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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Synchrophasor Data Compression Under Disturbance Conditions via Cross-Entropy-Based Singular Value Decomposition

The increasing deployment of phasor measurement units and the advances of their reporting rates are challenging the present data centers in terms of storing and analyzing large-volume data. Under power system disturbance conditions, it is difficult to retain critical information while compressing the synchrophasor data effectively. This article combines the cross entropy and the singular value decomposition, proposing a novel model to compress the synchrophasor data to an extremely small size yet keep superior accuracy. The proposed model is extensively tested and compared with the state-of-the-art algorithms using the simulated and the FNET/GridEye field-collected data. The result indicates that the proposed algorithm has superior performance in compressing the data while retaining critical information under disturbance conditions.

42 ENGINEERING↗
NASA NTRS1994

Effects of low sampling rate in the digital data-transition tracking loop

This article describes the performance of the all-digital data-transition tracking loop (DTTL) with coherent and noncoherent sampling using nonlinear theory. The effects of few samples per symbol and of noncommensurate sampling and symbol rates are addressed and analyzed. Their impact on the probability density and variance of the phase error are quantified through computer simulations. It is shown that the performance of the all-digital DTTL approaches its analog counterpart when the sampling and symbol rates are noncommensurate (i.e., the number of samples per symbol is an irrational number). The loop signal-to-noise ratio (SNR) (inverse of phase error variance) degrades when the number of samples per symbol is an odd integer but degrades even further for even integers.

Mileant, A.↗
DOE OSTI2025

Strength and ductility of additively manufactured 316L stainless steel: Impact of neutron irradiation and data variability

Here, this article presents the mechanical properties of additively manufactured (AM) 316L stainless steel processed via the laser powder bed fusion (LPBF) method, focusing on the effects of neutron irradiation on mechanical properties and the variability in strength and ductility data. The rapid melting-solidification process and multiple heating-cooling cycles inherent in LPBF typically result in a fine, metastable microstructure with significant local variability. AM 316L builds of varying thicknesses were fabricated, and SS-J3 miniature tensile specimens were machined from six different locations. These specimens were irradiated with fast neutrons to doses of 2 and 10 dpa at target temperatures of 300 °C and 600 °C. Post-irradiation tensile tests were conducted at room temperature, 300 °C, and 600 °C. Compared to conventional 316L stainless steel, AM 316L exhibited higher initial strength but lower ductility. Irradiation at 300 °C caused significant hardening and prompt necking at yield, with limited uniform ductility, although embrittlement was not observed up to 10 dpa. While neutron irradiation, particularly at 600 °C, increased the variability in strength and ductility data, no clear dependence of mechanical properties on build thickness or sampling location was found—contrary to the conventional perception that AM materials may exhibit high property variability. Furthermore, we observed that the variability in property data for LPBF-processed 316L was relatively low compared to that of wrought 316L stainless steel. This reduced variability in AM 316L steel may be attributed to its highly metastable, stress-containing microstructure, which is discussed in the context of general tensile property variations.

Additively manufactured 316L stainless steel↗
DOE OSTI2017

Cluster 1: commercializing additive manufacturing—hurdles in materials characterization and testing

A major challenge in the commercialization of additive manufactured (AM) materials and processes is the ability to achieve acceptance of processes and products. There has been some progress towards acceptance has been made by adapting legacy qualification paradigms to match with the very limited process control and monitoring offered by AM machines. The opportunity for in-situ measurement can provide process monitoring and control perhaps changing the way we qualify parts however it is limited by lack of adequate process measurement methods. New measurement techniques, sensors and correlations to relevant phenomena are needed that enable process control and monitoring for consistently producing high quality articles. Beyond process data we need to characterize uncertainties of performance in all aspects of material, process and final part. These are prerequisites to achieving articles that are indeed worthy of materials characterization efforts that establish a microstructural reference of desirable performance through process-structure-property relations. Only then can industry apply physics based understanding of the material, part and process to probabilistically predict performance of an AM part. Our paper provides a brief overview, discussion of hurdles and key areas where R&D investment is needed.

