestrian models were constructed with multi-body dynamics computing method. The crashes were simulated at different impact speeds (20, 30, 40, 50 and 60 km/h) and different positions (front, lateral and rear of pedestrians). Crash-courses and their biomechanical responses were studied. If the type of automobile and impact position were the same, the crash-courses were similar (impact speed < or = 60 km/h). There were some characteristics in the head acceleration, upper neck axial force and leg axial force. Multi-body dynamics computer simulation of crash can be applied to analyze crash-course and injuries (head, neck and leg) of pedestrians.
NASA Astrophysics Data System (ADS)
Reiss, P.
2018-05-01
Chemical analysis of lunar soil samples often involves thermal processing to extract their volatile constituents, such as loosely adsorbed water. For the characterization of volatiles and their bonding mechanisms it is important to determine their desorption temperature. However, due to the low thermal diffusivity of lunar regolith, it might be difficult to reach a uniform heat distribution in a sample that is larger than only a few particles. Furthermore, the mass transport through such a sample is restricted, which might lead to a significant delay between actual desorption and measurable outgassing of volatiles from the sample. The entire volatiles extraction process depends on the dynamically changing heat and mass transfer within the sample, and is influenced by physical parameters such as porosity, tortuosity, gas density, temperature and pressure. To correctly interpret measurements of the extracted volatiles, it is important to understand the interaction between heat transfer, sorption, and gas transfer through the sample. The present paper discusses the molecular kinetics and mechanisms that are involved in the thermal extraction process and presents a combined parametrical computation model to simulate this process. The influence of water content on the gas diffusivity and thermal diffusivity is discussed and the issue of possible resorption of desorbed molecules within the sample is addressed. Based on the multi-physical computation model, a case study for the ProSPA instrument for in situ analysis of lunar volatiles is presented, which predicts relevant dynamic process parameters, such as gas pressure and process duration.
Tang, Dalin; Yang, Chun; Geva, Tal; Gaudette, Glenn; del Nido, Pedro J.
2011-01-01
Multi-physics right and left ventricle (RV/LV) fluid-structure interaction (FSI) models were introduced to perform mechanical stress analysis and evaluate the effect of patch materials on RV function. The FSI models included three different patch materials (Dacron scaffold, treated pericardium, and contracting myocardium), two-layer construction, fiber orientation, and active anisotropic material properties. The models were constructed based on cardiac magnetic resonance (CMR) images acquired from a patient with severe RV dilatation and solved by ADINA. Our results indicate that the patch model with contracting myocardium leads to decreased stress level in the patch area, improved RV function and patch area contractility. PMID:21765559
Multi-Tissue Computational Modeling Analyzes Pathophysiology of Type 2 Diabetes in MKR Mice
Kumar, Amit; Harrelson, Thomas; Lewis, Nathan E.; Gallagher, Emily J.; LeRoith, Derek; Shiloach, Joseph; Betenbaugh, Michael J.
2014-01-01
Computational models using metabolic reconstructions for in silico simulation of metabolic disorders such as type 2 diabetes mellitus (T2DM) can provide a better understanding of disease pathophysiology and avoid high experimentation costs. There is a limited amount of computational work, using metabolic reconstructions, performed in this field for the better understanding of T2DM. In this study, a new algorithm for generating tissue-specific metabolic models is presented, along with the resulting multi-confidence level (MCL) multi-tissue model. The effect of T2DM on liver, muscle, and fat in MKR mice was first studied by microarray analysis and subsequently the changes in gene expression of frank T2DM MKR mice versus healthy mice were applied to the multi-tissue model to test the effect. Using the first multi-tissue genome-scale model of all metabolic pathways in T2DM, we found out that branched-chain amino acids' degradation and fatty acids oxidation pathway is downregulated in T2DM MKR mice. Microarray data showed low expression of genes in MKR mice versus healthy mice in the degradation of branched-chain amino acids and fatty-acid oxidation pathways. In addition, the flux balance analysis using the MCL multi-tissue model showed that the degradation pathways of branched-chain amino acid and fatty acid oxidation were significantly downregulated in MKR mice versus healthy mice. Validation of the model was performed using data derived from the literature regarding T2DM. Microarray data was used in conjunction with the model to predict fluxes of various other metabolic pathways in the T2DM mouse model and alterations in a number of pathways were detected. The Type 2 Diabetes MCL multi-tissue model may explain the high level of branched-chain amino acids and free fatty acids in plasma of Type 2 Diabetic subjects from a metabolic fluxes perspective. PMID:25029527
Development of a Multi-Disciplinary Aerothermostructural Model Applicable to Hypersonic Flight
NASA Technical Reports Server (NTRS)
Kostyk, Chris; Risch, Tim
2013-01-01
The harsh and complex hypersonic flight environment has driven design and analysis improvements for many years. One of the defining characteristics of hypersonic flight is the coupled, multi-disciplinary nature of the dominant physics. In an effect to examine some of the multi-disciplinary problems associated with hypersonic flight engineers at the NASA Dryden Flight Research Center developed a non-linear 6 degrees-of-freedom, full vehicle simulation that includes the necessary model capabilities: aerothermal heating, ablation, and thermal stress solutions. Development of the tool and results for some investigations will be presented. Requirements and improvements for future work will also be reviewed. The results of the work emphasize the need for a coupled, multi-disciplinary analysis to provide accurate
NASA Technical Reports Server (NTRS)
Mall, G. H.
1983-01-01
Modifications to a multi-degree-of-freedom flexible aircraft take-off and landing analysis (FATOLA) computer program, including a provision for actively controlled landing gears to expand the programs simulation capabilities, are presented. Supplemental instructions for preparation of data and for use of the modified program are included.
Computer Animation with Adobe Flash Professional Cs6 in Newton’s Law
NASA Astrophysics Data System (ADS)
Aji, S. D.; Hudha, M. N.; Huda, C.; Gufran, G.
2018-01-01
The purpose of this research is to develop computer-based physics learning media with Adobe Flash Professional CS6 on Newton’s Law of physics subject for senior high school (SMA / MA) class X. Type of research applied is Research and Development with ADDIE development model covering 5 stages: Analysis (Analysis), Design (Design), Development (Production), Implementation (Implementation) and Evaluation (Evaluation). The results of this study were tested toward media experts, media specialists, physics teachers, and students test results with media outcomes that are declared very feasible.
The change in critical technologies for computational physics
NASA Technical Reports Server (NTRS)
Watson, Val
1990-01-01
It is noted that the types of technology required for computational physics are changing as the field matures. Emphasis has shifted from computer technology to algorithm technology and, finally, to visual analysis technology as areas of critical research for this field. High-performance graphical workstations tied to a supercommunicator with high-speed communications along with the development of especially tailored visualization software has enabled analysis of highly complex fluid-dynamics simulations. Particular reference is made here to the development of visual analysis tools at NASA's Numerical Aerodynamics Simulation Facility. The next technology which this field requires is one that would eliminate visual clutter by extracting key features of simulations of physics and technology in order to create displays that clearly portray these key features. Research in the tuning of visual displays to human cognitive abilities is proposed. The immediate transfer of technology to all levels of computers, specifically the inclusion of visualization primitives in basic software developments for all work stations and PCs, is recommended.
Optimized planning methodologies of ASON implementation
NASA Astrophysics Data System (ADS)
Zhou, Michael M.; Tamil, Lakshman S.
2005-02-01
Advanced network planning concerns effective network-resource allocation for dynamic and open business environment. Planning methodologies of ASON implementation based on qualitative analysis and mathematical modeling are presented in this paper. The methodology includes method of rationalizing technology and architecture, building network and nodal models, and developing dynamic programming for multi-period deployment. The multi-layered nodal architecture proposed here can accommodate various nodal configurations for a multi-plane optical network and the network modeling presented here computes the required network elements for optimizing resource allocation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Haque, A.K.M. Mahmudul; Oh, Geum Seok; Kim, Taeoh
Highlights: • We study the microwave effect on the multi-walled carbon nanotubes (MWCNTs). • We examine the non uniform heating effect on the physical structure of MWCNTs. • We examine the purification of MWCNTs by microwave. • We analyze the thermal characteristics of microwave treated MWCNTs. - Abstract: This paper reports the effect of microwave on the physical properties of multi-walled carbon nanotubes (MWCNTs) where different power levels of microwave were applied on MWCNTs in order to apprehend the effect of microwave on MWCNTs distinctly. A low energy ball milling in aqueous circumstance was also applied on both MWCNTs andmore » microwave treated MWCNTs. Temperature profile, morphological analysis by field emission scanning electron microscopy (FESEM), defect analysis by Raman spectroscopy, thermal conductivity, thermal diffusivity as well as heat transfer coefficient enhancement ratio were studied which expose some strong witnesses of the effect of microwave on the both purification and dispersion properties of MWCNTs in base fluid distilled water. The highest thermal conductivity enhancement (6.06% at 40 °C) of MWCNTs based nanofluid is achieved by five minutes microwave treatment as well as wet grinding at 500 rpm for two hours.« less
Multi-level optimization of a beam-like space truss utilizing a continuum model
NASA Technical Reports Server (NTRS)
Yates, K.; Gurdal, Z.; Thangjitham, S.
1992-01-01
A continuous beam model is developed for approximate analysis of a large, slender, beam-like truss. The model is incorporated in a multi-level optimization scheme for the weight minimization of such trusses. This scheme is tested against traditional optimization procedures for savings in computational cost. Results from both optimization methods are presented for comparison.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kim, Seung Jun; Buechler, Cynthia Eileen
The current study aims to predict the steady state power of a generic solution vessel and to develop a corresponding heat transfer coefficient correlation for a Moly99 production facility by conducting a fully coupled multi-physics simulation. A prediction of steady state power for the current application is inherently interconnected between thermal hydraulic characteristics (i.e. Multiphase computational fluid dynamics solved by ANSYS-Fluent 17.2) and the corresponding neutronic behavior (i.e. particle transport solved by MCNP6.2) in the solution vessel. Thus, the development of a coupling methodology is vital to understand the system behavior at a variety of system design and postulated operatingmore » scenarios. In this study, we report on the k-effective (keff) calculation for the baseline solution vessel configuration with a selected solution concentration using MCNP K-code modeling. The associated correlation of thermal properties (e.g. density, viscosity, thermal conductivity, specific heat) at the selected solution concentration are developed based on existing experimental measurements in the open literature. The numerical coupling methodology between multiphase CFD and MCNP is successfully demonstrated, and the detailed coupling procedure is documented. In addition, improved coupling methods capturing realistic physics in the solution vessel thermal-neutronic dynamics are proposed and tested further (i.e. dynamic height adjustment, mull-cell approach). As a key outcome of the current study, a multi-physics coupling methodology between MCFD and MCNP is demonstrated and tested for four different operating conditions. Those different operating conditions are determined based on the neutron source strength at a fixed geometry condition. The steady state powers for the generic solution vessel at various operating conditions are reported, and a generalized correlation of the heat transfer coefficient for the current application is discussed. The assessment of multi-physics methodology and preliminary results from various coupled calculations (power prediction and heat transfer coefficient) can be further utilized for the system code validation and generic solution vessel design improvement.« less
NASA Astrophysics Data System (ADS)
Balaji, V.; Benson, Rusty; Wyman, Bruce; Held, Isaac
2016-10-01
Climate models represent a large variety of processes on a variety of timescales and space scales, a canonical example of multi-physics multi-scale modeling. Current hardware trends, such as Graphical Processing Units (GPUs) and Many Integrated Core (MIC) chips, are based on, at best, marginal increases in clock speed, coupled with vast increases in concurrency, particularly at the fine grain. Multi-physics codes face particular challenges in achieving fine-grained concurrency, as different physics and dynamics components have different computational profiles, and universal solutions are hard to come by. We propose here one approach for multi-physics codes. These codes are typically structured as components interacting via software frameworks. The component structure of a typical Earth system model consists of a hierarchical and recursive tree of components, each representing a different climate process or dynamical system. This recursive structure generally encompasses a modest level of concurrency at the highest level (e.g., atmosphere and ocean on different processor sets) with serial organization underneath. We propose to extend concurrency much further by running more and more lower- and higher-level components in parallel with each other. Each component can further be parallelized on the fine grain, potentially offering a major increase in the scalability of Earth system models. We present here first results from this approach, called coarse-grained component concurrency, or CCC. Within the Geophysical Fluid Dynamics Laboratory (GFDL) Flexible Modeling System (FMS), the atmospheric radiative transfer component has been configured to run in parallel with a composite component consisting of every other atmospheric component, including the atmospheric dynamics and all other atmospheric physics components. We will explore the algorithmic challenges involved in such an approach, and present results from such simulations. Plans to achieve even greater levels of coarse-grained concurrency by extending this approach within other components, such as the ocean, will be discussed.
