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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Integrating Multi-agency Data Products in a Cloud-based Platform for Streamlined Discovery, Visualization, and Use

Earth science data users almost always have an interest in utilizing geospatial data from multiple agencies. As computing capability and cloud-based infrastructures accelerate the pace at which scientific research can be done, there is a growing need to enable search, discovery, and use of multi-agency geospatial observations relevant for a common use case - without undergoing the search and discovery process in a less efficient, disparate path with each agency. NASA’s Earth Observing System Data and Information System (EOSDIS) and NOAA’s National Environmental Satellite, Data and Information Service (NESDIS) both support a wide range of Earth science disciplines’ research, operations, and applications activities. Presently, however, there are few examples of data discovery frameworks supporting an inquiry of both NASA’s and NOAA’s extensive archives of Earth observations that are equally suitable for a particular science scenario, regardless of the agency that “owns” the data. NASA and NOAA are collaborating on a data expedition platform for exploring fire weather using data products from both agencies. Users will be able to search, discover, and visualize NASA and NOAA products in one interface. Each agency will curate metadata for its respective datasets, providing for a rich search experience. The collaboration will pilot a shared search interface into these metadata datastores. Data products will be stored in the cloud in cloud-optimized format(s). These formats will allow for optimized data access and visualization to support the “data expedition”. Avenues for further development and application of this cloud-based, multi-agency data provisioning platform will also be discussed.

cloud-based technology↗
DOE OSTI2024

Low-Income Energy Affordability Data - LEAD Tool - 2022 Update

The Low-Income Energy Affordability Data (LEAD) Tool was created by the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA) to help state and local partners understand housing and energy characteristics for the low- and moderate-income (LMI) communities they serve. The LEAD Tool provides estimated LMI household energy data based on income, energy expenditures, fuel type, housing type, and geography, which stakeholders can use to make data-driven decisions when planning for their energy goals. From the LEAD Tool website, users can also create and download customized heat-maps and charts for various geographies, housing, energy characteristics, and population demographics and educational attainment. Datasets are available for 50 states plus Puerto Rico and Washington D.C., along with their cities, counties, and census tracts, as well as tribal areas. The file below, "01. Description of Files," provides a list of all files included in this dataset. A description of the abbreviations and units used in the LEAD Tool data can be found in the file below titled "02. Data Dictionary 2022". A list of geographic regions used in the LEAD Tool can be found in files 04-11. The Low-Income Energy Affordability Data comes primarily from the 2022 U.S. Census American Community Survey 5-Year Public Use Microdata Samples and is calibrated to 2022 U.S. Energy Information Administration electric utility (Survey Form-861) and natural gas utility (Survey Form-176) data. The methodology for the LEAD Tool can viewed below (3. Methodology Document). For more information, and to access the interactive LEAD Tool platform, please visit the "10. LEAD Tool Platform" resource link below. For more information on the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA), please visit the "11. CELICA Website" resource below.

AMI↗
NASA NTRS1986

The composition of solar energetic particles

The present measurements of elemental abundances in 15 large solar energetic particle events confirm the existence of two major effects: systematic differences between solar energetic particle abundances and photospheric abundances that are approximately correlated with first ionization potential (implying that the solar corona is the likely source population for these particles), and an enhancement of heavy ion abundances relative to a baseline of solar energetic particle abundances whose magnitude increases with rising atomic number. These data suggest the possibility that the degree of heavy ion enhancement has some correlation with spectral slope, and confirm that the aforementioned effects are not due to time or energy variations within individual events. The maximum column density above the solar acceleration region is less than 0.1 g/sq cm, on the basis of these data.

