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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Effective Exploration of New 760°C-Capability Steels for Coal Energy

Cost effective and high performance alloys that are capable of operating at 760 °C or higher for extended periods of time under a very aggressive environment are critically required for the design and development of advanced ultrasupercritical (AUSC) boilers and steam turbines. Finely dispersed Laves phase precipitates have been shown by Takeyama and co-workers to be a viable strengthening mechanism in high temperature austenitic steels. There is currently no straightforward theory that can predict what other intermetallic phases can serve as potent precipitation-strengthening phases for steels; thus we employed a highly effective dual-anneal diffusion multiple (DADM) approach to screen for viable strengthening precipitates over a wide range of compositions. From the Fe-Co-Cr-Ni-Mo DADMs, the Fe-Cr-Mo based Chi phase was identified as a new strengthening phase for high temperature ferritic steels; and from the Fe-Mn-Cr-Nb-Ni-Mo-FeAl DADMs, the Laves phase was identified as a viable strengthening precipitate in Fe-Mn and Fe-Ni based austenitic steels. After identification of viable strengthening phases from the DADMs that covered compositions in the basic ternary and quaternary systems, we employed computation thermodynamics to perform multicomponent alloy design and optimization. For the new the Chi-phase strengthened steels, we performed thermodynamic calculations to vary the volume fraction of the Chi phase and introduced Nb and carbon to promote the formation of stable carbides for grain size control during solution heat treatment. For the Fe-Ni-Mn based austenitic steels, we performed extensive parametric optimization of compositions in order to reduce the expensive Ni content, add Cr and Al for oxidation resistance, and balance the alloying contents (Ni, Mn, Cr, Al, Mo) to suppress the ferritic phase and promote the austenitic matrix phase. Four steels (two ferritic + two austenitic) were designed and tested. The two Chi-phase strengthened ferritic steels exhibited excellent oxidation resistance and good creep-rupture strength at moderate temperatures, considering their ferritic matrix that usually results in lower creep resistance than austenitic steels. These steels showed brittleness and sample-to-sample variability in ductility. The low ductility might be due to the macro segregation during solidification or the significant grain growth during the solution heat treatments. We believe there is no inherent brittleness based on the chemistry of the steels. The creep-rupture performance of the steels is comparable to the 9Cr steels. Due to their ferritic matrix, the new Chi-phase strengthened ferritic steels may not be suited for the 760 °C AUSC applications, but they are very good candidates for intermediate temperature applications due to their outstanding oxidation resistance and high strength. Further study is required to find the source of low and highly variable ductility. We believe the compositions of the Chi-phase strengthened steels are not inherently brittle. The Chi-phase strengthened ferritic steels may also be excellent candidates for intermediate-temperature and room-temperature cast stainless steels, thus we highly recommend further investigations. The two Mn-containing austenitic steels based on the Laves phase showed good ductility, excellent oxidation resistance (slightly inferior to the two ferritic steels) at high temperatures and moderate creep strength. The creep-strength of the two austenitic steels based on the Larson-Miller parameters is higher than that of the traditional 316 stainless steels, but lower than the alumina-forming alloys (AFAs) developed at Oak Ridge National Laboratories. We do not recommend high priority in further studying these compositions unless higher Cr alloys are required for hot-corrosion resistance.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2014

Parallel computation safety analysis irradiation targets fission product molybdenum in neutronic aspect using the successive over-relaxation algorithm

One of the research activities in support of commercial radioisotope production program is a safety research on target FPM (Fission Product Molybdenum) irradiation. FPM targets form a tube made of stainless steel which contains nuclear-grade high-enrichment uranium. The FPM irradiation tube is intended to obtain fission products. Fission materials such as Mo{sup 99} used widely the form of kits in the medical world. The neutronics problem is solved using first-order perturbation theory derived from the diffusion equation for four groups. In contrast, Mo isotopes have longer half-lives, about 3 days (66 hours), so the delivery of radioisotopes to consumer centers and storage is possible though still limited. The production of this isotope potentially gives significant economic value. The criticality and flux in multigroup diffusion model was calculated for various irradiation positions and uranium contents. This model involves complex computation, with large and sparse matrix system. Several parallel algorithms have been developed for the sparse and large matrix solution. In this paper, a successive over-relaxation (SOR) algorithm was implemented for the calculation of reactivity coefficients which can be done in parallel. Previous works performed reactivity calculations serially with Gauss-Seidel iteratives. The parallel method can be used to solve multigroup diffusion equation system and calculate the criticality and reactivity coefficients. In this research a computer code was developed to exploit parallel processing to perform reactivity calculations which were to be used in safety analysis. The parallel processing in the multicore computer system allows the calculation to be performed more quickly. This code was applied for the safety limits calculation of irradiated FPM targets containing highly enriched uranium. The results of calculations neutron show that for uranium contents of 1.7676 g and 6.1866 g (× 10{sup 6} cm{sup −1}) in a tube, their delta reactivities are the still within safety limits; however, for 7.9542 g and 8.838 g (× 10{sup 6} cm{sup −1}) the limits were exceeded.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS1990

