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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Legacy Survey of Space and Time Data Preview 2: deep_coadd_input_summary dataset type

We present Rubin Data Preview 2 (DP2), the second data preview from the NDF-DOE Vera C. Rubin Observatory. Data Preview 2 (DP2) comprises coadds, detection catalogs, and ancillary data products; and when fully released will also include single-epoch images and difference images. DP2 is derived from observations acquired by the LSST Science Camera (LSSTCam) on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile, primarily during the on-sky commissioning campaign between 2025-04-16 and 2025-09-21, supplemented by observations taken between 2025-10-25 and 2026-01-06 that overlap the commissioning footprint. The DP2 footprint comprises the Science Validation wide-area survey, five Deep Drilling Fields, and a number of targeted small-field regions, including Trifid and Lagoon, Prawn, M49, and New Horizons, all observed as part of the Rubin First Look campaign. Each field was imaged in up to six broad photometric bands, ugrizy, and coadded to produce deep imaging covering an estimated 3,000 deg2. The addition of single-visit-only areas expands the total DP2 footprint to an estimated 15,000 deg2, with coverage in at least one filter. The median per-visit PSF FWHM across the wide-area survey ranges from 1.17 arcsec in the z band to 1.26 arcsec in g and r bands. The deepest field, reaches estimated coadded 5σ depths of u=26 mag, g=26.8 mag, r=26.3 mag, i=26.1 mag, z=25.3 mag, y=23.9 mag. Based on a roughly five-month primary observing baseline and covering only part of the eventual LSST footprint, DP2's area, depth, and multiband coverage nonetheless support a broad range of early science investigations ahead of LSST Data Release This dataset is a subset of the full data release consisting of the deep_coadd_input_summary dataset type. These are summary of the visit images that contribute to each deep coadd patch. This release contains 1 dataset of this type.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

DOME: Directional medical embedding vectors from Electronic Health Records

Motivation: The increasing availability of Electronic Health Record (EHR) systems has created enormous potential for translational research. Recent developments in representation learning techniques have led to effective large-scale representations of EHR concepts along with knowledge graphs that empower downstream EHR studies. However, most existing methods require training with patient-level data, limiting their abilities to expand the training with multi-institutional EHR data. On the other hand, scalable approaches that only require summary-level data do not incorporate temporal dependencies between concepts. Methods: We introduce a DirectiOnal Medical Embedding (DOME) algorithm to encode temporally directional relationships between medical concepts, using summary-level EHR data. Specifically, DOME first aggregates patient-level EHR data into an asymmetric co-occurrence matrix. Then it computes two Positive Pointwise Mutual Information (PPMI) matrices to correspondingly encode the pairwise prior and posterior dependencies between medical concepts. Following that, a joint matrix factorization is performed on the two PPMI matrices, which results in three vectors for each concept: a semantic embedding and two directional context embeddings. They collectively provide a comprehensive depiction of the temporal relationship between EHR concepts. Results: We highlight the advantages and translational potential of DOME through three sets of validation studies. First, DOME consistently improves existing direction-agnostic embedding vectors for disease risk prediction in several diseases, for example achieving a relative gain of 5.5% in the area under the receiver operating characteristic (AUROC) for lung cancer. Second, DOME excels in directional drug-disease relationship inference by successfully differentiating between drug side effects and indications, correspondingly achieving relative AUROC gain over the state-of-the-art methods by 10.8% and 6.6%. Finally, DOME effectively constructs directional knowledge graphs, which distinguish disease risk factors from comorbidities, thereby revealing disease progression trajectories. The source codes are provided at https://github.com/celehs/Directional-EHRembedding.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1978

An investigation of wing buffeting response at subsonic and transonic speeds: Phase 1: F-111A flight data analysis. Volume 1: Summary of technical approach, results and conclusions

The structural response to aerodynamic buffet during moderate to high-g maneuvers at subsonic and transonic speeds was investigated. The investigation is reported in three volumes. This volume presents a summary of the investigation with a complete description of the technical approach, description of the aircraft, its instrumentation, the data reduction procedures, results and conclusion.

