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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Integrating Energy-Efficient Computing with Computational Research to Accelerate Energy Technology

NREL's computational sciences center hosts the largest high performance computing (HPC) capabilities dedicated to energy research while functioning as a living laboratory for energy-efficient computing. NREL's HPC capabilities support the research needs of the Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE). In ten years of operation, HPC use in EERE-sponsored research has grown by a factor of 30, including work in electricity generation, energy efficiency, transportation, and energy system modeling. This paper analyzes this research portfolio, providing examples of individual use cases. The paper documents NREL's history of operating one of the world's most energy-efficient data centers while examining pathways to reduce economic and environmental impact beyond reduction of Power Usage Efficiency (PUE). This paper concludes by examining the unique opportunities created for accelerating improvements in data center efficiency created by combining an HPC system dedicated to energy research and a research program in energy-efficient computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Uncertain quantum computing futures and potential energy and physical resource impacts at scale

Considerable attention has recently focused on the vast energy and water demands of supercomputing, namely large-scale data centers that underpin artificial intelligence (AI), one of the great disruptors of contemporary society. Looking ahead some years from now, quantum computing is poised to disrupt established computing paradigms once again. Scientists and engineers are now working intensely to bring this century-old dream of physicists to fruition. Yet, as quantum computers begin to be integrated with classical supercomputing architectures, the implications for energy and physical resource use also need to be understood, especially how they compare to today’s AI data centers. These impacts have not yet been quantified by the research community – a notable gap in the literature, even if commercial-scale deployment of Quantum-Accelerated Computing Infrastructure (QuACI) is not expected for a few more years. This study is the first to conduct such an assessment. Using publicly available information from academic sources and private industry, we characterize multiple configurations of superconducting qubit-based, fault-tolerant quantum computers (FTQC) that could plausibly be deployed at scale in the 2030s and into the 2040s. By parameterizing these FTQC systems at a process level, we conduct a prospective scenario analysis to quantify their energy and physical resource needs. While these estimates are uncertain, given the current state of quantum technologies and their unknown future trajectories, important insights can already be drawn. One key finding is that while the electricity needs for a fleet of FTQCs are within the bounds of previous modeling studies that have explored high electricity demand futures, the needs for certain physical resources, namely water and helium-3, could pose bottlenecks to QuACI scale-up.

Computing↗
DOE OSTI2024

Optimal environmental and economic performance trade-offs for fifth generation district heating and cooling network topologies with waste heat recovery

Network topology greatly influences both the economic and environmental performance of fifth generation district heating and cooling (5GDHC) systems. In this study the optimal trade-offs between the environmental and economic performance of 5GDHC network topologies for a five-building district with waste heat recovery were explored. A life cycle assessment method was used to calculate the total life cycle CO 2 emissions (LCCO2) associated with the installation and operation of various network topologies. Twelve months of empirical data from a data center cooling system were analyzed to assess its suitability for integration into a 5GDHC system. The most suitable method for utilizing this waste heat was selected based on the ambient loop warm pipe setpoint, waste heat temperature, and district energy system configuration. A multi-objective optimization algorithm was used to select the 5GDHC network topology that provided the optimal trade-off between LCCO2 and life cycle cost (LCC). A trade-off parameter was employed to weigh the importance of each objective in the selection process. The results showed waste heat from the data center was suitable for integration into the 5GDHC system due to its availability and consistent temperature profile. When return temperatures of 25 °C or higher were available from the liquid-cooled system, direct pre-heating of the ambient loop warm pipe was found to be the most effective waste heat integration method. The selection of the network topology that provided the optimal trade-off between LCCO2 and LCC (optimal trade-off topology) was highly dependent on factors such as fuel prices, CO 2 prices, electricity CO 2 emissions factors, availability of waste heat, embodied CO 2 emissions associated with network installation and network infrastructure costs. Optimal trade-off topologies produced substantial LCCO2 reductions relative to corresponding LCC increases. LCCO2 reduction to LCC increase ratios from 5.78 to 117.79 were identified with CO 2 offset costs ranging from 4.77 to 60.08 ($/tCO 2 e).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Adoption of AI in the Utility T&D Sector: Use Cases, Consequence, Assessment and Benefits