Mcguire, R. E.↗
DOE OSTI2025

Navigating Integration: Key Challenges for Data Centers, Nuclear Stakeholders, and Utility Operators

The rapid expansion of data centers, driven by the exponential growth in data-processing and storage needs, presents significant challenges and opportunities for various stakeholders, including data center developers, nuclear energy providers, and utility companies. Data centers are projected to consume 6.7–12% of United States (U.S.) electricity by 2028, driven by artificial intelligence (AI) and cloud-computing demands. Nuclear energy offers reliability and dispatchable baseload power, but data centers need power now while nuclear still needs time to address siting, fast power ramping, and regulatory hurdles. Utilities must keep pace with the unprecedented acceleration of large load interconnection requests and urgently adapt to high-density loads while maintaining grid stability, reliability, and accelerating interconnection timelines. This report dives into these challenges and proposes key collaboration strategies to streamline data center integration that aligns with recent federal initiatives like America’s AI Action Plan and related executive orders that emphasize the importance of data center growth, nuclear energy expansion, and maintaining a competitive edge in the global AI race.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
NASA NTRS2016

Unsteady Aerodynamic Force Sensing from Measured Strain

A simple approach for computing unsteady aerodynamic forces from simulated measured strain data is proposed in this study. First, the deflection and slope of the structure are computed from the unsteady strain using the two-step approach. Velocities and accelerations of the structure are computed using the autoregressive moving average model, on-line parameter estimator, low-pass filter, and a least-squares curve fitting method together with analytical derivatives with respect to time. Finally, aerodynamic forces over the wing are computed using modal aerodynamic influence coefficient matrices, a rational function approximation, and a time-marching algorithm. A cantilevered rectangular wing built and tested at the NASA Langley Research Center (Hampton, Virginia, USA) in 1959 is used to validate the simple approach. Unsteady aerodynamic forces as well as wing deflections, velocities, accelerations, and strains are computed using the CFL3D computational fluid dynamics (CFD) code and an MSC/NASTRAN code (MSC Software Corporation, Newport Beach, California, USA), and these CFL3D-based results are assumed as measured quantities. Based on the measured strains, wing deflections, velocities, accelerations, and aerodynamic forces are computed using the proposed approach. These computed deflections, velocities, accelerations, and unsteady aerodynamic forces are compared with the CFL3D/NASTRAN-based results. In general, computed aerodynamic forces based on the lifting surface theory in subsonic speeds are in good agreement with the target aerodynamic forces generated using CFL3D code with the Euler equation. Excellent aeroelastic responses are obtained even with unsteady strain data under the signal to noise ratio of -9.8dB. The deflections, velocities, and accelerations at each sensor location are independent of structural and aerodynamic models. Therefore, the distributed strain data together with the current proposed approaches can be used as distributed deflection, velocity, and acceleration sensors. This research demonstrates the feasibility of obtaining induced drag and lift forces through the use of distributed sensor technology with measured strain data. An active induced drag control system thus can be designed using the two computed aerodynamic forces, induced drag and lift, to improve the fuel efficiency of an aircraft. Interpolation elements between structural finite element grids and the CFD grids and centroids are successfully incorporated with the unsteady aeroelastic computation scheme. The most critical technology for the success of the proposed approach is the robust on-line parameter estimator, since the least-squares curve fitting method depends heavily on aeroelastic system frequencies and damping factors.

shape sensing↗
NASA NTRS1976

Full-scale crash test of a CH-47C helicopter

A full-scale crash test of a large troop/cargo carrying CH-47C helicopter was conducted at the Langley impact dynamics research facility. The crash test of this large helicopter was performed as part of a joint U.S. Army-NASA helicopter test program to provide dynamic structural and seat response data. The test, the procedures employed, the instrumentation, a general assessment of the resulting damage, and typical levels of accelerations experienced during the crash are reported. Various energy-absorbing seating systems for crew and troops were installed and instrumented to provide data for use in the development of design criteria for future aircraft. The crash conditions were selected to simulate known crash conditions and are representative of the 95th percentile accident environment for an autorotating helicopter. Visual examination of the crashed test specimen indicated irreparable damage to many of the structural components. The highest accelerations were recorded by the accelerometers located on the cabin floor in the aft section of the helicopter, directly above the primary impact location and on the floor of the cockpit above the secondary impact location(s).

