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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Inferring microbial co-occurrence networks from amplicon data: a systematic evaluation

Microbes commonly organize into communities consisting of hundreds of species involved in complex interactions with each other. 16S ribosomal RNA (16S rRNA) amplicon profiling provides snapshots that reveal the phylogenies and abundance profiles of these microbial communities. These snapshots, when collected from multiple samples, can reveal the co-occurrence of microbes, providing a glimpse into the network of associations in these communities. However, the inference of networks from 16S data involves numerous steps, each requiring specific tools and parameter choices. Moreover, the extent to which these steps affect the final network is still unclear. In this study, we perform a meticulous analysis of each step of a pipeline that can convert 16S sequencing data into a network of microbial associations. Through this process, we map how different choices of algorithms and parameters affect the co-occurrence network and identify the steps that contribute substantially to the variance. We further determine the tools and parameters that generate robust co-occurrence networks and develop consensus network algorithms based on benchmarks with mock and synthetic data sets. The Microbial Co-occurrence Network Explorer, or MiCoNE (available at https://github.com/segrelab/MiCoNE) follows these default tools and parameters and can help explore the outcome of these combinations of choices on the inferred networks. We envisage that this pipeline could be used for integrating multiple data sets and generating comparative analyses and consensus networks that can guide our understanding of microbial community assembly in different biomes.

16S rRNA↗
NASA NTRS1991

Performance analysis of LAN bridges and routers

Bridges and routers are used to interconnect Local Area Networks (LANs). The performance of these devices is important since they can become bottlenecks in large multi-segment networks. Performance metrics and test methodology for bridges and routers were not standardized. Performance data reported by vendors is not applicable to the actual scenarios encountered in an operational network. However, vendor-provided data can be used to calibrate models of bridges and routers that, along with other models, yield performance data for a network. Several tools are available for modeling bridges and routers - Network II.5 was used. The results of the analysis of some bridges and routers are presented.

Hajare, Ankur R.↗
NASA NTRS1998

Verification of Space Station Secondary Power System Stability Using Design of Experiment

This paper describes analytical methods used in verification of large DC power systems with applications to the International Space Station (ISS). Large DC power systems contain many switching power converters with negative resistor characteristics. The ISS power system presents numerous challenges with respect to system stability such as complex sources and undefined loads. The Space Station program has developed impedance specifications for sources and loads. The overall approach to system stability consists of specific hardware requirements coupled with extensive system analysis and testing. Testing of large complex distributed power systems is not practical due to size and complexity of the system. Computer modeling has been extensively used to develop hardware specifications as well as to identify system configurations for lab testing. The statistical method of Design of Experiments (DoE) is used as an analysis tool for verification of these large systems. DOE reduces the number of computer runs which are necessary to analyze the performance of a complex power system consisting of hundreds of DC/DC converters. DoE also provides valuable information about the effect of changes in system parameters on the performance of the system. DoE provides information about various operating scenarios and identification of the ones with potential for instability. In this paper we will describe how we have used computer modeling to analyze a large DC power system. A brief description of DoE is given. Examples using applications of DoE to analysis and verification of the ISS power system are provided.

Karimi, Kamiar J.↗
DOE OSTI2020

Effect of Anode Porosity and Temperature on the Performance and Lithium Plating During Fast-Charging of Lithium-Ion Cells

Twenty-four single-layer approximate to 32 mAh pouch cells are tested to determine the effect of electrode porosity on lithium plating. Twelve cells contain a graphite electrode that is 26% porous, and 47% for the other twelve. The cells are cycled using a 6-C charge and a C/2 discharge protocol at temperatures in the range of 20-50 degrees C. A macro-homogeneous electrochemical model and microstructure analysis tool set are used to help interpret experimental observations for the effect of anode porosity and ambient temperature on fast-charging performance. Additionally, comparison between the two also highlights gaps in current theoretical understanding that need to be addressed. In post-test examination, lithium plating is seen in all cells, regardless of porosity. Elevated temperature is shown to reduce the amount of lithium plating and improve initial fast-charge capacity, but also changes the rate of other, less well-understood degradation mechanisms. Apparent kinetic rate laws, At + Bt 1/2 , where A and B are constants, can be fit to most of the capacity loss and resistance increase data. The relative magnitudes of A and B change with temperature and porosity. The capacity loss data at 50 degrees C from the high-porosity cells are fit by a logistics rate law.