ISIS and META projects

The ISIS project has developed a new methodology, virtual synchony, for writing robust distributed software. High performance multicast, large scale applications, and wide area networks are the focus of interest. Several interesting applications that exploit the strengths of ISIS, including an NFS-compatible replicated file system, are being developed. The META project is distributed control in a soft real-time environment incorporating feedback. This domain encompasses examples as diverse as monitoring inventory and consumption on a factory floor, and performing load-balancing on a distributed computing system. One of the first uses of META is for distributed application management: the tasks of configuring a distributed program, dynamically adapting to failures, and monitoring its performance. Recent progress and current plans are reported.

Birman, Kenneth↗
DOE OSTI2021

Performance Analysis of PIConGPU: Particle-in-Cell on GPUs using NVIDIA’s NSight Systems and NSight Compute

PIConGPU, Particle In Cell on GPUs, is an open source simulations framework for plasma and laser-plasma physics used to develop advanced particle accelerators for radiation therapy of cancer, high energy physics and photon science. While PIConGPU has been optimized for at least 5 years to run well on NVIDIA GPU-based clusters, there has been limited exploration by the development team of potential scalability bottlenecks using recently updated and new tools including NVIDIA’s NVProf tool and the brand-new NVIDIA NSight Suite (Systems and Compute) tools. PIConGPU is a highly optimized application that runs production jobs at scale on a system Oak Ridge Leadership Facility’s (OLCF) Summit supercomputer (using the full machine at 4600 nodes; at 98% of GPU utilization on all ~28000 NVIDIA Volta GPUs). PIConGPU has been selected as one of the the eight applications for OLCF’s coveted Center for Accelerated Application Readiness (CAAR) program aimed at the facility’s Frontier supercomputer (OLCF’s first exascale system to launch in 2021), to partner with our vendors (primary vendors: AMD and Cray/HPE) ensuring that Frontier will be able to perform large-scale science when it opens to users in 2022. To this effect, performance engineers on the PIConGPU team wanted to dive deep into the application to understand at the finest granularity, which portions of the code could be further optimized to exploit the hardware on Summit at it’s maximum potential and also to elucidate which key kernels should be tracked and optimized for the CAAR effort to port this code to Frontier. Any bottlenecks that are observed via performance profiling on Summit are likely to also impact scalability on the Frontier-dev system and the Frontier Early Access (EA) system. Additionally, the engineers wanted to take a closer look at the newest NVIDIA profiling tools which allows us to identify the most useful features on these tools and will provide an opportunity to compare it to new AMD and Cray’s performance analysis tool releases and provide feedback to our vendor partners on what features are most important and mission critical for CAAR efforts. The primary goal of this report is to focus on the evaluation of PIConGPU’s most time-intensive kernels using NVProf and NSight Suite. Three kernels, Current Deposition (also known as Compute Current), Particle Push (Move and Mark), and Shift Particles are known to be some of the most time-consuming kernels in PIConGPU. The Current xi Deposition kernel and Particle Push kernel both set up the particle attributes for running any physics simulation with PIConGPU, so it is crucial to improve the performance of these two kernels. In this report, we measure single GPU metrics for the three kernels, offer high level takeaways from the conducted analysis, and compare the profiling data from NSight Compute to that of NVProf. This analysis was performed using a grid size of 240 x 272 x 224, and 10 time steps with the Mid-November Figure of Merit (FOM) run setup. The Traveling Wave Electron Acceleration (TWEAC) science case used in this run is a representative science case for PIConGPU. This execution can also be used for baseline analysis on AMD MI50/ MI60 systems. As of the time of writing, the PIConGPU application has limited use for features of NSight Systems, so this report will mainly focus on insights garnered from NSight Compute. For this analysis, we run the “full” metric set available in NSight Compute version 2020.1.2 and use NSight Systems version 2020.3.1 to generate the application timeline.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

rvGAHP: push-based job submission using reverse SSH connections. In: WORKS '17 Proceedings of the 12th Workshop on Workflows in Support of Large-Scale Science, Article No. 3

