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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 289 records · Page 16

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NASA NTRS1978

Interaction of a two-dimensional strip boundary layer with a three-dimensional transonic swept-wing code

A 3D inviscid transonic analysis code was combined with a 2D strip integral boundary layer technique to form an approximate interaction procedure for analyzing the flow over a high aspect ratio wing near cruise conditions. Converged results obtained using the procedure for an aspect ratio 10.3 supercritical wing are discussed. Angle of attack adjustments were made during the iterative procedure in order to compensate for the viscous lift loss. A comparison of the calculations with experimental data is presented.

Newman, P. A.↗

NASA NTRS1988

Spatial and temporal variability of VAS radiance measurements by structure and correlation analysis

The statistical structure function analysis presently applied to VISSR Atmospheric Sounder (VAS) measurements has been extended to include time, and yields structure plots in either two spatial dimensions or one spatial dimension and time that indicate three-dimensional measurement variability. The analyses that include time as a coordinate also yield an indication of the mean speed and direction of the analyzed data. Results for three-hourly VAS data indicate that sampling at a high, approximately 1-hour, frequency is required in order to correctly monitor VAS measurements' temporal variability in a way equivalent to high spatial resolution.

Hillger, Donald W.↗

NASA NTRS1937

Theoretical span loading and moments of tapered wings produced by aileron deflection

The effect of tapered ailerons on linearly tapered wings is theoretically determined. Four different aileron spans are considered for each of three wing aspect ratios and each of four wing taper ratios. The change in lift on one half of the wing, the rolling moment, the additional induced drag, and the yawing moment, due to aileron deflection, are represented by non dimensional coefficients. Similar coefficients are given for the damping and yawing moments, the additional drag, and the change in lift, due to rolling. It was found possible to effect a fairly close agreement between the theoretical and experimental rolling moments by introducing into the theoretical expression for the rolling moment an effective change in angle of attack obtained from an analysis of flap data. The theoretical curves show that the highly tapered wing with long ailerons has a lower ratio of yawing to rolling moment and a lower additional induced drag than wings with less taper.

Pearson, H A↗

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

Gust Response Analysis of a Turbine Cascade

A study was made of the gust response of an annular turbine cascade using a two-dimensional Navier Stokes code. The time-marching CFD code, NPARC, was used to calculate the unsteady forces due to the fluid flow. The computational results were compared with a previously published experimental data for the annular cascade reported in the literature. Reduced frequency, Mach number and angle of incidence were varied independently and the gust velocity was sinusoidal. For the high inlet velocity case, the cascade was nearly choked.

Gorla, R. S. R.↗

DOE OSTI2026

Generation of lognormal synthetic Lyman-α forest spectra for P 1 D analysis

The one-dimensional flux power spectrum (P 1 D ) of the Lyman-α forest probes small-scale structure in the intergalactic medium (IGM) and is therefore sensitive to a variety of cosmological and astrophysical parameters. These include the amplitude and shape of the matter power spectrum, the thermal history of the IGM, the sum of neutrino masses, and potential small-scale fluctuations due to the nature of dark matter. However, P 1 D is also highly sensitive to observational and instrumental systematics, making accurate synthetic spectra essential for validating analyses and quantifying these effects, especially in high-volume surveys like the Dark Energy Spectroscopic Instrument (DESI). We present an efficient lognormal mock framework for generating one-dimensional Lyman-α forest spectra tailored for P 1 D analysis. Our method captures the redshift evolution of the mean transmitted flux and the scale-dependent shape and amplitude of the one-dimensional flux power spectrum by tuning Gaussian field correlations and transformation parameters. Across the DESI Early Data Release (EDR) redshift range (2.0 ≤ z ≤ 3.8), and a wide range of scales (10 -4 s km -1 ≤ k ≤ 1.0 s km -1 ), our mocks recover the mean flux evolution with redshift to sub-percent accuracy, and the P 1 D at the percent level. Additionally, we discuss potential extensions of this framework, such as the incorporation of astrophysical contaminants, continuum uncertainties, and instrumental effects. Such improvements would expand its utility in ongoing and upcoming surveys and enable a broader range of validation efforts and systematics studies for P 1 D inference and precision cosmology.

