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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Monitoring Subsystem For Testing Bearings

Electronic monitoring subsystem designed to be used in conjunction with controlling subsystem described in article, "Stepping-Motion Motor-Control Subsystem For Testing Bearings" (GSC-13418). Gathers data used to evaluate performance of bearing motor or other rotary mechanism being tested by subjecting it to stepping motions like those in its intended application. Data gathered at rate high enough to characterize dynamic properties of mechanism.

Powers, Charles E.↗
NASA NTRS1993

Cryogenic Fluid Film Bearing Tester Development Study

Conceptual designs were developed for the determination of rotordynamic coefficients of cryogenic fluid film bearings. The designs encompassed the use of magnetic and conventional excitation sources as well as the use of magnetic bearings as support bearings. Test article configurations reviewed included overhung, floating housing, and fixed housing. Uncertainty and forced response analyses were performed to assess quality of data and suitability of each for testing a variety of fluid film bearing designs. Development cost and schedule estimates were developed for each design. Facility requirements were reviewed and compared with existing MSFC capability. The recommended configuration consisted of a fixed test article housing centrally located between two magnetic bearings. The magnetic bearings would also serve as the excitation source.

Scharrer, Joseph K.↗
NASA NTRS1995

Micron Accuracy Deployment Experiment (MADE), phase A. Volume 1

This report documents a Phase A In-STEP flight experiment development effort. The objective of the experiment is to deploy a portion of a segmented reflector on the Shuttle and study its micron-level mechanics. Ground test data are presented which projects that the on-orbit precision of the test article should be approximately 5 microns. Extensive hardware configuration development information is also provided.

Peterson, Lee D.↗
NASA NTRS1995

Enhanced decoding for the Galileo low-gain antenna mission: Viterbi redecoding with four decoding stages

The Galileo low-gain antenna mission will be supported by a coding system that uses a (14,1/4) inner convolutional code concatenated with Reed-Solomon codes of four different redundancies. Decoding for this code is designed to proceed in four distinct stages of Viterbi decoding followed by Reed-Solomon decoding. In each successive stage, the Reed-Solomon decoder only tries to decode the highest redundancy codewords not yet decoded in previous stages, and the Viterbi decoder redecodes its data utilizing the known symbols from previously decoded Reed-Solomon codewords. A previous article analyzed a two-stage decoding option that was not selected by Galileo. The present article analyzes the four-stage decoding scheme and derives the near-optimum set of redundancies selected for use by Galileo. The performance improvements relative to one- and two-stage decoding systems are evaluated.

Dolinar, S.↗
NASA NTRS2010

Structural Verification and Modeling of a Tension Cone Inflatable Aerodynamic Decelerator

Verification analyses were conducted on membrane structures pertaining to a tension cone inflatable aerodynamic decelerator using the analysis code LS-DYNA. The responses of three structures - a cylinder, torus, and tension shell - were compared against linear theory for various loading cases. Stress distribution, buckling behavior, and wrinkling behavior were investigated. In general, agreement between theory and LS-DYNA was very good for all cases investigated. These verification cases exposed the important effects of using a linear elastic liner in membrane structures under compression. Finally, a tension cone wind tunnel test article is modeled in LS-DYNA for which preliminary results are presented. Unlike data from supersonic wind tunnel testing, the segmented tension shell and torus experienced oscillatory behavior when subjected to a steady aerodynamic pressure distribution. This work is presented as a work in progress towards development of a fluid-structures interaction mechanism to investigate aeroelastic behavior of inflatable aerodynamic decelerators.

Tanner, Christopher L.↗
NASA NTRS2013

High resolution wind measurements for offshore wind energy development

A method, apparatus, system, article of manufacture, and computer readable storage medium provide the ability to measure wind. Data at a first resolution (i.e., low resolution data) is collected by a satellite scatterometer. Thin slices of the data are determined. A collocation of the data slices are determined at each grid cell center to obtain ensembles of collocated data slices. Each ensemble of collocated data slices is decomposed into a mean part and a fluctuating part. The data is reconstructed at a second resolution from the mean part and a residue of the fluctuating part. A wind measurement is determined from the data at the second resolution using a wind model function. A description of the wind measurement is output.

