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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Theoretical and calculable dependent variables and their covariance in nuclear data libraries [Slides]

This presentation begins by defining observables, including theoretical observable, calculable observable, and measured observable. It also provides definitions and examples of experimental effects. Additionally, uncertainty in evaluated libraries and a metric to probe evaluated uncertainty is presented. In conclusion, being related to theoretical quantities such as resonance parameters, the uncertainty in ENDF libraries (e.g., ENDF/B-VIII.0) can be overestimated because it is usually evaluated under the guidance of experimental uncertainty: lim Δσexp.corr.→0 Δσ = Δσ theoretical model . The presentation states that a clear distinction of the uncertainty between nuclear theoretical models and experimental corrections should be revisited and this is important since (e.g., transport) simulations need theoretical quantities convoluted with specific operational parameters and material configurations. It also states that strong coupling between uncertainty quantification methodologies and optimization procedures exists, and it is necessary to develop methodologies to obtain uncertainty on theoretical models from physical and mathematical constraints.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Compilation of Experimental Yield Data for Spontaneous Fission of 252 Cf

We present a comprehensive compilation and curation of experimental fission yield (FY) data for the spontaneous fission of 252 Cf, extracted from the EXFOR database. The compilation follows a structured methodology developed for prior compilations of neutron-induced fission yields, and incorporates both independent (IFY) and cumulative (CFY) yields. A total of 62 datasets were reviewed, with entries spanning from 1955 to 2021. A significant portion of the literature reports pre-neutron emission yields, which were excluded from the present compilation due to limitations in format compatibility. Each accepted dataset was processed into a standardized JSON format, including metadata, uncertainties, and bibliographic references. Where available, decay radiation information was used to update the FY data using the latest ENSDF evaluations; 237 data points were corrected accordingly. These corrections are fully traceable and preserve original values. The result is a curated dataset suitable for use in nuclear data evaluations. This work is part of an ongoing effort to modernize the handling of FY data and provide evaluators with high-quality, machine-readable experimental inputs

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2009

Estimation of Separation Buffers for Wind-Prediction Error in an Airborne Separation Assistance System

Wind prediction errors are known to affect the performance of automated air traffic management tools that rely on aircraft trajectory predictions. In particular, automated separation assurance tools, planned as part of the NextGen concept of operations, must be designed to account and compensate for the impact of wind prediction errors and other system uncertainties. In this paper we describe a high fidelity batch simulation study designed to estimate the separation distance required to compensate for the effects of wind-prediction errors throughout increasing traffic density on an airborne separation assistance system. These experimental runs are part of the Safety Performance of Airborne Separation experiment suite that examines the safety implications of prediction errors and system uncertainties on airborne separation assurance systems. In this experiment, wind-prediction errors were varied between zero and forty knots while traffic density was increased several times current traffic levels. In order to accurately measure the full unmitigated impact of wind-prediction errors, no uncertainty buffers were added to the separation minima. The goal of the study was to measure the impact of wind-prediction errors in order to estimate the additional separation buffers necessary to preserve separation and to provide a baseline for future analyses. Buffer estimations from this study will be used and verified in upcoming safety evaluation experiments under similar simulation conditions. Results suggest that the strategic airborne separation functions exercised in this experiment can sustain wind prediction errors up to 40kts at current day air traffic density with no additional separation distance buffer and at eight times the current day with no more than a 60% increase in separation distance buffer.

Consiglio, Maria C.↗
NASA NTRS1988

Chronology of early lunar crust

The chronology of lunar rocks is summarized. The oldest pristine (i.e., lacking meteoritic contamination of admixed components) lunar rock, recently dated with Sm-Nd by Lugmair, is a ferroan anorthosite, with an age of 4.44 + 0.02 Ga. Ages of Mg-suite rocks (4.1 to 4.5 Ga) have large uncertainties, so that age differences between lunar plutonic rock suites cannot yet be resolved. Most mare basalts crystallized between 3.1 and 3.9 Ga. The vast bulk of the lunar crust, therefore, formed before the oldest preserved terrestrial rocks. If the Moon accreted at 4.56 Ga, then 120 Ma may have elapsed before lunar crust was formed.