Lyman alpha forest↗

NASA NTRS1991

Infrared measurements of HF and HCl total column abundances above Kitt Peak, 1977-1990 - Seasonal cycles, long-term increases, and comparisons with model calculations

The paper deals with hydrogen-chloride and hydrogen-fluoride total column measurements, their estimated long-term rates of increase, seasonal cycles, and variability, deduced from the analysis of a set of high-resolution infrared solar spectra recorded at Kitt Peak. The Kitt Peak observations and methods of analysis are described, the results are presented and compared with previously reported measurements and trends. The data is analyzed by using a multilayer nonlinear least-squares spectral fitting procedure and a consistent set of spectroscopic line parameters. Model-calculated hydrogen-chloride and hydrogen-fluoride total columns obtained with a two-dimensional model are discussed, and the model results are compared with the measured hydrogen-chloride and hydrogen-fluoride total columns, seasonal cycles, and trends. It is pointed out that the observed trends of both molecules are in satisfactory agreement with the model results calculated from emission histories and photooxidation rates for the source molecules.

Rinsland, C. P.↗

NASA NTRS1986

Landsat D Thematic Mapper image dimensionality reduction and geometric correction accuracy

To characterize and quantify the performance of the Landsat thematic mapper (TM), techniques for dimensionality reduction by linear transformation have been studied and evaluated and the accuracy of the correction of geometric errors in TM images analyzed. Theoretical evaluations and comparisons for existing methods for the design of linear transformation for dimensionality reduction are presented. These methods include the discrete Karhunen Loeve (KL) expansion, Multiple Discriminant Analysis (MDA), Thematic Mapper (TM)-Tasseled Cap Linear Transformation and Singular Value Decomposition (SVD). A unified approach to these design problems is presented in which each method involves optimizing an objective function with respect to the linear transformation matrix. From these studies, four modified methods are proposed. They are referred to as the Space Variant Linear Transformation, the KL Transform-MDA hybrid method, and the First and Second Version of the Weighted MDA method. The modifications involve the assignment of weights to classes to achieve improvements in the class conditional probability of error for classes with high weights. Experimental evaluations of the existing and proposed methods have been performed using the six reflective bands of the TM data. It is shown that in terms of probability of classification error and the percentage of the cumulative eigenvalues, the six reflective bands of the TM data require only a three dimensional feature space. It is shown experimentally as well that for the proposed methods, the classes with high weights have improvements in class conditional probability of error estimates as expected.

Ford, G. E.↗

NASA NTRS1990

Use of high-dimensional spectral data to evaluate organic matter, reflectance relationships in soils

Recent breakthroughs in remote sensing technology have led to the development of a spaceborne high spectral resolution imaging sensor, HIRIS, to be launched in the mid-1990s for observation of earth surface features. The effects of organic carbon content on soil reflectance over the spectral range of HIRIS, and to examine the contributions of humic and fulvic acid fractions to soil reflectance was evaluated. Organic matter from four Indiana agricultural soils was extracted, fractionated, and purified, and six individual components of each soil were isolated and prepared for spectral analysis. The four soils, ranging in organic carbon content from 0.99 percent, represented various combinations of genetic parameters such as parent material, age, drainage, and native vegetation. An experimental procedure was developed to measure reflectance of very small soil and organic component samples in the laboratory, simulating the spectral coverage and resolution of the HIRIS sensor. Reflectance in 210 narrow (10 nm) bands was measured using the CARY 17D spectrophotometer over the 400 to 2500 nm wavelength range. Reflectance data were analyzed statistically to determine the regions of the reflective spectrum which provided useful information about soil organic matter content and composition. Wavebands providing significant information about soil organic carbon content were located in all three major regions of the reflective spectrum: visible, near infrared, and middle infrared. The purified humic acid fractions of the four soils were separable in six bands in the 1600 to 2400 nm range, suggesting that longwave middle infrared reflectance may be useful as a non-destructive laboratory technique for humic acid characterization.

