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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

The Faster, Better, Cheaper Approach to Space Missions: An Engineering Management Assessment

NASA was chartered as an independent civilian space agency in 1958 following the Soviet Union's dramatic launch of the Sputnik 1 (1957). In his state of the union address in May of 1961, President Kennedy issued to the fledging organization his famous challenge for a manned lunar mission by the end of the decade. The Mercury, Gemini and Apollo programs that followed put the utmost value on high quality, low risk (as low as possible within the context of space flight), quick results, all with little regard for cost. These circumstances essentially melded NASAs culture as an organization capable of great technological achievement but at extremely high cost. The Space Shuttle project, the next major agency endeavor, was put under severe annual budget constraints in the 1970's. NASAs response was to hold to the high quality standards, low risk and annual cost and let schedule suffer. The result was a significant delay in the introduction of the Shuttle as well as overall total cost growth. By the early 1990's, because NASA's budget was declining, the number of projects was also declining. Holding the same cost and schedule productivity levels as before was essentially causing NASA to price itself out of business. In 1992, the helm of NASA was turned over to a new Administrator. Dan Goldin's mantra was "faster, better, cheaper" and his enthusiasm and determination to change the NASA culture was not to be ignored. This research paper documents the various implementations of "faster, better, cheaper" that have been attempted, analyzes their impact and compares the cost performance of these new projects to previous NASA benchmarks. Fundamentally, many elements of "faster, better, cheaper" are found to be working well, especially on smaller projects. Some of the initiatives are found to apply only to smaller or experimental projects however, so that extrapolation to "flagship" projects may be problematic.

Hamaker, Joseph W.↗
NASA NTRS2003

Comparing the OpenMP, MPI, and Hybrid Programming Paradigm on an SMP Cluster

Clusters of SMP (Symmetric Multi-Processors) nodes provide support for a wide range of parallel programming paradigms. The shared address space within each node is suitable for OpenMP parallelization. Message passing can be employed within and across the nodes of a cluster. Multiple levels of parallelism can be achieved by combining message passing and OpenMP parallelization. Which programming paradigm is the best will depend on the nature of the given problem, the hardware components of the cluster, the network, and the available software. In this study we compare the performance of different implementations of the same CFD benchmark application, using the same numerical algorithm but employing different programming paradigms.

Jost, Gabriele↗
NASA NTRS2004

A status report on the characterization of the microgravity environment of the International Space Station

A primary objective of the International Space Station is to provide a long-term quiescent environment for the conduct of scientific research for a variety of microgravity science disciplines. Since continuous human presence on the space station began in November 2000 through the end of Increment-6, over 1260 hours of crew time have been allocated to research. However, far more research time has been accumulated by experiments controlled on the ground. By the end of the time period covered by this paper (end of Increment-6), the total experiment hours performed on the station are well over 100,000 hours (Expedition 6 Press Kit: Station Begins Third Year of Human Occupation, Boeing/USA/NASA, October 25, 2002). This paper presents the results of the on-going effort by the Principal Investigator Microgravity Services project, at NASA Glenn Research Center, in Cleveland, Ohio, to characterize the microgravity environment of the International Space Station in order to keep the microgravity scientific community apprised of the reduced gravity environment provided by the station for the performance of space experiments. This paper focuses on the station microgravity environment for Increments 5 and 6. During that period over 580 Gbytes of acceleration data were collected, out of which over 34,790 hours were analyzed. The results presented in this paper are divided into two sections: quasi-steady and vibratory. For the quasi-steady analysis, over 7794 hours of acceleration data were analyzed, while over 27,000 hours were analyzed for the vibratory analysis. The results of the data analysis are presented in this paper in the form of a grand summary for the period under consideration. For the quasi-steady acceleration response, results are presented in the form of a 95% confidence interval for the station during "normal microgravity mode operations" for the following three attitudes: local vertical local horizontal, X-axis perpendicular to the orbit plane and the Russian torque equilibrium attitude. The same analysis was performed for the station during "non-microgravity mode operations" to assess the station quasi-steady acceleration environment over a long period of time. The same type of analysis was performed for the vibratory, but a 95th percentile benchmark was used, which shows the overall acceleration magnitude during Increments 5 and 6. The results, for both quasi-steady and vibratory acceleration response, show that the station is not yet meeting the microgravity requirements during the microgravity mode operations. However, it should be stressed that the requirements apply only at assembly complete, whereas the results presented below apply up to the station's configuration at the end of Increment-6. c2004 Elsevier Ltd. All rights reserved.