36 MATERIALS SCIENCE↗
NASA NTRS2012

On Shaft Data Acquisition System (OSDAS)

On Shaft Data Acquisition System (OSDAS) is a rugged, compact, multiple-channel data acquisition computer system that is designed to record data from instrumentation while operating under extreme rotational centrifugal or gravitational acceleration forces. This system, which was developed for the Heritage Fuel Air Turbine Test (HFATT) program, addresses the problem of recording multiple channels of high-sample-rate data on most any rotating test article by mounting the entire acquisition computer onboard with the turbine test article. With the limited availability of slip ring wires for power and communication, OSDAS utilizes its own resources to provide independent power and amplification for each instrument. Since OSDAS utilizes standard PC technology as well as shared code interfaces with the next-generation, real-time health monitoring system (SPARTAA Scalable Parallel Architecture for Real Time Analysis and Acquisition), this system could be expanded beyond its current capabilities, such as providing advanced health monitoring capabilities for the test article. High-conductor-count slip rings are expensive to purchase and maintain, yet only provide a limited number of conductors for routing instrumentation off the article and to a stationary data acquisition system. In addition to being limited to a small number of instruments, slip rings are prone to wear quickly, and introduce noise and other undesirable characteristics to the signal data. This led to the development of a system capable of recording high-density instrumentation, at high sample rates, on the test article itself, all while under extreme rotational stress. OSDAS is a fully functional PC-based system with 48 channels of 24-bit, high-sample-rate input channels, phase synchronized, with an onboard storage capacity of over 1/2-terabyte of solid-state storage. This recording system takes a novel approach to the problem of recording multiple channels of instrumentation, integrated with the test article itself, packaged in a compact/rugged form factor, consuming limited power, all while rotating at high turbine speeds.

Pedings, Marc↗
NASA NTRS1995

A seismic data compression system using subband coding

This article presents a study of seismic data compression techniques and a compression algorithm based on subband coding. The algorithm includes three stages: a decorrelation stage, a quantization stage that introduces a controlled amount of distortion to allow for high compression ratios, and a lossless entropy coding stage based on a simple but efficient arithmetic coding method. Subband coding methods are particularly suited to the decorrelation of nonstationary processes such as seismic events. Adaptivity to the nonstationary behavior of the waveform is achieved by dividing the data into separate blocks that are encoded separately with an adaptive arithmetic encoder. This is done with high efficiency due to the low overhead introduced by the arithmetic encoder in specifying its parameters. The technique could be used as a progressive transmission system, where successive refinements of the data can be requested by the user. This allows seismologists to first examine a coarse version of waveforms with minimal usage of the channel and then decide where refinements are required. Rate-distortion performance results are presented and comparisons are made with two block transform methods.

Kiely, A. B.↗
DOE OSTI2015

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining

When can reliable inference be drawn in the ‘‘Big Data’’ context? This article presents a framework for answering this fundamental question in the context of correlation mining, with implications for general large-scale inference. In large-scale data applications like genomics, connectomics, and eco-informatics, the data set is often variable rich but sample starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than the number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for ‘‘Big Data.’’ Sample complexity, however, has received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address this gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where the variable dimension is fixed and the sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; and 3) the purely high-dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa-scale data dimension. We illustrate this high-dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables that are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. We demonstrate various regimes of correlation mining based on the unifying perspective of high-dimensional learning rates and sample complexity for different structured covariance models and different inference tasks.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2019