Digital transformation and utilization of artificial intelligence (AI) in the electric grid are fundamentally changing the industry’s approach to common problems and enabling a broader paradigm shift in grid planning and operations. The change in approach is circularly both enabling and driving modernization, with load growth and reliable management of data center and AI infrastructure shifting away from planning approaches with relatively predictable behaviors and toward a mix of consumer and industrial choices that surpass human cognitive abilities to process. This movement has potential to condition humans to not understand the system on which the AI depends, while requiring it for development of the necessary infrastructure. Approaches which would address most likely grid conditions and events, such as faults, aging of equipment, and weather, now must also account for large loads which shift not based upon weather or time of day, but the computational load. Quantifying computational load is independent of the traditional grid forecasting variables, where a data center’s aggregate load is determined by user and AI system behavior and decoupled from normal grid planning and operations. AI is both the cause and solution for these challenges, with new grid planning tools integrating massive amounts of decisions into frameworks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1990

Fifth Fundamental Catalogue (FK5). Part 1: Basic fundamental stars (Fricke, Schwan, and Lederle 1988): Documentation for the machine-readable version

The machine-readable version of the catalog, as it is currently being distributed from the Astronomical Data Center, is described. The Basic FK5 provides improved mean positions and proper motions for the 1535 classical fundamental stars that had been included in the FK3 and FK4 catalogs. The machine version of the catalog contains the positions and proper motions of the Basic FK5 stars for the epochs and equinoxes J2000.0 and B1950.0, the mean epochs of individual observed right ascensions and declinations used to determine the final positions, and the mean errors of the final positions and proper motions for the reported epochs. The cross identifications to other designations used for the FK5 stars that are given in the published catalog were not included in the original machine versions, but the Durchmusterung numbers have been added at the Astronomical Data Center.

Warren, Wayne H., Jr.↗
DOE OSTI2026

A Methodology to Evaluate the Grid Reliability Impact of Oscillations Induced by Large Loads

The rapid growth of hyperscale AI data centers is bringing renewed attention to the reliability risk that sustained forced oscillations pose to bulk power systems, with cyclic computational workloads emerging as a new forcing source. Unlike the broadband, stochastic disturbances from traditional industrial loads such as arc furnaces, AI training and inference facilities can inject large active power swings concentrated at specific frequencies over extended durations - characteristics that existing grid planning practices do not account for. While the North American Electric Reliability Corporation (NERC) has recognized this gap and called for system-level studies of large load interconnections, no standardized methodology exists to screen, simulate, and quantify these risks at the planning stage. This report presents the Risk Assessment Tool for Large Load-induced Events (RATLLE), a Python-based, publicly available script suite developed at the Pacific Northwest National Laboratory to evaluate bulk power system reliability risks from data center-induced oscillations. RATLLE implements a three-module workflow: a screening module that identifies vulnerable interconnection locations and excitable system modes; a simulation module that models cyclic data center load behavior using a commercial positive sequence simulation platform; and an analysis module that computes risk metrics and generates interactive visualization dashboards. The risk metrics, formulated around simulation observables, map oscillation impacts to a three-stage severity scale spanning latent equipment fatigue through imminent cascading failure. The methodology is demonstrated on two Western Electricity Coordinating Council (WECC) system models: a publicly available 240-bus reduced representation and a detailed 2031 Heavy Winter planning case. Case studies illustrate that even modest 50 MW forced oscillations at resonant frequencies can produce wide-area power swings, N-1 security constraint violations, and cascading generator trips through protection actions - outcomes that would not occur under normal operating conditions without oscillations present. The results underscore the need for standardized oscillation impact assessment in large load interconnection studies and provide a reproducible, extensible framework for utilities to adopt or customize within their existing planning workflows.