Uncoordinated MAC for Adaptive Multi-Beam Directional Networks: Analysis and Evaluation
2016-04-10
transmission times, hence traditional CSMA approaches are not appropriate. We first present our model of these multi-beamforming capa- bilities and the...resulting wireless interference. We then derive an upper bound on multi-access performance for an idealized version of this physical layer. We then present... transmissions and receptions in a mobile ad-hoc network has in practice led to very constrained topologies. As mentioned, one approach for system design is to de
Multi-threading: A new dimension to massively parallel scientific computation
NASA Astrophysics Data System (ADS)
Nielsen, Ida M. B.; Janssen, Curtis L.
2000-06-01
Multi-threading is becoming widely available for Unix-like operating systems, and the application of multi-threading opens new ways for performing parallel computations with greater efficiency. We here briefly discuss the principles of multi-threading and illustrate the application of multi-threading for a massively parallel direct four-index transformation of electron repulsion integrals. Finally, other potential applications of multi-threading in scientific computing are outlined.
Physical Interpretation of the Correlation Between Multi-Angle Spectral Data and Canopy Height
NASA Technical Reports Server (NTRS)
Schull, M. A.; Ganguly, S.; Samanta, A.; Huang, D.; Shabanov, N. V.; Jenkins, J. P.; Chiu, J. C.; Marshak, A.; Blair, J. B.; Myneni, R. B.;
2007-01-01
Recent empirical studies have shown that multi-angle spectral data can be useful for predicting canopy height, but the physical reason for this correlation was not understood. We follow the concept of canopy spectral invariants, specifically escape probability, to gain insight into the observed correlation. Airborne Multi-Angle Imaging Spectrometer (AirMISR) and airborne Laser Vegetation Imaging Sensor (LVIS) data acquired during a NASA Terrestrial Ecology Program aircraft campaign underlie our analysis. Two multivariate linear regression models were developed to estimate LVIS height measures from 28 AirMISR multi-angle spectral reflectances and from the spectrally invariant escape probability at 7 AirMISR view angles. Both models achieved nearly the same accuracy, suggesting that canopy spectral invariant theory can explain the observed correlation. We hypothesize that the escape probability is sensitive to the aspect ratio (crown diameter to crown height). The multi-angle spectral data alone therefore may not provide enough information to retrieve canopy height globally
Korczowski, L; Congedo, M; Jutten, C
2015-08-01
The classification of electroencephalographic (EEG) data recorded from multiple users simultaneously is an important challenge in the field of Brain-Computer Interface (BCI). In this paper we compare different approaches for classification of single-trials Event-Related Potential (ERP) on two subjects playing a collaborative BCI game. The minimum distance to mean (MDM) classifier in a Riemannian framework is extended to use the diversity of the inter-subjects spatio-temporal statistics (MDM-hyper) or to merge multiple classifiers (MDM-multi). We show that both these classifiers outperform significantly the mean performance of the two users and analogous classifiers based on the step-wise linear discriminant analysis. More importantly, the MDM-multi outperforms the performance of the best player within the pair.
SMAC7; Sequential multi-channel analysis with computer-7; SMA7; Metabolic panel 7; CHEM-7 ... breathing problems, diabetes or diabetes-related complications, and medicine side effects. Talk to your provider about the ...
Xarray: multi-dimensional data analysis in Python
NASA Astrophysics Data System (ADS)
Hoyer, Stephan; Hamman, Joe; Maussion, Fabien
2017-04-01
xarray (http://xarray.pydata.org) is an open source project and Python package that provides a toolkit and data structures for N-dimensional labeled arrays, which are the bread and butter of modern geoscientific data analysis. Key features of the package include label-based indexing and arithmetic, interoperability with the core scientific Python packages (e.g., pandas, NumPy, Matplotlib, Cartopy), out-of-core computation on datasets that don't fit into memory, a wide range of input/output options, and advanced multi-dimensional data manipulation tools such as group-by and resampling. In this contribution we will present the key features of the library and demonstrate its great potential for a wide range of applications, from (big-)data processing on super computers to data exploration in front of a classroom.
Some Issues in Programming Multi-Mini-Processors
1975-01-01
Hardware ^nd software are to be combined optimally to perform that specialized task. This in essence is the stategy followed by the BBN group in...large memory is directly addressable. MIXED SOLUTIONS The most promising approach appears to involve mixing several of the previous solutions...mini- or micro-computers. Possibly the problem will be solved by avoiding it. Some new minis are appearing on the market now with large physical
Magician Simulator. A Realistic Simulator for Heterogenous Teams of Autonomous Robots
2011-01-18
IMU, and LIDAR systems for identifying and tracking mobile OOI at long range (>20m), providing early warnings and allowing neutralization from a... LIDAR and Computer Vision template-based feature tracking approaches. Mapping was solved through Multi-Agent particle-filter based Simultaneous...Locali- zation and Mapping ( SLAM ). Our system contains two maps, a physical map and an influence map (location of hostile OOI, explored and unexplored
Genten: Software for Generalized Tensor Decompositions v. 1.0.0
DOE Office of Scientific and Technical Information (OSTI.GOV)
Phipps, Eric T.; Kolda, Tamara G.; Dunlavy, Daniel
Tensors, or multidimensional arrays, are a powerful mathematical means of describing multiway data. This software provides computational means for decomposing or approximating a given tensor in terms of smaller tensors of lower dimension, focusing on decomposition of large, sparse tensors. These techniques have applications in many scientific areas, including signal processing, linear algebra, computer vision, numerical analysis, data mining, graph analysis, neuroscience and more. The software is designed to take advantage of parallelism present emerging computer architectures such has multi-core CPUs, many-core accelerators such as the Intel Xeon Phi, and computation-oriented GPUs to enable efficient processing of large tensors.
NASA Technical Reports Server (NTRS)
Razzaq, Zia; Prasad, Venkatesh; Darbhamulla, Siva Prasad; Bhati, Ravinder; Lin, Cai
1987-01-01
Parallel computing studies are presented for a variety of structural analysis problems. Included are the substructure planar analysis of rectangular panels with and without a hole, the static analysis of space mast, using NICE/SPAR and FORCE, and substructure analysis of plane rigid-jointed frames using FORCE. The computations are carried out on the Flex/32 MultiComputer using one to eighteen processors. The NICE/SPAR runstream samples are documented for the panel problem. For the substructure analysis of plane frames, a computer program is developed to demonstrate the effectiveness of a substructuring technique when FORCE is enforced. Ongoing research activities for an elasto-plastic stability analysis problem using FORCE, and stability analysis of the focus problem using NICE/SPAR are briefly summarized. Speedup curves for the panel, the mast, and the frame problems provide a basic understanding of the effectiveness of parallel computing procedures utilized or developed, within the domain of the parameters considered. Although the speedup curves obtained exhibit various levels of computational efficiency, they clearly demonstrate the excellent promise which parallel computing holds for the structural analysis problem. Source code is given for the elasto-plastic stability problem and the FORCE program.
Bird impact analysis package for turbine engine fan blades
NASA Technical Reports Server (NTRS)
Hirschbein, M. S.
1982-01-01
A computer program has been developed to analyze the gross structural response of turbine engine fan blades subjected to bird strikes. The program couples a NASTRAN finite element model and modal analysis of a fan blade with a multi-mode bird impact analysis computer program. The impact analysis uses the NASTRAN blade model and a fluid jet model of the bird to interactively calculate blade loading during a bird strike event. The analysis package is computationaly efficient, easy to use and provides a comprehensive history of the gross structual blade response. Example cases are presented for a representative fan blade.
NASA Astrophysics Data System (ADS)
Sizov, Gennadi Y.
In this dissertation, a model-based multi-objective optimal design of permanent magnet ac machines, supplied by sine-wave current regulated drives, is developed and implemented. The design procedure uses an efficient electromagnetic finite element-based solver to accurately model nonlinear material properties and complex geometric shapes associated with magnetic circuit design. Application of an electromagnetic finite element-based solver allows for accurate computation of intricate performance parameters and characteristics. The first contribution of this dissertation is the development of a rapid computational method that allows accurate and efficient exploration of large multi-dimensional design spaces in search of optimum design(s). The computationally efficient finite element-based approach developed in this work provides a framework of tools that allow rapid analysis of synchronous electric machines operating under steady-state conditions. In the developed modeling approach, major steady-state performance parameters such as, winding flux linkages and voltages, average, cogging and ripple torques, stator core flux densities, core losses, efficiencies and saturated machine winding inductances, are calculated with minimum computational effort. In addition, the method includes means for rapid estimation of distributed stator forces and three-dimensional effects of stator and/or rotor skew on the performance of the machine. The second contribution of this dissertation is the development of the design synthesis and optimization method based on a differential evolution algorithm. The approach relies on the developed finite element-based modeling method for electromagnetic analysis and is able to tackle large-scale multi-objective design problems using modest computational resources. Overall, computational time savings of up to two orders of magnitude are achievable, when compared to current and prevalent state-of-the-art methods. These computational savings allow one to expand the optimization problem to achieve more complex and comprehensive design objectives. The method is used in the design process of several interior permanent magnet industrial motors. The presented case studies demonstrate that the developed finite element-based approach practically eliminates the need for using less accurate analytical and lumped parameter equivalent circuit models for electric machine design optimization. The design process and experimental validation of the case-study machines are detailed in the dissertation.
Numerical Simulations of Reacting Flows Using Asynchrony-Tolerant Schemes for Exascale Computing
NASA Astrophysics Data System (ADS)
Cleary, Emmet; Konduri, Aditya; Chen, Jacqueline
2017-11-01
Communication and data synchronization between processing elements (PEs) are likely to pose a major challenge in scalability of solvers at the exascale. Recently developed asynchrony-tolerant (AT) finite difference schemes address this issue by relaxing communication and synchronization between PEs at a mathematical level while preserving accuracy, resulting in improved scalability. The performance of these schemes has been validated for simple linear and nonlinear homogeneous PDEs. However, many problems of practical interest are governed by highly nonlinear PDEs with source terms, whose solution may be sensitive to perturbations caused by communication asynchrony. The current work applies the AT schemes to combustion problems with chemical source terms, yielding a stiff system of PDEs with nonlinear source terms highly sensitive to temperature. Examples shown will use single-step and multi-step CH4 mechanisms for 1D premixed and nonpremixed flames. Error analysis will be discussed both in physical and spectral space. Results show that additional errors introduced by the AT schemes are negligible and the schemes preserve their accuracy. We acknowledge funding from the DOE Computational Science Graduate Fellowship administered by the Krell Institute.
Time-Accurate Simulations and Acoustic Analysis of Slat Free-Shear-Layer. Part 2
NASA Technical Reports Server (NTRS)
Khorrami, Mehdi R.; Singer, Bart A.; Lockard, David P.
2002-01-01
Unsteady computational simulations of a multi-element, high-lift configuration are performed. Emphasis is placed on accurate spatiotemporal resolution of the free shear layer in the slat-cove region. The excessive dissipative effects of the turbulence model, so prevalent in previous simulations, are circumvented by switching off the turbulence-production term in the slat cove region. The justifications and physical arguments for taking such a step are explained in detail. The removal of this excess damping allows the shear layer to amplify large-scale structures, to achieve a proper non-linear saturation state, and to permit vortex merging. The large-scale disturbances are self-excited, and unlike our prior fully turbulent simulations, no external forcing of the shear layer is required. To obtain the farfield acoustics, the Ffowcs Williams and Hawkings equation is evaluated numerically using the simulated time-accurate flow data. The present comparison between the computed and measured farfield acoustic spectra shows much better agreement for the amplitude and frequency content than past calculations. The effect of the angle-of-attack on the slat's flow features radiated acoustic field are also simulated presented.
NASA Astrophysics Data System (ADS)
Yang, Hong-Yong; Lu, Lan; Cao, Ke-Cai; Zhang, Si-Ying
2010-04-01
In this paper, the relations of the network topology and the moving consensus of multi-agent systems are studied. A consensus-prestissimo scale-free network model with the static preferential-consensus attachment is presented on the rewired link of the regular network. The effects of the static preferential-consensus BA network on the algebraic connectivity of the topology graph are compared with the regular network. The robustness gain to delay is analyzed for variable network topology with the same scale. The time to reach the consensus is studied for the dynamic network with and without communication delays. By applying the computer simulations, it is validated that the speed of the convergence of multi-agent systems can be greatly improved in the preferential-consensus BA network model with different configuration.