Castle, C. B.↗
NASA NTRS1993

Microgravity acceleration measurement environment characterization

The Space Acceleration Measurement System (SAMS) is a general-purpose instrumentation system designed to measure the accelerations onboard the shuttle Orbiter and shuttle/Spacelab vehicles. These measurements are used to support microgravity experiments and investigations into the microgravity environment of the vehicle. Acceleration measurement can be made at locations remote from the SAMS main instrumentation unit by the use of up to three remote triaxial sensor heads. The SAMS was developed by NASA's Lewis Research Center (LeRC) in support of NASA's microgravity science programs. In the past, numerous acceleration measurement systems have flown on various space missions. These systems were tailored to measure accelerations for a narrow set of requirements and were limited in bandwidth, dynamic range, and recording capability. In addition, these systems were mission-peculiar and not easily modified for other applications or missions. The result has been an inability to accurately assess the expected microgravity environment prior to a mission for a particular experiment and/or location. The prime science objective for SAMS on the SL-J mission will be to measure the accelerations experienced by a multitude of experiments in the two racks of the Japanese First Materials Processing Test (FMPT). The FMPT consists of a variety of materials science and life science experiments contained in racks no. 7 and no. 10. The SAMS data will be made available to the FMPT principal investigators after the mission for their analysis with the FMPT data. A secondary science objective for SAMS will be the characterization of the acceleration environment of the Spacelab module. This will include an analysis of the acceleration transfer function of the Spacelab module which will utilize the FMPT acceleration measurement along with measurements at the rack no. 9 structure. Another analytical effort to be undertaken is a general characterization of the acceleration environment of the Spacelab as an orbiting laboratory. These analysis efforts will be in conjunction with similar measurements and analyses on other SAMS Spacelab missions.

Delombard, Richard↗
NASA NTRS1997

Solar wind acceleration in the solar corona

The intensity ratio of the O VI doublet in the extended area is analyzed. The O VI intensity data were obtained with the ultraviolet coronagraph spectrometer (UVCS) during the SOHO campaign 'whole sun month'. The long term observations above the north pole of the sun were used for the polar coronal data. Using these measurements, the solar wind outflow velocity in the extended corona was determined. The 100 km/s level is running along the streamer borders. The acceleration of the solar wind is found to be high in regions between streamers. In the central part of streamers, the outflow velocity of the coronal plasma remains below 100 km/s at least within 3.8 solar radii. The regions at the north and south poles, characterized by a more rapid acceleration of the solar wind, correspond to regions where the UVCS observes enhanced O VI line broadenings.

Giordano, S.↗
NASA NTRSDate not supplied

Statistical Engineering

This webinar provides an overview of the International Statistical Engineering Association (ISEA), and it illustrates the practice of statistical engineering at NASA. ISEA was formed to promote the study of how successful data-based problem-solving methods are leveraged to realize innovative opportunities and solve problems sustainably. ISEA is comprised of statisticians, engineers, scientists, and other professionals that exchange ideas and experiences in the development and application of statistical engineering theories. ISEA is building the body of knowledge of the statistical engineering discipline with a particular focus on improving academic preparation for tackling complex problems. Over the past 15 years, the practice of statistical engineering has gained recognition within NASA by spurring innovation and efficiency, and it has demonstrated significant impact. Aerospace research and development benefits from an application-focused statistical engineering perspective to accelerate learning, maximize knowledge, ensure strategic resource investment, and inform data-driven decisions. The second portion of this presentation provides an overview of infusing statistical engineering at NASA through pioneering case studies in aeronautics, space exploration, and atmospheric science.

Peter A Parker↗
NASA NTRS1984

Ion beamlet steering for two-grid electrostatic thrusters

An experimental study of ion beamlet steering in which the direction of beamlets emitted from a two grid aperture system is controlled by relative translation of the grids, is described. The results can be used to design electrostatic accelerating devices for which the direction and focus of emerging beamlets are important. Deflection and divergence angle data are presented for two grid systems as a function of the relative lateral displacement of the holes in these grids. At large displacements, accelerator grid impingements become excessive and this determines the maximum allowable displacement and as a result the useful range of beamlet deflection. Beamlet deflection is shown to vary linearly with grid offset angle over this range. The divergence of the beamlets is found to be unaffected by deflection over the useful range of beamlet deflection. The grids of a typical dished grid ion thruster are examined to determine the effects of thermally induced grid distortion and prescribed offsets of grid hole centerlines on the characteristics of the emerging beamlets. The results are used to determine the region on the grid surface where ion beamlet deflections exceed the useful range. Over this region high accelerator grid impingement currents and rapid grid erosion are predicted.