Dasch, E. J.↗
DOE OSTI2021

Muon reconstruction and identification efficiency in ATLAS using the full Run 2 $pp$ collision data set at $\sqrt{s}=13$ TeV

This article documents the muon reconstruction and identification efficiency obtained by the ATLAS experiment for 139 fb$^{-1}$ of $pp$ collision data at $\sqrt{s}=13$ TeV collected between 2015 and 2018 during Run 2 of the LHC. The increased instantaneous luminosity delivered by the LHC over this period required a reoptimisation of the criteria for the identification of prompt muons. Improved and newly developed algorithms were deployed to preserve high muon identification efficiency with a low misidentification rate and good momentum resolution. The availability of large samples of $Z\to\mu\mu$ and $J/\psi\to\mu\mu$ decays, and the minimisation of systematic uncertainties, allows the efficiencies of criteria for muon identification, primary vertex association, and isolation to be measured with an accuracy at the per-mille level in the bulk of the phase space, and up to the percent level in complex kinematic configurations. Excellent performance is achieved over a range of transverse momenta from 3 GeV to several hundred GeV, and across the full muon detector acceptance of $|\eta|<2.7$.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Partnership Center for High-Fidelity Boundary Plasma Simulation (Final Report)

Within the Partnership Center for High-Fidelity Boundary Plasma Simulation (HBPS), work at UT-Austin was aimed at improved verification, validation, and uncertainty quantification (VVUQ) for edge plasma simulations and on performing gyrokinetics simulations of pedestal instabilities and turbulence in order to expand foundational understanding of pedestal transport. Regarding VVUQ, the accomplishments can be summarized as follows. First, it was shown that the Moment Preserving Constrained Resampling technique, when applied periodically in particle-in-cell simulations in the XGC code, can dramatically improve the accuracy of the simulation at essentially equivalent computational cost. Second, a technique for estimating model correlations, which are required to solve the model selection and sample allocation problem in multifidelity UQ techniques, without sampling the highest fidelity, most computationally expensive model, was developed and demonstrated. Third, previously developed methods for estimating statistical and discretization errors were applied to numerical methods relevant to edge plasma simulations, namely in particle-in-cell-based approaches, and shown to work. Finally, benchmark studies for comparing gyrokinetic codes were developed and performed, leading to reasonable agreement between four commonly used codes. Regarding physics studies, gyrokinetic simulations to investigate microtearing modes in the DIII-D pedestal were performed using the GENE code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Bringing solar to agriculture: An interdisciplinary design and analysis of a Concord grape agrivoltaic system

Agrivoltaics presents an opportunity to integrate solar photovoltaics (PV) with agricultural production, but crop-specific challenges and operational constraints remain underexplored. This study develops and evaluates a Concord grape agrivoltaic system in the Lake Erie American Viticulture Area, where vineyards face economic pressures and land use conflicts with solar development. Starting with vertical, tracking, and overhead PV systems, we model photosynthetic photon flux density (PPFD) reduction in grapevines and power generation losses from shading using the Agrivoltaic Radiation Tool (ART). Based on these results, which indicate 0.47 % annual grapevine PPFD loss for vertical designs, 1.6 % for tracking, and up to 25 % for the overhead systems, the vertical and tracking designs are selected for further computational fluid dynamics (CFD) analysis to evaluate airflow interactions. CFD results show that vertical panels do not significantly impact airflow through the grapevine canopy, and that tracking systems in horizontal position may enhance airflow compared to a vine-only scenario. Considering operational constraints for tracking systems, the vertical design is selected for an economic evaluation to reveal key financial outcomes for solar developers (14-year payback period) and growers ($408 reduction in financial losses per acre annually). A sensitivity analysis quantifies uncertainty in power generation (±8.8 %) and PPFD (±5.0 %), ensuring model robustness across different vineyard conditions. Furthermore, these findings provide quantitative evidence for the feasibility of Concord grape agrivoltaics, demonstrating a synergistic opportunity for dual-use solar while preserving cultural heritage in grape-growing regions.

