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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Statistical Decomposition and Machine Learning to Clean In Situ Spaceflight Magnetic Field Measurements

Robust in situ magnetic field measurements are critical to understanding the various mechanisms that couple mass, momentum, and energy throughout our solar system. However, the spacecraft on which magnetometers are often deployed contaminate the magnetic field measurements via onboard subsystems including reaction wheels and magnetorquers. Two magnetometers can be deployed at different distances from the spacecraft to determine an approximation of the interfering field for subsequent removal, but constant data streams from both magnetometers can be impractical due to power and telemetry limitations. Here we propose a method to identify and remove time-varying magnetic interference from sources such as reaction wheels using statistical decomposition and convolutional neural networks, providing high-fidelity magnetic field data even in cases where dual-sensor measurements are not constantly available. For example, a measurement interval from the Parker Solar Probe outboard magnetometer experienced a 95.1% reduction in reaction wheel interference following application of the proposed technique.

magnetic field data↗
DOE OSTI2024

Machine learning in materials research: Developments over the last decade and challenges for the future

The number of studies that apply machine learning (ML) to materials science has been growing at a rate of approximately 1.67 times per year over the past decade. In this review, I examine this growth in various contexts. First, I present an analysis of the most commonly used tools (software, databases, materials science methods, and ML methods) used within papers that apply ML to materials science. The analysis demonstrates that despite the growth of deep learning techniques, the use of classical machine learning is still dominant as a whole. It also demonstrates how new research can effectively build upon past research, particular in the domain of ML models trained on density functional theory calculation data. Next, I present the progression of best scores as a function of time on the matbench materials science benchmark for formation enthalpy prediction. In particular, a dramatic improvement of 7 times reduction in error is obtained when progressing from feature-based methods that use conventional ML (random forest, support vector regression, etc.) to the use of graph neural network techniques. Finally, I provide views on future challenges and opportunities, focusing on data size and complexity, extrapolation, interpretation, access, and relevance.

36 MATERIALS SCIENCE↗
NASA NTRS1997

Controls/CFD Interdisciplinary Research Software Generates Low-Order Linear Models for Control Design From Steady-State CFD Results

The NASA Lewis Research Center is developing analytical methods and software tools to create a bridge between the controls and computational fluid dynamics (CFD) disciplines. Traditionally, control design engineers have used coarse nonlinear simulations to generate information for the design of new propulsion system controls. However, such traditional methods are not adequate for modeling the propulsion systems of complex, high-speed vehicles like the High Speed Civil Transport. To properly model the relevant flow physics of high-speed propulsion systems, one must use simulations based on CFD methods. Such CFD simulations have become useful tools for engineers that are designing propulsion system components. The analysis techniques and software being developed as part of this effort are an attempt to evolve CFD into a useful tool for control design as well. One major aspect of this research is the generation of linear models from steady-state CFD results. CFD simulations, often used during the design of high-speed inlets, yield high resolution operating point data. Under a NASA grant, the University of Akron has developed analytical techniques and software tools that use these data to generate linear models for control design. The resulting linear models have the same number of states as the original CFD simulation, so they are still very large and computationally cumbersome. Model reduction techniques have been successfully applied to reduce these large linear models by several orders of magnitude without significantly changing the dynamic response. The result is an accurate, easy to use, low-order linear model that takes less time to generate than those generated by traditional means. The development of methods for generating low-order linear models from steady-state CFD is most complete at the one-dimensional level, where software is available to generate models with different kinds of input and output variables. One-dimensional methods have been extended somewhat so that linear models can also be generated from two- and three-dimensional steady-state results. Standard techniques are adequate for reducing the order of one-dimensional CFD-based linear models. However, reduction of linear models based on two- and three-dimensional CFD results is complicated by very sparse, ill-conditioned matrices. Some novel approaches are being investigated to solve this problem.

Melcher, Kevin J.↗
NASA NTRS1989

The determination of third order linear models from a seventh order nonlinear jet engine model

Results are presented that demonstrate how good reduced-order models can be obtained directly by recursive parameter identification using input/output (I/O) data of high-order nonlinear systems. Three different methods of obtaining a third-order linear model from a seventh-order nonlinear turbojet engine model are compared. The first method is to obtain a linear model from the original model and then reduce the linear model by standard reduction techniques such as residualization and balancing. The second method is to identify directly a third-order linear model by recursive least-squares parameter estimation using I/O data of the original model. The third method is to obtain a reduced-order model from the original model and then linearize the reduced model. Frequency responses are used as the performance measure to evaluate the reduced models. The reduced-order models along with their Bode plots are presented for comparison purposes.

