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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Application of a U.S.-based analysis approach to Argentina crop identification

A generic, U.S.-based analysis approach was evaluated with respect to corn and soybean identification in Argentina. Using crop separability expectations derived from the analysis of Argentina ancillary data and U.S. spectral data, the approach was applied to Argentina spectral data by an expert analyst. Eight classes were detected and labeled independent of ground data. A high correspondence between the labels and limited ground data was achieved. It was concluded that an approach of this type could be applied to Argentina without major difficulty.

Odenweller, J. B.↗
NASA NTRS1985

Three-dimensional inviscid analysis of radial turbine flow and a limited comparison with experimental data

The three-dimensional inviscid DENTON code is used to analyze flow through a radial-inflow turbine rotor. Experimental data from the rotor are compared with analytical results obtained by using the code. The experimental data available for comparison are the radial distributions of circumferentially averaged values of absolute flow angle and total pressure downstream of the rotor exit. The computed rotor-exit flow angles are generally underturned relative to the experimental values, which reflect the boundary-layer separation at the trailing edge and the development of wakes downstream of the rotor. The experimental rotor is designed for a higher-than-optimum work factor of 1.126 resulting in a nonoptimum positive incidence and causing a region of rapid flow adjustment and large velocity gradients. For this experimental rotor, the computed radial distribution of rotor-exit to turbine-inlet total pressure ratios are underpredicted due to the errors in the finite-difference approximations in the regions of rapid flow adjustment, and due to using the relatively coarser grids in the middle of the blade region where the flow passage is highly three-dimensional. Additional results obtained from the three-dimensional inviscid computation are also presented, but without comparison due to the lack of experimental data. These include quasi-secondary velocity vectors on cross-channel surfaces, velocity components on the meridional and blade-to-blade surfaces, and blade surface loading diagrams. Computed results show the evolution of a passage vortex and large streamline deviations from the computational streamwise grid lines. Experience gained from applying the code to a radial turbine geometry is also discussed.

Choo, Y. K.↗
NASA NTRS1985

Three-dimensional inviscid analysis of radial-turbine flow and a limited comparison with experimental data

The three-dimensional inviscid DENTON code is used to analyze flow through a radial-inflow turbine rotor. Experimental data from the rotor are compared with analytical results obtained by using the code. The experimental data available for comparison are the radial distributions of circumferentially averaged values of absolute flow angle and total pressure downstream of the rotor exit. The computed rotor-exit flow angles are generally underturned relative to the experimental values, which reflect the boundary-layer separation at the trailing edge and the development of wakes downstream of the rotor. The experimental rotor is designed for a higher-than-optimum work factor of 1.126 resulting in a nonoptimum positive incidence and causing a region of rapid flow adjustment and large velocity gradients. For this experimental rotor, the computed radial distribution of rotor-exit to turbine-inlet total pressure ratios are underpredicted due to the errors in the finite-difference approximations in the regions of rapid flow adjustment, and due to using the relatively coarser grids in the middle of the blade region where the flow passage is highly three-dimensional. Additional results obtained from the three-dimensional inviscid computation are also presented, but without comparison due to the lack of experimental data. These include quasi-secondary velocity vectors on cross-channel surfaces, velocity components on the meridional and blade-to-blade surfaces, and blade surface loading diagrams. Computed results show the evolution of a passage vortex and large streamline deviations from the computational streamwise grid lines. Experience gained from applying the code to a radial turbine geometry is also discussed.

Choo, Y. K.↗
DOE OSTI2021

Data for: Spatial access and resource limitations control carbon mineralization in soils