Investigation of atmospheric anomalies associated with Kashmir and Awaran Earthquakes
NASA Astrophysics Data System (ADS)
Mahmood, Irfan; Iqbal, Muhammad Farooq; Shahzad, Muhammad Imran; Qaiser, Saddam
2017-02-01
The earthquake precursors' anomalies at diverse elevation ranges over the seismogenic region and prior to the seismic events are perceived using Satellite Remote Sensing (SRS) techniques and reanalysis datasets. In the current research, seismic precursors are obtained by analyzing anomalies in Outgoing Longwave Radiation (OLR), Air Temperature (AT), and Relative Humidity (RH) before the two strong Mw>7 earthquakes in Pakistan occurred on 8th October 2005 in Azad Jammu Kashmir with Mw 7.6, and 24th September 2013 in Awaran, Balochistan with Mw 7.7. Multi-parameter data were computed based on multi-year background data for anomalies computation. Results indicate significant transient variations in observed parameters before the main event. Detailed analysis suggests presence of pre-seismic activities one to three weeks prior to the main earthquake event that vanishes after the event. These anomalies are due to increase in temperature after release of gases and physical and chemical interactions on earth surface before the earthquake. The parameter variations behavior for both Kashmir and Awaran earthquake events are similar to other earthquakes in different regions of the world. This study suggests that energy release is not concentrated to a single fault but instead is released along the fault zone. The influence of earthquake events on lightning were also investigated and it was concluded that there is a significant atmospheric lightning activity after the earthquake suggesting a strong possibility for an earthquake induced thunderstorm. This study is valuable for identifying earthquake precursors especially in earthquake prone areas.
Contention Modeling for Multithreaded Distributed Shared Memory Machines: The Cray XMT
DOE Office of Scientific and Technical Information (OSTI.GOV)
Secchi, Simone; Tumeo, Antonino; Villa, Oreste
Distributed Shared Memory (DSM) machines are a wide class of multi-processor computing systems where a large virtually-shared address space is mapped on a network of physically distributed memories. High memory latency and network contention are two of the main factors that limit performance scaling of such architectures. Modern high-performance computing DSM systems have evolved toward exploitation of massive hardware multi-threading and fine-grained memory hashing to tolerate irregular latencies, avoid network hot-spots and enable high scaling. In order to model the performance of such large-scale machines, parallel simulation has been proved to be a promising approach to achieve good accuracy inmore » reasonable times. One of the most critical factors in solving the simulation speed-accuracy trade-off is network modeling. The Cray XMT is a massively multi-threaded supercomputing architecture that belongs to the DSM class, since it implements a globally-shared address space abstraction on top of a physically distributed memory substrate. In this paper, we discuss the development of a contention-aware network model intended to be integrated in a full-system XMT simulator. We start by measuring the effects of network contention in a 128-processor XMT machine and then investigate the trade-off that exists between simulation accuracy and speed, by comparing three network models which operate at different levels of accuracy. The comparison and model validation is performed by executing a string-matching algorithm on the full-system simulator and on the XMT, using three datasets that generate noticeably different contention patterns.« less
NASA Astrophysics Data System (ADS)
Peng, Yahui; Jiang, Yulei; Liarski, Vladimir M.; Kaverina, Natalya; Clark, Marcus R.; Giger, Maryellen L.
2012-03-01
Analysis of interactions between B and T cells in tubulointerstitial inflammation is important for understanding human lupus nephritis. We developed a computer technique to perform this analysis, and compared it with manual analysis. Multi-channel immunoflourescent-microscopy images were acquired from 207 regions of interest in 40 renal tissue sections of 19 patients diagnosed with lupus nephritis. Fresh-frozen renal tissue sections were stained with combinations of immunoflourescent antibodies to membrane proteins and counter-stained with a cell nuclear marker. Manual delineation of the antibodies was considered as the reference standard. We first segmented cell nuclei and cell membrane markers, and then determined corresponding cell types based on the distances between cell nuclei and specific cell-membrane marker combinations. Subsequently, the distribution of the shortest distance from T cell nuclei to B cell nuclei was obtained and used as a surrogate indicator of cell-cell interactions. The computer and manual analyses results were concordant. The average absolute difference was 1.1+/-1.2% between the computer and manual analysis results in the number of cell-cell distances of 3 μm or less as a percentage of the total number of cell-cell distances. Our computerized analysis of cell-cell distances could be used as a surrogate for quantifying cell-cell interactions as either an automated and quantitative analysis or for independent confirmation of manual analysis.
Time-Of-Flight Camera, Optical Tracker and Computed Tomography in Pairwise Data Registration.
Pycinski, Bartlomiej; Czajkowska, Joanna; Badura, Pawel; Juszczyk, Jan; Pietka, Ewa
2016-01-01
A growing number of medical applications, including minimal invasive surgery, depends on multi-modal or multi-sensors data processing. Fast and accurate 3D scene analysis, comprising data registration, seems to be crucial for the development of computer aided diagnosis and therapy. The advancement of surface tracking system based on optical trackers already plays an important role in surgical procedures planning. However, new modalities, like the time-of-flight (ToF) sensors, widely explored in non-medical fields are powerful and have the potential to become a part of computer aided surgery set-up. Connection of different acquisition systems promises to provide a valuable support for operating room procedures. Therefore, the detailed analysis of the accuracy of such multi-sensors positioning systems is needed. We present the system combining pre-operative CT series with intra-operative ToF-sensor and optical tracker point clouds. The methodology contains: optical sensor set-up and the ToF-camera calibration procedures, data pre-processing algorithms, and registration technique. The data pre-processing yields a surface, in case of CT, and point clouds for ToF-sensor and marker-driven optical tracker representation of an object of interest. An applied registration technique is based on Iterative Closest Point algorithm. The experiments validate the registration of each pair of modalities/sensors involving phantoms of four various human organs in terms of Hausdorff distance and mean absolute distance metrics. The best surface alignment was obtained for CT and optical tracker combination, whereas the worst for experiments involving ToF-camera. The obtained accuracies encourage to further develop the multi-sensors systems. The presented substantive discussion concerning the system limitations and possible improvements mainly related to the depth information produced by the ToF-sensor is useful for computer aided surgery developers.
NASA Astrophysics Data System (ADS)
Shi, X.; Zhang, G.
2013-12-01
Because of the extensive computational burden, parametric uncertainty analyses are rarely conducted for geological carbon sequestration (GCS) process based multi-phase models. The difficulty of predictive uncertainty analysis for the CO2 plume migration in realistic GCS models is not only due to the spatial distribution of the caprock and reservoir (i.e. heterogeneous model parameters), but also because the GCS optimization estimation problem has multiple local minima due to the complex nonlinear multi-phase (gas and aqueous), and multi-component (water, CO2, salt) transport equations. The geological model built by Doughty and Pruess (2004) for the Frio pilot site (Texas) was selected and assumed to represent the 'true' system, which was composed of seven different facies (geological units) distributed among 10 layers. We chose to calibrate the permeabilities of these facies. Pressure and gas saturation values from this true model were then extracted and used as observations for subsequent model calibration. Random noise was added to the observations to approximate realistic field conditions. Each simulation of the model lasts about 2 hours. In this study, we develop a new approach that improves computational efficiency of Bayesian inference by constructing a surrogate system based on an adaptive sparse-grid stochastic collocation method. This surrogate response surface global optimization algorithm is firstly used to calibrate the model parameters, then prediction uncertainty of the CO2 plume position is quantified due to the propagation from parametric uncertainty in the numerical experiments, which is also compared to the actual plume from the 'true' model. Results prove that the approach is computationally efficient for multi-modal optimization and prediction uncertainty quantification for computationally expensive simulation models. Both our inverse methodology and findings can be broadly applicable to GCS in heterogeneous storage formations.
NASA Astrophysics Data System (ADS)
Ahmad, J. A.; Forman, B. A.
2017-12-01
High Mountain Asia (HMA) serves as a water supply source for over 1.3 billion people, primarily in south-east Asia. Most of this water originates as snow (or ice) that melts during the summer months and contributes to the run-off downstream. In spite of its critical role, there is still considerable uncertainty regarding the total amount of snow in HMA and its spatial and temporal variation. In this study, the NASA Land Information Systems (LIS) is used to model the hydrologic cycle over the Indus basin. In addition, the ability of support vector machines (SVM), a machine learning technique, to predict passive microwave brightness temperatures at a specific frequency and polarization as a function of LIS-derived land surface model output is explored in a sensitivity analysis. Multi-frequency, multi-polarization passive microwave brightness temperatures as measured by the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) over the Indus basin are used as training targets during the SVM training process. Normalized sensitivity coefficients (NSC) are then computed to assess the sensitivity of a well-trained SVM to each LIS-derived state variable. Preliminary results conform with the known first-order physics. For example, input states directly linked to physical temperature like snow temperature, air temperature, and vegetation temperature have positive NSC's whereas input states that increase volume scattering such as snow water equivalent or snow density yield negative NSC's. Air temperature exhibits the largest sensitivity coefficients due to its inherent, high-frequency variability. Adherence of this machine learning algorithm to the first-order physics bodes well for its potential use in LIS as the observation operator within a radiance data assimilation system aimed at improving regional- and continental-scale snow estimates.
Parallel Aircraft Trajectory Optimization with Analytic Derivatives
NASA Technical Reports Server (NTRS)
Falck, Robert D.; Gray, Justin S.; Naylor, Bret
2016-01-01
Trajectory optimization is an integral component for the design of aerospace vehicles, but emerging aircraft technologies have introduced new demands on trajectory analysis that current tools are not well suited to address. Designing aircraft with technologies such as hybrid electric propulsion and morphing wings requires consideration of the operational behavior as well as the physical design characteristics of the aircraft. The addition of operational variables can dramatically increase the number of design variables which motivates the use of gradient based optimization with analytic derivatives to solve the larger optimization problems. In this work we develop an aircraft trajectory analysis tool using a Legendre-Gauss-Lobatto based collocation scheme, providing analytic derivatives via the OpenMDAO multidisciplinary optimization framework. This collocation method uses an implicit time integration scheme that provides a high degree of sparsity and thus several potential options for parallelization. The performance of the new implementation was investigated via a series of single and multi-trajectory optimizations using a combination of parallel computing and constraint aggregation. The computational performance results show that in order to take full advantage of the sparsity in the problem it is vital to parallelize both the non-linear analysis evaluations and the derivative computations themselves. The constraint aggregation results showed a significant numerical challenge due to difficulty in achieving tight convergence tolerances. Overall, the results demonstrate the value of applying analytic derivatives to trajectory optimization problems and lay the foundation for future application of this collocation based method to the design of aircraft with where operational scheduling of technologies is key to achieving good performance.
A second-order closure analysis of turbulent diffusion flames. [combustion physics
NASA Technical Reports Server (NTRS)
Varma, A. K.; Fishburne, E. S.; Beddini, R. A.
1977-01-01
A complete second-order closure computer program for the investigation of compressible, turbulent, reacting shear layers was developed. The equations for the means and the second order correlations were derived from the time-averaged Navier-Stokes equations and contain third order and higher order correlations, which have to be modeled in terms of the lower-order correlations to close the system of equations. In addition to fluid mechanical turbulence models and parameters used in previous studies of a variety of incompressible and compressible shear flows, a number of additional scalar correlations were modeled for chemically reacting flows, and a typical eddy model developed for the joint probability density function for all the scalars. The program which is capable of handling multi-species, multistep chemical reactions, was used to calculate nonreacting and reacting flows in a hydrogen-air diffusion flame.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nash, T.; Atac, R.; Cook, A.