Lalonde, Rick J.↗
DOE OSTI2022

Efficient Data Query for Gaussian Process Compressed Data through Value Range Estimation [Slides]

When the resolution of the data increases, data reduction methods are applied to simulation output, including Gaussian process, neural representation and compression algorithms. Lots of data analysis/visualization techniques requires data query, but data query from reduced representation is still challenging. This report will provide examples and provide possible answers to why data query from reduced representation is still challenging.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1972

Development of procedures for calculating stiffness and damping properties of elastomers in engineering applications. Part 1: Verification of basic methods

The primary aim of this investigation was verification of basic methods which are to be used in cataloging elastomer dynamic properties (stiffness and damping) in terms of viscoelastic model constants. These constants may then be used to predict dynamic properties for general elastomer shapes and operating conditions, thereby permitting optimum application of elastomers as energy absorption and/or energy storage devices in the control of vibrations in a broad variety of applications. The efforts reported involved: (1) literature search; (2) the design, fabrication and use of a test rig for obtaining elastomer dynamic test data over a wide range of frequencies, amplitudes, and preloads; and (3) the reduction of the test data, by means of a selected three-element elastomer model and specialized curve fitting techniques, to material properties. Material constants thus obtained have been used to calculate stiffness and damping for comparison with measured test data. These comparisons are excellent for a number of test conditions and only fair to poor for others. The results confirm the validity of the basic approach of the overall program and the mechanics of the cataloging procedure, and at the same time suggest areas in which refinements should be made.

Chiang, T.↗
NASA NTRS1972

Quantitative simultaneous multi-element microprobe analysis using combined wavelength and energy dispersive systems

A combined WDS-EDS system obviates the severe X-ray peak overlap problems encountered with Na, Mg, Al and Si common to pure EDS systems. By application of easily measured empirical correction factors for pulse pile-up and peak overlaps which are normally observed in the analysis of silicate minerals, the accuracy of analysis is comparable with that expected for WDS electron microprobe analyses. The continuum backgrounds are subtracted for the spectra by a spline fitting technique based on integrated intensities between the peaks. The preprocessed data are then reduced to chemical analyses by existing data reduction programs.

Walter, L. S.↗
NASA NTRS1978

Automatic welding of stainless steel tubing

The use of automatic welding for making girth welds in stainless steel tubing was investigated as well as the reduction in fabrication costs resulting from the elimination of radiographic inspection. Test methodology, materials, and techniques are discussed, and data sheets for individual tests are included. Process variables studied include welding amperes, revolutions per minute, and shielding gas flow. Strip chart recordings, as a definitive method of insuring weld quality, are studied. Test results, determined by both radiographic and visual inspection, are presented and indicate that once optimum welding procedures for specific sizes of tubing are established, and the welding machine operations are certified, then the automatic tube welding process produces good quality welds repeatedly, with a high degree of reliability. Revised specifications for welding tubing using the automatic process and weld visual inspection requirements at the Kennedy Space Center are enumerated.

Clautice, W. E.↗
NASA NTRS1985

An Eigensystem Realization Algorithm (ERA) for modal parameter identification and model reduction

A method, called the Eigensystem Realization Algorithm (ERA), is developed for modal parameter identification and model reduction of dynamic systems from test data. A new approach is introduced in conjunction with the singular value decomposition technique to derive the basic formulation of minimum order realization which is an extended version of the Ho-Kalman algorithm. The basic formulation is then transformed into modal space for modal parameter identification. Two accuracy indicators are developed to quantitatively identify the system modes and noise modes. For illustration of the algorithm, examples are shown using simulation data and experimental data for a rectangular grid structure.

Juang, J. N.↗
NASA NTRS1986

A fast-response aspirating probe for measurements of total temperature and pressure in transonic cryogenic wind tunnel

A newly developed, 3-mm-diam, dual hot-wire aspirating probe was used to measure the time-resolved stagnation temperature and pressure in a transonic cryogenic wind tunnel. The probe consists of two coplanar constant temperature hot wires at different overheat ratios operating in a 1.5-mm-diam channel with a choked exit. Thus, the constant Mach number flow by the wires is influenced only by free-stream stagnation temperature and pressure. Diffusion of the free-stream Mach number to a lower value in the channel reduces the dynamic drag on the hot-wire. Frequency response of the present design is dc to 20 kHz. The probe was used to measure the unsteady wake shed from an oscillating airfoil tested in the 0.3-m Transonic Cryogenic Tunnel at NASA-Langley Research Center. The hot-wire lasted for more than ten hours before breaking, proving the ruggedness of the probe and the usefulness of the technique in a high dynamic pressure, transonic cryogenic wind tunnel. Typical data obtained from the experiment are presented after reduction to stagnation pressure and temperature.