25 ENERGY STORAGE↗
DOE OSTI2025

Blending Pipeline Analysis Tool for Hydrogen (BlendPATH) Documentation and User Manual

The Blending Pipeline Analysis Tool for Hydrogen (BlendPATH) is a flexible, open-source Python tool designed to provide users with case-by-case analysis capabilities to identify the necessary modifications to repurpose existing natural gas transmission pipeline networks to transport hydrogen as a blend of a user-specified volume fraction of hydrogen or as a pure stream and to estimate the associated capital and operating expenditures resulting from those modifications. This tool is intended to be applied during the initial screening stage of a prospective project when pipeline developers compile transmission pipeline technical documentation and history but prior to performing detailed pipeline inspections. Performing analysis with BlendPATH during this initial screening stage can provide the user with an understanding of promising opportunities and probable economic outcomes of repurposing their pipeline network for hydrogen before proceeding with detailed pipeline materials testing and pipeline inspections. BlendPATH consists of multiple modules to simulate, assess, and modify existing natural gas transmission pipeline network designs to be compatible with hydrogen as a blend or pure stream. The tool employs an open-source gas network hydraulic model to simulate existing, user-specified transmission pipeline networks, and it applies ASME B31.12 to assess the pipe segments within these networks for compatibility with hydrogen and to modify the networks to achieve compatibility where the existing infrastructure is inadequate. Users can specify ASME B31.12 design options for pipeline assessment and can select from multiple methods for pipeline modification. This report details the functionalities of BlendPATH Version 2.0.2 and demonstrates an example of applying BlendPATH to a case study. Potential and intended users of this framework include natural gas pipeline developers and operators and researchers at both public and private institutions. BlendPATH is publicly available at https://github.com/NREL/BlendPATH.