Benepe, D. B.↗
DOE OSTI2025

Monitoring L2 Milestone Summary: Converged HPC Center-Wide Data Analytics

This document is the summary for the ASC 2025 L2 milestone Converged HPC Center-Wide Data Analytics. It describes the convergence of the center-wide monitoring at LC, the data sources involved, and different ways this has enabled analyzing and gaining insights from the data.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2002

TIMED Solar EUV Experiment: Phase E

The timed Solar EUV Experiment (SEE) Phase E Annual Report for 2002 is presented. The contents include: 1) SEE Science Overview; 2) SEE Instrument Overview and Status; 3) Summary of SEE Data Products; 4) Summary of SEE Results; 5) Summary of SEE Related Talks and Papers; and 6) Future Plans for SEE Team. This paper is in viewgraph form.

Woods, Tom↗
NASA NTRS1973

Mariner 9 data storage subsystem flight performance summary

The performance is summarized of the Mariner 9 Data Storage Subsystem (DSS) throughout the primary and extended missions. Information presented is limited to reporting of anomalies which occurred during the playback sequences. Tables and figures describe the anomalies (dropouts, missing and added bits, in the imaging data) as a function of time (accumulated tape passes). The data results indicate that the performance of the DSS was satisfactory and within specification throughout the mission. The data presented is taken from the Spacecraft Team Incident/Surprise Anomaly Log recorded during the mission. Pertinent statistics concerning the tape transport performance are given. Also presented is a brief description of DSS operation, particularly that related to the recorded anomalies. This covers the video data encoding and how it is interpreted/decoded by ground data processing and the functional operation of the DSS in abnormal conditions such as loss of lock to the playback signal.

Thomas, N. E.↗
NASA NTRS2001

A summary of spacecraft engineering sensors

This paper gives a data table summary of the different types of engineering sensors that are used onboard a typical spacecraft.

vehicle health management fault protection spacecr↗
NASA NTRS2023

NASA GRC ICME Schema for Materials Data Management: An Executive Summary

Integrated Computational Materials Engineering (ICME) has received a growing emphasis in attention due its potential impact on rapid material design, reduction in cost and time to market for new applications, and the promise of ‘fit-for-purpose’ materials coupled with recent advances in high performance computing and material characterization tools. However, for an organization to implement ICME practices for material discovery and design, a series of both technical and cultural challenges must be overcome to foster an environment that enables efficient, traceable, and predictive multiscale simulations of material behavior to enable virtual design of materials. In 2016, NASA sponsored a 2040 Vision study to define the potential 25-year future state required for integrated multiscale modeling of materials and systems to improve both the associated time and cost for aerospace and aeronautical innovation. The study envisions a cyber-physical-social ecosystem of experimentally validated computational models, tools, and techniques, along with the associated digital tapestry, that can enable rapid, optimized, ‘fit-for-purpose’ design of materials, components, and systems. A key requirement for such an ecosystem is the development of a robust information management system for materials across their full lifecycle, including material pedigree, experimental (real) and virtual (simulation) data, developed material models, and the implementation of models in engineering applications, such that process-structure-property-performance relationships can be established, thereby enabling the virtual design and optimization of materials. Such an information management system must be able to effectively capture: i) material information at each length scale; ii) test data and analysis; iii) associated material models; and iv) material and model deployment in engineering applications. These systems must also provide traceability between experimental and virtual representations of the material to ensure, when appropriate, the material digital twin is maintained. Additionally, this robust material information management system must be able to seamlessly connect with both commercial and an organization’s in-house software tools, be they analysis tools, other material databases, product lifecycle management (PLM) or simulation data management (SDM) tools, etc., such that automation of the design and analysis of a material across multiple length scales is possible. In this paper, an executive summary of the NASA GRC ICME Schema for materials information management is presented. The database best practices and schema design philosophy specifically for ICME materials data management and an overview description of each element in the schema is given, along with its associated role in an ICME workflow. Additionally, auxiliary tools that interact with the database and provide judicious automation with regards to importing, exporting, and analyzing materials data are presented. Such tools are critical to an ICME ecosystem, not only for their role in enabling optimization, but also in relieving users of tedious manual tasks, thus helping to promote adoption and combat the cultural challenges organizations face in enabling ICME.

