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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Thermal and Pressure Characterization of a Wind Tunnel Force Balance Using the Single Vector System

Wind tunnel research at NASA Langley Research Center s 31-inch Mach 10 hypersonic facility utilized a 5-component force balance, which provided a pressurized flow-thru capability to the test article. The goal of the research was to determine the interaction effects between the free-stream flow and the exit flow from the reaction control system on the Mars Science Laboratory aeroshell during planetary entry. In the wind tunnel, the balance was exposed to aerodynamic forces and moments, steady-state and transient thermal gradients, and various internal balance cavity pressures. Historically, these effects on force measurement accuracy have not been fully characterized due to limitations in the calibration apparatus. A statistically designed experiment was developed to adequately characterize the behavior of the balance over the expected wind tunnel operating ranges (forces/moments, temperatures, and pressures). The experimental design was based on a Taylor-series expansion in the seven factors for the mathematical models. Model inversion was required to calculate the aerodynamic forces and moments as a function of the strain-gage readings. Details regarding transducer on-board compensation techniques, experimental design development, mathematical modeling, and wind tunnel data reduction are included in this paper.

Lynn, Keith C.↗
NASA NTRS1989

Measurement of surface microtopography using helicopter-mounted stereo film cameras and two stereo matching techniques

A common problem in acquiring ground-truth data for use in microwave interaction modeling is the capture of surface roughness data that are both sampled at distances comparable to a fraction of the wavelength and extensive enough to represent the surface statistics in at least one resolution cell of the microwave remote sensor used. A technique has been developed for acquiring the necessary photogrammetric data using twin 70-mm film cameras mounted on a helicopter boom. The apparatus is described, and the accuracy with which ground surface roughness can be characterized using this device is estimated. Both standard and cross-correlation methods were used for data reduction. Stereogrammetry is compared with a completely automated image-matching technique. Dense disparity images were generated from the helicopter stereo pairs. Using interior orientation parameters supplied by the camera manufacturers, and assuming that exterior orientation parameters remain constant between control target and test field photography, an extremely dense DEM (digital elevation model) for a test field has been derived. Results are compared, and accuracy estimates are presented.

Wall, S. D.↗
DOE OSTI2023

SonicPy: a suite of programs for ultrasound pulse-echo data acquisition and analysis

Sound speed and elastic constants measurements in solids and liquids are commonly performed using the ultrasound pulse-echo technique. Recent advances have expanded the use of this technique at numerous high pressure synchrotron beamlines and offline laboratories. However, the increased experimental throughput has revealed many limitations in existing software for handling the rapid measurement and the subsequent data-reduction. Here, we report the development of a collection of computer programs for sound speed measurements using the ultrasound pulse-echo technique, compatible with stepped multi-frequency, as well as broadband-pulse, couplant-corrected methods. The programs provide a highly interactive graphical interface, enable efficient measurement, exploration and near real-time analysis of the ultrasound data, and contain features useful for working with samples under high pressure and/or high temperature. The included analysis programs can alleviate the time required for data reduction from hours to less than a minute, allowing users to make timely and informed decisions regarding the appropriate experimental parameters.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1977

Analyses of atmospheric extinction data obtained by astronomers. I - A time-trend analysis of data with internal accidental errors obtained at four observatories

Long-term time-trend analysis was performed on astronomical atmospheric extinction data in wideband UBV and various narrow-band systems recorded at Cerro Tololo, Kitt Peak, Lick, and McDonald observatories. All of the data had to be transformed into uniform monochromatic extinction data before trend analysis could be performed. The paper describes the various reduction techniques employed. The time-trend analysis was then carried out by the method of least squares. A special technique, called 'histogram shaping', was employed to adjust for the fact that the errors of the reduced monochromatic extinction data were not essentially Gaussian. On the assumption that there are no compensatory background and local extinction changes, the best values obtained for extinction trends due to background aerosol changes during the years 1960 to 1972 are 0.006 + or - 0.013 (rms) and 0.009 + or - 0.009 (rms) stellar magnitudes per air mass per decade in the blue and yellow wavelength regions, respectively.

Taylor, B. J.↗
NASA NTRS1988

Research in planetary astronomy

The objective is the continuation of a long-term research program designed to study the composition, structure and processes operating on the surfaces of solar system objects using the Mauna Kea Observatory with techniques and modern instrumentation. Reflectance spectroscopy and multispectral imaging in the spectral region, 0.3 to 5.0 micrometer are the major techniques used, although thermal (10 micrometer and 20 micrometer) radiometry are used in some aspects of the research. Some specific projects include: (1) systematic spectral imaging observations of the Moon; (2) systematic spectral imaging and spectral monitoring of the Martian surface; (3) thermal radiometry of asteroids as part of the IRAS follow-up and other target specific programs; (4) searches for asteroid satellites and dust belts using a stellar coronagraph; and (5) studies of circumstellar disks using a stellar coronagraph. Progress for each of the programs included is discussed. minerals; (2) completed observations of lunar multi-ringed basins and crater deposits in search of high-Ca spectral anomalies; (3) completed data reduction of an additional 5 asteroids observed by the coronagraphic technique in the search for asteroids satellites and debris clouds; and (4) completed the reduction and calibration of 350 asteroids observed at 10 micron and 20 micron using the NASA IRTF.