Computational science researchers running large-scale scientific workflow applications often want to run their workflows on the largest available compute systems to improve time to solution. Workflow tools used in distributed, heterogeneous, high performance computing environments typically rely on either a push-based or a pull-based approach for resource provisioning from these compute systems. However, many large clusters have moved to two-factor authentication for job submission, making traditional automated push-based job submission impossible. On the other hand, pull-based approaches such as pilot jobs may lead to increased complexity and a reduction in node-hour efficiency. In this paper, we describe a new, efficient approach based on HTCondor-G called reverse GAHP (rvGAHP) that allows us to push jobs using reverse SSH submissions with better efficiency than pull-based methods. We successfully used this approach to perform a large probabilistic seismic hazard analysis study using SCEC's CyberShake workflow in March 2017 on the Titan Cray XK7 hybrid system at Oak Ridge National Laboratory.

Callaghan, Scott↗
DOE OSTI2014

Store-operate-coherence-on-value

A system, method and computer program product for performing various store-operate instructions in a parallel computing environment that includes a plurality of processors and at least one cache memory device. A queue in the system receives, from a processor, a store-operate instruction that specifies under which condition a cache coherence operation is to be invoked. A hardware unit in the system runs the received store-operate instruction. The hardware unit evaluates whether a result of the running the received store-operate instruction satisfies the condition. The hardware unit invokes a cache coherence operation on a cache memory address associated with the received store-operate instruction if the result satisfies the condition. Otherwise, the hardware unit does not invoke the cache coherence operation on the cache memory device.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Quantum computing and preconditioners for hydrological linear systems

Modeling hydrological fracture networks is a hallmark challenge in computational earth sciences. Accurately predicting critical features of fracture systems, e.g. percolation, can require solving large linear systems far beyond current or future high performance capabilities. Quantum computers can theoretically bypass the memory and speed constraints faced by classical approaches, however several technical issues must first be addressed. Chief amongst these difficulties is that such systems are often ill-conditioned, i.e. small changes in the system can produce large changes in the solution, which can slow down the performance of linear solving algorithms. We test several existing quantum techniques to improve the condition number, but find they are insufficient. We then introduce the inverse Laplacian preconditioner, which improves the scaling of the condition number of the system from O(N) to O($\sqrt{N}$) and admits a quantum implementation. These results are a critical first step in developing a quantum solver for fracture systems, both advancing the state of hydrological modeling and providing a novel real-world application for quantum linear systems algorithms.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1974

A computer simulation of Skylab dynamics and attitude control for performance verification and operational support

A simulation of the Skylab attitude and pointing control system (APCS) is outlined and discussed. Implementation is via a large hybrid computer and includes those factors affecting system momentum management, propellant consumption, and overall vehicle performance. The important features of the flight system are discussed; the mathematical models necessary for this treatment are outlined; and the decisions involved in implementation are discussed. A brief summary of the goals and capabilities of this tool is also included.

Buchanan, H.↗
NASA NTRS2004

HEC Applications on Columbia Project

NASA's Columbia system consists of a cluster of twenty 512 processor SGI Altix systems. Each of these systems is 3 TFLOP/s in peak performance - approximately the same as the entire compute capability at NAS just one year ago. Each 512p system is a single system image machine with one Linunx O5, one high performance file system, and one globally shared memory. The NAS Terascale Applications Group (TAG) is chartered to assist in scaling NASA's mission critical codes to at least 512p in order to significantly improve emergency response during flight operations, as well as provide significant improvements in the codes. and rate of scientific discovery across the scientifc disciplines within NASA's Missions. Recent accomplishments are 4x improvements to codes in the ocean modeling community, 10x performance improvements in a number of computational fluid dynamics codes used in aero-vehicle design, and 5x improvements in a number of space science codes dealing in extreme physics. The TAG group will continue its scaling work to 2048p and beyond (10240 cpus) as the Columbia system becomes fully operational and the upgrades to the SGI NUMAlink memory fabric are in place. The NUMlink uprades dramatically improve system scalability for a single application. These upgrades will allow a number of codes to execute faster at higher fidelity than ever before on any other system, thus increasing the rate of scientific discovery even further