Henderson, T. L.↗

DOE OSTI2024

Mathematical methods for optimal polynomial recovery of high-dimensional systems from noisy data

The goal of our Early Career Research Project (ECRP) is to establish a modern mathematical foundation that will enable next-generation computational methods for polynomial approximation of high-dimensional systems, having a certain set of constraints, from a limited amount of noisy data. Such a foundation is critical to realizing the future potential of the DOE user facilities, and will ultimately empower scientists to address a fundamental question, namely, “how many realizations of a nonlinear manifold are required to recover the entire high-dimensional solution map, with optimal approximation guarantees and minimal computational cost?” The central theme of this effort aims to conquer this challenge by pioneering the development of extraordinarily innovative theoretical analysis and transformational non-intrusive computational methodologies. Such approaches will enable the reconstruction of the entire high-dimensional solution map, with accuracy comparable to the best approximation, while utilizing an optimal number of samples. During this reporting period we have made significant progress on four thrusts.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1987

Correlations of TOMS total ozone data (Nimbus-7 satellite) with tropopause height

Two correlation studies of Total Ozone Mapping Spectrometer (TOMS) data with tropopause height from radiosondes performed over Europe showed a correlation coefficient of 0.94 and 0.96. As a result, the rms error in the prediction of tropopause height from total ozone was found to be 20 mb. Correlation between tropopause height and TOMS data was the highest of all the other correlations with variables directly derived from radiosondes or simulated thermal radiances over the location of radiosondes. Comparing the two dimensional fields of TOMS, tropopause height from radiosondes and tropopause height field from TIROS-N retrievals, we can say that the first field is much closer to the true field from radiosondes than the third. The correlation coefficient for a ten-day study between TOMS data and tropopause height from radiosondes is between 0.85 and 0.9 for 30-70N. Tropopause analysis provided by GLA model also shows a very high correlation with TOMS data.

Munteanu, Marie-Jeanne↗

NASA NTRS2006

Slat Cove Unsteadiness Effect of 3D Flow Structures

Previous studies have indicated that 2D, time accurate computations based on a pseudo-laminar zonal model of the slat cove region (within the framework of the Reynolds-Averaged Navier-Stokes equations) are inadequate for predicting the full unsteady dynamics of the slat cove flow field. Even though such computations could capture the large-scale, unsteady vorticity structures in the slat cove region without requiring any external forcing, the simulated vortices were excessively strong and the recirculation zone was unduly energetic in comparison with the PIV measurements for a generic high-lift configuration. To resolve this discrepancy and to help enable physics based predictions of slat aeroacoustics, the present paper is focused on 3D simulations of the slat cove flow over a computational domain of limited spanwise extent. Maintaining the pseudo-laminar approach, current results indicate that accounting for the three-dimensionality of flow fluctuations leads to considerable improvement in the accuracy of the unsteady, nearfield solution. Analysis of simulation data points to the likely significance of turbulent fluctuations near the reattachment region toward the generation of broadband slat noise. The computed acoustic characteristics (in terms of the frequency spectrum and spatial distribution) within short distances from the slat resemble the previously reported, subscale measurements of slat noise.

Choudhari, Meelan M.↗

NASA NTRSDate not supplied

Increasing accessibility to deep learning-based analytics for space biology: pretrained models, transfer learning, and analytics platform development