Ng, W.-F.↗
NASA NTRS1992

Importance of Geosat orbit and tidal errors in the estimation of large-scale Indian Ocean variations

To improve the estimate accuracy of large-scale meridional sea-level variations, Geosat ERM data on the Indian Ocean for a 26-month period were processed using two different techniques of orbit error reduction. The first technique removes an along-track polynomial of degree 1 over about 5000 km and the second technique removes an along-track once-per-revolution sine wave about 40,000 km. Results obtained show that the polynomial technique produces stronger attenuation of both the tidal error and the large-scale oceanic signal. After filtering, the residual difference between the two methods represents 44 percent of the total variance and 23 percent of the annual variance. The sine-wave method yields a larger estimate of annual and interannual meridional variations.

Perigaud, Claire↗
NASA NTRS2001

The Nature of the Vela Supernova Remnant as Revealed by O VI and C IV Absorption

Highly ionized gas, in particular C IV and O VI, is produced in the interstellar medium in regions with hot (T approx. 10(exp 6) K) X-ray emitting gas and at the boundaries where hot gas and cooler (T approx. 10(exp 4) K) gas interact. Supernova remnant shocks produce most of the hot gas in the ISM and, if they are in the correct range of speeds, should produce observable quantities of C IV and O VI absorption. In turn, the column densities of these ions are potentially powerful diagnostics of the shock speed and interstellar environment in which the SNR is evolving. With the advent of FUSE, the power of this diagnostic technique is now available. We have FUSE data toward 8 stars behind the Vela SNR, and have developed a data reduction and analysis method that produces reasonably reliable O VI column densities, in spite of the complexities of the FUSE spectra in this region. In order to gain insight into the observational results, the Vela SNR evolution was modelled using Piecewise Parabolic Method numerical hydrodynamics code. The code is 1-D and incorporates non-equilibrium ionization, radiative cooling, thermal conduction and magnetic pressure.

Lines, Nichols J.↗
NASA NTRS2004

A Method for Estimating Noise from Full-Scale Distributed Exhaust Nozzles

A method to estimate the full-scale noise suppression from a scale model distributed exhaust nozzle (DEN) is presented. For a conventional scale model exhaust nozzle, Strouhal number scaling using a scale factor related to the nozzle exit area is typically applied that shifts model scale frequency in proportion to the geometric scale factor. However, model scale DEN designs have two inherent length scales. One is associated with the mini-nozzles, whose size do not change in going from model scale to full scale. The other is associated with the overall nozzle exit area which is much smaller than full size. Consequently, lower frequency energy that is generated by the coalesced jet plume should scale to lower frequency, but higher frequency energy generated by individual mini-jets does not shift frequency. In addition, jet-jet acoustic shielding by the array of mini-nozzles is a significant noise reduction effect that may change with DEN model size. A technique has been developed to scale laboratory model spectral data based on the premise that high and low frequency content must be treated differently during the scaling process. The model-scale distributed exhaust spectra are divided into low and high frequency regions that are then adjusted to full scale separately based on different physics-based scaling laws. The regions are then recombined to create an estimate of the full-scale acoustic spectra. These spectra can then be converted to perceived noise levels (PNL). The paper presents the details of this methodology and provides an example of the estimated noise suppression by a distributed exhaust nozzle compared to a round conic nozzle.

Kinzie, Kevin W.↗
NASA NTRS2009

Advanced Laser Based Measurements in Porous Media Combustion

We present measurements using dual-pump dual-broadband coherent anti-Stokes Raman scattering spectroscopy (DP-DBB-CARS) inside a porous media burner. This work continues our previous measurements in such combustion systems. The existing setup was significantly modified with the aim of providing improved data quality and data rate, reduction of interferences and additional species information. These changes are presented and discussed in detail. The CARS technique was expanded to a dual-pump dual-broadband CARS system which in principle enables acquisition of temperatures together with relative H2/N2- and O2/N2- species concentrations. Experimental complexity was reduced by the use of a modified spectrometer enabling the detection of both signals, vibrational and rotational CARS, with only one detection system.