08 HYDROGEN↗
DOE OSTI2018

DESIGN AND EXPERIMENTAL STUDY OF A HIGH PRESSURE AND SUPERCRITICAL METHANE-OXYGEN BURNER

Directly heated supercritical oxy-fuel power cycles have potential to offer a higher thermal efficiency and lower pollutant emissions compared to existing power cycles. Recent thermodynamic analysis of the cycle performed by several groups including the UTEP-Air Liquide research team show that combustion in the vicinity of 300 bar pressure and 1000-1400 K temperature allows for relatively high system efficiencies while operating within the limit of practical combustor materials. However, the realization of directly heated supercritical power cycle requires combustion systems be designed to operate in supercritical conditions and at temperature far below the blowout limit of conventional flames (above 1500 K), where not only the thermodynamic properties but also the combustion properties and kinetics are unexplored. To minimize these knowledge gaps, some intermediate pressure ranges (up to 20 bar) are experimented and modeled using a CFD simulation tool. The knowledge obtained from the high pressure test will assist in understanding the combustion chamber pressurization mechanism, ignition and flame behavior at the elevated pressure. This is a systematic first step in testing at higher pressures of 100 and 300 bar pressures. The primary objective of this dissertation is to perform qualitative analysis on oxy-methane combustion at high pressure (< 20 bar) and compare to CFD model for future scale up to supercritical condition. For modeling of the system, a commercial computational fluid dynamics simulation tool, ANSYS Fluent, is used. The inlet conditions for the CFD analysis are obtained from the experiments. The geometry used for the study is same as the test apparatus and operates at the same power ratings. The expertise gained from this experimental study is important to accurately and safely design combustors at elevated pressures up to 300bar. A high pressure methane-oxygen fuel burner and combustor have been developed to accommodate oxycombustion environment. A detailed CFD analysis is conducted to understand the flame length and cooling phenomenon inside the combustor first at pressures up to 20 bar to compare to experiments then at supercritical pressure. The first part of the dissertation compares CFD results with high pressure burner experiments at pressures up to 20 bar. The test is conducted for 30 s within 150 kW – 250 kW thermal power inputs. Afterwards, based on the simulation results a cooling system is proposed for steady state high pressure combustion experiments. It is observed from the experimental study that the proposed pressurization mechanism able to pressurize the vessel up to 20 bar. It is also determined that the current combustor can operate up to 20 bar for short term. The steady state CFD simulation demonstrates that a cooling system must be incorporated for continuous operation. Additionally, the study focuses on the ignition delay due to added diluent during the combustion process. It is observed that as the carbon dioxide recirculation ratio increases the ignition delay time increases. Later part of the dissertation provides a preliminary guideline for developing a laboratory scale supercritical oxy combustor. The employment of supercritical fluid in gas turbine is fairly a new concept. Hence, there are many questions that need to be answered. During this dissertation study an investigation is performed to understand the impact of equation of state in the supercritical combustion simulation. Finally, a CFD model for developing supercritical oxy-methane burner and the combustor, incorporating real gas model, is presented. Although Lee-Kesler equation of state provides better accuracy than Peng Robinson, due to the computational time Peng Robinson equation of state is used for the simulation. It is found that existing knowledge is not enough to simulate combustion at supercritical phase. Detailed combustion chemistry at the supercritical condition must be developed and should be incorporated to accurately replicate the combustion phenomenon.

Chowdhury, ASM Arifur Rahim↗
DOE OSTI2018

Hydrologic Model Analyses for Decision Support at the Los Alamos National Laboratory Site - 18363

Modeling hydrologic flow and transport in the subsurface presents a number of challenges including large datasets that contain limited information about the properties of the subsurface and models with a large number of parameters characterizing the properties of the subsurface and the ambient hydrologic conditions (e.g., groundwater recharge). This, in turn, leads to substantial uncertainty in predictions about quantities of interest (e.g., the concentration of a contaminant at points of compliance). We present a number of methods and tools that have recently been developed to address these problems. The model calibration tools are capable of assimilating large datasets (for example, on the order of 1,000,000 model calibration targets) into numerical models, calibrating models with a large number of model parameters (on the order of 1,000,000), or both. These tools leverage recently developed methods in numerical linear algebra such as matrix-free methods and randomized matrix sketching. The uncertainty quantification tools are highly-parallel and enable us to robustly quantify the uncertainties in model parameters (and therefore uncertainty in quantities of interest). Having these capabilities in model analysis tools enables more informed decision making related to remediation of groundwater contaminants. The model analyses that we present are related to the Los Alamos National Laboratory (LANL) chromium site. The analyses are performed by MADS (Model Analysis and Decision Support; http://mads.lanl.gov). (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Open-source framework for power system transmission and distribution dynamics co-simulation

The promise of the smart grid entails more interactions between the transmission and distribution networks, and there is an immediate need for tools to provide the comprehensive modelling and simulation required to integrate operations at both transmission and distribution levels. Existing electromagnetic transient simulators can perform simulations with integration of transmission and distribution systems, but the computational burden is high for large-scale system analysis. For transient stability analysis, currently there are only separate tools for simulating transient dynamics of the transmission and distribution systems. In this paper, we introduce an open source co-simulation framework “Framework for Network Co-Simulation” (FNCS), together with the decoupled simulation approach that links existing transmission and distribution dynamic simulators through FNCS. FNCS is a middleware interface and framework that manages the interaction and synchronization of the transmission and distribution simulators. Preliminary testing results show the validity and capability of the proposed open-source co-simulation framework and the decoupled co-simulation methodology.