TPSAS-NF1676L-32540-DND

The supersonic/hypersonic ground testing serves a multitude of purposes and objectives. From structural and material integrity, to force and moment models; from pressure mapping, thermal imaging, shock structure to scramjet/ramjet engine operability and ignition studies. Hypersonics has become more of a high profile area of late. Compared to flight testing, ground testing typically it is less expensive and usually is not a one single-test test program. It is more forgiving in the fact that a test program can utilize a single test article and get data from a number of tests. Ground test data is the input to the formation of research databases, as well as, validation of CFD models/tools. To understand the output, one must first understand the inputs. To achieve supersonic/hypersonic speeds the use of compressors or compressed air storage along with converging-diverging nozzles are needed. Flight temperatures also need to be achieved for the ground test to truly simulate flight conditions. At NASA Langley's 8' High Temperature Tunnel (HTT), compressed natural gas (methane) is burned to heat the air. To validate that the desired test condition is met, test instrumentation is used and data is collected from the combustor all the way through the nozzle exit plane. In this talk, NASA Langley's 8' HTT will be the basis for what kind of test capabilities hypersonic ground testing offers. It certainly does not offer every capability within ground testing, nor will the discussion cover all types. Specific test techniques used and data collection methods will be discussed and how these confirm certain flight conditions have been achieved. There will be subsequent thoughts on experimental methods that aid test articles such as thrust stands, model actuation, etc.

Aaron W Fuchs↗
DOE OSTI2022

Research and Test Reactor Fuels

PRO-RR is the research reactor focused program element of the broader Proliferation Resistance Optimization program (PRO-X) under the National Nuclear Safety Administration (NNSA) in the U.S. Department of Energy (DOE). PRO-X provides a framework for integrating proliferation resistance in nuclear system designs to minimize weapons usable nuclear materials (WUNM) production and diversion pathways while optimizing systems performance for peaceful use missions. PRO-RR applies the PRO-X mission objectives to research reactor system design. This document serves as one of the foundational documents for the PRO-RR-Fuel System Design technical team by documenting current research reactor fuels usage. The PRO-RR-Fuel System Design technical team consists of subject matter experts from Argonne National Laboratory (Argonne) and Savannah River National Laboratory (SRNL). In order to determine the preferred fuel of use in upcoming research and test reactors to optimize proliferation resistance, performance, and safety, it is useful to assess the fuels that have been used in the past, or are currently in use. This report reviews the historical and current fuels used in research and test reactors to inform future fuel selection. Chapter 2 discusses the low-enriched uranium (LEU) fuels currently in use in terms of thermal power level and utilization of the reactor. Chapter 3 summarizes the fabrication processes for common fuel types. Chapter 4 discusses in detail the fuel types in use in research and test reactors. A review of the cladding types in use is presented in Chapter 5, and a historical review of research and test reactor fuel fabricators is presented in Chapter 6. The data collection strategy used the International Atomic Energy Agency (IAEA) research reactor database [1] as a starting point. Information on the fuel used was gathered on research reactors (other than critical assemblies) that were listed as operational, planned, or in temporary shutdown in the IAEA database. Data on the fuel type, geometry, enrichment, uranium loading, cladding type, and fabricator were collected for each of the reactors available in the public domain. Sources of data included conference papers, journal articles, and facility and fabricator websites. Data on research reactors operating on LEU fuels are presented in Appendix A, while Appendix B presents data collected on all reactors at the time of publication of this report. Appendix C presents data collected on reactors that were part of the M3 research and test reactor conversion program.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2005

Pressurization System Modeling for a Generic Bimese Two- Stage-to-Orbit Reusable Launch Vehicle

A pressurization system model was developed for a generic bimese Two-Stage-to-orbit Reusable Launch Vehicle using a cross-feed system and operating with densified propellants. The model was based on the pressurization system model for a crossfeed subscale water test article and was validated with test data obtained from the test article. The model consists of the liquid oxygen and liquid hydrogen pressurization models, each made up of two submodels, Booster and Orbiter tank pressurization models. The tanks are controlled within a 0.2-psi band and pressurized on the ground with ambient helium and autogenously in flight with gaseous oxygen and gaseous hydrogen. A 15-psi pressure difference is maintained between the Booster and Orbiter tanks to ensure crossfeed check valve closure before Booster separation. The analysis uses an ascent trajectory generated for a generic bimese vehicle and a tank configuration based on the Space Shuttle External Tank. It determines the flow rates required to pressurize the tanks on the ground and in flight, and demonstrates the model's capability to analyze the pressurization system performance of a full-scale bimese vehicle with densified propellants.