Biological systems react in complex ways to the stressors of spaceflight, and the data capturing these relationships is concomitantly high-dimensional and complex. Deep learning and machine learning approaches are increasingly popular as an analytical approach for space biosciences, due to their ability to model complex relationships in complex data. However, such approaches often require large datasets and extensive computational resources. New approaches that minimize data sizes and computational power needed to leverage machine learning, and resources that make these approaches accessible, are needed to increase accessibility and adoption of machine learning in the space biosciences. Transfer learning, in which a pretrained model of broad utility is trained on a large dataset, and subsequently reused on downstream applications for which data is more limited, is one approach to minimizing data and computational intensity of deep learning applications. This transfer learning approach results in more performant models in high-dimensional, low-sample-size settings such as space biology, as compared to training models on limited data from scratch. This presentation will outline efforts to generate pretrained models for the space biology community, and highlight transfer learning applications modeling microbial antibiotic resistance during spaceflight. Finally, in order to increase accessibility of these models and tools, as well as others, for the broader space biology community, we present a modeling and analysis platform facilitating machine learning applications in space biology. This platform streamlines machine learning training and analysis in a notebook format, facilitates download and use of space biology data from the NASA GeneLab database, and can be utilized on NASA-hosted servers or downloaded and hosted locally. This effort, as part of the AI4LS (Artificial Intelligence for Life in Space) working group, will increase accessibility, feasibility, and performance of machine learning approaches for the space biology community.

Adrienne Hoarfrost↗

NASA NTRS2012

Leveraging Data Intensive Computing to Support Automated Event Services

A large portion of Earth Science investigations is phenomenon- or event-based, such as the studies of Rossby waves, mesoscale convective systems, and tropical cyclones. However, except for a few high-impact phenomena, e.g. tropical cyclones, comprehensive records are absent for the occurrences or events of these phenomena. Phenomenon-based studies therefore often focus on a few prominent cases while the lesser ones are overlooked. Without an automated means to gather the events, comprehensive investigation of a phenomenon is at least time-consuming if not impossible. An Earth Science event (ES event) is defined here as an episode of an Earth Science phenomenon. A cumulus cloud, a thunderstorm shower, a rogue wave, a tornado, an earthquake, a tsunami, a hurricane, or an EI Nino, is each an episode of a named ES phenomenon," and, from the small and insignificant to the large and potent, all are examples of ES events. An ES event has a finite duration and an associated geolocation as a function of time; its therefore an entity in four-dimensional . (4D) spatiotemporal space. The interests of Earth scientists typically rivet on Earth Science phenomena with potential to cause massive economic disruption or loss of life, but broader scientific curiosity also drives the study of phenomena that pose no immediate danger. We generally gain understanding of a given phenomenon by observing and studying individual events - usually beginning by identifying the occurrences of these events. Once representative events are identified or found, we must locate associated observed or simulated data prior to commencing analysis and concerted studies of the phenomenon. Knowledge concerning the phenomenon can accumulate only after analysis has started. However, except for a few high-impact phenomena. such as tropical cyclones and tornadoes, finding events and locating associated data currently may take a prohibitive amount of time and effort on the part of an individual investigator. And even for these high-impact phenomena, the availability of comprehensive records is still only a recent development. A major reason for the lack of comprehensive ,records for the majority of the ES phenomena is the perception that they do not pose immediate and/or severe threat to life and property and are thus not consistently tracked. monitored, and catalogued. Many phenomena even lack commonly accepted criteria for definitions. However. the lack of comprehensive records is also due to the increasingly prohibitive volume of observations and model data that must be examined. NASA Earth Observing System Data Information System (EOSDIS) alone archives several petabytes (PB) of satellite remote sensing data and steadily increases. All of these factors contribute to the difficulty of methodically identifying events corresponding to a given phenomenon and significantly impede systematic investigations. In the following we present a couple motivating scenarios, demonstrating the issues faced by Earth scientists studying ES phenomena.

Clune, Thomas L.↗

DOE OSTI2025

Autonomous platform for solution processing of electronic polymers

The manipulation of electronic polymers’ solid-state properties through processing is crucial in electronics and energy research. Yet, efficiently processing electronic polymer solutions into thin films with specific properties remains a formidable challenge. We introduce Polybot, an artificial intelligence (AI) driven automated material laboratory designed to autonomously explore processing pathways for achieving high-conductivity, low-defect electronic polymers films. Leveraging importance-guided Bayesian optimization, Polybot efficiently navigates a complex 7-dimensional processing space. In particular, the automated workflow and algorithms effectively explore the search space, mitigate biases, employ statistical methods to ensure data repeatability, and concurrently optimize multiple objectives with precision. The experimental campaign yields scale-up fabrication recipes, producing transparent conductive thin films with averaged conductivity exceeding 4500 S/cm. Feature importance analysis and morphological characterizations reveal key design factors. This work signifies a significant step towards transforming the manufacturing of electronic polymers, highlighting the potential of AI-driven automation in material science.