14 SOLAR ENERGY↗
DOE OSTI2026

Scalable Generation of High-fidelity Synthetic Population Ensembles

Used within social simulations, synthetic population ensembles enable uncertainty quantification (UQ) methods for obtaining more robust model inference and prediction. A synthetic population ensemble is a series of plausible virtual reconstructions of an area’s population at the granularity of people and residences, generated stochastically to preserve privacy of the source population survey’s respondents. In this paper, we demonstrate the production of large synthetic population ensembles for the U.S. via Oak Ridge National Laboratory’s UrbanPop framework to support modeling of high spatial resolution energy affordability metrics from nationwide social surveys in collaboration with the fusionACS project. The study involves two scenarios: creating ensembles for (1) 17 U.S. metropolitan areas in 2019 and (2) full U.S. Census Divisions in 2023, with each scenario consisting of 41 population instances (a base realization and 40 replicates). To accomplish this task at scale, we configured an integrated system within a research cloud, comprised of virtual containerizations, GPU-enhanced functionality, and orchestrated deployments of UrbanPop’s maturing Likeness Python ecosystem. Results demonstrate we maintained high-fidelity approximations of residential totals by areas of interest and the demographic characteristics of neighborhoods while reducing manual workflow burdens. Finally, we discuss plans to fine-tune and further develop our automated workflows for truly distributed job orchestration to increase computational efficiency, as well as provide an outlook for broadening applications of the ensembles.

Cluster computing↗
DOE OSTI2025

Producing High-fidelity Synthetic Population Ensembles at Scale

Used within social simulations, synthetic population ensembles enable uncertainty quantification (UQ) methods for obtaining more robust model inference and prediction. A synthetic population ensemble is a series of plausible virtual reconstructions of an area’s population at the granularity of people and residences, generated stochastically to preserve privacy of the source population survey’s respondents. In this paper, we demonstrate the production of large synthetic population ensembles for the US via Oak Ridge National Laboratory’s UrbanPop framework to support modeling of high spatial resolution energy affordability metrics from nationwide social surveys in collaboration with the fusionACS project. Our initial task involves creating ensembles for 17 US metropolitan areas, each consisting of 41 population instances (a base realization and 40 replicates). To accomplish this task at scale, we configured an integrated system comprised of a research cloud, virtual containerization, GPU-enhanced functionality, and a dual API/CLI to interact with UrbanPop’s maturing Likeness Python ecosystem. We observe a reduction in theoretical execution time while maintaining high-fidelity approximations of residential totals by metropolitan area and the demographic characteristics of neighborhoods. We discuss expansion of our approach to produce synthetic population ensembles for the entire US, particularly plans to establish automated workflows for job orchestration to increase computational efficiency, as well as provide outlook for broadening applications of the ensembles.

Gaboardi, James [ORNL] (ORCID:0000000247766826)↗
NASA NTRS1994

Hypersonic vehicle model and control law development using H(infinity) and micron synthesis

The control system design for a Single Stage To Orbit (SSTO) air breathing vehicle will be central to a successful mission because a precise ascent trajectory will preserve narrow payload margins. The air breathing propulsion system requires the vehicle to fly roughly halfway around the Earth through atmospheric turbulence. The turbulence, the high sensitivity of the propulsion system to inlet flow conditions, the relatively large uncertainty of the parameters characterizing the vehicle, and continuous acceleration make the problem especially challenging. Adequate stability margins must be provided without sacrificing payload mass since payload margins are critical. Therefore, a multivariable control theory capable of explicitly including both uncertainty and performance is needed. The H(infinity) controller in general provides good robustness but can result in conservative solutions for practical problems involving structured uncertainty. Structured singular value mu framework for analysis and synthesis is potentially much less conservative and hence more appropriate for problems with tight margins. An SSTO control system requires: highly accurate tracking of velocity and altitude commands while limiting angle-of-attack oscillations, minimized control power usage, and a stabilized vehicle when atmospheric turbulence and system uncertainty are present. The controller designs using H(infinity) and mu-synthesis procedures were compared. An integrated flight/propulsion dynamic mathematical model of a conical accelerator vehicle was linearized as the vehicle accelerated through Mach 8. Vehicle acceleration through the selected flight condition gives rise to parametric variation that was modeled as a structured uncertainty. The mu-analysis approach was used in the frequency domain to conduct controller analysis and was confirmed by time history plots. Results demonstrate the inherent advantages of the mu framework for this class of problems.