ISS Project↗
NASA NTRS2016

Isolated Open Rotor Noise Prediction Assessment Using the F31A31 Historical Blade Set

In an effort to mitigate next-generation fuel efficiency and environmental impact concerns for aviation, open rotor propulsion systems have received renewed interest. However, maintaining the high propulsive efficiency while simultaneously meeting noise goals has been one of the challenges in making open rotor propulsion a viable option. Improvements in prediction tools and design methodologies have opened the design space for next generation open rotor designs that satisfy these challenging objectives. As such, validation of aerodynamic and acoustic prediction tools has been an important aspect of open rotor research efforts. This paper describes validation efforts of a combined computational fluid dynamics and Ffowcs Williams and Hawkings equation methodology for open rotor aeroacoustic modeling. Performance and acoustic predictions were made for a benchmark open rotor blade set and compared with measurements over a range of rotor speeds and observer angles. Overall, the results indicate that the computational approach is acceptable for assessing low-noise open rotor designs. Additionally, this approach may be used to provide realistic incident source fields for acoustic shielding/scattering studies on various aircraft configurations.

Nark, Douglas M.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-35370-DND

The above anvil cirrus plume (AACP) is a weather phenomenon that signifies an intense tropopause penetrating updraft which can inject cirrus clouds several kilometers into the stratosphere. Storms that have such intense updrafts are often supercells which generate severe weather such as tornadoes, high winds, and hail. In addition, AACPs moisten the stratosphere and influence the Earth's radiative balance. Though an AACP can be identified by the human eye, no automated AACP detection methods currently exist. Lack of detection inhibits understanding of where and how often AACPs occur, and how these storms influence stratospheric air composition. Previous work involved synthesis of multiple remote sensing and severe weather report/warning data sources to identify AACPs in Geostationary Operational Environmental Satellite system (GOES) satellite imagery and better understand their weather impacts (Bedka et al. (Wea. Forecasting, 2018)). This current study demonstrates an automated AACP identification method based on the application of a deep learning segmentation model known as a U-net. This study documents the development of a U-net model capable of identifying emergent AACPs using only satellite infrared (IR) and visible reflected sunlight imagery. The performance of a U-net is quantitatively benchmarked with human AACP identifications and qualitatively assessed through animations of detections generated from GOES-16 1-minute temporal resolution imagery.

Charles Liles↗
NASA NTRSDate not supplied

Optimized Combined Compact Differencing Methods for Computational Aeroacoustics

The sixth order Combined Compact Differencing (CCD) scheme of Chu and Fan is optimized, resulting in exceptional performance. Results indicate that the best of these optimized schemes can accurately propagate linear simple harmonic waves with fewer than three points per wavelength, while using a three point differencing stencil. Stable and accurate boundary treatments for these schemes are given, and the performance of these schemes is assessed using a benchmark problem.

Computational Aeroacoustics↗
NASA NTRS2024

Transfer-AE: A novel autoencoder-based impact detection model for structural digital twin