1989-03-06
The ACPMAPS multipocessor is a highly cost effective, local memory parallel computer with a hypercube or compound hypercube architecture. Communication requires the attention of only the two communicating nodes. The design is aimed at floating point intensive, grid like problems, particularly those with extreme computing requirements. The processing nodes of the system are single board array processors, each with a peak power of 20 Mflops, supported by 8 Mbytes of data and 2 Mbytes of instruction memory. The system currently being assembled has a peak power of 5 Gflops. The nodes are based on the Weitek XL Chip set. Themore » system delivers performance at approximately $300/Mflop. 8 refs., 4 figs.« less
Taulaniemi, Annika; Kuusinen, Lotta; Tokola, Kari; Kankaanpää, Markku; Suni, Jaana H
2017-08-31
To investigate associations of various bio-psychosocial factors with bodily pain, physical func-tioning, and ability to work in low back pain. Cross-sectional study. A total of 219 female healthcare workers with recurrent non-specific low back pain. Associations between several physical and psychosocial factors and: (i) bodily pain, (ii) physical functioning and (iii) ability to work were studied. Variables with statistically significant associations (p < 0.05) in bivariate analysis were set within a generalized linear model to analyse their relationship with each dependent variable. In generalized linear model analysis, perceived work-induced lumbar exertion (p < 0.001), multi-site pain (p <0.001) and work-related fear-avoidance beliefs (FAB-W) (p = 0.02) best explained bodily pain. Multi-site pain (p < 0.001), lumbar exertion (p = 0.005), FAB-W (p = 0.01) and physical performance in figure-of-eight running (p = 0.01) and modified push-ups (p = 0.05) best explained physical functioning; FAB-W (p <0.001), lumbar exertion (p = 0.003), depression (p = 0.01) and recovery after work (p = 0.03) best explained work ability. In bivariate analysis lumbar exertion was associated with poor physical performance. FAB-W and work-induced lumbar exertion were associated with levels of pain, physical functioning and ability to work. Poor physical performance capacity was associated with work-induced lumbar exertion. Interventions that aim to reduce fear-avoidance and increase fitness capacity might be beneficial.
NASA Astrophysics Data System (ADS)
Spiegelman, M.; Wilson, C. R.
2011-12-01
A quantitative theory of magma production and transport is essential for understanding the dynamics of magmatic plate boundaries, intra-plate volcanism and the geochemical evolution of the planet. It also provides one of the most challenging computational problems in solid Earth science, as it requires consistent coupling of fluid and solid mechanics together with the thermodynamics of melting and reactive flows. Considerable work on these problems over the past two decades shows that small changes in assumptions of coupling (e.g. the relationship between melt fraction and solid rheology), can have profound changes on the behavior of these systems which in turn affects critical computational choices such as discretizations, solvers and preconditioners. To make progress in exploring and understanding this physically rich system requires a computational framework that allows more flexible, high-level description of multi-physics problems as well as increased flexibility in composing efficient algorithms for solution of the full non-linear coupled system. Fortunately, recent advances in available computational libraries and algorithms provide a platform for implementing such a framework. We present results from a new model building system that leverages functionality from both the FEniCS project (www.fenicsproject.org) and PETSc libraries (www.mcs.anl.gov/petsc) along with a model independent options system and gui, Spud (amcg.ese.ic.ac.uk/Spud). Key features from FEniCS include fully unstructured FEM with a wide range of elements; a high-level language (ufl) and code generation compiler (FFC) for describing the weak forms of residuals and automatic differentiation for calculation of exact and approximate jacobians. The overall strategy is to monitor/calculate residuals and jacobians for the entire non-linear system of equations within a global non-linear solve based on PETSc's SNES routines. PETSc already provides a wide range of solvers and preconditioners, from parallel sparse direct to algebraic multigrid, that can be chosen at runtime. In particular, we make extensive use of PETSc's FieldSplit block preconditioners that allow us to use optimal solvers for subproblems (such as Stokes, or advection/diffusion of temperature) as preconditioners for the full problem. Thus these routines let us reuse effective solving recipes/splittings from previous experience while monitoring the convergence of the global problem. These techniques often yield quadratic (Newton like) convergence for the work of standard Picard schemes. We will illustrate this new framework with examples from the Magma Dynamic Demonstration suite (MADDs) of well understood magma dynamics benchmark problems including stokes flow in ridge geometries, magmatic solitary waves and shear-driven melt bands. While development of this system has been driven by magma dynamics, this framework is much more general and can be used for a wide range of PDE based multi-physics models.
Gaussian curvature analysis allows for automatic block placement in multi-block hexahedral meshing.
Ramme, Austin J; Shivanna, Kiran H; Magnotta, Vincent A; Grosland, Nicole M
2011-10-01
Musculoskeletal finite element analysis (FEA) has been essential to research in orthopaedic biomechanics. The generation of a volumetric mesh is often the most challenging step in a FEA. Hexahedral meshing tools that are based on a multi-block approach rely on the manual placement of building blocks for their mesh generation scheme. We hypothesise that Gaussian curvature analysis could be used to automatically develop a building block structure for multi-block hexahedral mesh generation. The Automated Building Block Algorithm incorporates principles from differential geometry, combinatorics, statistical analysis and computer science to automatically generate a building block structure to represent a given surface without prior information. We have applied this algorithm to 29 bones of varying geometries and successfully generated a usable mesh in all cases. This work represents a significant advancement in automating the definition of building blocks.
Fast multi-core based multimodal registration of 2D cross-sections and 3D datasets
2010-01-01
Background Solving bioinformatics tasks often requires extensive computational power. Recent trends in processor architecture combine multiple cores into a single chip to improve overall performance. The Cell Broadband Engine (CBE), a heterogeneous multi-core processor, provides power-efficient and cost-effective high-performance computing. One application area is image analysis and visualisation, in particular registration of 2D cross-sections into 3D image datasets. Such techniques can be used to put different image modalities into spatial correspondence, for example, 2D images of histological cuts into morphological 3D frameworks. Results We evaluate the CBE-driven PlayStation 3 as a high performance, cost-effective computing platform by adapting a multimodal alignment procedure to several characteristic hardware properties. The optimisations are based on partitioning, vectorisation, branch reducing and loop unrolling techniques with special attention to 32-bit multiplies and limited local storage on the computing units. We show how a typical image analysis and visualisation problem, the multimodal registration of 2D cross-sections and 3D datasets, benefits from the multi-core based implementation of the alignment algorithm. We discuss several CBE-based optimisation methods and compare our results to standard solutions. More information and the source code are available from http://cbe.ipk-gatersleben.de. Conclusions The results demonstrate that the CBE processor in a PlayStation 3 accelerates computational intensive multimodal registration, which is of great importance in biological/medical image processing. The PlayStation 3 as a low cost CBE-based platform offers an efficient option to conventional hardware to solve computational problems in image processing and bioinformatics. PMID:20064262
Adaptive subdomain modeling: A multi-analysis technique for ocean circulation models
NASA Astrophysics Data System (ADS)
Altuntas, Alper; Baugh, John
2017-07-01
Many coastal and ocean processes of interest operate over large temporal and geographical scales and require a substantial amount of computational resources, particularly when engineering design and failure scenarios are also considered. This study presents an adaptive multi-analysis technique that improves the efficiency of these computations when multiple alternatives are being simulated. The technique, called adaptive subdomain modeling, concurrently analyzes any number of child domains, with each instance corresponding to a unique design or failure scenario, in addition to a full-scale parent domain providing the boundary conditions for its children. To contain the altered hydrodynamics originating from the modifications, the spatial extent of each child domain is adaptively adjusted during runtime depending on the response of the model. The technique is incorporated in ADCIRC++, a re-implementation of the popular ADCIRC ocean circulation model with an updated software architecture designed to facilitate this adaptive behavior and to utilize concurrent executions of multiple domains. The results of our case studies confirm that the method substantially reduces computational effort while maintaining accuracy.
Stability and Scalability of the CMS Global Pool: Pushing HTCondor and GlideinWMS to New Limits
DOE Office of Scientific and Technical Information (OSTI.GOV)
Balcas, J.; Bockelman, B.; Hufnagel, D.
The CMS Global Pool, based on HTCondor and glideinWMS, is the main computing resource provisioning system for all CMS workflows, including analysis, Monte Carlo production, and detector data reprocessing activities. The total resources at Tier-1 and Tier-2 grid sites pledged to CMS exceed 100,000 CPU cores, while another 50,000 to 100,000 CPU cores are available opportunistically, pushing the needs of the Global Pool to higher scales each year. These resources are becoming more diverse in their accessibility and configuration over time. Furthermore, the challenge of stably running at higher and higher scales while introducing new modes of operation such asmore » multi-core pilots, as well as the chaotic nature of physics analysis workflows, places huge strains on the submission infrastructure. This paper details some of the most important challenges to scalability and stability that the CMS Global Pool has faced since the beginning of the LHC Run II and how they were overcome.« less
Stability and scalability of the CMS Global Pool: Pushing HTCondor and glideinWMS to new limits
NASA Astrophysics Data System (ADS)
Balcas, J.; Bockelman, B.; Hufnagel, D.; Hurtado Anampa, K.; Aftab Khan, F.; Larson, K.; Letts, J.; Marra da Silva, J.; Mascheroni, M.; Mason, D.; Perez-Calero Yzquierdo, A.; Tiradani, A.
2017-10-01
The CMS Global Pool, based on HTCondor and glideinWMS, is the main computing resource provisioning system for all CMS workflows, including analysis, Monte Carlo production, and detector data reprocessing activities. The total resources at Tier-1 and Tier-2 grid sites pledged to CMS exceed 100,000 CPU cores, while another 50,000 to 100,000 CPU cores are available opportunistically, pushing the needs of the Global Pool to higher scales each year. These resources are becoming more diverse in their accessibility and configuration over time. Furthermore, the challenge of stably running at higher and higher scales while introducing new modes of operation such as multi-core pilots, as well as the chaotic nature of physics analysis workflows, places huge strains on the submission infrastructure. This paper details some of the most important challenges to scalability and stability that the CMS Global Pool has faced since the beginning of the LHC Run II and how they were overcome.
A Hybrid Optimization Framework with POD-based Order Reduction and Design-Space Evolution Scheme
NASA Astrophysics Data System (ADS)
Ghoman, Satyajit S.
The main objective of this research is to develop an innovative multi-fidelity multi-disciplinary design, analysis and optimization suite that integrates certain solution generation codes and newly developed innovative tools to improve the overall optimization process. The research performed herein is divided into two parts: (1) the development of an MDAO framework by integration of variable fidelity physics-based computational codes, and (2) enhancements to such a framework by incorporating innovative features extending its robustness. The first part of this dissertation describes the development of a conceptual Multi-Fidelity Multi-Strategy and Multi-Disciplinary Design Optimization Environment (M3 DOE), in context of aircraft wing optimization. M 3 DOE provides the user a capability to optimize configurations with a choice of (i) the level of fidelity desired, (ii) the use of a single-step or multi-step optimization strategy, and (iii) combination of a series of structural and aerodynamic analyses. The modularity of M3 DOE allows it to be a part of other inclusive optimization frameworks. The M 3 DOE is demonstrated within the context of shape and sizing optimization of the wing of a Generic Business Jet aircraft. Two different optimization objectives, viz. dry weight minimization, and cruise range maximization are studied by conducting one low-fidelity and two high-fidelity optimization runs to demonstrate the application scope of M3 DOE. The second part of this dissertation describes the development of an innovative hybrid optimization framework that extends the robustness of M 3 DOE by employing a proper orthogonal decomposition-based design-space order reduction scheme combined with the evolutionary algorithm technique. The POD method of extracting dominant modes from an ensemble of candidate configurations is used for the design-space order reduction. The snapshot of candidate population is updated iteratively using evolutionary algorithm technique of fitness-driven retention. This strategy capitalizes on the advantages of evolutionary algorithm as well as POD-based reduced order modeling, while overcoming the shortcomings inherent with these techniques. When linked with M3 DOE, this strategy offers a computationally efficient methodology for problems with high level of complexity and a challenging design-space. This newly developed framework is demonstrated for its robustness on a nonconventional supersonic tailless air vehicle wing shape optimization problem.
Multi-scale Material Appearance
NASA Astrophysics Data System (ADS)
Wu, Hongzhi
Modeling and rendering the appearance of materials is important for a diverse range of applications of computer graphics - from automobile design to movies and cultural heritage. The appearance of materials varies considerably at different scales, posing significant challenges due to the sheer complexity of the data, as well the need to maintain inter-scale consistency constraints. This thesis presents a series of studies around the modeling, rendering and editing of multi-scale material appearance. To efficiently render material appearance at multiple scales, we develop an object-space precomputed adaptive sampling method, which precomputes a hierarchy of view-independent points that preserve multi-level appearance. To support bi-scale material appearance design, we propose a novel reflectance filtering algorithm, which rapidly computes the large-scale appearance from small-scale details, by exploiting the low-rank structures of Bidirectional Visible Normal Distribution Functions and pre-rotated Bidirectional Reflectance Distribution Functions in the matrix formulation of the rendering algorithm. This approach can guide the physical realization of appearance, as well as the modeling of real-world materials using very sparse measurements. Finally, we present a bi-scale-inspired high-quality general representation for material appearance described by Bidirectional Texture Functions. Our representation is at once compact, easily editable, and amenable to efficient rendering.