Nghiem, Son Van↗
NASA NTRS2021

Properties of The RFI Environment at 1400-1427 MHz as observed by the Soil Moisture Active/Passive Mission Microwave Radiometer

The soil moisture active/passive (SMAP) satellite microwave radiometer has been providing global measurements of L-band thermal emission from Earth since April 2015. Although the radiometer operates in the protected 1400–1427 MHz portion of the radio spectrum, its measurements are still corrupted by either radio frequency interference (RFI) from out-of-band emissions via legal sources or by sources operating in-band illegally. The SMAP radiometer includes a digital backend that enables implementation of multiple ground-based RFI detection and filtering algorithms. This data is used to collect statistics and trends of Earth's RFI environment. This article examines properties of the global RFI environment as observed by SMAP, including information on RFI source properties (obtained from analysis of SMAP multiple detector outputs) and the evolution of the RFI environment in time. Residual RFI contributions after the application of SMAP RFI processing are also examined as preliminary information for the development of future methods to address their effect.

L-band radiometry↗
NASA NTRS2022

Measuring, mapping, and anticipating climate gentrification in Florida: Miami and Tampa case studies

This article introduces an experimental methodology to identify proxy indicators that are conceptually consistent with the processes of Climate Gentrification (“CG”), in which a change in demand preferences among consumers and investors drives the increased consumption for real estate, in part, on lower measures of physical risk from climate change. Evaluated through case studies in the state of Florida, this article builds on the integration of multiple datasets concerning rental properties, evictions, and socioeconomic data, as well as environmental risk indices to build a Climate Gentrification Risk Index (CGRI). In the Miami case study, we find that the CGRI identifies a hotly contested neighborhood that is already known to be in a state of transition consistent with the processes of CG. In the Tampa case, the index highlights a district that exhibits strong metrics for the future accelerated occurrence of CG. Our findings suggest that transitional land uses and flexible zoning in low-exposure areas are key elements for attracting new development consistent with CG and offer insight into the challenges that local governments face understanding the types and rates of change that may be catalyzed in the broader urban processes of public and private sector climate adaptation in the built environment.

Climate change↗
DOE OSTI2017

Determining Physical Parameters of Shielded Uranium using Gamma Spectroscopy and the Differential Evolution Adaptive Metropolis (DREAM) Method

Inverse radiation transport is a well-established method for determining unknown parameters within a system that exhibits particle leakage. Two significant challenges of solving inverse transport problems are (1) to determine multiple unknowns without false convergence on local minima and (2) to be able to quantify uncertainty. It was recently demonstrated that the Differential Evolution Adaptive Metropolis (DREAM) method effectively meets both of these challenges. In Bledsoe's 2014 article, the DREAM method was only applied to numerical test cases in which measured data were simulated using MCNP. This paper provides results of research conducted at Oak Ridge National Laboratory (ORNL) in which DREAM was applied to two-dimensional inverse transport problems using real-world measurements. The DREAM method uses a Markov chain Monte Carlo (MCMC) method to obtain a posterior distribution of unknown parameters. In this application, the posterior distribution is determined by using a uniform prior distribution and a likelihood function. The goal of the inverse problem is to find the regions in which the likelihood function is at or near its maximum. In the traditional MCMC approach, a single Markov chain is employed. In practice, MCMC approaches have a high acceptance rate to solutions that are near the current point of sampling, but they exhibit slow convergence to solutions far from the sampling point. The DREAM algorithm was designed to alleviate this issue by initiating multiple Markov chains and using the differential evolution algorithm to generate trial points for each chain. Solving for the mass of radioactive material within a voluminous source is a challenging problem for gamma-ray spectroscopy. Inverse gamma-ray transport can supply a range of possible material compositions, but reducing the differences between predicted and actual measurements can lead to false results. DREAM is a rapid technique for determining the most likely solution for several unknown parameters in an inverse transport problem. This work applies DREAM to a series of gamma spectroscopy experiments performed at ORNL.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Simulating the Autonomous Future: A Look at Virtual Vehicle Environments and How to Validate Simulation Using Public Data Sets

The rapid evolution of autonomous vehicles (AVs) has exposed the need for fast-paced development and testing processes of a variety of perception, planning, and control algorithms. To expedite development, the AV industry and researchers leverage virtual vehicle environments to simulate a range of test scenarios that may otherwise be costly or difficult to conduct on a real test track. However, the various virtual environments may have different results depending on the fidelity of various simulation features, such as vehicle dynamics, sensor simulation, and environment recreation. Herein, this tutorial article examines a proposed framework for constructing, parameterizing, and validating a virtual vehicle environment using an existing AV data set. First, an overview of several open source and commercially available simulation tools, including their associated workflows, for scene and scenario creation is presented. Next, various open AV data sets are examined to inform the data set selection for the validation framework. Then, an example workflow of recreating a real-world scene from the selected data set in a simulation tool with various emulated sensors parameterized to match the data set is demonstrated. Finally, an example AV-perception algorithm is subjected to data streams from virtual and real-world environments and suggested metrics for analyzing the results are discussed.