Homa, J. M.↗
NASA NTRS1990

Evaluation of EDR-3 vibration, shock, temperature, and humidity recording unit

The purpose of this evaluation was to determine if the self-contained, off-the-shelf, Environmental Data Recorder 3 (EDR-3) could be qualified to monitor shock, vibration, and temperature during rail transportation of space shuttle solid rocket components. The evaluation testing started in November 1989 and continued until June 1990. Two EDR-3 units were used to monitor both on- and off-plant shipments of shuttle components. In addition, extensive testing was performed at Thiokol's Vibration Test facility, T-53. Testing demonstrated that the EDR-3 is capable of successfully monitoring actual shipments of solid rocket hardware. Thiokol metrology has verified the accuracy of temperature monitoring. In addition, calibrated shock/vibration testing demonstrated that the EDR-3 does accurately record acceleration. It is recommended that the vendor modify the EDR-3 data recovery system to allow remote communication via a 30-foot cable. This would permit communication with the unit mounted on a case segment after a rail car cover is installed. The vendor will make this change and produce a new model, designated EDR-3-10. It is further recommended that Thiokol qualify the EDR-3-10 for transportation monitoring of redesigned solid rocket motor (RSRM) components.

Rees, Kevin G.↗
NASA NTRS1992

STS-40 orbital acceleration research experiment flight results during a typical sleep period

The Orbital Acceleration Research Experiment (OARE), an electrostatic accelerometer package with complete on-orbit calibration capabilities was flown aboard Shuttle on STS-40. The instrument is designed to measure and record the Shuttle aerodynamic acceleration environment from the free molecule flow regime through the rarefied flow transition into the hypersonic continuum regime. Because of its sensitivity, the OARE instrument detects aerodynamic behavior of the Shuttle while in low-earth orbit. A 2-h orbital time period on day seven of the mission, when the crew was asleep and other spacecraft activities were at a minimum, was examined. Examination of the model with the flight data shows the instrument to be sensitive to all major expected low-frequency acceleration phenomena; however, some erratic instrument bias behavior persists in two axes. In these axes, the OARE data can be made to match a comprehensive atmospheric-aerodynamic model by making bias adjustments and slight liner corrections for drift.

Blanchard, Robert C.↗
NASA NTRS1978

Lunar tidal acceleration obtained from satellite-derived ocean tide parameters

Observation equations for the M2 ocean tide are computed from Geos 3 data for the long periodic variations of the inclination and node of the orbit. M2 ocean tide parameter values C22+ = 3.23 + or - 0.25 cm, epsilon 22+ = 331 + or - 6 deg, and epsilon 42+ = 113 + or - 6 deg are determined. With the assumption of zero solid tide phase lag, the lunar tidal acceleration is mostly (85%) due to the C22+ term in the expansion of the M2 tide with additional small contributions from the O1 and N2 tides. The calculated value for the tidal acceleration in lunar longitude is -27.4 + or - 3 arc sec/sq (100 yr) which is similar to values determined from astronomical data. The mean elements of Geos 3 are presented in tabular form.

Goad, C. C.↗
DOE OSTI2021

2D Simulations of Diamagnetic Loop Calibrations

Diamagnetic loops can be used as a non-invasive method for measurements of beam size in electron beam accelerators that use solenoidal magnetic transport. A comprehensive theory for interpreting data from a diamagnetic loop relates the rms beam radius to the excluded flux measured by the loop and the beam current. Thus, primary calibration of the loop must relate the loop signal directly to the exclude d flux. We have simulated these calibrations with a 2D field solver in order to identify possible sources of uncertainty in our calibration technique.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Accelerated creep profiling: a high-throughput thermal- and stress-gradient approach applied to additive and wrought stainless steel