Mccord, Thomas B.↗
NASA NTRS1975

Flight flutter testing using pulse techniques

A case of flutter developed at a speed lower than had been flown previously. This incident precipitated the routine procedure of pulsing control surfaces as well as the firing of explosive charges during speed build-ups. In the interest of rapid evaluation of results, simple methods of data reduction were used. A case history is presented where in the pulse technique predicted flutter by extrapolating decay rates obtained at subcritical speeds; in addition, a case is presented where no valid extrapolation could be made.

Stringham, R. H., Jr.↗
NASA NTRS1979

A rocket-borne pulse-height analyzer for energetic particle measurements

The pulse-height analyzer basically resembles a time-sharing multiplexing data-acquisition system which acquires analog data (from energetic particle spectrometers) and converts them into digital code. The PHA simultaneously acquires pulse-height information from the analog signals of the four input channels and sequentially multiplexes the digitized data to a microprocessor. The PHA together with the microprocessor form an on-board real-time data-manipulation system. The system processes data obtained during the rocket flight and reduces the amount of data to be sent back to the ground station. Consequently the data-reduction process for the rocket experiments is speeded up. By using a time-sharing technique, the throughput rate of the microprocessor is increased. Moreover, data from several particle spectrometers are manipulated to share one information channel; consequently, the TM capacity is increased.

Leung, W.↗
DOE OSTI2024

Beyond PCA: Additional Dimension Reduction Techniques to Consider in the Development of Climate Fingerprints

Abstract Dimension reduction techniques are an essential part of the climate analyst’s toolkit. Due to the enormous scale of climate data, dimension reduction methods are used to identify major patterns of variability within climate dynamics, to create compelling and informative visualizations, and to quantify major named modes such as El Niño–Southern Oscillation. Principal components analysis (PCA), also known as the method of empirical orthogonal functions (EOFs), is the most commonly used form of dimension reduction, characterized by a remarkable confluence of attractive mathematical, statistical, and computational properties. Despite its ubiquity, PCA suffers from several difficulties relevant to climate science: high computational burden with large datasets, decreased statistical accuracy in high dimensions, and difficulties comparing across multiple datasets. In this paper, we introduce several variants of PCA that are likely to be of use in climate sciences and address these problems. Specifically, we introduce non-negative , sparse , and tensor PCA and demonstrate how each approach provides superior pattern recognition in climate data. We also discuss approaches to comparing PCA-family results within and across datasets in a domain-relevant manner. We demonstrate these approaches through an analysis of several runs of the E3SM climate model from 1991 to 1995, focusing on the simulated response to the Mt. Pinatubo eruption; our findings are consistent with a recently identified stratospheric warming fingerprint associated with this type of stratospheric aerosol injection.

Weylandt, Michael↗
DOE OSTI2022

Unsupervised Machine Learning for Exploratory Data Analysis of Exoplanet Transmission Spectra

Abstract Transit spectroscopy is a powerful tool for decoding the chemical compositions of the atmospheres of extrasolar planets. In this paper, we focus on unsupervised techniques for analyzing spectral data from transiting exoplanets. After cleaning and validating the data, we demonstrate methods for: (i) initial exploratory data analysis, based on summary statistics (estimates of location and variability); (ii) exploring and quantifying the existing correlations in the data; (iii) preprocessing and linearly transforming the data to its principal components; (iv) dimensionality reduction and manifold learning; (v) clustering and anomaly detection; and (vi) visualization and interpretation of the data. To illustrate the proposed unsupervised methodology, we use a well-known public benchmark data set of synthetic transit spectra. We show that there is a high degree of correlation in the spectral data, which calls for appropriate low-dimensional representations. We explore a number of different techniques for such dimensionality reduction and identify several suitable options in terms of summary statistics, principal components, etc. We uncover interesting structures in the principal component basis, namely well-defined branches corresponding to different chemical regimes of the underlying atmospheres. We demonstrate that those branches can be successfully recovered with a K-means clustering algorithm in a fully unsupervised fashion. We advocate for lower-dimensional representations of the spectroscopic data in terms of the main principal components, in order to reveal the existing structure in the data and quickly characterize the chemical class of a planet.