Accurately detecting the location and intensity of impacts is crucial for ensuring structural safety. Currently, AI-based structural impact detection methods are widely used for their excellent detection accuracy. However, their generalization capability is limited by the scenarios present in the training data. Many complex and dangerous impact scenarios are difficult to conduct real-world experiments on to collect sufficient samples. To capture all impact scenarios and fully leverage the advantages of AI-based detection technologies, advanced methods involve combining real-world structural monitoring data with corresponding numerical models to construct digital twins. These methods continuously refine the created numerical models with limited real-world data and provide diverse impact scenarios through numerical model simulations. However, there are inevitable differences between digital models and physical models that are challenging to correct through mechanical means. This discrepancy in data distribution between the two models significantly hinders the application of digital twin technology in impact/event identification tasks. To address this challenge, this study proposes a novel model based on autoencoders, named Transfer-AE. Transfer-AE encodes the common features of digital twins in the latent space to bridge the uncertainty gap at a macro scale between numerical models and physical models and synchronously fits the magnitude and location of the impact load in the decoder. This enables consistent detection results for the same impact event, whether the sample comes from the numerical model or the physical model. Transfer-AE includes two operating modes: Mode 1 has a fixed computational complexity with stable inference speed, but the training cost and difficulty increase with data distribution. Mode 2's computational complexity increases with data distribution, but it has a fixed training cost and speed. In both cases involving the geodesic dome structure simulating a deep space habitat and the IASC-ASCE benchmark structure, Transfer-AE demonstrated the best performance in impact localization and quantification tasks compared to mainstream domain-adaptive transfer models.

Chengjia Han↗
DOE OSTI2022

Accelerating the Inference of the Exa.TrkX Pipeline

Recently, graph neural networks (GNNs) have been successfully used for a variety of particle reconstruction problems in high energy physics, including particle tracking. The Exa.TrkX pipeline based on GNNs demonstrated promising performance in reconstructing particle tracks in dense environments. It includes five discrete steps: data encoding, graph building, edge filtering, GNN, and track labeling. All steps were written in Python and run on both GPUs and CPUs. In this work, we accelerate the Python implementation of the pipeline through customized and commercial GPU-enabled software libraries, and develop a C++ implementation for inferencing the pipeline. The implementation features an improved, CUDA-enabled fixed-radius nearest neighbor search for graph building and a weakly connected component graph algorithm for track labeling. GNNs and other trained deep learning models are converted to ONNX and inferenced via the ONNX Runtime C++ API. The complete C++ implementation of the pipeline allows integration with existing tracking software. We report the memory usage and average event latency tracking performance of our implementation applied to the TrackML benchmark dataset.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Advancing the Theory of Nuclear Data Evaluations [Abstract]

We present recent advances in the R-matrix formalism as well as the Bayesian evaluation framework for improved nuclear data evaluations. The advances in the R matrix formalism include: 1) direct processes, 2) doorway, as well as multistep, processes, and 3) various forms of the Reich-Moore approximation for eliminated capture channels. Furthermore, to address unreasonably small posterior uncertainties often encountered in nuclear data evaluations of large data sets using the conventional form of the Bayes’ theorem, we introduce imperfections (of the data or the model) as a formal evaluation tool for taming the evaluated uncertainties in harmony with Bayes’ theorem. These theoretical advances were motivated by the nuclear data evaluations of differential resolved resonance cross section data using the code SAMMY, as well as the integral benchmark experiments using the SCALE code system, being performed at Oak Ridge National Laboratory for the Nuclear Criticality Safety Program. Some pedagogical applications of the new formalism, as well as a snapshot of the SAMMY modernization efforts, will be presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Preliminary Results for Uncertainty Quantification on Asymptotic Hydrogen Redistribution in a Prototypical Yttrium-Hydride Moderated Heat-Pipe-Cooled Microreactor

Yttrium hydride is one of the most promising materials for moderating nuclear microreactors. This is due to its high hydrogen concentration at high operating conditions, high value of thermal conductivity, and chemical stability. However, when subject to thermal and concentration spatial gradients, the hydrogen tends to migrate within the yttrium matrix, potentially leading to power swings and reactivity changes. This paper aims to present selected results concerning the sensitivity of the thermal and hydrogen redistribution response for a prototypical heat-pipe-cooled yttrium-hydride moderated microreactor to thermal properties uncertainty and selected design characteristics. To the best knowledge of the authors, this is the first study examining the impact of uncertainties on microreactor hydrogen redistribution response. To achieve this goal, Bison was used in conjunction with Dakota to create a framework able to perform Uncertainty Quantification (UQ) for the Simplified Microreactor Benchmark Assessment (SiMBA) problem.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Efficient DNA sequence compression with neural networks