Gregory, Irene M.↗
DOE OSTI2024

LLNL IPD Tasks: ICSBEP and Pulsed Spheres Benchmark [Slides]

This lecture presented benchmark of the blank and polyethylene spheres at SINBAD in April 2023. In responding to comments about the building, we uncovered a large amount of additional detailed information about the building and experimental set up. We incorporated this new information into an even higher fidelity model and are working on uncertainty analysis at a low level. Scheduled to present at SINBAD meeting in April 2024.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2026

Pandora-based muon neutrino disappearance search in the SBN program with 1muonNp quasi-elastic like channel

The Short-Baseline Neutrino (SBN) program at Fermilab aims to perform a definitive search for light sterile neutrinos using multiple liquid argon time projection chamber detectors. We present the status of an analysis of muon neutrino charged-current interactions in two SBN detectors (SBND and ICARUS), selecting fully contained events with one muon and at least one proton in the final state, inspired by the recent ICARUS standalone results. This topology-driven selection reduces dependence on neutrino interaction cross-section modeling while preserving high statistics and good neutrino energy resolution, enabled by robust reconstruction and particle identification. Fully contained events enable precise kinematic reconstruction and support relative measurements between detectors, directly addressing the core goals of the SBN program. A detailed evaluation of systematic uncertainties is currently underway, with the objective of reducing the dominant systematics to the percent level. The current status of this analysis, with a particular focus on the event selection performance, will be presented in this poster.

Artero Pons, Maria [Padua U.; INFN, Padua]↗
NASA NTRS2014

Adaptive Control for Uncertain Nonlinear Multi-Input Multi-Output Systems

Systems and methods of adaptive control for uncertain nonlinear multi-input multi-output systems in the presence of significant unmatched uncertainty with assured performance are provided. The need for gain-scheduling is eliminated through the use of bandwidth-limited (low-pass) filtering in the control channel, which appropriately attenuates the high frequencies typically appearing in fast adaptation situations and preserves the robustness margins in the presence of fast adaptation.

Cao, Chengyu↗
DOE OSTI2026

Quantifying uncertainty in physics-based predictions of rare-isotope production cross sections via Bayesian-inspired model averaging across nuclear mass tables

Accurate prediction of fragmentation cross sections is essential for rare-isotope beam production, planning new-isotope searches, and designing experiments to study the most exotic regions of the nuclear chart. However, existing reaction models and phenomenological cross-section parametrizations often exhibit significant deviations over broad regions of mass and charge. In this work, a Bayesian-inspired model-averaging framework is developed to combine abrasion-ablation (AA) calculations based on multiple nuclear mass tables into a single statistically weighted estimate. For the calibrated systems, the model weights are assigned empirically according to the relative quality of fit to measured cross sections, thereby reducing systematic model bias while preserving the underlying physics content of the AA description. The weights are constrained using proton-rich fragmentation data for the 78 Kr and 124 Xe projectiles. The resulting parameter trends are then propagated to the 92 Mo and 144 Sm systems through a controlled scaling procedure. In the present implementation, the excitation-energy prescription is fixed, while the averaging is performed across nuclear-mass inputs; the framework provides both weighted cross sections and associated uncertainty estimates. Applied to proton-rich fragmentation, the present approach provides a practical basis for interpolation and limited extrapolation in regions relevant to rare-isotope production. The resulting predictions are used to assess the production of very proton-rich nuclei, and candidate new isotopes are discussed.

Bayesian methods↗
NASA NTRS1980

Near-comet trajectory design

The Halley Flyby/Tempel 2 Rendezvous mission requires not only a new spacecraft design and a new propulsion system (the Solar Electric Propulsion System), but it also requires new approaches to the trajectory and the mission design. Because of the feebleness of Tempel 2 gravitation and because of the presence of various other competing forces, a realization and/or preservation of a spacecraft trajectory about the comet is characteristically different from that about a more massive body. This paper surveys, compares, and evaluates the significance of various forces acting on the spacecraft in the vicinity of the comet. The range of variations and uncertainties inherent in modeling of these forces are also discussed. Then, a number of different types of trajectories relevant to the design of the Tempel 2 exploration are depicted and examined. These include short-arc trajectories, near-comet short- and long-term orbits, and comet-landing trajectories.