Matchev, Konstantin T. (ORCID:0000000341829096)↗
NASA NTRS1993

Flux measurements using the BATSE spectroscopic detectors

Among the Compton Gama-Ray Observatory instruments, the BATSE Spectroscopic Detectors (SD) have the distinction of being able to detect photons of energies less than about 20 keV. This is an interesting energy range for the examination of low mass X-ray binaries (LMXB's). In fact, Sco X-1, the prototype LMXB, is easily seen even in the raw BATSE spectroscopic data. The all-sky coverage afforded by these detectors offers a unique opportunity to monitor this source over time periods never before possible. The aim of this investigation was to test a number of ways in which both continous and discrete flux measurements can be obtained using the BATSE spectroscopic datasets. A instrumental description of a SD can be found in the Compton Workshop of Apr. 1989, this report will deal only with methods which can be used to analyze its datasets. Many of the items discussed below, particularly in regard to the earth occultation technique, have been developed, refined, and applied by the BATSE team to the reduction of BATSE LAD data. Code written as part of this project utilizes portions of that work. The following discussions will first address issues related to the reduction of SD datasets using the earth occultation technique. It will then discuss methods for the recovery of the flux history of strong sources while they are above the earth's limb. The report will conclude with recommended reduction procedures.

Mcnamara, Bernard↗
NASA NTRS2002

Spectral Data Reduction via Wavelet Decomposition

The greatest advantage gained from hyperspectral imagery is that narrow spectral features can be used to give more information about materials than was previously possible with broad-band multispectral imagery. For many applications, the new larger data volumes from such hyperspectral sensors, however, present a challenge for traditional processing techniques. For example, the actual identification of each ground surface pixel by its corresponding reflecting spectral signature is still one of the most difficult challenges in the exploitation of this advanced technology, because of the immense volume of data collected. Therefore, conventional classification methods require a preprocessing step of dimension reduction to conquer the so-called "curse of dimensionality." Spectral data reduction using wavelet decomposition could be useful, as it does not only reduce the data volume, but also preserves the distinctions between spectral signatures. This characteristic is related to the intrinsic property of wavelet transforms that preserves high- and low-frequency features during the signal decomposition, therefore preserving peaks and valleys found in typical spectra. When comparing to the most widespread dimension reduction technique, the Principal Component Analysis (PCA), and looking at the same level of compression rate, we show that Wavelet Reduction yields better classification accuracy, for hyperspectral data processed with a conventional supervised classification such as a maximum likelihood method.

Kaewpijit, S.↗
NASA NTRS2001

Determining Aerodynamic Loads Based on Optical Deformation Measurements

This paper describes a videogram metric technique for determining aerodynamic loads based on optical elastic deformation measurements. The data reduction methods are developed to extract the normal force and pitching moment from beam deformation data. The axial force is obtained by measuring the axial translational motion of a movable shaft in a spring/bearing device. Proof-of-concept calibration experiments are conducted to assess the accuracy of this optical technique.

Liu, Tianshu↗
NASA NTRS2001

Determining Aerodynamic Loads Based on Optical Deformation Measurements

This paper describes a videogrammetric technique for determining aerodynamic loads based on optical elastic deformation measurements. The data reduction methods are developed to extract the normal force and pitching moment from beam deformation data. The axial force is obtained by measuring the axial translational motion of a movable shaft in a spring/bearing device. Proof-of-concept calibration experiments are conducted to assess the accuracy of this optical technique.

Liu, Tianshu↗
DOE OSTI2022

Multimodal X-ray nano-spectromicroscopy analysis of chemically heterogeneous systems

Abstract Understanding the nanoscale chemical speciation of heterogeneous systems in their native environment is critical for several disciplines such as life and environmental sciences, biogeochemistry, and materials science. Synchrotron-based X-ray spectromicroscopy tools are widely used to understand the chemistry and morphology of complex material systems owing to their high penetration depth and sensitivity. The multidimensional (4D+) structure of spectromicroscopy data poses visualization and data-reduction challenges. This paper reports the strategies for the visualization and analysis of spectromicroscopy data. We created a new graphical user interface and data analysis platform named XMIDAS (X-ray multimodal image data analysis software) to visualize spectromicroscopy data from both image and spectrum representations. The interactive data analysis toolkit combined conventional analysis methods with well-established machine learning classification algorithms (e.g. nonnegative matrix factorization) for data reduction. The data visualization and analysis methodologies were then defined and optimized using a model particle aggregate with known chemical composition. Nanoprobe-based X-ray fluorescence (nano-XRF) and X-ray absorption near edge structure (nano-XANES) spectromicroscopy techniques were used to probe elemental and chemical state information of the aggregate sample. We illustrated the complete chemical speciation methodology of the model particle by using XMIDAS. Next, we demonstrated the application of this approach in detecting and characterizing nanoparticles associated with alveolar macrophages. Our multimodal approach combining nano-XRF, nano-XANES, and differential phase-contrast imaging efficiently visualizes the chemistry of localized nanostructure with the morphology. We believe that the optimized data-reduction strategies and tool development will facilitate the analysis of complex biological and environmental samples using X-ray spectromicroscopy techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Understanding and Estimating Error Propagation in Neural Networks for Scientific Data Analysis