Huang, Renke↗
DOE OSTI2017

Parallel peak pruning for scalable SMP contour tree computation

As data sets grow to exascale, automated data analysis and visualisation are increasingly important, to intermediate human understanding and to reduce demands on disk storage via in situ analysis. Trends in architecture of high performance computing systems necessitate analysis algorithms to make effective use of combinations of massively multicore and distributed systems. One of the principal analytic tools is the contour tree, which analyses relationships between contours to identify features of more than local importance. Unfortunately, the predominant algorithms for computing the contour tree are explicitly serial, and founded on serial metaphors, which has limited the scalability of this form of analysis. While there is some work on distributed contour tree computation, and separately on hybrid GPU-CPU computation, there is no efficient algorithm with strong formal guarantees on performance allied with fast practical performance. Here in this paper, we report the first shared SMP algorithm for fully parallel contour tree computation, withfor-mal guarantees of O(lgnlgt) parallel steps and O(n lgn) work, and implementations with up to 10x parallel speed up in OpenMP and up to 50x speed up in NVIDIA Thrust.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Scalable Contour Tree Computation by Data Parallel Peak Pruning

As data sets grow to exascale, automated data analysis and visualization are increasingly important, to intermediate human understanding and to reduce demands on disk storage via in situ analysis. Trends in architecture of high performance computing systems necessitate analysis algorithms to make effective use of combinations of massively multicore and distributed systems. One of the principal analytic tools is the contour tree, which analyses relationships between contours to identify features of more than local importance. Unfortunately, the predominant algorithms for computing the contour tree are explicitly serial, and founded on serial metaphors, which has limited the scalability of this form of analysis. While there is some work on distributed contour tree computation, and separately on hybrid GPU-CPU computation, there is no efficient algorithm with strong formal guarantees on performance allied with fast practical performance. Furthermore, we report the first shared SMP algorithm for fully parallel contour tree computation, with formal guarantees of O(lg V lg t) parallel steps and O(V lg V) work for data with V samples and t contour tree supernodes, and implementations with more than 30× parallel speed up on both CPU using TBB and GPU using Thrust and up 70× speed up compared to the serial sweep and merge algorithm.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2006

Tools to Support Human Factors and Systems Engineering Interactions During Early Analysis

We describe an approach and existing software tool support for effective interactions between human factors engineers and systems engineers in early analysis activities during system acquisition. We examine the tasks performed during this stage, emphasizing those tasks where system engineers and human engineers interact. The Concept of Operations (ConOps) document is an important product during this phase, and particular attention is paid to its influences on subsequent acquisition activities. Understanding this influence helps ConOps authors describe a complete system concept that guides subsequent acquisition activities. We identify commonly used system engineering and human engineering tools and examine how they can support the specific tasks associated with system definition. We identify possible gaps in the support of these tasks, the largest of which appears to be creating the ConOps document itself. Finally, we outline the goals of our future empirical investigations of tools to support system concept definition.

Thronesbery, Carroll↗
NASA NTRS2005

Tools to Support Human Factors and Systems Engineering Interactions During Early Analysis

We describe an approach and existing software tool support for effective interactions between human factors engineers and systems engineers in early analysis activities during system acquisition. We examine the tasks performed during this stage, emphasizing those tasks where system engineers and human engineers interact. The Concept of Operations (ConOps) document is an important product during this phase, and particular attention is paid to its influences on subsequent acquisition activities. Understanding this influence helps ConOps authors describe a complete system concept that guides subsequent acquisition activities. We identify commonly used system engineering and human engineering tools and examine how they can support the specific tasks associated with system definition. We identify possible gaps in the support of these tasks, the largest of which appears to be creating the ConOps document itself. Finally, we outline the goals of our future empirical investigations of tools to support system concept definition.