Jones, J. B.↗
DOE OSTI2026

Gearbox bearing crack growth prognostics and uncertainty quantification with physics-informed machine learning

This paper introduces the extreme theory of functional connections (X-TFC), a physics-informed machine learning algorithm, and tailors it to estimate the remaining useful life (RUL) of wind turbine gearbox bearings experiencing fatigue crack growth. Unlike purely data-driven methods, X-TFC embeds a physics model, based on Head's theory in this work, into its training objective. The core of X-TFC is a random-projection single-layer neural network trained via an extreme learning machine, which requires only limited damage progression data and solves for output weights with a least-squares optimization algorithm. A composite loss function balances the network's fit to observed degradation data against the residuals of the governing crack growth differential equation, ensuring the learned damage trajectory remains physically plausible. When applied to a vibration-based health-index (HI) dataset measured during the growth of a crack on the inner ring of a high-speed bearing in a wind turbine gearbox (Bechhoefer and Dubé, 2020), X-TFC achieves near-zero prediction bias. Even when trained on only the first 10 %–20 % of the damage progression data, with sufficient physics weighting its predictions remain monotonic and smooth, delivering high prognosability and trendability. To quantify the epistemic uncertainty, we employ a Monte Carlo ensemble of independently initialized X-TFC models trained on noise-perturbed data, which yields confidence intervals around each RUL estimate and captures both model-parameter and epistemic uncertainty. In addition to a vibration-based HI, we demonstrate that the proposed framework can be directly applied to a supervisory control and data acquisition (SCADA) data-based HI (Eftekhari Milani et al., 2026) measured during similar wind turbine gearbox bearing crack faults, preserving its accuracy and interpretability. This extension shows the versatility of our approach, which is applicable to bearings of multiple gearbox manufacturers, models, and ratings using only SCADA data. By integrating domain knowledge with machine learning, X-TFC offers a rapid, reliable tool for crack prognostics. Its adaptability to other bearing failure modes, such as pitch bearing ring cracks, positions X-TFC as a powerful enabler of data-driven, physics-informed asset management in the wind energy sector and beyond.

17 WIND ENERGY↗
DOE OSTI2022

Evaluation of Oak Ridge National Laboratory Health Physics Research Reactor Operation Data for Critical Benchmark Creation [Slides]

During the evaluation of Oak Ridge National Laboratory Health Physics Research Reactor operation data for critical benchmark creation, a detailed, functional SCALE model was built, and experimental data was evaluated for the creation of a critical benchmark. The estimated experimental uncertainty is about 3800 pcm, which is considered very high. The relative difference between expected and calculated keff values is about 1.5 %, also considered very high. It was concluded that a good quality critical benchmark worthy of the ICSBEP standards cannot be created from HPRR data in the present conditions. Locating the HPRR fuel to obtain an uncertainty on the density would aid in solving this issue.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Frost Tables, NGEE Areas B, C and D, Utqiagvik (Barrow), Alaska, 2012-2014

This dataset represents spatially intensive thaw depth surveys with individual point measurements spaced ~0.5 m apart. The three ~10x10m grids cover an ice wedge and a portion of its two neighboring polygons. The data contain thaw depth, frost table elevation, ground surface elevation, active layer depth and surface water inundation across three seasons (2012, 2013 and 2014) at Utqiagvik (Barrow) NGEE Areas B, C and D. There are a total of 69 extracted files separated by month, year, and area. The data were originally provided in excel workbooks, these files have been preserved within the zip "Original_Files." The files were transformed for archiving with images pulled out into JPEGs, data preserved as CSV files and some methodological information preserved as TXT files. Some functions, features, and formatting were lost during the transformation. Missing data were defined with blank cells. Additional documentation can be found in files labelled with "information.txt" file endings.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).[2024-07-15] Renamed BEO_Thaw_Depth_Frost_Table_Area_*_*_*.csv, BEO_Thaw_Depth_Frost_Table_Area_*_*_*_Plot_1.JPEG, and BEO_Thaw_Depth_Frost_Table_Area_*_*_*_Plot_2.JPEG names that had E or L to be Early or Late. Renamed BEO_Thaw_Depth_Frost_Table_Area_*_*_*_Plot_1.JPEG, BEO_Thaw_Depth_Frost_Table_Area_*_*_*_Plot_2.JPEG, and BEO_Thaw_Depth_Frost_Table_Area_*_information_Plot_1.JPEG to BEO_Thaw_Depth_Frost_Table_Area_*_*_*_Gridpoints.JPEG, BEO_Thaw_Depth_Frost_Table_Area_*_*_*_3Dgraphic.JPEG, and BEO_Thaw_Depth_Frost_Table_Area_*_information_LiDAR_DEM.JPEG, respectively. Updated BEO_Thaw_Depth_Frost_Table_flmd.csv file to reflect above updates.

54 ENVIRONMENTAL SCIENCES↗