Neural networks are increasingly integrated into scientific discovery, where input data reduction and model quantization play a key role in accelerating inference. However, understanding and mitigating the impact of these techniques on output error is critical for ensuring reliable results, particularly in tasks demanding high numerical precision. This paper introduces a comprehensive framework for optimizing neural network inference in scientific computing by combining data reduction and weight quantization while maintaining error-controlled outcomes. We develop theoretical analyses to bound error propagation under these reductions and propose a framework that balances computational performance with error constraints. Evaluation on real-world learning-based combustion simulations and satellite image classification demonstrates that our derived error bounds accurately predict observed errors while enabling significant computational speedup under our framework. This work highlights the potential for further leveraging advancements in modern lossy compression algorithms and hardware accelerators that support lower-precision formats.

He, Weiming [New Jersey Institute of Technology]↗
NASA NTRS1978

GEOS-3 coherent C-band tracking data reduction and analysis

The availability of a coherent C-Band transponder on an orbiting vehicle has permitted the development of calibration techniques for C-Band radars. Prior coherent tracking was limited to test vehicles in powered flight or skin tracking of orbiting spacecraft. The pulse Doppler range rate data available concurrently and independently with normal range and angle data provides an extremely useful data set for assessing the internal consistency of the radars measurements, particularly when coupled with a trajectory well constrained by orbit dynamics. In order to further assess the precision of the range rate data, a technique was developed to numerically integrate the rate measurements into a pseudo-range data set showing extremely low noise and high sensitivity to systematic radar errors. Evaluation of integrated range data led to improvements in calibration of both the rate and conventional range data. In particular, proper evaluation of the very sensitive integrated ranges required the development of a processing correction for beacon delay variation with signal strength, a significant error in the conventional ranging data.

Krabill, W. B.↗
DOE OSTI2021

Electrochemical measurement and analysis of YCl 3 , ScCl 3 , GdCl 3 and MgCl 2 in molten eutectic LiCl-KCl

For this work, electrochemical measurements of YCl 3 , ScCl 3 , GdCl 3 and MgCl 2 were obtained in molten LiCl-KCl eutectic at 773 K using a three-electrode configuration. Tungsten rods were used as the working and counter electrodes. Two quasi- and one reference electrode(s) (glassy carbon, nickel wire, and Ni/NiO) were used to collect electrochemical measurements of the analyte salts. Cyclic voltammetry data were analyzed to calculate values of diffusion coefficient, exchange current density, and charge transfer resistance and were determined to be on the order of 10 –5 cm 2 s –1 , 10 –2 A cm –2 , and 10 0 Ω; respectively. In general, the values of diffusion coefficients were found to be consistent with those reported of high-temperature molten salts. Relatively large values of exchange current density corresponded with smaller values of charge transfer resistance. These values were found to be reasonable in comparison to results available in the literature. The measured cyclic voltammograms were normalized with respect to both lithium reduction and chloride ion oxidation potentials. Such a normalization technique is effective for comparing experimentally obtained cyclic voltammetry data to those that have been published. An analysis of experimentally obtained results indicates the relation of electrode reactions (e.g., differences of reduction potentials) are independent of the choice of reference electrode. Additionally, the choice of reference electrode did not affect the electrochemical window, exchange current density, or diffusion coefficient values.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2011

The Impact of Traffic Prioritization on Deep Space Network Mission Traffic

A select number of missions supported by NASA's Deep Space Network (DSN) are demanding very high data rates. For example, the Kepler Mission was launched March 7, 2009 and at that time required the highest data rate of any NASA mission, with maximum rates of 4.33 Mb/s being provided via Ka band downlinks. The James Webb Space Telescope will require a maximum 28 Mb/s science downlink data rate also using Ka band links; as of this writing the launch is scheduled for a June 2014 launch. The Lunar Reconnaissance Orbiter, launched June 18, 2009, has demonstrated data rates at 100 Mb/s at lunar-Earth distances using NASA's Near Earth Network (NEN) and K-band. As further advances are made in high data rate space telecommunications, particularly with emerging optical systems, it is expected that large surges in demand on the supporting ground systems will ensue. A performance analysis of the impact of high variance in demand has been conducted using our Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) simulation tool. A comparison is made regarding the incorporation of Quality of Service (QoS) mechanisms and the resulting ground-to-ground Wide Area Network (WAN) bandwidth necessary to meet latency requirements across different user missions. It is shown that substantial reduction in WAN bandwidth may be realized through QoS techniques when low data rate users with low-latency needs are mixed with high data rate users having delay-tolerant traffic.

prioritization↗