Mazurkivich, Pete↗
DOE OSTI2023

Transfer Learning of High-Fidelity Opacity Spectra in Autoencoders and Surrogate Models

Simulations of high energy density physics are expensive, largely in part for the need to produce nonlocal thermodynamic equilibrium opacities. High-fidelity spectra may reveal new physics in the simulations not seen with low-fidelity spectra, but the cost of these simulations also scales with the level of fidelity of the opacities being used. Neural networks are capable of reproducing these spectra, but neural networks need data to train them, which limits the level of fidelity of the training data. Here this article demonstrates that it is possible to reproduce high-fidelity spectra with median errors in the realm of 3%–4% using as few as 50 samples of high-fidelity Krypton data by performing transfer learning on a neural network trained on many times more low-fidelity data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Persistent Classification: Understanding Adversarial Attacks by Studying Decision Boundary Dynamics

ABSTRACT There are a number of hypotheses underlying the existence of adversarial examples for classification problems. These include the high‐dimensionality of the data, the high codimension in the ambient space of the data manifolds of interest, and that the structure of machine learning models may encourage classifiers to develop decision boundaries close to data points. This article proposes a new framework for studying adversarial examples that does not depend directly on the distance to the decision boundary. Similarly to the smoothed classifier literature, we define a (natural or adversarial) data point to be ( γ , σ)‐stable if the probability of the same classification is at least for points sampled in a Gaussian neighborhood of the point with a given standard deviation . We focus on studying the differences between persistence metrics along interpolants of natural and adversarial points. We show that adversarial examples have significantly lower persistence than natural examples for large neural networks in the context of the MNIST and ImageNet datasets. We connect this lack of persistence with decision boundary geometry by measuring angles of interpolants with respect to decision boundaries. Finally, we connect this approach with robustness by developing a manifold alignment gradient metric and demonstrating the increase in robustness that can be achieved when training with the addition of this metric.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Use of the Wilshire Equations to Correlate and Extrapolate Creep Data of HR6W and Sanicro 25

Advanced power plant alloys must endure high temperatures and pressures for durations at which creep data are often not available, necessitating the extrapolation of creep life. Many methods have been proposed to extrapolate creep life, and one of recent significance is a set of equations known as the Wilshire equations. With this method, multiple approaches can be used to determine creep activation energy, increase the goodness of fit of available experimental data, and improve the confidence level of calculating long-term creep strength at times well beyond the available experimental data. In this article, the Wilshire equation is used to extrapolate the creep life of HR6W and Sanicro 25, and different methods to determine creep activation energy, region splitting, the use of short-duration test data, and the omission of very-short-term data are investigated to determine their effect on correlation and calculations. It was found that using a known value of the activation energy of lattice self-diffusion, rather than calculating Q C * from each data set, is both the simplest and most viable method to determine Q C * . Region-splitting improved rupture time calculations for both alloys. Extrapolating creep life from short-term data for these alloys was found to be reasonable.

36 MATERIALS SCIENCE↗
NASA NTRS1978

Phase insensitive acoustoelectric transducer

Conventional ultrasonic transducers transform acoustic waves into electrical signals preserving phase and amplitude information. When the acoustic wavelength is significantly smaller than the transducer diameter, severe phase modulation of the electrical signal can occur. This results in anomalous attenuation measurements, background noise in nondestructive evaluation, and in general complicates data interpretation. This article describes and evaluates a phase-insensitive transducer based on the acoustoelectric effect. Theory of operation of the acoustoelectric transducer (AET) is discussed, and some optimization procedures outlined for its use. Directivity data for the AET are contrasted with a conventional piezoelectric transducer. In addition, transmission scanning data of phantom flaws in metal plates are presented for both transducers and demonstrate a significant improvement in resolution with the AET.