Biswas, Shuchismita↗
DOE OSTI2026

Performance and Reliability Assessment of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Data Advisor (ADA)

The Atmospheric Radiation Measurement (ARM) User Facility provides one of the world's largest openly accessible repositories of atmospheric observations through the ARM Data Discovery platform. Although the repository contains more than three decades of measurements collected from permanent observatories, mobile facilities, aircraft campaigns, and field experiments, identifying appropriate datasets can be challenging, particularly for new users unfamiliar with ARM instrumentation and datastream organization. To improve data accessibility, the ARM Data Center developed the ARM Data Advisor (ADA), an artificial intelligence-powered assistant designed to facilitate scientific data discovery, dataset interpretation, and user guidance. This report evaluates ADA's performance as a domain-specific scientific assistant using realistic atmospheric science workflows. The evaluation examines five key capabilities: data retrieval and curation efficiency, hallucination resistance, scientific reasoning, response to ambiguous queries, and content retention and session continuity. Representative prompts were developed to simulate typical interactions between researchers and the ARM Data Discovery platform, and ADA's responses were assessed for retrieval completeness, scientific accuracy, consistency, and practical usefulness. In these representative tests, ADA reduced the complexity of discovering and accessing ARM datasets by recommending appropriate datastreams, explaining instrumentation, interpreting metadata, and assisting with data processing workflows. ADA also exhibits strong domain knowledge of atmospheric science terminology and generally resists hallucination by acknowledging unavailable datasets and requesting clarification when appropriate. Overall, the results indicate that ADA represents a promising advancement in scientific data discovery within the ARM User Facility and has considerable potential to improve researcher productivity, particularly for new users and interdisciplinary scientists seeking efficient access to ARM observations.

Salvador, Christian [ORNL] (ORCID:0000000283287777↗
NASA NTRS1982

Documentation for the machine-readable version of the Absolute Calibration of Stellar Spectrophotometry

The machine-readable data file of The Absolute Calibration of Stellar Spectrophotometry as distributed by the Astronomical Data Center is described. The data file contains the absolute fluxes for 16 stars published in Tables 1 and 2 of Johnson (1980). The absolute calibrations were accomplished by combining the 13-color photometry calibrations of Johnson and Mitchell (1975) with spectra obtained with a Michelson spectrophotometer and covering the wavelength range 4000 to 10300 A (Johnson 1977). The agreement between this absolute calibration and another recent one based upon data for a Lyr and 109 Vir by Tug, White and Lockwood (1977) is shown by Johnson (1980) to be quite good.

Warren, W. H., Jr.↗
NASA NTRS1983

Documentation for the machine-readable version of the Stellar Spectrophotometric Atlas, 3130 A lamda 10800 A of Gunn and Stryker (1983)

A detailed description of the machine-readable version of the atlas as it is currently beng distributed from the Astronomical Data Center is given. The data were obtained with the Oke multichannel scanner on the 5-meter Hale reflector for purposes of synthesizing galaxy spectra, and the digitized atlas contains normalized spectral energy distributions, computed colors, scan line and continuum indices for 175 selected stars covering the complete ranges of spectral type and luminosity class. The documentation includes a byte-by-byte format description, a table of the indigenous characteristics of the magnetic tape file, and a sample listing of logical records exactly as they are recorded on the tape.

Source record↗
NASA NTRS1984

In Situ Data

In-situ planetary data include all measurements made by a wide variety of instruments whose sensors are exposed directly to the planetry environment. Typical measurements include those of magnetic fields, energetic particle densities and energy distributions, plasma wave characteristics, ionospheric and neutral gas densities, temperatures, composition and motions. A large body of scientists in the United States, and the world, are involved in research using in-situ data. Many of these scientists are associated with Mission investigations groups which provide specific types of in-situ data. These groups, in the course of data analysis, use data provided by similar groups. The interdisciplinary nature of these investigations fosters exchange and reliance upon one another for data is heavy. To a lesser extent, correlative data sets are obtained from the National Space Science Data Center (NSSDC). However, the data entries often have limited temporal and spatial resolution, are of uncertain quality, and are usually available only for measurements that are several years old.

Source record↗
NASA NTRS1983

Venus gravity field - Pioneer Venus Orbiter navigation results

The gravity field of Venus has been modeled by a spherical harmonic expansion of the potential to degree and order seven. The estimates of these coeficients were obtained by combining information from 43 short arcs (4 hr) of line-of-sight Doppler data centered at periapsis. The data arcs were distributed in longitude and time over more than two circulations of Venus by the Pioneer Venus Orbiter subperiapsis point which was confined to the band of latitudes from 14 deg N to 17 deg N. Convergence of the solution has been assured by iterating upon the initial estimate. All estimates were performed with zero a priori information on the gravity coefficients. Since the altitude of periapsis for most of the orbits was within the sensible Venusian atmosphere, drag effects on the estimated harmonics have been removed using an exponential atmosphere density model. Estimates of the mass parameter (GM) of Venus using this dataset are also evaluated.