42 ENGINEERING↗
DOE OSTI2021

It’s Time to Talk About HPC Storage: Perspectives on the Past and Future

High-performance computing (HPC) storage systems are a key component of the success of HPC to date. Recently, we have seen major developments in storage-related technologies, as well as changes to how HPC platforms are used, especially in relation to artificial intelligence and experimental data analysis workloads. Additionally, these developments merit a revisit of HPC storage system architectural designs. In this article, we discuss the drivers, identify key challenges to status quo posed by these developments, and discuss directions future research might take to unlock the potential of new technologies for the breadth of HPC applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Department of Energy/IDEA: More best-practices research

This article continues the overview of the U.S. Department of Energy and IDEA collaboration by highlighting additional case studies that demonstrate innovative engineering approaches in district energy systems. It focuses on how campuses are improving efficiency, integrating advanced technologies, and reducing energy use and emissions through data-driven strategies. The University of Cincinnati is featured for its highly efficient chilled water system, using advanced algorithms and upgraded “smart chillers” to optimize performance, reduce energy consumption, and lower costs. Wake Forest University emphasizes a data-informed modernization process, using system optimization and targeted building improvements to significantly boost efficiency and reduce overall energy use. Arizona Western College showcases creative solutions to extreme cooling demands, including system redesign, smart controls, and thermal storage to improve reliability and cut peak energy costs. Overall, the article demonstrates that combining innovative engineering, real-time data analysis, and system optimization can significantly enhance performance, reduce emissions, and deliver cost savings in district energy systems.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

Opportunities for enhancing MLCommons efforts while leveraging insights from educational MLCommons earthquake benchmarks efforts

MLCommons is an effort to develop and improve the artificial intelligence (AI) ecosystem through benchmarks, public data sets, and research. It consists of members from start-ups, leading companies, academics, and non-profits from around the world. The goal is to make machine learning better for everyone. In order to increase participation by others, educational institutions provide valuable opportunities for engagement. In this article, we identify numerous insights obtained from different viewpoints as part of efforts to utilize high-performance computing (HPC) big data systems in existing education while developing and conducting science benchmarks for earthquake prediction. As this activity was conducted across multiple educational efforts, we project if and how it is possible to make such efforts available on a wider scale. This includes the integration of sophisticated benchmarks into courses and research activities at universities, exposing the students and researchers to topics that are otherwise typically not sufficiently covered in current course curricula as we witnessed from our practical experience across multiple organizations. As such, we have outlined the many lessons we learned throughout these efforts, culminating in the need for benchmark carpentry for scientists using advanced computational resources. The article also presents the analysis of an earthquake prediction code benchmark while focusing on the accuracy of the results and not only on the runtime; notedly, this benchmark was created as a result of our lessons learned. Energy traces were produced throughout these benchmarks, which are vital to analyzing the power expenditure within HPC environments. Additionally, one of the insights is that in the short time of the project with limited student availability, the activity was only possible by utilizing a benchmark runtime pipeline while developing and using software to generate jobs from the permutation of hyperparameters automatically. It integrates a templated job management framework for executing tasks and experiments based on hyperparameters while leveraging hybrid compute resources available at different institutions. The software is part of a collection called cloudmesh with its newly developed components, cloudmesh-ee (experiment executor) and cloudmesh-cc (compute coordinator).

58 GEOSCIENCES↗
DOE OSTI2018

A Practical Approach to Sizing Neural Networks

Most approaches to machine learning experiments currently involve tedious hyperparameter tuning. This article first shows how to practically estimate the maximum size of a neural network given a training data set. We present four easily applicable rules to analytically determine the capacity of neural network architectures. The rules are derived based on MacKay’s information theoretic model of supervised machine learning [22]. This allows the comparison of the efficiency of different architectures independently of a task. Second, we introduce and experimentally validate a heuristic method to estimate the neural network capacity requirement for a given dataset and labeling. This allows an estimate of the required size of a neural network for a given problem. We conclude the article with a discussion on the consequences of sizing the network wrongly, which includes both increased computation effort for training as well as reduced generalization capability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