Heyman, J. S.↗
NASA NTRS1992

A comparison of techniques for extracting emissivity information from thermal infrared data for geologic studies

This article evaluates three techniques developed to extract emissivity information from multispectral thermal infrared data. The techniques are the assumed Channel 6 emittance model, thermal log residuals, and alpha residuals. These techniques were applied to calibrated, atmospherically corrected thermal infrared multispectral scanner (TIMS) data acquired over Cuprite, Nevada in September 1990. Results indicate that the two new techniques (thermal log residuals and alpha residuals) provide two distinct advantages over the assumed Channel 6 emittance model. First, they permit emissivity information to be derived from all six TIMS channels. The assumed Channel 6 emittance model only permits emissivity values to be derived from five of the six TIMS channels. Second, both techniques are less susceptible to noise than the assumed Channel 6 emittance model. The disadvantage of both techniques is that laboratory data must be converted to thermal log residuals or alpha residuals to facilitate comparison with similarly processed image data. An additional advantage of the alpha residual technique is that the processed data are scene-independent unlike those obtained with the other techniques.

Hook, Simon J.↗
DOE OSTI2019

Data to Accompany "Metabotyping as a Stopover in Genome-to-Phenome Mapping"

This file contains all of the genotypic and metabolomic data analyzed in the article "Metabotyping as a Stopover in Genome-to-Phenome Mapping" published in Scientific Reportsvolume 9, Article number: 1858 (2019). The code that we used to analyze these data and produce the results and figures in this article can be found here https://github.com/PNNL-PREMIS/PREMIS-metabotyping .

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Dealing with the Data Scientist Shortage

Few areas in the economy have generated as much attention as big data and advanced analytics in recent years due to its potential of revolutionizing the way that business function in the coming years. One of the major challenges that organizations face in implementing analytics that have the potential of providing them a competitive advantage in the market is that of finding the elusive data scientist needed to execute on big data strategy. This article addresses what some business are doing to bridge that gap between vision and reality.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1997

Automated Test Systems for Toxic Vapor Detectors

The NASA Toxic Vapor Detection Laboratory (TVDL) at the Kennedy Space Center (KSC), Florida, has been using Personal Computer based Data Acquisition and Control Systems (PCDAS) for about nine years. These systems control the generation of toxic vapors of known concentrations under controlled conditions of temperature and humidity. The PCDAS also logs the test conditions and the test article responses in data files for analysis by standard spreadsheets or custom programs. The PCDAS was originally developed to perform standardized qualification and acceptance tests in a search for a commercial off-the-shelf (COTS) toxic vapor detector to replace the hydrazine detectors for the Space Shuttle launch pad. It has since become standard test equipment for the TVDL and is indispensable in producing calibration standards for the new hydrazine monitors at the 10 part per billion (ppb) level. The standard TVDL PCDAS can control two toxic vapor generators (TVG's) with three channels each and two flow/temperature/humidity (FIFH) controllers and it can record data from up to six toxic vapor detectors (TVD's) under test and can deliver flows from 5 to 50 liters per minute (L/m) at temperatures from near zero to 50 degrees Celsius (C) using an environmental chamber to maintain the sample temperature. The concentration range for toxic vapors depends on the permeation source installed in the TVG. The PCDAS can provide closed loop control of temperature and humidity to two sample vessels, typically one for zero gas and one for the standard gas. This is required at very low toxic vapor concentrations to minimize the time required to passivate the sample delivery system. Recently, there have been several requests for information about the PCDAS by other laboratories with similar needs, both on and off KSC. The purpose of this paper is to inform the toxic vapor detection community of the current status and planned upgrades to the automated testing of toxic vapor detectors at the Kennedy Space Center.

Mattson, C. B.↗