Thronesbery, Carroll↗
NASA NTRS2008

25th Space Simulation Conference. Environmental Testing: The Earth-Space Connection

Topics covered include: Methods of Helium Injection and Removal for Heat Transfer Augmentation; The ESA Large Space Simulator Mechanical Ground Support Equipment for Spacecraft Testing; Temperature Stability and Control Requirements for Thermal Vacuum/Thermal Balance Testing of the Aquarius Radiometer; The Liquid Nitrogen System for Chamber A: A Change from Original Forced Flow Design to a Natural Flow (Thermo Siphon) System; Return to Mercury: A Comparison of Solar Simulation and Flight Data for the MESSENGER Spacecraft; Floating Pressure Conversion and Equipment Upgrades of Two 3.5kw, 20k, Helium Refrigerators; Affect of Air Leakage into a Thermal-Vacuum Chamber on Helium Refrigeration Heat Load; Special ISO Class 6 Cleanroom for the Lunar Reconnaissance Orbiter (LRO) Project; A State-of-the-Art Contamination Effects Research and Test Facility Martian Dust Simulator; Cleanroom Design Practices and Their Influence on Particle Counts; Extra Terrestrial Environmental Chamber Design; Contamination Sources Effects Analysis (CSEA) - A Tool to Balance Cost/Schedule While Managing Facility Availability; SES and Acoustics at GSFC; HST Super Lightweight Interchangeable Carrier (SLIC) Static Test; Virtual Shaker Testing: Simulation Technology Improves Vibration Test Performance; Estimating Shock Spectra: Extensions beyond GEVS; Structural Dynamic Analysis of a Spacecraft Multi-DOF Shaker Table; Direct Field Acoustic Testing; Manufacture of Cryoshroud Surfaces for Space Simulation Chambers; The New LOTIS Test Facility; Thermal Vacuum Control Systems Options for Test Facilities; Extremely High Vacuum Chamber for Low Outgassing Processing at NASA Goddard; Precision Cleaning - Path to Premier; The New Anechoic Shielded Chambers Designed for Space and Commercial Applications at LIT; Extraction of Thermal Performance Values from Samples in the Lunar Dust Adhesion Bell Jar; Thermal (Silicon Diode) Data Acquisition System; Aquarius's Instrument Science Data System (ISDS) Automated to Acquire, Process, Trend Data and Produce Radiometric System Assessment Reports; Exhaustive Thresholds and Resistance Checkpoints; Reconfigurable HIL Testing of Earth Satellites; FPGA Control System for the Automated Test of MicroShutters; Ongoing Capabilities and Developments of Re-Entry Plasma Ground Tests at EADS-ASTRIUM; Operationally Responsive Space Standard Bus Battery Thermal Balance Testing and Heat Dissipation Analysis; Galileo - The Serial-Production AIT Challenge; The Space Systems Environmental Test Facility Database (SSETFD), Website Development Status; Simulated Reentry Heating by Torching; Micro-Vibration Measurements on Thermally Loaded Multi-Layer Insulation Samples in Vacuum; High Temperature Life Testing of 80Ni-20Cr Wire in a Simulated Mars Atmosphere for the Sample Analysis at Mars (SAM) Instrument Suit Gas Processing System (GPS) Carbon Dioxide Scrubber; The Planning and Implementation of Test Facility Improvements; and Development of a Silicon Carbide Molecular Beam Nozzle for Simulation Planetary Flybys and Low-Earth Orbit.