Wang, Chengshi [Argonne National Laboratory (ANL),↗

NASA NTRS2015

Estimation of Surface Temperature and Heat Flux by Inverse Heat Transfer Methods Using Internal Temperatures Measured While Radiantly Heating a Carbon/Carbon Specimen up to 1920 F

The ability to solve the heat conduction equation is needed when designing materials to be used on vehicles exposed to extremely high temperatures; e.g. vehicles used for atmospheric entry or hypersonic flight. When using test and flight data, computational methods such as finite difference schemes may be used to solve for both the direct heat conduction problem, i.e., solving between internal temperature measurements, and the inverse heat conduction problem, i.e., using the direct solution to march forward in space to the surface of the material to estimate both surface temperature and heat flux. The completed research first discusses the methods used in developing a computational code to solve both the direct and inverse heat transfer problems using one dimensional, centered, implicit finite volume schemes and one dimensional, centered, explicit space marching techniques. The developed code assumed the boundary conditions to be specified time varying temperatures and also considered temperature dependent thermal properties. The completed research then discusses the results of analyzing temperature data measured while radiantly heating a carbon/carbon specimen up to 1920 F. The temperature was measured using thermocouple (TC) plugs (small carbon/carbon material specimens) with four embedded TC plugs inserted into the larger carbon/carbon specimen. The purpose of analyzing the test data was to estimate the surface heat flux and temperature values from the internal temperature measurements using direct and inverse heat transfer methods, thus aiding in the thermal and structural design and analysis of high temperature vehicles.

Pizzo, Michelle↗

DOE OSTI2024

Laboratory-Based Micro-X-ray Computed Tomography of Energy Materials at Idaho National Laboratory

Abstract The Idaho National Laboratory (INL) has implemented laboratory-based micro-X-ray computed tomography in a laboratory equipped for the examination of highly radioactive samples. This capability provides nondestructive three-dimensional volumetric information on samples to inform subsequent traditional destructive examinations as well as real-world inputs for high-fidelity scientific modeling. Samples can be imaged with spatial resolutions ranging from several hundred nm/voxel up to ~ 100 µm/voxel. The best usable spatial resolution achieved to date is 384 nm/voxel with this instrument, while the highest radiological dose rate of a sample imaged is ~ 60 R/h β/γ on contact. Advanced data analysis, including custom tomographic reconstruction and segmentation methods, have also been developed to support this capability. In addition to traditional digital X-ray radiography and tomography, this instrument is also able to visualize in situ tensile and compression testing as well as perform diffraction contrast tomography. This work describes the X-ray computed tomography post-irradiation examination capabilities at INL, as well as detailing a variety of applications this instrument has examined.

36 MATERIALS SCIENCE↗

NASA NTRS1979

Effect of viscosity on wind-tunnel wall interference for airfoils at high lift

The effect of the walls of a wind tunnel on the subsonic, two-dimensional flow past airfoils at high angles of attack is studied theoretically and experimentally. The computerized analysis, which is based on iteratively coupled potential-flow, boundary-layer, and separated-flow analyses, includes determining the effect of viscosity and flow separation on the airfoil/wall interaction. Predictions of the effects of wind-tunnel wall on the lift of airfoils are compared with wall corrections based on inviscid image analyses, and with experimental data. These comparisons are made for airfoils that are large relative to the size of the test section of the wind tunnel. It is shown that the inviscid image modeling of the wind-tunnel interaction becomes inaccurate at lift coefficients near maximum lift or when the airfoil/wall interaction is particularly strong. It is also shown that the present method of analysis (which includes boundary-layer and flow-separation effects) will provide accurate wind-tunnel wall corrections for lift coefficients up to maximum lift.

Olson, L. E.↗