NASA Astrophysics Data System (ADS)
Kim, Sungtae; Lee, Soogab; Kim, Kyu Hong
2008-04-01
A new numerical method toward accurate and efficient aeroacoustic computations of multi-dimensional compressible flows has been developed. The core idea of the developed scheme is to unite the advantages of the wavenumber-extended optimized scheme and M-AUSMPW+/MLP schemes by predicting a physical distribution of flow variables more accurately in multi-space dimensions. The wavenumber-extended optimization procedure for the finite volume approach based on the conservative requirement is newly proposed for accuracy enhancement, which is required to capture the acoustic portion of the solution in the smooth region. Furthermore, the new distinguishing mechanism which is based on the Gibbs phenomenon in discontinuity, between continuous and discontinuous regions is introduced to eliminate the excessive numerical dissipation in the continuous region by the restricted application of MLP according to the decision of the distinguishing function. To investigate the effectiveness of the developed method, a sequence of benchmark simulations such as spherical wave propagation, nonlinear wave propagation, shock tube problem and vortex preservation test problem are executed. Also, throughout more realistic shock-vortex interaction and muzzle blast flow problems, the utility of the new method for aeroacoustic applications is verified by comparing with the previous numerical or experimental results.
Recent advances in non-LTE stellar atmosphere models
NASA Astrophysics Data System (ADS)
Sander, Andreas A. C.
2017-11-01
In the last decades, stellar atmosphere models have become a key tool in understanding massive stars. Applied for spectroscopic analysis, these models provide quantitative information on stellar wind properties as well as fundamental stellar parameters. The intricate non-LTE conditions in stellar winds dictate the development of adequate sophisticated model atmosphere codes. The increase in both, the computational power and our understanding of physical processes in stellar atmospheres, led to an increasing complexity in the models. As a result, codes emerged that can tackle a wide range of stellar and wind parameters. After a brief address of the fundamentals of stellar atmosphere modeling, the current stage of clumped and line-blanketed model atmospheres will be discussed. Finally, the path for the next generation of stellar atmosphere models will be outlined. Apart from discussing multi-dimensional approaches, I will emphasize on the coupling of hydrodynamics with a sophisticated treatment of the radiative transfer. This next generation of models will be able to predict wind parameters from first principles, which could open new doors for our understanding of the various facets of massive star physics, evolution, and death.
Numerical modeling of the fetal blood flow in the placental circulatory system
NASA Astrophysics Data System (ADS)
Shannon, Alexander; Gallucci, Sergio; Mirbod, Parisa
2015-11-01
The placenta is a unique organ of exchange between the growing fetus and the mother. It incorporates almost all functions of the adult body, acting as the fetal lung, digestive and immune systems, to mention a few. The exchange of oxygen and nutrients takes place at the surface of the villous tree. Using an idealized geometry of the fetal villous trees in the mouse placenta, in this study we performed 3D computational analysis of the unsteady fetal blood flow, gas, and nutrient transport over the chorionic plate. The fetal blood was treated as an incompressible Newtonian fluid, and the oxygen and nutrient were treated as a passive scalar dissolved in blood plasma. The flow was laminar, and a commercial CFD code (COMSOL Multiphysics) has been used for the simulation. COMSOL has been selected because it is multi-physics FEM software that allows for the seamless coupling of different physics represented by partial differential equations. The results clearly illustrate that the specific branching pattern and the in-plane curvature of the fetal villous trees affect the delivery of blood, gas and nutrient transport to the whole placenta.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Friedman, A.; Barnard, J. J.; Cohen, R. H.
The Heavy Ion Fusion Science Virtual National Laboratory(a collaboration of LBNL, LLNL, and PPPL) is using intense ion beams to heat thin foils to the"warm dense matter" regime at<~;; 1 eV, and is developing capabilities for studying target physics relevant to ion-driven inertial fusion energy. The need for rapid target heating led to the development of plasma-neutralized pulse compression, with current amplification factors exceeding 50 now routine on the Neutralized Drift Compression Experiment (NDCX). Construction of an improved platform, NDCX-II, has begun at LBNL with planned completion in 2012. Using refurbished induction cells from the Advanced Test Accelerator at LLNL,more » NDCX-II will compress a ~;;500 ns pulse of Li+ ions to ~;;1 ns while accelerating it to 3-4 MeV over ~;;15 m. Strong space charge forces are incorporated into the machine design at a fundamental level. We are using analysis, an interactive 1D PIC code (ASP) with optimizing capabilities and centroid tracking, and multi-dimensional Warpcode PIC simulations, to develop the NDCX-II accelerator. This paper describes the computational models employed, and the resulting physics design for the accelerator.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Friedman, A; Barnard, J J; Cohen, R H
The Heavy Ion Fusion Science Virtual National Laboratory (a collaboration of LBNL, LLNL, and PPPL) is using intense ion beams to heat thin foils to the 'warm dense matter' regime at {approx}< 1 eV, and is developing capabilities for studying target physics relevant to ion-driven inertial fusion energy. The need for rapid target heating led to the development of plasma-neutralized pulse compression, with current amplification factors exceeding 50 now routine on the Neutralized Drift Compression Experiment (NDCX). Construction of an improved platform, NDCX-II, has begun at LBNL with planned completion in 2012. Using refurbished induction cells from the Advanced Testmore » Accelerator at LLNL, NDCX-II will compress a {approx}500 ns pulse of Li{sup +} ions to {approx} 1 ns while accelerating it to 3-4 MeV over {approx} 15 m. Strong space charge forces are incorporated into the machine design at a fundamental level. We are using analysis, an interactive 1D PIC code (ASP) with optimizing capabilities and centroid tracking, and multi-dimensional Warpcode PIC simulations, to develop the NDCX-II accelerator. This paper describes the computational models employed, and the resulting physics design for the accelerator.« less
NASA Astrophysics Data System (ADS)
Qiang, Ji
2017-10-01
A three-dimensional (3D) Poisson solver with longitudinal periodic and transverse open boundary conditions can have important applications in beam physics of particle accelerators. In this paper, we present a fast efficient method to solve the Poisson equation using a spectral finite-difference method. This method uses a computational domain that contains the charged particle beam only and has a computational complexity of O(Nu(logNmode)) , where Nu is the total number of unknowns and Nmode is the maximum number of longitudinal or azimuthal modes. This saves both the computational time and the memory usage of using an artificial boundary condition in a large extended computational domain. The new 3D Poisson solver is parallelized using a message passing interface (MPI) on multi-processor computers and shows a reasonable parallel performance up to hundreds of processor cores.
Satellite Imagery Analysis for Automated Global Food Security Forecasting
NASA Astrophysics Data System (ADS)
Moody, D.; Brumby, S. P.; Chartrand, R.; Keisler, R.; Mathis, M.; Beneke, C. M.; Nicholaeff, D.; Skillman, S.; Warren, M. S.; Poehnelt, J.
2017-12-01
The recent computing performance revolution has driven improvements in sensor, communication, and storage technology. Multi-decadal remote sensing datasets at the petabyte scale are now available in commercial clouds, with new satellite constellations generating petabytes/year of daily high-resolution global coverage imagery. Cloud computing and storage, combined with recent advances in machine learning, are enabling understanding of the world at a scale and at a level of detail never before feasible. We present results from an ongoing effort to develop satellite imagery analysis tools that aggregate temporal, spatial, and spectral information and that can scale with the high-rate and dimensionality of imagery being collected. We focus on the problem of monitoring food crop productivity across the Middle East and North Africa, and show how an analysis-ready, multi-sensor data platform enables quick prototyping of satellite imagery analysis algorithms, from land use/land cover classification and natural resource mapping, to yearly and monthly vegetative health change trends at the structural field level.
Cost-Effectiveness and Cost-Benefit Analysis: Confronting the Problem of Choice.
ERIC Educational Resources Information Center
Clardy, Alan
Cost-effectiveness analysis and cost-benefit analysis are two related yet distinct methods to help decision makers choose the best course of action from among competing alternatives. For both types of analysis, costs are computed similarly. Costs may be reduced to present value amounts for multi-year programs, and parameters may be altered to show…
El Ansari, Walid; Berg-Beckhoff, Gabriele
2017-07-11
Research on healthy behaviour such as physical activity and healthy nutrition and their combination is lacking among university students in Arab countries. The current survey assessed healthy nutrition, and moderate/vigorous physical activity (PA) of 6266 students in Egypt, Libya, and Palestine. We computed a nutrition guideline achievement index using WHO recommendation, as well as the achievement of PA recommendations using guidelines for adults of the American Heart Association guidelines. Latent class regression analysis identified homogenous groups of male and female students, based on their achievements of both guidelines. We examined associations between group membership and achievement of guidelines. A three-class solution model best fitted the data, generating three student Groups: "Healthy Eaters" (7.7% of females, 10.8% of males), "Physically Active" (21.7% of females, 25.8% of males), and "Low Healthy Behaviour" (70.6% of females, 63.4% of males). We did not observe a latent class that exhibited combined healthy behaviours (physically active and healthy eaters), and there were no major differences between countries. We observed a very low rate of healthy nutrition (≈10% of students achieved greater than four of the eight nutrition guidelines), with little gender differences across the countries. About 18-47% of students achieved the PA guidelines, depending on country and gender, more often among males. Few females achieved the PA guidelines, particularly in Libya and Palestine. Culturally adapted multi-behavioural interventions need to encourage healthy lifestyles, nutrition and PA behaviours. National policies need to promote active living while addressing cultural, geographic, and other barriers to young adults' engagement in PA.
El Ansari, Walid; Berg-Beckhoff, Gabriele
2017-01-01
Research on healthy behaviour such as physical activity and healthy nutrition and their combination is lacking among university students in Arab countries. The current survey assessed healthy nutrition, and moderate/vigorous physical activity (PA) of 6266 students in Egypt, Libya, and Palestine. We computed a nutrition guideline achievement index using WHO recommendation, as well as the achievement of PA recommendations using guidelines for adults of the American Heart Association guidelines. Latent class regression analysis identified homogenous groups of male and female students, based on their achievements of both guidelines. We examined associations between group membership and achievement of guidelines. A three-class solution model best fitted the data, generating three student Groups: “Healthy Eaters” (7.7% of females, 10.8% of males), “Physically Active” (21.7% of females, 25.8% of males), and “Low Healthy Behaviour” (70.6% of females, 63.4% of males). We did not observe a latent class that exhibited combined healthy behaviours (physically active and healthy eaters), and there were no major differences between countries. We observed a very low rate of healthy nutrition (≈10% of students achieved greater than four of the eight nutrition guidelines), with little gender differences across the countries. About 18–47% of students achieved the PA guidelines, depending on country and gender, more often among males. Few females achieved the PA guidelines, particularly in Libya and Palestine. Culturally adapted multi-behavioural interventions need to encourage healthy lifestyles, nutrition and PA behaviours. National policies need to promote active living while addressing cultural, geographic, and other barriers to young adults’ engagement in PA. PMID:28696407
DOE Office of Scientific and Technical Information (OSTI.GOV)
McNab, W; Ezzedine, S; Detwiler, R
2007-02-26
Industrial organic solvents such as trichloroethylene (TCE) and tetrachloroethylene (PCE) constitute a principal class of groundwater contaminants. Cleanup of groundwater plume source areas associated with these compounds is problematic, in part, because the compounds often exist in the subsurface as dense nonaqueous phase liquids (DNAPLs). Ganglia (or 'blobs') of DNAPL serve as persistent sources of contaminants that are difficult to locate and remediate (e.g. Fenwick and Blunt, 1998). Current understanding of the physical and chemical processes associated with dissolution of DNAPLs in the subsurface is incomplete and yet is critical for evaluating long-term behavior of contaminant migration, groundwater cleanup, andmore » the efficacy of source area cleanup technologies. As such, a goal of this project has been to contribute to this critical understanding by investigating the multi-phase, multi-component physics of DNAPL dissolution using state-of-the-art experimental and computational techniques. Through this research, we have explored efficient and accurate conceptual and numerical models for source area contaminant transport that can be used to better inform the modeling of source area contaminants, including those at the LLNL Superfund sites, to re-evaluate existing remediation technologies, and to inspire or develop new remediation strategies. The problem of DNAPL dissolution in natural porous media must be viewed in the context of several scales (Khachikian and Harmon, 2000), including the microscopic level at which capillary forces, viscous forces, and gravity/buoyancy forces are manifested at the scale of individual pores (Wilson and Conrad, 1984; Chatzis et al., 1988), the mesoscale where dissolution rates are strongly influenced by the local hydrodynamics, and the field-scale. Historically, the physico-chemical processes associated with DNAPL dissolution have been addressed through the use of lumped mass transfer coefficients which attempt to quantify the dissolution rate in response to local dissolved-phase concentrations distributed across the source area using a volume-averaging approach (Figure 1). The fundamental problem with the lumped mass transfer parameter is that its value is typically derived empirically through column-scale experiments that combine the effects of pore-scale flow, diffusion, and pore-scale geometry in a manner that does not provide a robust theoretical basis for upscaling. In our view, upscaling processes from the pore-scale to the field-scale requires new computational approaches (Held and Celia, 2001) that are directly linked to experimental studies of dissolution at the pore scale. As such, our investigation has been multi-pronged, combining theory, experiments, numerical modeling, new data analysis approaches, and a synthesis of previous studies (e.g. Glass et al, 2001; Keller et al., 2002) aimed at quantifying how the mechanisms controlling dissolution at the pore-scale control the long-term dissolution of source areas at larger scales.« less
Implementing Computer Based Laboratories
NASA Astrophysics Data System (ADS)
Peterson, David
2001-11-01
Physics students at Francis Marion University will complete several required laboratory exercises utilizing computer-based Vernier probes. The simple pendulum, the acceleration due to gravity, simple harmonic motion, radioactive half lives, and radiation inverse square law experiments will be incorporated into calculus-based and algebra-based physics courses. Assessment of student learning and faculty satisfaction will be carried out by surveys and test results. Cost effectiveness and time effectiveness assessments will be presented. Majors in Computational Physics, Health Physics, Engineering, Chemistry, Mathematics and Biology take these courses, and assessments will be categorized by major. To enhance the computer skills of students enrolled in the courses, MAPLE will be used for further analysis of the data acquired during the experiments. Assessment of these enhancement exercises will also be presented.