Packard, Edward↗
NASA NTRS2026

Development of the METMAN Thermal Desktop Human Model for System Integration

Human thermal analysis and model development inform NASA’s space suit development, vehicle/habitat design, and survivability studies. Historically, human thermal models such as the 41-node metabolic man (METMAN) and the Wissler model have been standalone software tools developed with FORTRAN, a programming language known for its high performance in computationally intensive applications. Though efficient, these standalone programs pose challenges to coupled human-system analysis with detailed life support and thermal control subsystem models in other commercial software. This paper describes the conversion of the METMAN human thermal model from a standalone FORTRAN program to a model in Thermal Desktop (Ansys), a commonly used CAD-based simulation software for engineering that specializes in heat transfer, thermal radiation, and fluid flow analysis. This format was chosen to best facilitate model sharing and compatibility, enabling the direct integration of METMAN human thermal analysis with subsystem models across NASA programs and commercial partners.

Elizabeth Thurston↗
NASA NTRSDate not supplied

DLES Unreal Simulation Tool (DUST)

NASA’s future Artemis missions to the Moon seek to explore areas around the Lunar South Pole. Though humans have previously set foot on the lunar surface, the proposed region provides unique and challenging environments that require insight and investigation prior to arrival. Several teams throughout the agency are performing this site and mission planning, design, and analysis to support areas like the Human Landing System (HLS), surface mobility, habitation elements, and scientific exploration. The NASA Exploration Systems Simulation (NExSyS) team at Johnson Space Center is developing a graphical environment of the Lunar South Pole region. Lunar terrain information collected from the Lunar Reconnaissance Orbiter (LRO) is compiled and made available through Johnson Space Center’s Digital Lunar Exploration Sites (DLES) data sets. The DLES data is used to build this graphic environment. The process of ingesting and accurately modeling this information in a meaningful way for analysis creates its own challenges such as generating a performant model from the source data and the application of curvature. Additionally, the area around the Lunar South Pole experiences different lighting conditions than those observed from the Apollo missions. The need to use the lunar environmental data products provided by DLES combined with the capability to calculate date specific ephemerides in real-time has given rise to the development of the DLES Unreal Simulation Tool (DUST). DUST incorporates augmented terrain from the DLES product into a desktop application that allows exploration of the Lunar South Pole region and its complex lighting conditions. DUST leverages advanced capabilities in the recently released Unreal Engine 5 renderer by Epic Games such as double precision for positioning of planetary bodies and surface elements, multiple infinite light sources to represent the Sun and eventually Earthshine, high resolution shadow maps for dynamic shadow accuracy, real-time software ray-tracing for multi-surface bounce lighting to render sunlight reflected off surface elements and terrain features, and performance optimized level of detail shifting as the eyepoint changes in a scene. This paper details the DUST application, the technologies of the engine platform that enable scientific and engineering analysis, the unique techniques and processes developed to consume the DLES data sets, and how the tool is being used to support the Artemis program.

Lunar Visualization↗
DOE OSTI2024

Sensitivity Analysis of Irradiated Fueled Experiments using the MOOSE Framework [Slides]

Modeling and simulation (M&S) methods are able to predict uncertainties in experimental parameters (e.g., power and fission density) during irradiation. A shortfall exists in predicting how sensitive some of the parameters will behave during the experimental process. Sensitivity and Uncertainty Quantification (SUQ) is critical in support of qualification and licensing reactor fuels. The application of a method to quantify the uncertainty in these experiments is critical to the prediction of their performance. In this work, we propose the use of a polynomial chaos expansion (PCE) method to quantify the sensitive parameters in these simulations and, in an extension, their experimental surrogates. We propose to perform M&S using PCE uncertainty quantification on a previously irradiated fueled experiment in order to provide a validation case for Griffin and expand its use as a verification and validation (V&V) tool for experiments with a neutronics component. Griffin is an advanced, deterministic neutronics analysis code built using the MOOSE (multiphysics object-oriented simulation environment) framework which can provide state-of-the-art neutronic analysis on M&S of experiments. We will use the stochastic tools module (STM) in MOOSE to provide PCE uncertainty quantification on the proposed experimental setup. Idaho National Laboratory (INL) does not yet have an in-house developed code with V&V approval for experiments performed on-site; this work would provide a necessary addition of support for experiments performed at INL. The Nuclear Regulatory Commission (NRC) has explicitly requested uncertainties in calculated values such as fuel power and burnup, and the development of this capability would benefit the relationship between INL and the NRC.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Institute for Sustained Performance, Energy, and Resilience (SuPER)