Taft, Jim↗
DOE OSTI2015

Understanding the Performance and Potential of Cloud Computing for Scientific Applications

In this paper, commercial clouds bring a great opportunity to the scientific computing area. Scientific applications usually require significant resources, however not all scientists have access to sufficient high-end computing systems, may of which can be found in the Top500 list. Cloud Computing has gained the attention of scientists as a competitive resource to run HPC applications at a potentially lower cost. But as a different infrastructure, it is unclear whether clouds are capable of running scientific applications with a reasonable performance per money spent. This work studies the performance of public clouds and places this performance in context to price. We evaluate the raw performance of different services of AWS cloud in terms of the basic resources, such as compute, memory, network and I/O. We also evaluate the performance of the scientific applications running in the cloud. This paper aims to assess the ability of the cloud to perform well, as well as to evaluate the cost of the cloud running scientific applications. We developed a full set of metrics and conducted a comprehensive performance evlauation over the Amazon cloud. We evaluated EC2, S3, EBS and DynamoDB among the many Amazon AWS services. We evaluated the memory sub-system performance with CacheBench, the network performance with iperf, processor and network performance with the HPL benchmark application, and shared storage with NFS and PVFS in addition to S3. We also evaluated a real scientific computing application through the Swift parallel scripting system at scale. Armed with both detailed benchmarks to gauge expected performance and a detailed monetary cost analysis, we expect this paper will be a recipe cookbook for scientists to help them decide where to deploy and run their scientific applications between public clouds, private clouds, or hybrid clouds.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Technical Characterization and Benefit Evaluation of 5G-Enabled Grid Data Transport and Applications

This report summarizes the Year 1 work of Pacific Northwest National Laboratory’s (PNNL’s) 5G Fabricated Resource and Asset Management Encompassment for energy infrastructure (Energy FRAME) project funded by the Department of Energy Office of Science’s Advanced Scientific Computing Research Program. 5G is a breakthrough technology that enables a fully mobile and connected society, and a 5G-enabled digital continuum will be one of the critical foundations for a clean energy economy and grid modernization. In collaboration with PNNL’s Advanced Wireless Communication team and Center for Advanced Technology Evaluation team, the project team has been evaluating the system performance of 5G testbeds in the PNNL 5G Innovation Studio, and has formulated a co-simulation test case of power system transmission, distribution, and communication (T&D&C) networks considering 5G technology and high penetration of distributed energy resources. The methodology developed in the 5G Energy FRAME project can be customized to fit different future grid scenarios to evaluate multiple (dynamic) configurations (computing, sensing, communication, environment) for different stakeholders. In summary, our main technical highlights in project Year 1 are as follows: 1) Technical characterization of 5G standalone architectures, 2) Formulation of co-simulation test case of T&D&C networks embedded with 5G, 3) Initial benefit evaluation of 5G communication platform for grid use cases, and 4) Additional extended discussions on edge computing, artificial intelligence and machine learning, and high-performance computing and cloud computing adoptions. In addition, a collection of system performance data is shared through the publicly available weblink, https://www.pnnl.gov/projects/5g-energy-frame/publications

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1979

Performability evaluation of the SIFT computer

Performability modeling and evaluation techniques are applied to the SIFT computer as it might operate in the computational evironment of an air transport mission. User-visible performance of the total system (SIFT plus its environment) is modeled as a random variable taking values in a set of levels of accomplishment. These levels are defined in terms of four attributes of total system behavior: safety, no change in mission profile, no operational penalties, and no economic process whose states describe the internal structure of SIFT as well as relavant conditions of the environment. Base model state trajectories are related to accomplishment levels via a capability function which is formulated in terms of a 3-level model hierarchy. Performability evaluation algorithms are then applied to determine the performability of the total system for various choices of computer and environment parameter values. Numerical results of those evaluations are presented and, in conclusion, some implications of this effort are discussed.

Meyer, J. F.↗
DOE OSTI2022

Probabilistic Neural Computing with Stochastic Devices

Abstract The brain has effectively proven a powerful inspiration for the development of computing architectures in which processing is tightly integrated with memory, communication is event‐driven, and analog computation can be performed at scale. These neuromorphic systems increasingly show an ability to improve the efficiency and speed of scientific computing and artificial intelligence applications. Herein, it is proposed that the brain's ubiquitous stochasticity represents an additional source of inspiration for expanding the reach of neuromorphic computing to probabilistic applications. To date, many efforts exploring probabilistic computing have focused primarily on one scale of the microelectronics stack, such as implementing probabilistic algorithms on deterministic hardware or developing probabilistic devices and circuits with the expectation that they will be leveraged by eventual probabilistic architectures. A co‐design vision is described by which large numbers of devices, such as magnetic tunnel junctions and tunnel diodes, can be operated in a stochastic regime and incorporated into a scalable neuromorphic architecture that can impact a number of probabilistic computing applications, such as Monte Carlo simulations and Bayesian neural networks. Finally, a framework is presented to categorize increasingly advanced hardware‐based probabilistic computing technologies.