Abstract Background The increasing production of genomic data has led to an intensified need for models that can cope efficiently with the lossless compression of DNA sequences. Important applications include long-term storage and compression-based data analysis. In the literature, only a few recent articles propose the use of neural networks for DNA sequence compression. However, they fall short when compared with specific DNA compression tools, such as GeCo2. This limitation is due to the absence of models specifically designed for DNA sequences. In this work, we combine the power of neural networks with specific DNA models. For this purpose, we created GeCo3, a new genomic sequence compressor that uses neural networks for mixing multiple context and substitution-tolerant context models. Findings We benchmark GeCo3 as a reference-free DNA compressor in 5 datasets, including a balanced and comprehensive dataset of DNA sequences, the Y-chromosome and human mitogenome, 2 compilations of archaeal and virus genomes, 4 whole genomes, and 2 collections of FASTQ data of a human virome and ancient DNA. GeCo3 achieves a solid improvement in compression over the previous version (GeCo2) of $2.4\%$, $7.1\%$, $6.1\%$, $5.8\%$, and $6.0\%$, respectively. To test its performance as a reference-based DNA compressor, we benchmark GeCo3 in 4 datasets constituted by the pairwise compression of the chromosomes of the genomes of several primates. GeCo3 improves the compression in $12.4\%$, $11.7\%$, $10.8\%$, and $10.1\%$ over the state of the art. The cost of this compression improvement is some additional computational time (1.7–3 times slower than GeCo2). The RAM use is constant, and the tool scales efficiently, independently of the sequence size. Overall, these values outperform the state of the art. Conclusions GeCo3 is a genomic sequence compressor with a neural network mixing approach that provides additional gains over top specific genomic compressors. The proposed mixing method is portable, requiring only the probabilities of the models as inputs, providing easy adaptation to other data compressors or compression-based data analysis tools. GeCo3 is released under GPLv3 and is available for free download at https://github.com/cobilab/geco3.

Silva, Milton↗
DOE OSTI2023

Joint LLNL, LANL, SNL, and IRSN High Multiplication Subcritical (Multiplicity) Benchmark Integral Experiment Execution (CED-3b Report)

This report documents the experimental configurations and measurements for IER-518: Joint LLNL, LANL, SNL, and IRSN High Multiplication Subcritical (Multiplicity) Benchmark Experiments. These measurements involved a series of subcritical configurations at the Sandia Critical Experiments (SCX) facility at Sandia National Laboratories (SNL). The purpose of these measurements was to produce time tagged neutron count data of configurations that exceed a subcritical multiplication of 20, which is the high end of the fundamental physics benchmarks currently available in the International Criticality Safety Benchmark Evaluation Project Handbook (ICSBEP). These measurements leverage experimental configurations 1 and detector systems 2 from previously accepted ICSBEP benchmark evaluations, allowing evaluations of these measurements to be performed at greatly reduced cost.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Benchmark Calculation for the Watts Bar Unit 1 Cycles 1-3 Using the SCALE 6.3/Polaris–PARCS v3.4.2 Code Package

Benchmark calculations for the Watts Bar Unit 1 cycles 1–3 were performed to validate the SCALE 6.3/Polaris–PARCS v3.4.2 with the ENDF/B-VII.1 56-group library by comparing the simulated results with the measured data. The benchmark results are used in evaluating uncertainties of the SCALE/Polaris–PARCS code package for pressurized water reactor physics analysis for key nuclear parameters such as reactivity, control bank worth, temperature coefficients, and pin and assembly power peaking factors. This report details plant and fuel design specifications and input data for SCALE/Polaris, GenPMAXS, and PARCS. Additional details are provided for the input and output files produced for the benchmark calculations. The benchmark results were summarized such that they can be used in evaluating uncertainties for key nuclear parameters with other benchmark results.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Modeling Enhancements, Cross-Section Generation Updates, and Benchmarking with Shift