This dataset contains data and code used for the paper "Spatial access and resource limitations control carbon mineralization in soils", https://doi.org/10.1016/j.soilbio.2021.108427. Core-scale soil carbon fluxes are ultimately regulated by pore-scale dynamics of substrate availability and microbial access. These are constrained by physicochemical and biochemical phenomena (e.g. spatial access and hydrologic connectivity, physical occlusion, adsorption-desorption with mineral surfaces, nutrient and resource limitations). We conducted an experiment to determine how spatial access and resource limitations influence core-scale water-soluble soil organic matter (SOM) mineralization, and how these are regulated by antecedent moisture conditions. Intact soil cores were incubated at field-moist vs. drought conditions, after which they were saturated from above (to simulate precipitation) or below (to simulate groundwater recharge). Soluble carbon (acetate) and nitrogen (nitrate) forms were added to some cores during the rewetting process to alleviate potential nutrient limitations. Soil respiration was measured during the incubation, after which pore water was extracted from the saturated soils and analyzed for water soluble organic carbon concentrations and characterization. Our results showed that carbon (C) amendments increased the cumulative carbon dioxide (CO2) evolved from the soil cores, suggesting that the soils were C-limited. Drought and rewetting increased soil respiration, and there was a greater abundance of complex aromatic molecules in pore waters sampled from these soils. This newly available substrate appeared to alleviate nutrient limitations on respiration, because there were no further respiration increases with subsequent C and N amendments. We had hypothesized that respiration would be influenced by wetting direction, as simulated precipitation would mobilize C from the surface. However, as a main effect, this response was seen only in the C-amended soils, indicating that surface-C may not have been bioavailable. At the pore scale (pore water samples), drought and the C, N amendments caused a net loss of identified molecules when the soils were rewet from below, whereas wetting from above caused a net increase in identified molecules, suggesting that fresh inputs stimulated the C-and N-limited microbial populations present deeper in the soil profile. Our experiment highlights the complex and interactive role of antecedent moisture conditions, wetting direction, and resource limitations in driving core-scale C fluxes.This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/kaizadp/TES_spatial_access_2021 (DOI: 10.5281/zenodo.5522938).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Representations and strategies for transferable machine learning improve model performance in chemical discovery

Strategies for machine-learning (ML)-accelerated discovery that are general across material composition spaces are essential, but demonstrations of ML have been primarily limited to narrow composition variations. By addressing the scarcity of data in promising regions of chemical space for challenging targets such as open-shell transition-metal complexes, general representations and transferable ML models that leverage known relationships in existing data will accelerate discovery. Over a large set (~1000) of isovalent transition-metal complexes, we quantify evident relationships for different properties (i.e., spin-splitting and ligand dissociation) between rows of the Periodic Table (i.e., 3d/4d metals and 2p/3p ligands). We demonstrate an extension to the graph-based revised autocorrelation (RAC) representation (i.e., eRAC) that incorporates the group number alongside the nuclear charge heuristic that otherwise overestimates dissimilarity of isovalent complexes. To address the common challenge of discovery in a new space where data are limited, we introduce a transfer learning approach in which we seed models trained on a large amount of data from one row of the Periodic Table with a small number of data points from the additional row. We demonstrate the synergistic value of the eRACs alongside this transfer learning strategy to consistently improve model performance. Analysis of these models highlights how the approach succeeds by reordering the distances between complexes to be more consistent with the Periodic Table, a property we expect to be broadly useful for other material domains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Distributed Tomographic Reconstruction with Quantization

Conventional tomographic reconstruction typically depends on centralized servers for both data storage and computation, leading to concerns about memory limitations and data privacy. Distributed reconstruction algorithms mitigate these issues by partitioning data across multiple nodes, reducing server load and enhancing privacy. However, these algorithms often encounter challenges related to memory constraints and communication overhead between nodes. In this paper, we introduce a decentralized Alternating Directions Method of Multipliers (ADMM) with configurable quantization. By distributing local objectives across nodes, our approach is highly scalable and can efficiently reconstruct images while adapting to available resources. To overcome communication bottlenecks, we propose two quantization techniques based on K-means clustering and JPEG compression. Numerical experiments with benchmark images illustrate the tradeoffs between communication efficiency, memory use, and reconstruction accuracy.