Misra, Shashank↗
DOE OSTI2021

The LSBmax algorithm for boosting resilience of electric grids post (N‐2) contingencies

Abstract A computationally improved algorithm is presented to find the best transmission switching (TS) candidate for boosting resilience of electricity grids subject to ( N ‐2) contingencies. Here, resilience is computed as the reduction in load shed after the above‐mentioned ( N‐ ) contingencies. TS is a planned line outage, and past research shows that changing the transmission system's topology changes the power flow and removes post contingency violations. Finding the best TS candidate in a computationally suitable time for effectively boosting resilience is a challenge. The best TS candidate is found using a novel heuristic method by decreasing the search space based on proximity to the bus with the maximum load shedding (LSB). The LSB algorithm is faster than existing algorithms in the literature; and, it is compatible with both the AC and DC optimal power flow formulations. To validate the authors' claims of speedup and accuracy, two metrics are used to analyze the results from the IEEE 39‐bus and 118‐bus systems. Finally, the inherent parallelism of the LSB algorithm is leveraged on a high‐performance computing platform and applied to the large‐scale Polish 2383‐bus test system to validate scalability in both size and speedup in computation time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1993

Stellar Photometry Software

We describe the Stellar Photometry Software (SPS), which combines in a single program procedures for locating stars, computing a mean stellar point-spread function (PSF), and performing aperture and/or multiple PSF-fitting photometry, along with related bookkeeping functions. The software can be run either interactively or in batch mode on computers using the UNIX operating system. The performance of SPS is compared to that of the photometry programs DoPHOT and IRAF/DAOPHOT, using both real and simulated CCD observations. A direct comparison of the instrumental magnitudes shows that all three programs produce comparable results.

Janes, Kenneth A.↗
DOE OSTI2022

Computing Free Energies with Fluctuation Relations on Quantum Computers

As a central thermodynamic property, free energy enables the calculation of virtually any equilibrium property of a physical system, allowing for the construction of phase diagrams and predictions about transport, chemical reactions, and biological processes. Thus, methods for efficiently computing free energies, which in general is a difficult problem, are of great interest to broad areas of physics and the natural sciences. The majority of techniques for computing free energies target classical systems, leaving the computation of free energies in quantum systems less explored. Recently developed fluctuation relations enable the computation of free energy differences in quantum systems from an ensemble of dynamic simulations. While performing such simulations is exponentially hard on classical computers, quantum computers can efficiently simulate the dynamics of quantum systems. Here, we present an algorithm utilizing a fluctuation relation known as the Jarzynski equality to approximate free energy differences of quantum systems on a quantum computer. In this work we discuss under which conditions our approximation becomes exact, and under which conditions it serves as a strict upper bound. Furthermore, we successfully demonstrate a proof of concept of our algorithm using the transverse field Ising model on a real quantum processor. As quantum hardware continues to improve, we anticipate that our algorithm will enable computation of free energy differences for a wide range of quantum systems useful across the natural sciences.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Systems and methods for application performance profiling and improvement

Methods for analyzing and improving a target computer application and corresponding systems and computer-readable mediums. A method includes receiving the target application. The method includes generating a parallel control flow graph (ParCFG) corresponding to the target application. The method includes analyzing the ParCFG by the computer system. The method includes generating and storing the modified ParCFG for the target application.

Leidel, John D.↗
NASA NTRS1994

Modeling Improvements and Users Manual for Axial-flow Turbine Off-design Computer Code AXOD

An axial-flow turbine off-design performance computer code used for preliminary studies of gas turbine systems was modified and calibrated based on the experimental performance of large aircraft-type turbines. The flow- and loss-model modifications and calibrations are presented in this report. Comparisons are made between computed performances and experimental data for seven turbines over wide ranges of speed and pressure ratio. This report also serves as the users manual for the revised code, which is named AXOD.

Glassman, Arthur J.↗