Williams, B. G.↗
NASA NTRS1984

Documentation for the machine-readable version of the Stellar Spectrophotometric Atlas, 3130 A lambda 10800 A of Gunn and Stryker (1983)

The machine-readable version of the Atlas as it is currently being distributed from the Astronomical Data Center is described. The data were obtained with the Oke multichannel scanner on the 5-meter Hale reflector for purposes of synthesizing galaxy spectra, and the digitized Atlas contains normalized spectral energy distributions, computed colors, scan line and continuum indices for 175 selected stars covering the complete ranges of spectral type and luminosity class. The documentation includes a byte-by-byte format description, a table of the indigenous characteristics of the magnetic tape file, and a sample listing of logical records exactly as they are recorded on the tape.

Warren, W. H., Jr.↗
NASA NTRS1992

A southwest monsoon hydrographic climatology for the Northwestern Arabian Sea

This paper provides a detailed hydrographic climatology for the shallow northwestern Arabian Sea prior to and during the southwest monsoon, presented as multiple-year composite vertical hydrographic sections based on National Oceanographic Data Center historical ocean station data. Temperature and salinity measurements are used to infer the water masses present in the upper 500 m. The hydrographic evolution depicted on bimonthly sections is inferred to result from wind-driven physical processes. In the northwestern Arabian Sea the water mass in the upper 50 m is the Arabian Sea Surface Water. Waters from 50 to 500 m are formed by mixing of Arabian Sea Surface Water with Antarctic and Indonesian intermediate waters. The inflow of Persian Gulf Water does not significantly influence the hydrography of the northwestern Arabian Sea along the Omani coast. Nitrate has a high inverse correlation with temperature and oxygen in the premonsoon thermocline in the depth interval 50-150 m. During the southwest monsoon, coastal upwelling off Oman and adjacent offshore upward Ekman pumping alter the shallow hydrography.

Brock, John C.↗
NASA NTRS2004

Making NASA Earth Observing System Satellite Data Accessible to the K-12 and Citizen Scientist Communities

The Atmospheric Sciences Data Center (ASDC) at NASA s Langley Research Center houses over 700 data sets related to Earth s radiation budget, clouds, aerosols and tropospheric chemistry. These data sets are produced to increase academic understanding of the natural and anthropogenic perturbations that influence global climate change. The Mentoring and inquirY using NASA Data on Atmospheric and earth science for Teachers and Amateurs (MY NASA DATA) project has been established to systematically support educational activities at all levels of formal and informal education by reducing these large data holdings to microsets that will be easily explored and understood by the K-12 and the amateur scientist communities

Moore, Susan W.↗
NASA NTRS2004

Intelligent Systems Technologies and Utilization of Earth Observation Data

The addition of raw data and derived geophysical parameters from several Earth observing satellites over the last decade to the data held by NASA data centers has created a data rich environment for the Earth science research and applications communities. The data products are being distributed to a large and diverse community of users. Due to advances in computational hardware, networks and communications, information management and software technologies, significant progress has been made in the last decade in archiving and providing data to users. However, to realize the full potential of the growing data archives, further progress is necessary in the transformation of data into information, and information into knowledge that can be used in particular applications. Sponsored by NASA s Intelligent Systems Project within the Computing, Information and Communication Technology (CICT) Program, a conceptual architecture study has been conducted to examine ideas to improve data utilization through the addition of intelligence into the archives in the context of an overall knowledge building system (KBS). Potential Intelligent Archive concepts include: 1) Mining archived data holdings to improve metadata to facilitate data access and usability; 2) Building intelligence about transformations on data, information, knowledge, and accompanying services; 3) Recognizing the value of results, indexing and formatting them for easy access; 4) Interacting as a cooperative node in a web of distributed systems to perform knowledge building; and 5) Being aware of other nodes in the KBS, participating in open systems interfaces and protocols for virtualization, and achieving collaborative interoperability.

Ramapriyan, H. K.↗