Radiation Physics for Space and High Altitude Air Travel
NASA Technical Reports Server (NTRS)
Cucinotta, F. A.; Wilson, J. W.; Goldhagen, P.; Saganti, P.; Shavers, M. R.; McKay, Gordon A. (Technical Monitor)
2000-01-01
Galactic cosmic rays (GCR) are of extra-solar origin consisting of high-energy hydrogen, helium, and heavy ions. The GCR are modified by physical processes as they traverse through the solar system, spacecraft shielding, atmospheres, and tissues producing copious amounts of secondary radiation including fragmentation products, neutrons, mesons, and muons. We discuss physical models and measurements relevant for estimating biological risks in space and high-altitude air travel. Ambient and internal spacecraft computational models for the International Space Station and a Mars mission are discussed. Risk assessment is traditionally based on linear addition of components. We discuss alternative models that include stochastic treatments of columnar damage by heavy ion tracks and multi-cellular damage following nuclear fragmentation in tissue.
A Chaos MIMO-OFDM Scheme for Mobile Communication with Physical-Layer Security
NASA Astrophysics Data System (ADS)
Okamoto, Eiji
Chaos communications enable a physical-layer security, which can enhance the transmission security in combining with upper-layer encryption techniques, or can omit the upper-layer secure protocol and enlarges the transmission efficiency. However, the chaos communication usually degrades the error rate performance compared to unencrypted digital modulations. To achieve both physical-layer security and channel coding gain, we have proposed a chaos multiple-input multiple-output (MIMO) scheme in which a rate-one chaos convolution is applied to MIMO multiplexing. However, in the conventional study only flat fading is considered. To apply this scheme to practical mobile environments, i.e., multipath fading channels, we propose a chaos MIMO-orthogonal frequency division multi-plexing (OFDM) scheme and show its effectiveness through computer simulations.
A new predictive multi-zone model for HCCI engine combustion
Bissoli, Mattia; Frassoldati, Alessio; Cuoci, Alberto; ...
2016-06-30
Here, this work introduces a new predictive multi-zone model for the description of combustion in Homogeneous Charge Compression Ignition (HCCI) engines. The model exploits the existing OpenSMOKE++ computational suite to handle detailed kinetic mechanisms, providing reliable predictions of the in-cylinder auto-ignition processes. All the elements with a significant impact on the combustion performances and emissions, like turbulence, heat and mass exchanges, crevices, residual burned gases, thermal and feed stratification are taken into account. Compared to other computational approaches, this model improves the description of mixture stratification phenomena by coupling a wall heat transfer model derived from CFD application with amore » proper turbulence model. Furthermore, the calibration of this multi-zone model requires only three parameters, which can be derived from a non-reactive CFD simulation: these adaptive variables depend only on the engine geometry and remain fixed across a wide range of operating conditions, allowing the prediction of auto-ignition, pressure traces and pollutants. This computational framework enables the use of detail kinetic mechanisms, as well as Rate of Production Analysis (RoPA) and Sensitivity Analysis (SA) to investigate the complex chemistry involved in the auto-ignition and the pollutants formation processes. In the final sections of the paper, these capabilities are demonstrated through the comparison with experimental data.« less
AtomPy: an open atomic-data curation environment
NASA Astrophysics Data System (ADS)
Bautista, Manuel; Mendoza, Claudio; Boswell, Josiah S; Ajoku, Chukwuemeka
2014-06-01
We present a cloud-computing environment for atomic data curation, networking among atomic data providers and users, teaching-and-learning, and interfacing with spectral modeling software. The system is based on Google-Drive Sheets, Pandas (Python Data Analysis Library) DataFrames, and IPython Notebooks for open community-driven curation of atomic data for scientific and technological applications. The atomic model for each ionic species is contained in a multi-sheet Google-Drive workbook, where the atomic parameters from all known public sources are progressively stored. Metadata (provenance, community discussion, etc.) accompanying every entry in the database are stored through Notebooks. Education tools on the physics of atomic processes as well as their relevance to plasma and spectral modeling are based on IPython Notebooks that integrate written material, images, videos, and active computer-tool workflows. Data processing workflows and collaborative software developments are encouraged and managed through the GitHub social network. Relevant issues this platform intends to address are: (i) data quality by allowing open access to both data producers and users in order to attain completeness, accuracy, consistency, provenance and currentness; (ii) comparisons of different datasets to facilitate accuracy assessment; (iii) downloading to local data structures (i.e. Pandas DataFrames) for further manipulation and analysis by prospective users; and (iv) data preservation by avoiding the discard of outdated sets.
Solid oxide fuel cell simulation and design optimization with numerical adjoint techniques
NASA Astrophysics Data System (ADS)
Elliott, Louie C.
This dissertation reports on the application of numerical optimization techniques as applied to fuel cell simulation and design. Due to the "multi-physics" inherent in a fuel cell, which results in a highly coupled and non-linear behavior, an experimental program to analyze and improve the performance of fuel cells is extremely difficult. This program applies new optimization techniques with computational methods from the field of aerospace engineering to the fuel cell design problem. After an overview of fuel cell history, importance, and classification, a mathematical model of solid oxide fuel cells (SOFC) is presented. The governing equations are discretized and solved with computational fluid dynamics (CFD) techniques including unstructured meshes, non-linear solution methods, numerical derivatives with complex variables, and sensitivity analysis with adjoint methods. Following the validation of the fuel cell model in 2-D and 3-D, the results of the sensitivity analysis are presented. The sensitivity derivative for a cost function with respect to a design variable is found with three increasingly sophisticated techniques: finite difference, direct differentiation, and adjoint. A design cycle is performed using a simple optimization method to improve the value of the implemented cost function. The results from this program could improve fuel cell performance and lessen the world's dependence on fossil fuels.
Multi-threaded Event Processing with DANA
DOE Office of Scientific and Technical Information (OSTI.GOV)
David Lawrence; Elliott Wolin
2007-05-14
The C++ data analysis framework DANA has been written to support the next generation of Nuclear Physics experiments at Jefferson Lab commensurate with the anticipated 12GeV upgrade. The DANA framework was designed to allow multi-threaded event processing with a minimal impact on developers of reconstruction software. This document describes how DANA implements multi-threaded event processing and compares it to simply running multiple instances of a program. Also presented are relative reconstruction rates for Pentium4, Xeon, and Opteron based machines.
Introduction to the Space Physics Analysis Network (SPAN)
NASA Technical Reports Server (NTRS)
Green, J. L. (Editor); Peters, D. J. (Editor)
1985-01-01
The Space Physics Analysis Network or SPAN is emerging as a viable method for solving an immediate communication problem for the space scientist. SPAN provides low-rate communication capability with co-investigators and colleagues, and access to space science data bases and computational facilities. The SPAN utilizes up-to-date hardware and software for computer-to-computer communications allowing binary file transfer and remote log-on capability to over 25 nationwide space science computer systems. SPAN is not discipline or mission dependent with participation from scientists in such fields as magnetospheric, ionospheric, planetary, and solar physics. Basic information on the network and its use are provided. It is anticipated that SPAN will grow rapidly over the next few years, not only from the standpoint of more network nodes, but as scientists become more proficient in the use of telescience, more capability will be needed to satisfy the demands.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nadolsky, Pavel M.
2015-08-31
The report summarizes research activities of the project ”Integrated analysis of particle interactions” at Southern Methodist University, funded by 2010 DOE Early Career Research Award DE-SC0003870. The goal of the project is to provide state-of-the-art predictions in quantum chromodynamics in order to achieve objectives of the LHC program for studies of electroweak symmetry breaking and new physics searches. We published 19 journal papers focusing on in-depth studies of proton structure and integration of advanced calculations from different areas of particle phenomenology: multi-loop calculations, accurate long-distance hadronic functions, and precise numerical programs. Methods for factorization of QCD cross sections were advancedmore » in order to develop new generations of CTEQ parton distribution functions (PDFs), CT10 and CT14. These distributions provide the core theoretical input for multi-loop perturbative calculations by LHC experimental collaborations. A novel ”PDF meta-analysis” technique was invented to streamline applications of PDFs in numerous LHC simulations and to combine PDFs from various groups using multivariate stochastic sampling of PDF parameters. The meta-analysis will help to bring the LHC perturbative calculations to the new level of accuracy, while reducing computational efforts. The work on parton distributions was complemented by development of advanced perturbative techniques to predict observables dependent on several momentum scales, including production of massive quarks and transverse momentum resummation at the next-to-next-to-leading order in QCD.« less
Avatar - a multi-sensory system for real time body position monitoring.
Jovanov, E; Hanish, N; Courson, V; Stidham, J; Stinson, H; Webb, C; Denny, K
2009-01-01
Virtual reality and computer assisted physical rehabilitation applications require an unobtrusive and inexpensive real time monitoring systems. Existing systems are usually complex and expensive and based on infrared monitoring. In this paper we propose Avatar, a hybrid system consisting of off-the-shelf components and sensors. Absolute positioning of a few reference points is determined using infrared diode on subject's body and a set of Wii Remotes as optical sensors. Individual body segments are monitored by intelligent inertial sensor nodes iSense. A network of inertial nodes is controlled by a master node that serves as a gateway for communication with a capture device. Each sensor features a 3D accelerometer and a 2 axis gyroscope. Avatar system is used for control of avatars in Virtual Reality applications, but could be used in a variety of augmented reality, gaming, and computer assisted physical rehabilitation applications.
Students' Experience of Synchronous Learning in Distributed Environments
ERIC Educational Resources Information Center
Stewart, Anissa R.; Harlow, Danielle B.; DeBacco, Kim
2011-01-01
This article reports on a two-year ethnographic study of learners participating in multi-site, graduate-level education classes. Classes sometimes met face-to-face in the same physical location; at other times part of the class met physically elsewhere. Yet all were linked through the virtual space. Ethnographic analysis of four data types…
NASA Astrophysics Data System (ADS)
Kuan, Wen-Hsuan; Tseng, Chi-Hung; Chen, Sufen; Wong, Ching-Chang
2016-06-01
We propose an integrated curriculum to establish essential abilities of computer programming for the freshmen of a physics department. The implementation of the graphical-based interfaces from Scratch to LabVIEW then to LabVIEW for Arduino in the curriculum `Computer-Assisted Instrumentation in the Design of Physics Laboratories' brings rigorous algorithm and syntax protocols together with imagination, communication, scientific applications and experimental innovation. The effectiveness of the curriculum was evaluated via statistical analysis of questionnaires, interview responses, the increase in student numbers majoring in physics, and performance in a competition. The results provide quantitative support that the curriculum remove huge barriers to programming which occur in text-based environments, helped students gain knowledge of programming and instrumentation, and increased the students' confidence and motivation to learn physics and computer languages.