The ARM Climate Research Facility: A Review of Structure and Capabilities

The Atmospheric Radiation Measurement (ARM) program (www.arm.gov) is a Department of Energy, Office of Science, climate research user facility that provides atmospheric observations from diverse climatic regimes around the world. Use of ARM data is free and available to anyone through the ARM data archive. ARM is approaching 20 years of operations. In recent years, the facility has grown to add two mobile facilities and an aerial facility to its network of fixed-location sites. Over the past year, ARM has enhanced its observational capabilities with a broad array of new instruments at its fixed and mobile sites and the aerial facility. Instruments include scanning millimeter- and centimeter-wavelength radars; water vapor, cloud/aerosol extinction, and Doppler lidars; a suite of aerosol instruments for measuring optical, physical, and chemical properties; instruments including eddy correlation systems to expand measurements of the surface and boundary layer; and aircraft probes for measuring cloud and aerosol properties. Taking full advantage of these instruments will involve the development of complex data products. This work is underway but will benefit from engagement with the broader scientific community. In this article we will describe the current status of the ARM program with an emphasis on developments over the past eight years since ARM was designated a DOE scientific user facility. We will also describe the new measurement capabilities and provide thoughts for how these new measurements can be used to serve the climate research community with an invitation to the community to engage in the development and use of these data products.

Atmospheric Radiation Measurement↗
DOE OSTI2014

A reconsideration of the noise equivalent power and the data analysis procedure for the infrared imaging video bolometers

The infrared imaging video bolometer (IRVB) used for measurement of the two-dimensional (2D) radiation profiles from the Large Helical Device has been significantly upgraded recently to improve its signal to noise ratio, sensitivity, and calibration, which ultimately provides quantitative measurements of the radiation from the plasma. The reliability of the quantified data needs to be established by various checks. The noise estimates also need to be revised and more realistic values need to be established. It is shown that the 2D heat diffusion equation can be used for estimating the power falling on the IRVB foil, even with a significant amount of spatial variation in the thermal diffusivity across the area of the platinum foil found experimentally during foil calibration. The equation for the noise equivalent power density (NEPD) is re-derived to include the errors in the measurement of the thermophysical and the optical properties of the IRVB foil. The theoretical value estimated using this newly derived equation matches closely, within 5.5%, with the mean experimental value. The change in the contribution of each error term of the NEPD equation with rising foil temperature is also studied and the blackbody term is found to dominate the other terms at elevated operating temperatures. The IRVB foil is also sensitive to the charge exchange (CX) neutrals escaping from the plasma. The CX neutral contribution is estimated to be marginally higher than the noise equivalent power (NEP) of the IRVB. It is also established that the radiation measured by the IRVB originates from the impurity line radiation from the plasma and not from the heated divertor tiles. The change in the power density due to noise reduction measures such as data smoothing and averaging is found to be comparable to the IRVB NEPD. The precautions that need to be considered during background subtraction are also discussed with experimental illustrations. Finally, the analysis algorithm with all the improvements is validated and found to reproduce the input power well within 10% accuracy. This article answers many fundamental questions relevant to the IRVB and illustrates the care to be exercised while processing the IRVB data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2012

Mapping Impervious Surface Expansion using Medium-resolution Satellite Image Time Series: A Case Study in the Yangtze River Delta, China

Cities have been expanding rapidly worldwide, especially over the past few decades. Mapping the dynamic expansion of impervious surface in both space and time is essential for an improved understanding of the urbanization process, land-cover and land-use change, and their impacts on the environment. Landsat and other medium-resolution satellites provide the necessary spatial details and temporal frequency for mapping impervious surface expansion over the past four decades. Since the US Geological Survey opened the historical record of the Landsat image archive for free access in 2008, the decades-old bottleneck of data limitation has gone. Remote-sensing scientists are now rich with data, and the challenge is how to make best use of this precious resource. In this article, we develop an efficient algorithm to map the continuous expansion of impervious surface using a time series of four decades of medium-resolution satellite images. The algorithm is based on a supervised classification of the time-series image stack using a decision tree. Each imerpervious class represents urbanization starting in a different image. The algorithm also allows us to remove inconsistent training samples because impervious expansion is not reversible during the study period. The objective is to extract a time series of complete and consistent impervious surface maps from a corresponding times series of images collected from multiple sensors, and with a minimal amount of image preprocessing effort. The approach was tested in the lower Yangtze River Delta region, one of the fastest urban growth areas in China. Results from nearly four decades of medium-resolution satellite data from the Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper plus (ETM+) and China-Brazil Earth Resources Satellite (CBERS) show a consistent urbanization process that is consistent with economic development plans and policies. The time-series impervious spatial extent maps derived from this study agree well with an existing urban extent polygon data set that was previously developed independently. The overall mapping accuracy was estimated at about 92.5% with 3% commission error and 12% omission error for the impervious type from all images regardless of image quality and initial spatial resolution.

Gao, Feng↗