Tedder, Sarah A.↗
NASA NTRS2017

Overview of SLS Aeroacoustic Environment Development

The Space Launch System (SLS) ascent aeroacoustic environments provide the externally driven noise levels predicted for vehicle ascent during transonic and supersonic flight, and serve as an important input for component and secondary structure vibroacoustic design criteria. This aerodynamically induced noise is predominantly generated by unsteady flow within the local boundary layer due to free stream interaction with the outer mold line (OML). Additional sources are shear flow interactions, shocks, protuberance flows, and wake flows. This presentation provides an overview of the aeroacoustics discipline along with the SLS environment development process, including wind tunnel testing and general data reduction methods. The state of the discipline is also presented with a summary of aeroacoustic measurement and computational techniques currently on the horizon.

Steva, Thomas↗
NASA NTRS1992

Astronomical CCD observing and reduction techniques

CCD instrumentation and techniques in observational astronomy are surveyed. The general topics addressed include: history of large array scientific CCD imagers; noise sources and reduction processes; basic photometry techniques; introduction to differential time-series astronomical photometry using CCDs; 2D imagery; point source spectroscopy; extended object spectrophotometry; introduction to CCD astrometry; solar system applications for CCDs; CCD data; observing with infrared arrays; image processing, data analysis software, and computer systems for CCD data reduction and analysis. (No individual items are abstracted in this volume)

Howell, Steve B.↗
NASA NTRSDate not supplied

More Data Needed for Failure Rate Estimation, Validation, and Uncertainty Reduction

The currently planned schedule for advanced Environmental Control and Life Support System (ECLSS) development and test activities to support human exploration missions is unlikely to generate sufficient data to enable statistically-supportable, precise Orbital Replacement Unit (ORU) failure rate estimates to meet existing crew safety expectations. Accurate and precise failure rate estimates are critical for missions beyond Low Earth Orbit (LEO) because current risk mitigation approaches –namely regular resupply and rapid abort capabilities –will not be available. Safe operations will depend on mission planners’ ability to accurately forecast spares demand and efficiently provide the necessary resources. However, even after more than a decade of International Space Station (ISS) ECLSS operations, a significant amount of uncertainty remains in failure rate estimates. Uncertain or inaccurate failure rates result in increased risk and spares mass. A Bayesian estimation approach, such as the one currently implemented by the ISS Program, can reduce uncertainty by incorporating engineering judgement into failure rate estimates. However, experience on the ISS and with other complex systems shows that these prior failure rate estimates are often inaccurate. In addition, prior estimates are typically point values; some level of uncertainty must be added to convert these into probability distributions for Bayesian updating, and there are several potential methods for doing so. Due to the low rate of data collection, any inaccuracy in theseprior estimates currently hasa strong influence on the end result. This paper examines the challenges associated with failure rate estimation, validation, and uncertainty reduction in the context of ECLSS development for beyond-LEO missions. A variety of techniques for generating and updating Bayesian priors are discussed and evaluated using both real-world and simulated data. Potential solutions for improving failure rate estimation, including testing additional units, are analyzed and discussed, and a set of recommendations are provided for next-generation system development activities.

Reliability↗
NASA NTRSDate not supplied

More Data Needed for Failure Rate Estimation, Validation, and Uncertainty Reduction

The currently planned schedule for advanced Environmental Control and Life Support System (ECLSS) development and test activities to support human exploration missions is unlikely to generate sufficient data to enable statistically-supportable, precise Orbital Replacement Unit (ORU) failure rate estimates to meet existing crew safety expectations. Accurate and precise failure rate estimates are critical for missions beyond Low Earth Orbit (LEO) because current risk mitigation approaches –namely regular resupply and rapid abort capabilities –will not be available. Safe operations will depend on mission planners’ ability to accurately forecast spares demand and efficiently provide the necessary resources. However, even after more than a decade of International Space Station (ISS) ECLSS operations, a significant amount of uncertainty remains in failure rate estimates. Uncertain or inaccurate failure rates result in increased risk and spares mass. A Bayesian estimation approach, such as the one currently implemented by the ISS Program, can reduce uncertainty by incorporating engineering judgement into failure rate estimates. However, experience on the ISS and with other complex systems shows that these prior failure rate estimates are often inaccurate. In addition, prior estimates are typically point values; some level of uncertainty must be added to convert these into probability distributions for Bayesian updating, and there are several potential methods for doing so. Due to the low rate of data collection, any inaccuracy in theseprior estimates currently hasa strong influence on the end result. This paper examines the challenges associated with failure rate estimation, validation, and uncertainty reduction in the context of ECLSS development for beyond-LEO missions. A variety of techniques for generating and updating Bayesian priors are discussed and evaluated using both real-world and simulated data. Potential solutions for improving failure rate estimation, including testing additional units, are analyzed and discussed, and a set of recommendations are provided for next-generation system development activities.

Reliability↗