Automated quantitative muscle biopsy analysis system
NASA Technical Reports Server (NTRS)
Castleman, Kenneth R. (Inventor)
1980-01-01
An automated system to aid the diagnosis of neuromuscular diseases by producing fiber size histograms utilizing histochemically stained muscle biopsy tissue. Televised images of the microscopic fibers are processed electronically by a multi-microprocessor computer, which isolates, measures, and classifies the fibers and displays the fiber size distribution. The architecture of the multi-microprocessor computer, which is iterated to any required degree of complexity, features a series of individual microprocessors P.sub.n each receiving data from a shared memory M.sub.n-1 and outputing processed data to a separate shared memory M.sub.n+1 under control of a program stored in dedicated memory M.sub.n.
Large scale cardiac modeling on the Blue Gene supercomputer.
Reumann, Matthias; Fitch, Blake G; Rayshubskiy, Aleksandr; Keller, David U; Weiss, Daniel L; Seemann, Gunnar; Dössel, Olaf; Pitman, Michael C; Rice, John J
2008-01-01
Multi-scale, multi-physical heart models have not yet been able to include a high degree of accuracy and resolution with respect to model detail and spatial resolution due to computational limitations of current systems. We propose a framework to compute large scale cardiac models. Decomposition of anatomical data in segments to be distributed on a parallel computer is carried out by optimal recursive bisection (ORB). The algorithm takes into account a computational load parameter which has to be adjusted according to the cell models used. The diffusion term is realized by the monodomain equations. The anatomical data-set was given by both ventricles of the Visible Female data-set in a 0.2 mm resolution. Heterogeneous anisotropy was included in the computation. Model weights as input for the decomposition and load balancing were set to (a) 1 for tissue and 0 for non-tissue elements; (b) 10 for tissue and 1 for non-tissue elements. Scaling results for 512, 1024, 2048, 4096 and 8192 computational nodes were obtained for 10 ms simulation time. The simulations were carried out on an IBM Blue Gene/L parallel computer. A 1 s simulation was then carried out on 2048 nodes for the optimal model load. Load balances did not differ significantly across computational nodes even if the number of data elements distributed to each node differed greatly. Since the ORB algorithm did not take into account computational load due to communication cycles, the speedup is close to optimal for the computation time but not optimal overall due to the communication overhead. However, the simulation times were reduced form 87 minutes on 512 to 11 minutes on 8192 nodes. This work demonstrates that it is possible to run simulations of the presented detailed cardiac model within hours for the simulation of a heart beat.
NASA Technical Reports Server (NTRS)
Hussaini, M. Y. (Editor); Kumar, A. (Editor); Salas, M. D. (Editor)
1993-01-01
The purpose here is to assess the state of the art in the areas of numerical analysis that are particularly relevant to computational fluid dynamics (CFD), to identify promising new developments in various areas of numerical analysis that will impact CFD, and to establish a long-term perspective focusing on opportunities and needs. Overviews are given of discretization schemes, computational fluid dynamics, algorithmic trends in CFD for aerospace flow field calculations, simulation of compressible viscous flow, and massively parallel computation. Also discussed are accerelation methods, spectral and high-order methods, multi-resolution and subcell resolution schemes, and inherently multidimensional schemes.
Comparison of existing digital image analysis systems for the analysis of Thematic Mapper data
NASA Technical Reports Server (NTRS)
Likens, W. C.; Wrigley, R. C.
1984-01-01
Most existing image analysis systems were designed with the Landsat Multi-Spectral Scanner in mind, leaving open the question of whether or not these systems could adequately process Thematic Mapper data. In this report, both hardware and software systems have been evaluated for compatibility with TM data. Lack of spectral analysis capability was not found to be a problem, though techniques for spatial filtering and texture varied. Computer processing speed and data storage of currently existing mini-computer based systems may be less than adequate. Upgrading to more powerful hardware may be required for many TM applications.
Bailey, Sarah F; Scheible, Melissa K; Williams, Christopher; Silva, Deborah S B S; Hoggan, Marina; Eichman, Christopher; Faith, Seth A
2017-11-01
Next-generation Sequencing (NGS) is a rapidly evolving technology with demonstrated benefits for forensic genetic applications, and the strategies to analyze and manage the massive NGS datasets are currently in development. Here, the computing, data storage, connectivity, and security resources of the Cloud were evaluated as a model for forensic laboratory systems that produce NGS data. A complete front-to-end Cloud system was developed to upload, process, and interpret raw NGS data using a web browser dashboard. The system was extensible, demonstrating analysis capabilities of autosomal and Y-STRs from a variety of NGS instrumentation (Illumina MiniSeq and MiSeq, and Oxford Nanopore MinION). NGS data for STRs were concordant with standard reference materials previously characterized with capillary electrophoresis and Sanger sequencing. The computing power of the Cloud was implemented with on-demand auto-scaling to allow multiple file analysis in tandem. The system was designed to store resulting data in a relational database, amenable to downstream sample interpretations and databasing applications following the most recent guidelines in nomenclature for sequenced alleles. Lastly, a multi-layered Cloud security architecture was tested and showed that industry standards for securing data and computing resources were readily applied to the NGS system without disadvantageous effects for bioinformatic analysis, connectivity or data storage/retrieval. The results of this study demonstrate the feasibility of using Cloud-based systems for secured NGS data analysis, storage, databasing, and multi-user distributed connectivity. Copyright © 2017 Elsevier B.V. All rights reserved.
Multi-million atom electronic structure calculations for quantum dots
NASA Astrophysics Data System (ADS)
Usman, Muhammad
Quantum dots grown by self-assembly process are typically constructed by 50,000 to 5,000,000 structural atoms which confine a small, countable number of extra electrons or holes in a space that is comparable in size to the electron wavelength. Under such conditions quantum dots can be interpreted as artificial atoms with the potential to be custom tailored to new functionality. In the past decade or so, these nanostructures have attracted significant experimental and theoretical attention in the field of nanoscience. The new and tunable optical and electrical properties of these artificial atoms have been proposed in a variety of different fields, for example in communication and computing systems, medical and quantum computing applications. Predictive and quantitative modeling and simulation of these structures can help to narrow down the vast design space to a range that is experimentally affordable and move this part of nanoscience to nano-Technology. Modeling of such quantum dots pose a formidable challenge to theoretical physicists because: (1) Strain originating from the lattice mismatch of the materials penetrates deep inside the buffer surrounding the quantum dots and require large scale (multi-million atom) simulations to correctly capture its effect on the electronic structure, (2) The interface roughness, the alloy randomness, and the atomistic granularity require the calculation of electronic structure at the atomistic scale. Most of the current or past theoretical calculations are based on continuum approach such as effective mass approximation or k.p modeling capturing either no or one of the above mentioned effects, thus missing some of the essential physics. The Objectives of this thesis are: (1) to model and simulate the experimental quantum dot topologies at the atomistic scale; (2) to theoretically explore the essential physics i.e. long range strain, linear and quadratic piezoelectricity, interband optical transition strengths, quantum confined stark shift, coherent coupling of electronic states in a quantum dot molecule etc.; (3) to assess the potential use of the quantum dots in real device implementation and to provide physical insight to the experimentalists. Full three dimensional strain and electronic structure simulations of quantum dot structures containing multi-million atoms are done using NEMO 3-D. Both single and vertically stacked quantum dot structures are analyzed in detail. The results show that the strain and the piezoelectricity significantly impact the electronic structure of these devices. This work shows that the InAs quantum dots when placed in the InGaAs quantum well red shifts the emission wavelength. Such InAs/GaAs-based optical devices can be used for optical-fiber based communication systems at longer wavelengths (1.3um -- 1.5um). Our atomistic simulations of InAs/InGaAs/GaAs quantum dots quantitatively match with the experiment and give the critical insight of the physics involved in these structures. A single quantum dot molecule is studied for coherent quantum coupling of electronic states under the influence of static electric field applied in the growth direction. Such nanostructures can be used in the implementation of quantum information technologies. A close quantitative match with the experimental optical measurements allowed us to get a physical insight into the complex physics of quantum tunnel couplings of electronic states as the device operation switches between atomic and molecular regimes. Another important aspect is to design the quantum dots for a desired isotropic polarization of the optical emissions. Both single and coupled quantum dots are studied for TE/TM ratio engineering. The atomistic study provides a detailed physical analysis of these computationally expensive large nanostructures and serves as a guide for the experimentalists for the design of the polarization independent devices for the optical communication systems.
Multi-threaded ATLAS simulation on Intel Knights Landing processors
NASA Astrophysics Data System (ADS)
Farrell, Steven; Calafiura, Paolo; Leggett, Charles; Tsulaia, Vakhtang; Dotti, Andrea; ATLAS Collaboration
2017-10-01
The Knights Landing (KNL) release of the Intel Many Integrated Core (MIC) Xeon Phi line of processors is a potential game changer for HEP computing. With 72 cores and deep vector registers, the KNL cards promise significant performance benefits for highly-parallel, compute-heavy applications. Cori, the newest supercomputer at the National Energy Research Scientific Computing Center (NERSC), was delivered to its users in two phases with the first phase online at the end of 2015 and the second phase now online at the end of 2016. Cori Phase 2 is based on the KNL architecture and contains over 9000 compute nodes with 96GB DDR4 memory. ATLAS simulation with the multithreaded Athena Framework (AthenaMT) is a good potential use-case for the KNL architecture and supercomputers like Cori. ATLAS simulation jobs have a high ratio of CPU computation to disk I/O and have been shown to scale well in multi-threading and across many nodes. In this paper we will give an overview of the ATLAS simulation application with details on its multi-threaded design. Then, we will present a performance analysis of the application on KNL devices and compare it to a traditional x86 platform to demonstrate the capabilities of the architecture and evaluate the benefits of utilizing KNL platforms like Cori for ATLAS production.
NASA Astrophysics Data System (ADS)
Hofierka, Jaroslav; Lacko, Michal; Zubal, Stanislav
2017-10-01
In this paper, we describe the parallelization of three complex and computationally intensive modules of GRASS GIS using the OpenMP application programming interface for multi-core computers. These include the v.surf.rst module for spatial interpolation, the r.sun module for solar radiation modeling and the r.sim.water module for water flow simulation. We briefly describe the functionality of the modules and parallelization approaches used in the modules. Our approach includes the analysis of the module's functionality, identification of source code segments suitable for parallelization and proper application of OpenMP parallelization code to create efficient threads processing the subtasks. We document the efficiency of the solutions using the airborne laser scanning data representing land surface in the test area and derived high-resolution digital terrain model grids. We discuss the performance speed-up and parallelization efficiency depending on the number of processor threads. The study showed a substantial increase in computation speeds on a standard multi-core computer while maintaining the accuracy of results in comparison to the output from original modules. The presented parallelization approach showed the simplicity and efficiency of the parallelization of open-source GRASS GIS modules using OpenMP, leading to an increased performance of this geospatial software on standard multi-core computers.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Song
CFD (Computational Fluid Dynamics) is a widely used technique in engineering design field. It uses mathematical methods to simulate and predict flow characteristics in a certain physical space. Since the numerical result of CFD computation is very hard to understand, VR (virtual reality) and data visualization techniques are introduced into CFD post-processing to improve the understandability and functionality of CFD computation. In many cases CFD datasets are very large (multi-gigabytes), and more and more interactions between user and the datasets are required. For the traditional VR application, the limitation of computing power is a major factor to prevent visualizing largemore » dataset effectively. This thesis presents a new system designing to speed up the traditional VR application by using parallel computing and distributed computing, and the idea of using hand held device to enhance the interaction between a user and VR CFD application as well. Techniques in different research areas including scientific visualization, parallel computing, distributed computing and graphical user interface designing are used in the development of the final system. As the result, the new system can flexibly be built on heterogeneous computing environment, dramatically shorten the computation time.« less
Advances in High-Fidelity Multi-Physics Simulation Techniques
2008-01-01
predictor - corrector method is used to advance the solution in time. 33 x (m) y (m ) 0 1 2 3.00001 0 1 2 3 4 5 40 x 50 Grid 3 Figure 17: Typical...Unclassified c . THIS PAGE Unclassified 17. LIMITATION OF ABSTRACT: SAR 18. NUMBER OF PAGES 60 Datta Gaitonde 19b. TELEPHONE...advanced parallel computing platforms. The motivation to develop high-fidelity algorithms derives from considerations in various areas of current
NASA Astrophysics Data System (ADS)
Bonura, A.; Capizzo, M. C.; Fazio, C.; Guastella, I.
2008-05-01
In this paper we present a pedagogic approach aimed at modeling electric conduction in semiconductors, built by using NetLogo, a programmable modeling environment for building and exploring multi-agent systems. `Virtual experiments' are implemented to confront predictions of different microscopic models with real measurements of electric properties of matter, such as resistivity. The relations between these electric properties and other physical variables, like temperature, are, then, analyzed.