This technical report documents the modeling enhancements, cross-section generation updates, and bench marking with the Shift Monte Carlo code performed under the US Department of Energy Nuclear Energy Advanced Modeling and Simulation Program in FY 2024. The work performed included several modeling enhancements, such as integration of cross-section generation in Titan and the ability to produce microscopic multigroup cross sections with Shift. Benchmarking of the cross sections produced by Shift and the two-step workflow with Griffin was performed for three problems: the Advanced Breeder Test Reactor, a generic pebble bed reactor, and a TRISO heat pipe microreactor. Comparisons of results from these benchmark problems were done with Serpent, OpenMC, and Griffin. These enhancements provide a robust foundation for applying Shift for both reference and two-step neutronics analysis for advanced reactor simulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Optimization with the OpenACC-to-FPGA framework on the Arria 10 and Stratix 10 FPGAs

The reconfigurable computing paradigm with field programmable gate arrays (FPGAs) has received renewed interest in the high-performance computing field due to FPGAs’ unique combination of performance and energy efficiency. However, difficulties in programming and optimizing FPGAs have prevented them from being widely accepted as general-purpose computing devices. In accelerator-based heterogeneous computing, portability across diverse heterogeneous devices is also an important issue, but the unique architectural features in FPGAs make this difficult to achieve. To address these issues, a directive-based, high-level FPGA programming and optimization framework was previously developed. In this work, developed optimizations were combined holistically using the directive-based approach to show that each individual benchmark requires a unique set of optimizations to maximize performance. We perform this exploration on Intel Arria 10 and Stratix 10 FPGAs. We also explored the relationships between performance, resource usages, and compilation times, and investigated implications for performance portability. Finally, we present an initial evaluation of a real-world proxy application, LULESH.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

In-Depth Optimization with the OpenACC-to-FPGA Framework on an Arria 10 FPGA

The reconfigurable computing paradigm that uses field programmable gate arrays (FPGAs) has received renewed interest in the high-performance computing field due to FPGAs' unique combination of performance and energy efficiency. However, difficulties in programming and optimizing FPGAs have prevented them from being widely accepted as general-purpose computing devices. In accelerator-based heterogeneous computing, portability across diverse heterogeneous devices is also an important issue, but the unique architectural features in FPGAs make this difficult to achieve. To address these issues, a directive-based, high-level FPGA programming and optimization framework was previously developed. In this work, developed optimizations were combined holistically using the directive-based approach to show that each individual benchmark requires a unique set of optimizations to maximize performance. The relationships between FPGA resource usages and runtime performance were also explored.

Lambert, Jacob↗
NASA NTRS2015

TPSAS-NF1676L-21817-DND

This presentation summarizes the results of various contributed analyses of a microphone array benchmark problem. The benchmark problem, known as NASA2, consists of a phased array measurement performed on a generic leading edge/trailing edge airfoil in the NASA Langley Quiet Flow Facility. An invitation went out to the broader microphone phased array community to submit analysis results for this benchmark using various array processing methodologies of the contributor's choosing. This presentation summarizes those results.

William M Humphreys, Jr↗
NASA NTRS2018

A Benchmark Example for Delamination Propagation Predictions Based on the Single Leg Bending Specimen Under Quasi-Static and Fatigue Loading

Benchmark examples based on Single Leg Bending (SLB) specimens with equal and unequal bending arm thicknesses were used to assess the performance of delamination prediction capabilities in finite element codes. First, the development of the quasi-static benchmark cases using the Virtual Crack Closure Technique (VCCT) is discussed in detail. Second, based on the quasi-static benchmark results, additional benchmark cases to assess delamination propagation under fatigue loading are created. Third, the application is demonstrated for the commercial finite element code Abaqus Standard 2018. The benchmark cases are compared to results obtained from VCCT-based, automated quasi-static propagation analysis. A comparison with results from automated fatigue propagation analysis was not performed at this point since the current version of Abaqus does not include this capability under variable mixed-mode conditions. In general, good agreement between the results obtained from the quasi-static propagation analysis and the benchmark results were achieved. Overall, the benchmarking procedure proved valuable for analysis verification.

Krueger, Ronald↗