Miao, Runxuan↗
DOE OSTI2021

Flow over an espresso cup: inferring 3-D velocity and pressure fields from tomographic background oriented Schlieren via physics-informed neural networks

Tomographic background oriented Schlieren (Tomo-BOS) imaging measures density or temperature fields in three dimensions using multiple camera BOS projections, and is particularly useful for instantaneous flow visualizations of complex fluid dynamics problems. We propose a new method based on physics-informed neural networks (PINNs) to infer the full continuous three-dimensional (3-D) velocity and pressure fields from snapshots of 3-D temperature fields obtained by Tomo-BOS imaging. The PINNs seamlessly integrate the underlying physics of the observed fluid flow and the visualization data, hence enabling the inference of latent quantities using limited experimental data. In this hidden fluid mechanics paradigm, we train the neural network by minimizing a loss function composed of a data mismatch term and residual terms associated with the coupled Navier–Stokes and heat transfer equations. We first quantify the accuracy of the proposed method based on a two-dimensional synthetic data set for buoyancy-driven flow, and subsequently apply it to the Tomo-BOS data set, where we are able to infer the instantaneous velocity and pressure fields of the flow over an espresso cup based only on the temperature field provided by the Tomo-BOS imaging. Moreover, we conduct an independent PIV experiment to validate the PINN inference for the unsteady velocity field at a centre plane. To explain the observed flow physics, we also perform systematic PINN simulations at different Reynolds and Richardson numbers and quantify the variations in velocity and pressure fields. Furthermore, the results in this paper indicate that the proposed deep learning technique can become a promising direction in experimental fluid mechanics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Integrated Energy-Water Data for Cross-Sector Resilience

This white paper focuses on the “energy-for-water” domain, addressing the urgent need for integrated, empirical data to support regional management, benchmarking, and research on improving efficiency and developing technologies for water and wastewater management systems. The costs and energy required for the supply, treatment, and distribution of water and wastewater lack a standard data collection mechanism and centralized database or storage infrastructure, limiting data-driven decision-making across interdependent infrastructure systems.

42 ENGINEERING↗
NASA NTRS1958

Survey of Hydrogen Combustion Properties

This literature digest of hydrogen-air combustion fundamentals presents data on flame temperature, burning velocity, quenching distance, flammability limits, ignition energy, flame stability, detonation, spontaneous ignition, and explosion limits. The data are assessed, recommended values are given, and relations among various combustion properties are discussed. New material presented includes: theoretical treatment of variation in spontaneous ignition lag with temperature, pressure, and composition, based on reaction kinetics of hydrogen-air composition range for 0.01 to 100 atmospheres and initial temperatures of 0 degrees to 1400 degrees k.

Drell, Isadore L↗
NASA NTRSDate not supplied

Shock-Buffet Prediction Report in Support of the High Angle Working Group at the Third Aeroelastic Prediction Workshop

This paper presents a summary of the computational shock-buffet results associated with the third Aeroelastic Prediction Workshop (AePW-3) High-Angle Working Group. The computational results are compared against experimental data collected during the Oscillating Turn Table (OTT) Benchmark Supercritical Wing (BSCW) test campaign conducted in NASA Langley Research Center Transonic Dynamics Tunnel (TDT) in early 2000. In addition to experimental forced oscillation data, unsteady pressure data was collected at a single spanwise station at transonic Mach numbers, several values of dynamic pressure, and fixed angles of attack. It is acknowledged that the current experimental data are limited, but future experiments are planned to obtain pressure data at two wingspan stations in addition to unsteady Pressure Sensitive Paint (uPSP). With that, the computational results presented here are considered to be semi-blind. The results are presented in the form of time-varying pressure coefficients, running-mean values of the pressure coefficients, Power Spectral Density (PSD) and Strouhal number computations. The results are split into two parts. In the first part, the computational results obtained by each team using their flow solvers and grids are compared. In the second part, a single computational tool was used to compute unsteady pressure on participant-generated grids. In addition, a description of each participating team’s software and methods is included.