First experience with particle-in-cell plasma physics code on ARM-based HPC systems
NASA Astrophysics Data System (ADS)
Sáez, Xavier; Soba, Alejandro; Sánchez, Edilberto; Mantsinen, Mervi; Mateo, Sergi; Cela, José M.; Castejón, Francisco
2015-09-01
In this work, we will explore the feasibility of porting a Particle-in-cell code (EUTERPE) to an ARM multi-core platform from the Mont-Blanc project. The used prototype is based on a system-on-chip Samsung Exynos 5 with an integrated GPU. It is the first prototype that could be used for High-Performance Computing (HPC), since it supports double precision and parallel programming languages.
2002-03-07
Michalewicz, Eds., Evolutionary Computation 1: Basic Algorithms and Operators, Institute of Physics, Bristol (UK), 2000. [3] David A. Van Veldhuizen ...2000. [4] Carlos A. Coello Coello, David A. Van Veldhuizen , and Gary B. Lamont, Evolutionary Algorithms for Solving Multi-Objective Problems, Kluwer...Academic Publishers, 233 Spring St., New York, NY 10013, 2002. [5] David A. Van Veldhuizen , Multiobjective Evolution- ary Algorithms: Classifications
Multi-Physics Demonstration Problem with the SHARP Reactor Simulation Toolkit
DOE Office of Scientific and Technical Information (OSTI.GOV)
Merzari, E.; Shemon, E. R.; Yu, Y. Q.
This report describes to employ SHARP to perform a first-of-a-kind analysis of the core radial expansion phenomenon in an SFR. This effort required significant advances in the framework Multi-Physics Demonstration Problem with the SHARP Reactor Simulation Toolkit used to drive the coupled simulations, manipulate the mesh in response to the deformation of the geometry, and generate the necessary modified mesh files. Furthermore, the model geometry is fairly complex, and consistent mesh generation for the three physics modules required significant effort. Fully-integrated simulations of a 7-assembly mini-core test problem have been performed, and the results are presented here. Physics models ofmore » a full-core model of the Advanced Burner Test Reactor have also been developed for each of the three physics modules. Standalone results of each of the three physics modules for the ABTR are presented here, which provides a demonstration of the feasibility of the fully-integrated simulation.« less
Mapping university students' epistemic framing of computational physics using network analysis
NASA Astrophysics Data System (ADS)
Bodin, Madelen
2012-06-01
Solving physics problem in university physics education using a computational approach requires knowledge and skills in several domains, for example, physics, mathematics, programming, and modeling. These competences are in turn related to students’ beliefs about the domains as well as about learning. These knowledge and beliefs components are referred to here as epistemic elements, which together represent the students’ epistemic framing of the situation. The purpose of this study was to investigate university physics students’ epistemic framing when solving and visualizing a physics problem using a particle-spring model system. Students’ epistemic framings are analyzed before and after the task using a network analysis approach on interview transcripts, producing visual representations as epistemic networks. The results show that students change their epistemic framing from a modeling task, with expectancies about learning programming, to a physics task, in which they are challenged to use physics principles and conservation laws in order to troubleshoot and understand their simulations. This implies that the task, even though it is not introducing any new physics, helps the students to develop a more coherent view of the importance of using physics principles in problem solving. The network analysis method used in this study is shown to give intelligible representations of the students’ epistemic framing and is proposed as a useful method of analysis of textual data.
Automating quantum experiment control
NASA Astrophysics Data System (ADS)
Stevens, Kelly E.; Amini, Jason M.; Doret, S. Charles; Mohler, Greg; Volin, Curtis; Harter, Alexa W.
2017-03-01
The field of quantum information processing is rapidly advancing. As the control of quantum systems approaches the level needed for useful computation, the physical hardware underlying the quantum systems is becoming increasingly complex. It is already becoming impractical to manually code control for the larger hardware implementations. In this chapter, we will employ an approach to the problem of system control that parallels compiler design for a classical computer. We will start with a candidate quantum computing technology, the surface electrode ion trap, and build a system instruction language which can be generated from a simple machine-independent programming language via compilation. We incorporate compile time generation of ion routing that separates the algorithm description from the physical geometry of the hardware. Extending this approach to automatic routing at run time allows for automated initialization of qubit number and placement and additionally allows for automated recovery after catastrophic events such as qubit loss. To show that these systems can handle real hardware, we present a simple demonstration system that routes two ions around a multi-zone ion trap and handles ion loss and ion placement. While we will mainly use examples from transport-based ion trap quantum computing, many of the issues and solutions are applicable to other architectures.
NASA Astrophysics Data System (ADS)
Peng, Ao-Ping; Li, Zhi-Hui; Wu, Jun-Lin; Jiang, Xin-Yu
2016-12-01
Based on the previous researches of the Gas-Kinetic Unified Algorithm (GKUA) for flows from highly rarefied free-molecule transition to continuum, a new implicit scheme of cell-centered finite volume method is presented for directly solving the unified Boltzmann model equation covering various flow regimes. In view of the difficulty in generating the single-block grid system with high quality for complex irregular bodies, a multi-block docking grid generation method is designed on the basis of data transmission between blocks, and the data structure is constructed for processing arbitrary connection relations between blocks with high efficiency and reliability. As a result, the gas-kinetic unified algorithm with the implicit scheme and multi-block docking grid has been firstly established and used to solve the reentry flow problems around the multi-bodies covering all flow regimes with the whole range of Knudsen numbers from 10 to 3.7E-6. The implicit and explicit schemes are applied to computing and analyzing the supersonic flows in near-continuum and continuum regimes around a circular cylinder with careful comparison each other. It is shown that the present algorithm and modelling possess much higher computational efficiency and faster converging properties. The flow problems including two and three side-by-side cylinders are simulated from highly rarefied to near-continuum flow regimes, and the present computed results are found in good agreement with the related DSMC simulation and theoretical analysis solutions, which verify the good accuracy and reliability of the present method. It is observed that the spacing of the multi-body is smaller, the cylindrical throat obstruction is greater with the flow field of single-body asymmetrical more obviously and the normal force coefficient bigger. While in the near-continuum transitional flow regime of near-space flying surroundings, the spacing of the multi-body increases to six times of the diameter of the single-body, the interference effects of the multi-bodies tend to be negligible. The computing practice has confirmed that it is feasible for the present method to compute the aerodynamics and reveal flow mechanism around complex multi-body vehicles covering all flow regimes from the gas-kinetic point of view of solving the unified Boltzmann model velocity distribution function equation.
Granovsky, Alexander A
2011-06-07
The distinctive desirable features, both mathematically and physically meaningful, for all partially contracted multi-state multi-reference perturbation theories (MS-MR-PT) are explicitly formulated. The original approach to MS-MR-PT theory, called extended multi-configuration quasi-degenerate perturbation theory (XMCQDPT), having most, if not all, of the desirable properties is introduced. The new method is applied at the second order of perturbation theory (XMCQDPT2) to the 1(1)A(')-2(1)A(') conical intersection in allene molecule, the avoided crossing in LiF molecule, and the 1(1)A(1) to 2(1)A(1) electronic transition in cis-1,3-butadiene. The new theory has several advantages compared to those of well-established approaches, such as second order multi-configuration quasi-degenerate perturbation theory and multi-state-second order complete active space perturbation theory. The analysis of the prevalent approaches to the MS-MR-PT theory performed within the framework of the XMCQDPT theory unveils the origin of their common inherent problems. We describe the efficient implementation strategy that makes XMCQDPT2 an especially useful general-purpose tool in the high-level modeling of small to large molecular systems. © 2011 American Institute of Physics
An extraction algorithm of pulmonary fissures from multislice CT image
NASA Astrophysics Data System (ADS)
Tachibana, Hiroyuki; Saita, Shinsuke; Yasutomo, Motokatsu; Kubo, Mitsuru; Kawata, Yoshiki; Niki, Noboru; Nakano, Yasutaka; Sasagawa, Michizo; Eguchi, Kenji; Moriyama, Noriyuki
2005-04-01
Aging and smoking history increases number of pulmonary emphysema. Alveoli restoration destroyed by pulmonary emphysema is difficult and early direction is important. Multi-slice CT technology has been improving 3-D image analysis with higher body axis resolution and shorter scan time. And low-dose high accuracy scanning becomes available. Multi-slice CT image helps physicians with accurate measuring but huge volume of the image data takes time and cost. This paper is intended for computer added emphysema region analysis and proves effectiveness of proposed algorithm.
Nanostructure symmetry: Relevance for physics and computing
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dupertuis, Marc-André; Oberli, D. Y.; Karlsson, K. F.
2014-03-31
We review the research done in recent years in our group on the effects of nanostructure symmetry, and outline its relevance both for nanostructure physics and for computations of their electronic and optical properties. The exemples of C3v and C2v quantum dots are used. A number of surprises and non-trivial aspects are outlined, and a few symmetry-based tools for computing and analysis are shortly presented.
Mogol, Burçe Ataç; Gökmen, Vural
2014-05-01
Computer vision-based image analysis has been widely used in food industry to monitor food quality. It allows low-cost and non-contact measurements of colour to be performed. In this paper, two computer vision-based image analysis approaches are discussed to extract mean colour or featured colour information from the digital images of foods. These types of information may be of particular importance as colour indicates certain chemical changes or physical properties in foods. As exemplified here, the mean CIE a* value or browning ratio determined by means of computer vision-based image analysis algorithms can be correlated with acrylamide content of potato chips or cookies. Or, porosity index as an important physical property of breadcrumb can be calculated easily. In this respect, computer vision-based image analysis provides a useful tool for automatic inspection of food products in a manufacturing line, and it can be actively involved in the decision-making process where rapid quality/safety evaluation is needed. © 2013 Society of Chemical Industry.
Analysis of a Multi-Fidelity Surrogate for Handling Real Gas Equations of State
NASA Astrophysics Data System (ADS)
Ouellet, Frederick; Park, Chanyoung; Rollin, Bertrand; Balachandar, S.
2017-06-01
The explosive dispersal of particles is a complex multiphase and multi-species fluid flow problem. In these flows, the detonation products of the explosive must be treated as real gas while the ideal gas equation of state is used for the surrounding air. As the products expand outward from the detonation point, they mix with ambient air and create a mixing region where both state equations must be satisfied. One of the most accurate, yet computationally expensive, methods to handle this problem is an algorithm that iterates between both equations of state until pressure and thermal equilibrium are achieved inside of each computational cell. This work aims to use a multi-fidelity surrogate model to replace this process. A Kriging model is used to produce a curve fit which interpolates selected data from the iterative algorithm using Bayesian statistics. We study the model performance with respect to the iterative method in simulations using a finite volume code. The model's (i) computational speed, (ii) memory requirements and (iii) computational accuracy are analyzed to show the benefits of this novel approach. Also, optimizing the combination of model accuracy and computational speed through the choice of sampling points is explained. This work was supported by the U.S. Department of Energy, National Nuclear Security Administration, Advanced Simulation and Computing Program as a Cooperative Agreement under the Predictive Science Academic Alliance Program under Contract No. DE-NA0002378.
PREFACE: New trends in Computer Simulations in Physics and not only in physics
NASA Astrophysics Data System (ADS)
Shchur, Lev N.; Krashakov, Serge A.
2016-02-01
In this volume we have collected papers based on the presentations given at the International Conference on Computer Simulations in Physics and beyond (CSP2015), held in Moscow, September 6-10, 2015. We hope that this volume will be helpful and scientifically interesting for readers. The Conference was organized for the first time with the common efforts of the Moscow Institute for Electronics and Mathematics (MIEM) of the National Research University Higher School of Economics, the Landau Institute for Theoretical Physics, and the Science Center in Chernogolovka. The name of the Conference emphasizes the multidisciplinary nature of computational physics. Its methods are applied to the broad range of current research in science and society. The choice of venue was motivated by the multidisciplinary character of the MIEM. It is a former independent university, which has recently become the part of the National Research University Higher School of Economics. The Conference Computer Simulations in Physics and beyond (CSP) is planned to be organized biannually. This year's Conference featured 99 presentations, including 21 plenary and invited talks ranging from the analysis of Irish myths with recent methods of statistical physics, to computing with novel quantum computers D-Wave and D-Wave2. This volume covers various areas of computational physics and emerging subjects within the computational physics community. Each section was preceded by invited talks presenting the latest algorithms and methods in computational physics, as well as new scientific results. Both parallel and poster sessions paid special attention to numerical methods, applications and results. For all the abstracts presented at the conference please follow the link http://csp2015.ac.ru/files/book5x.pdf