Here, this study investigates logarithmic creep behavior at temperatures near room temperature in wrought and additively manufactured (AM) 316 L austenitic stainless steel. A novel high-throughput (HiTp) methodology employed thermal gradients to obtain stress- and temperature-dependence of creep behavior. The findings, based on 104 two-week creep tests, reveal significant differences in creep response between wrought and AM materials. Compared to the wrought material, the AM material exhibited a higher activation energy and a lower activation volume. These differences were attributed to the materials’ distinct microstructural features, e.g., dislocation cell structures and precipitate distributions, which alter the susceptibility to dislocation glide creep, particularly at stresses below the yield stress. The HiTp methodology provides both an accelerated determination of low-temperature creep mechanisms, offering critical data for the design and optimization of alloys in near-ambient, high stress applications.

316 L Stainless steel↗
DOE OSTI2022

Accelerating high-order mesh optimization using finite element partial assembly on GPUs

In this paper we present a new GPU-oriented mesh optimization method based on high order finite elements. Our approach relies on node movement with fixed topology, through the Target-Matrix Optimization Paradigm (TMOP) and uses a global nonlinear solve over the whole computational mesh, i.e., all mesh nodes are moved together. A key property of the method is that the mesh optimization process is recast in terms of finite element operations, which allows us to utilize recent advances in the field of GPU-accelerated high order finite element algorithms. For example, we reduce data motion by using tensor factorization and matrix-free methods, which have superior performance characteristics compared to traditional full finite element matrix assembly and offer advantages for GPU based HPC hardware. Furthermore, we describe the major mathematical components of the method along with their efficient GPU-oriented implementation. In addition, we propose an easily reproducible mesh optimization test that can serve as a performance benchmark for the mesh optimization community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Active learning of ternary alloy structures and energies

Abstract Machine learning models with uncertainty quantification have recently emerged as attractive tools to accelerate the navigation of catalyst design spaces in a data-efficient manner. Here, we combine active learning with a dropout graph convolutional network (dGCN) as a surrogate model to explore the complex materials space of high-entropy alloys (HEAs). We train the dGCN on the formation energies of disordered binary alloy structures in the Pd-Pt-Sn ternary alloy system and improve predictions on ternary structures by performing reduced optimization of the formation free energy, the target property that determines HEA stability, over ensembles of ternary structures constructed based on two coordinate systems: (a) a physics-informed ternary composition space, and (b) data-driven coordinates discovered by the Diffusion Maps manifold learning scheme. Both reduced optimization techniques improve predictions of the formation free energy in the ternary alloy space with a significantly reduced number of DFT calculations compared to a high-fidelity model. The physics-based scheme converges to the target property in a manner akin to a depth-first strategy, whereas the data-driven scheme appears more akin to a breadth-first approach. Both sampling schemes, coupled with our acquisition function, successfully exploit a database of DFT-calculated binary alloy structures and energies, augmented with a relatively small number of ternary alloy calculations, to identify stable ternary HEA compositions and structures. This generalized framework can be extended to incorporate more complex bulk and surface structural motifs, and the results demonstrate that significant dimensionality reduction is possible in thermodynamic sampling problems when suitable active learning schemes are employed.

Chemistry↗
DOE OSTI2025

Autonomous phase mapping of gold nanoparticles synthesis with differentiable models of spectral shape

Autonomous experimentation–or self-driving labs–offers a systematic approach to accelerate materials discovery by integrating automated synthesis, characterization, and data-driven decision-making. We present a closed-loop workflow for the on-demand synthesis and structural characterization of colloidal gold nanoparticles, enabling direct mapping from composition to nanoscale structure. Our framework leverages differentiable models of spectral shape to address two central tasks in self-driving labs: (a) phase mapping, or identifying compositional regions with distinct structural behavior; and (b) material retrosynthesis, or optimizing compositions for target structure. Using functional data analysis, we develop a data-driven model with generative pre-training, active learning, and high-throughput experiments to predict spectral responses across composition space. We demonstrate the approach on seed-mediated growth of gold nanoparticles, showcasing its ability to extract design rules, reveal secondary interactions, and efficiently navigate morphology space. Gradient-based optimization of the models enables inverse design, making this a unified platform.

36 MATERIALS SCIENCE↗