Pawel Chwalowski↗
NASA NTRS2017

Petrology of Zircon-Bearing Diogenite Northwest Africa 10666

The howardite, eucrite, and diogenite (HED) meteorites are a group of achondrites thought to be derived from the asteroid 4 Vesta, though there is active debate as to whether all diogenites are part of the HED suite. Petrologic investigation of the HED meteorite group provides a means of understanding early planetary differentiation processes and early evolution of planets in our solar system. Diogenites are predominantly coarse grained ortho-pyroxenites with some samples containing appreciable amounts of clinopyroxene, olivine, chromite, and plagioclase. Accessory metal, troilite, and apatite are common. Many diogenites are brecciated, however, there are few poorly to unbrecciated samples. Diogenites are important because they may represent the lower crust of 4 Vesta. Although Mg isotope data indicates that the sources of diogenites are ancient, their crystallization ages are difficult to constrain due to their protracted thermal histories. The limited chronologic data for diogenites also limits the ability to test petrogenetic connections with eucrites and even parent body. A reliable and high closure-temperature isotope system, such as U-Pb in zircon, is needed to address the timing of diogenite igneous crystallization. Description of the textures and mineralogy of diogenites are essential to their classification and understanding their formation, in particular, whether all phases are petrogenetically related. Here, we present detailed petrographic data from a rare zircon-bearing feldspathic diogenite, Northwest Africa (NWA) 10666 and provide textural evidence for igneous crystallization of the zircon.

Tanner, T. B.↗
DOE OSTI2025

The Vertebrate Breed Ontology: Toward Effective Breed Data Standardization

Abstract Background Limited universally-adopted data standards in veterinary medicine hinder data interoperability and therefore integration and comparison; this ultimately impedes the application of existing information-based tools to support advancement in diagnostics, treatments, and precision medicine. Hypothesis/Objectives A single, coherent, logic-based standard for documenting breed names in health, production, and research-related records will improve data use capabilities in veterinary and comparative medicine. Animals No live animals were used. Methods The Vertebrate Breed Ontology (VBO) was created from breed names and related information compiled from the Food and Agriculture Organization of the United Nations, breed registries, communities, and experts, using manual and computational approaches. Each breed is represented by a VBO term that includes breed information and provenance as metadata. VBO terms are classified using description logic to allow computational applications and Artificial Intelligence–readiness. Results VBO is an open, community-driven ontology representing over 19 500 livestock and companion animal breed concepts covering 49 species. Breeds are classified based on community and expert conventions (e.g., cattle breed) and supported by relations to the breed's genus and species indicated by National Center for Biotechnology Information (NCBI) Taxonomy terms. Relationships between VBO terms (e.g., relating breeds to their foundation stock) provide additional context to support advanced data analytics. VBO term metadata includes synonyms, breed identifiers/codes, and attributed cross-references to other databases. Conclusion and Clinical Importance The adoption of VBO as a standard for breed names in databases and veterinary electronic health records enhances veterinary data interoperability and computability, supporting precision medicine.

Veterinary Sciences↗
NASA NTRSDate not supplied

Inception of a Spaceflight-specific Mouse to Human Expression Profiling Translation Model

Rodents are foundational model organisms often utilized due to their seemingly analogous morphologies and biological responses to humans. However, recent studies have demonstrated that murine model data are limited in their applicability, particularly in inflammatory disease. In space studies, accurately predicting human response from mouse data is critical due to extreme limiting factors in both rodent and human spaceflight research. With successful prediction, spaceflight ailments can be predicted and prevented while respecting the constraints of the spaceflight industry and minimizing danger to humans. To do so, novel methodologies must be developed that predict human response from murine data after considering biological differences between rodents and humans in spaceflight. After considering terrestrial models, we determined that a spaceflight-based expression profiting translation tool should be created to accurately capture predictions of human gene expression in spaceflight from mouse data. To prepare to build this model, we organized known human spaceflight risks, chose analog human diseases as training data categories, then identified existing RNASeq disease datasets from GEO as potential training data. In addition, we classified existing Genelab mouse differential gene expression datasets for use as experimental data.

Translation↗
DOE OSTI2023

Data from: "Moisture rivals temperature in limiting photosynthesis by trees establishing beyond their cold-edge range limit under ambient and warmed conditions"