Materials↗
DOE OSTI2016

Processing and Monthly Summaries of Downscaled Climate Data for Knoxville, Tennessee and Surrounding Region

Oak Ridge National Laboratory (ORNL) and the City of Knoxville, Tennessee have partnered to work on a Laboratory Directed Research and Development (LDRD) project towards investigating climate change, mitigation, and adaptation measures in mid-sized cities. ORNL has statistically and dynamically downscaled ten Global Climate Models (GCMs) to both 1 km and 4 km resolutions. The processing and summary of those ten gridded datasets for use in a web-based tool is described. The summaries of each model are shown individually to assist in determining the similarities and differences between the model scenarios. The variables of minimum and maximum daily temperature and total monthly precipitation are summarized for the area of Knoxville, Tennessee for the periods of 1980-2005 and 2025-2050.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

MEDLI2: MISP Inferred Aerothermal Environment and Flow Transition Assessment

The Mars Entry, Descent, and Landing Instrumentation 2 (MEDLI2) sensor suite on the Mars2020 mission contained multiple sensors on the aeroshell to measure the aerothermal environment during entry into the Martian atmosphere. These sensors performed superbly and successfully returned forebody and aftbody heating measurements. Analysis of MEDLI2 data indicated flow transitioning from a laminar to turbulent state on the heatshield. No evidence of flow transition was observed on the backshell. Two methods were used to estimate flow transition times on the heatshield: (1) temperature gradient of near-surface thermocouple data and (2) heat flux gradient from an inverse reconstruction approach using thermocouple data and material response modeling. Both methods produced similar transition times with an estimated accuracy of ±1 s. To assess various transition criteria, transition parameters were evaluated at each sensor location using flow field solutions from computational fluid dynamics (CFD) simulations. The idea was to use conservative values inferred from MEDLI2 data as transition criteria for other Mars missions. To test this hypothesis, MEDLI data from the Mars Science Laboratory (MSL) mission was used to compare predicted vs. actual flow transition times. The comparisons suggest smooth wall transition criteria are not well-suited in modeling the rapid progression of a turbulent transition front. Transition criteria containing a roughness element parameter agreed better with the flight data. In summary, critical transition values derived from MEDLI2 data may be used as a starting point in constructing a flow transition model for future Mars missions.

Chun Y Tang↗
NASA NTRSDate not supplied

Data-Driven Turbulence Modeling: Summary and Outcomes of the 2022 NASA Symposium

A three-day symposium sponsored by NASA was held in July 2022 in Suffolk, Virginia on the subject of Turbulence Modeling: Roadblocks, and the Potential for Machine Learning. This meeting brought together over 80 experts from academia, government, and industry to discuss critical issues for Reynolds-averaged Navier-Stokes (RANS) turbulence and transition models, as well as to evaluate the results from a collaborative testing challenge based on data-driven methods and machine learning (ML) technology. The symposium represents a continuation of an earlier symposium sponsored by the University of Michigan and NASA, held in Ann Arbor, MI in 2017. The 2022 symposium included a wide variety of talks on the subjects of RANS and ML, five invited talks, and three panel discussions. This talk summarizes the main outcomes of the symposium, and includes suggested recommendations and future directions.