The University of Tennessee (UTK) and University of Texas at El Paso (UTEP) partnership supported the three main thrusts of the SUPER project---performance, energy, and resilience. The UTK-UTEP effort thus helped advance the main goal of SUPER, which was to ensure that DOE's computational scientists can successfully exploit the emerging generation of high performance computing (HPC) systems. This goal is being met by providing application scientists with strategies and tools to productively maximize performance, conserve energy, and attain resilience. The primary vehicle through which UTK provided performance measurement support to SUPER and the larger HPC community is the Performance Application Programming Interface (PAPI). PAPI is an ongoing project that provides a consistent interface and methodology for collecting hardware performance information from various hardware and software components, including most major CPUs, GPUs and accelerators, interconnects, I/O systems, and power interfaces, as well as virtual cloud environments. The PAPI software is widely used for performance modeling of scientific and engineering applications---for example, the HOMME (High Order Methods Modeling Environment) climate code, and the GAMESS and NWChem computational chemistry codes---on DOE supercomputers. PAPI is widely deployed as middleware for use by higher-level profiling, tracing, and sampling tools (e.g., CrayPat, HPCToolkit, Scalasca, Score-P, TAU, Vampir, PerfExpert), making it the de facto standard for hardware counter analysis. PAPI has established itself as fundamental software infrastructure in every application domain (spanning academia, government, and industry), where improving performance can be mission critical. Ultimately, as more application scientists migrate their applications to HPC platforms, they will benefit from the extended capabilities this grant brought to PAPI to analyze and optimize performance in these environments, whether they use PAPI directly, or via third-party performance tools. Capabilities added to PAPI through this grant include support for new architectures such as the lastest GPU and Xeon Phi accelerators, and advanced power measurement and management features. Another important topic for the UTK team was providing support for a rich ecosystem of different fault management strategies in the context of parallel computing. Our long term efforts have been oriented toward proposing flexible strategies and providing building boxes that application developers can use to build the most efficient fault management technique for their application. These efforts span across the entire software spectrum, from theoretical models of existing strategies to easily assess their performance, to algorithmic modifications to take advantage of specific mathematical properties for data redundancy and to extensions to widely used programming paradigms to empower the application developers to deal with all types of faults. We have also continued our tight collaborations with users to help them adopt these technologies to ensure their application always deliver meaningful scientific data. Large supercomputer systems are becoming more and more power and energy constrained, and future systems and applications running on them will need to be optimized to run under power caps and/or minimize energy consumption. The UTEP team contributed to the SUPER energy thrust by developing power modeling methodologies and investigating power management strategies. Scalability modeling results showed that some applications can scale better with respect to an increasing power budget than with respect to only the number of processors. Power management, in particular shifting power to processors on the critical path of an application execution, can reduce perturbation due to system noise and other sources of runtime variability, which are growing problems on large-scale power-constrained computer systems.

42 ENGINEERING↗
NASA NTRS1987

Use of computer graphics for visualization of flow fields

A high-performance graphics workstation has been combined with software developed for flow-field visualization to yield a highly effective tool for analysis of fluid-flow dynamics. After the flow fields are obtained from experimental measurements or computer simulations, the workstation permits one to interactively view the dynamics of the flow fields; e.g., the viewer can zoom into a region or rotate his viewing position about the region to study it in more detail. Several techniques for visualization of flow fields with this workstation are described in this paper and illustrated with a videotape available from the authors. The computer hardware and software required to create effective flow visualization displays are discussed. Additional software and hardware required to create videotapes or 16mm movies are also described. Limitations imposed by current workstation performance is addressed and future workstation performance is forecast.

Watson, Val↗