This archive contains data files that were used to draw conclusions in “Moisture rivals temperature in limiting photosynthesis by trees establishing beyond their cold-edge range limit under ambient and warmed conditions”, by Moyes et al., 2015. All field research was completed in common garden plots set up as part of the Alpine Treeline Warming Experiment (ATWE) on Niwot Ridge, Colorado, USA.There are two main data file formats in this archive: comma-separated values (.csv), and Microsoft Excel (.xls and .xlsx). .xlsx files can be read using Microsoft Excel and Google Sheets, and .csv files can be read using any simple text editor program, such as TextEdit (Mac) and Notepad (Windows). This .pdf data user’s guide can be read using Adobe Acrobat Reader, or any other compatible software. Seedling photographs and their corresponding leaf area-processed images are available in .jpg/.JPG image format, and can be opened using Preview (Mac) and Photos (Windows). To provide additional spatial context, two types of geospatial files are also published in this data package: ESRI shapefiles (.shp) and .kml files. Shapefiles are compatible with any GIS software able to read the file type (such as QGIS or ESRI’s ArcGIS suite), and .kml files can be opened with Google Earth or Google Maps. Figures 3 and 4 in the publication contain data from Moyes et al. 2013. This publication is cited in the References section in this archive, and data files can be accessed via the Alpine Treeline Warming Experiment project portal on ESS-DIVE. ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Climate change is altering plant species distributions globally, and warming is expected to promote uphill shifts in mountain trees. However, at many cold-edge range limits, such as alpine treelines in the western United States, tree establishment may be colimited by low temperature and low moisture, making recruitment patterns with warming difficult to predict.- We measured response functions linking carbon (C) assimilation and temperature- and moisture-related microclimatic factors for limber pine (Pinus flexilis) seedlings growing in a heating × watering experiment within and above the alpine treeline. We then extrapolated these response functions using observed microclimate conditions to estimate the net effects of warming and associated soil drying on C assimilation across an entire growing season.- Moisture and temperature limitations were each estimated to reduce potential growing season C gain from a theoretical upper limit by 15–30% (c. 50% combined). Warming above current treeline conditions provided relatively little benefit to modeled net assimilation, whereas assimilation was sensitive to either wetter or drier conditions.- Summer precipitation may be at least as important as temperature in constraining C gain by establishing subalpine trees at and above current alpine treelines as seasonally dry subalpine and alpine ecosystems continue to warm.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Antarctic ice sheet model comparison with uncurated geological constraints shows that higher spatial resolution improves deglacial reconstructions

Accurately reconstructing past changes to the shape and volume of the Antarctic ice sheet relies on the use of physically based and thus internally consistent ice sheet modeling, benchmarked against spatially limited geologic data. The challenge in model benchmarking against geologic data is diagnosing whether model-data misfits are the result of an inadequate model, inherently noisy or biased geologic data, and/or incorrect association between modeled quantities and geologic observations. In this work we address this challenge by (i) the development and use of a new model-data evaluation framework applied to an uncurated data set of geologic constraints, and (ii) nested high-spatial-resolution modeling designed to test the hypothesis that model resolution is an important limitation in matching geologic data. While previous approaches to model benchmarking employed highly curated datasets, our approach applies an automated screening and quality control algorithm to an uncurated public dataset of geochronological observations (specifically, cosmogenic-nuclide exposure-age measurements from glacial deposits in ice-free areas). This optimizes data utilization by including more geological constraints, reduces potential interpretive bias, and allows unsupervised assimilation of new data as they are collected. We also incorporate a nested model framework in which high-resolution domains are downscaled from a continent-wide ice sheet model. We highlight the application of this framework by applying these methods to a small ensemble of deglacial ice-sheet model simulations, and demonstrate that the nested approach improves the ability of model simulations to match exposure age data collected from areas of complex topography and ice flow. We develop a range of diagnostic model-data comparison metrics to provide more insight into model performance than possible from a single-valued misfit statistic, showing that different metrics capture different aspects of ice sheet deflation.

Geosciences↗
NASA NTRS1998

Derivation of multi-dimensional ellipsoidal convex model for experimental data

This paper deals with determination of the best ellipsoidal model fitting the available limited experimental data. The problem is defined as that of finding the minimum volume ellipsoid containing all experimental data. A general transformation matrix for the rotation of N-dimensional coordinate system is first obtained by the Gramm-Schmidt orthogonalization procedure. The use of this matrix makes it possible to search in all possible directions to find an ellipsoid with a minimum volume. The general procedure is illustrated by examples in which the real data is utilized. An invariance property of the response with uncertain parameters of different physical nature is also discussed.

Zhu, L. P.↗