machine learning↗
DOE OSTI2023

Review and Summary of Oxide Thickness Data for Aluminum-Clad Spent Nuclear Fuel

The U.S. Department of Energy (DOE) owns a large inventory of aluminum-clad spent nuclear fuel (ASNF) in interim storage pending ultimate disposition, with more being generated by currently operating research reactors. Dry storage in sealed DOE Standard Canisters is being investigated as an approach for long-term interim storage and/or disposition in a repository for ASNF. A primary challenge for ASNF storage is the presence of aluminum (oxy)hydroxide layers formed on the cladding surfaces during water exposure in the reactor and in wet storage, which forms a reservoir of chemisorbed water not readily removed at low (<100°C) drying temperatures. Free, physisorbed, and chemisorbed water are all susceptible to radiolytic breakdown under irradiation and can release hydrogen gas. Identifying the likely range of (oxy)hydroxide loadings on ASNF that may be placed in dry storage will help to ensure that the impact of the (oxy)hydroxide is adequately accounted for while avoiding over conservatism and enable mitigation strategies to be implemented where needed. The current report summarizes information on (oxy)hydroxide thicknesses and characteristics from the literature and from recent measurements taken in the present research campaign. In general, corrosion studies have indicated that the corrosion and oxide buildup on aluminum are affected by numerous conditions, including pH, temperature and heat flux, coolant flowrates, irradiation (in-reactor vs. unirradiated tests), duration of water exposure, and the amount of oxide already on the surface. Some of these factors are interrelated (e.g., the local temperature, heat flux, and coolant flowrate). Observations of the impact of irradiation (in-reactor versus ex-reactor measurements) on corrosion and oxide thickness are mixed, but multiple studies indicate that there is a significant difference between in-reactor and ex-reactor corrosion kinetics, even when other operating conditions such as pH, flowrate, heat flux, etc., simulate those in a reactor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1974

Statistical summary of air quality data for metropolitian Cleveland, Ohio, 1967 - 1972: Total suspended particulates, nitrogen dioxide, and sulfur dioxide

Air-quality data for metropolitan Cleveland, Ohio, from 1967 through 1972 were collated and statistically analyzed. Total suspended particulates (TSP) departed from lognormal distribution in 1972. Nitrogen dioxide and sulfur dioxide, departed significantly from lognormal distributions in 1972. In Cleveland the Ohio standards were not met. However, the data indicate a general improvement in air quality. Unusually high precipitation (43% above the average in 1972) may be responsible in lowering these values from the 1971 levels. The mean values of TSP, NO2, and SO2 are 104, 191, and 83 microgram/cu m respectively.

King, R. B.↗
NASA NTRS1975

A summary of ERTS-1 data collection system applications

Geographically, applications were made over nearly the entire area where direct readout could be accomplished using the data acquisition stations in the ERTS-1 system. The extreme areas included Iceland, the Canadian Arctic, Alaska, Hawaii and Central America. In the discipline sense the majority of applications were in the water resources area with other applications being formally and informally reported in meteorology, oceanography, volcano surveillance and forestry. Installation and maintenance of the data collection platforms, as is true with nearly all new systems, was not accomplished without difficulty. On the whole, however, it has gone well enough so that it is agreed that it is a system which is amenable to installation in a variety of physical situations and the installation is accomplished with an ease commensurate with eventual use in an operational system.

Salomonson, V. V.↗
NASA NTRS1978

Tabulation and summary of thermodynamic effects data for developed cavitation on ogive-nosed bodies

Thermodynamic effects data for developed cavitation on zero and quarter caliber ogives in Freon 113 and water are tabulated and summarized. These data include temperature depression (delta T), flow coefficient (C sub Q), and various geometrical characteristics of the cavity. For the delta T tests, the free-stream temperature varied from 35 C to 95 C in Freon 113 and from 60 C to 125 C in water for a velocity range of 19.5 m/sec to 36.6 m/sec. Two correlations of the delta T data by the entrainment method are presented. These correlations involve different combinations of the Nusselt, Reynolds, Froude, Weber, and Peclet numbers and dimensionless cavity length.

Holl, J. W.↗