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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Magnetic contribution of itinerant electrons to neutron diffraction in the topological antiferromagnet CeAlGe

We report a neutron diffraction study of the magnetic structure of CeAlGe, a candidate topological semimetal that hosts a noncollinear, multi-𝐤 magnetic phase. By measuring both low- and high-momentum-transfer magnetic Bragg peaks within a single experimental setup, we refine a magnetic structure model based solely on localized Ce moments. This model, which differs from that obtained using only high-𝑄 data, quantitatively reproduces the observed intensities, including the (000) zeroth-order magnetic satellites that are especially sensitive to subtle components of the modulation. While a contribution from itinerant electrons to the zeroth satellite cannot be definitively excluded, our analysis reveals no unambiguous evidence for such effects within experimental uncertainty. The refined magnetic structures exhibit topologically nontrivial winding patterns, derived from the fitted magnetic parameters, that support localized, particle-like spin textures with half-integer topological charges. These features provide a natural microscopic origin for the observed topological Hall effect, establishing CeAlGe as a model system where magnetism and topology are intimately linked.

Magnetic coupling↗
DOE OSTI2021

Tracking Soiling Losses: Assessment, Uncertainty, and Challenges in Mapping

Several models have been presented in the recent years to estimate the magnitude of soiling from environmental parameters. However, these models are often based on data from a single site, or at most a few sites, and only limited data are, as of yet, available on their uncertainty. The present work aims to present a first comparative analysis of soiling estimation models, using measured soiling data from various locations in the USA. The study also investigates the impact that the source of the input data can have on the estimation. The results show that the model selection is only one of the factors that can affect the evaluation. Indeed, the use of satellite-derived or ground-mounted particulate matter data can lead to the generation of different soiling maps, with factors greater than 2x between the modeled losses. The current challenges and the unanswered questions that can bias soiling estimation are discussed. Additionally, potential research directions to improve the quality of soiling modeling are identified.

14 SOLAR ENERGY↗
DOE OSTI2023

Considering the Variability of Soiling in Long-Term PV Performance Forecasting

This study presents the development of a methodology for evaluating the variability associated with soiling on long-term photovoltaic (PV) forecasting. Independent engineering firms typically build forecasts for large PV plants through the use of the PVsyst software, where monthly soiling losses are one of many inputs to the P50 model. Subsequently, long-term performance distributions are constructed through a Monte Carlo analysis that includes various factors, such as satellite irradiance modeling uncertainty, uncertainty in the PVsyst model, and long-term irradiance variability. Often the PVsyst model uncertainty is increased to account for sites with significant soiling concerns but no systematic method has been presented in the literature to specifically include soiling variability within long-term performance uncertainty. In this work soiling information from 16 sites in the U.S. Southwest are combined with 24 years of rainfall data to generate 24 years of energy production with soiling losses and then subsequently generate probability of exceedance values (e.g., P50, P90, P95…). The results show that the size of the 90% confidence interval (P5–P95) can increase from –0.7% to 10.1% when interannual soiling variability and soiling rate uncertainty is included.

14 SOLAR ENERGY↗
DOE OSTI2022

Determination of the parton distribution functions of the proton using diverse ATLAS data from pp collisions at $$\sqrt{s} = 7$$, 8 and 13 TeV

This paper presents an analysis at next-to-next-to-leading order in the theory of quantum chromodynamics for the determination of a new set of proton parton distribution functions using diverse measurements in pp collisions at $\sqrt{s}$ = 7, 8 and 13 TeV, performed by the ATLAS experiment at the Large Hadron Collider, together with deep inelastic scattering data from ep collisions at the HERA collider. The ATLAS data sets considered are differential cross-section measurements of inclusive W ± and Z/γ* boson production, W ± and Z boson production in association with jets, $t\bar{t}$ production, inclusive jet production and direct photon production. In the analysis, particular attention is paid to the correlation of systematic uncertainties within and between the various ATLAS data sets and to the impact of model, theoretical and parameterisation uncertainties. The resulting set of parton distribution functions is called ATLASpdf21.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Dakota Graphical User Interface v.6.14

Dakota GUI is a graphical analysis environment for Sandia’s Dakota software for optimization and uncertainty quantification. This version of the Dakota GUI includes new functionality such as plotting capabilities, Eclipse-based resource management, and integration with the SAW-IF Next Gen Workflow editor. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-10629 O

Glickman, Matthew↗
DOE OSTI2022

Particle-in-cell (hPIC) data

Data generated from the hPIC particle-in-cell code to construct a surrogate ion energy-angle distribution (IEAD) model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Impact of hydropower availability on resource adequacy of the United States western interconnection

Hydropower is a key energy source in the western interconnection of the United States, comprising about 25% of the annual installed nameplate capacity in 2020. However, its generation is increasingly impacted by changing hydrological conditions, operational constraints, environmental factors, water availability, and aging dam infrastructure. Assessing hydropower availability and resource adequacy is valuable for shaping energy policies and infrastructure requirements. In this study we evaluate the sensitivity of resource adequacy in the Western Interconnection to the unavailability of hydropower plants, under a wide-ranging set of 16,384 hydropower loss scenarios derived from a combination of 14 major hydrologic regions. Although a complete loss of hydropower capacity in any region is unlikely, studying such scenarios helps in identifying hydrologic regions most critical for maintaining resource adequacy. So, we identify key hydrologic regions with disproportionately large adequacy impacts relative to their installed hydropower capacity and study compounding effects between regions using classification and regression trees. Even after controlling for total installed capacity, we find that hydropower resources in the Pacific Northwest contribute the most to interconnection-wide adequacy outcomes, with resources in Northern California and the Desert Southwest providing more moderate incremental contributions.

13 HYDRO ENERGY↗
DOE OSTI2025

Source Characterization at Low Yields from Physics Experiment One A

The detonation of a well-recorded coupled explosion at the well-characterized Nevada National Security Site, as part of Physics Experiment One, has provided us with an opportunity to compare and contrast methods and results of yield estimation and other event characterization methods. Yield estimates are made using several methods, including local/regional magnitudes, waveform envelopes, acoustic amplitudes, joint seismoacoustic yield, and moment tensors. We include in our analysis a discussion and comparison of applicability, calibrations, assumptions, and uncertainties involved in each. With the exception of magnitude-based methods, all the techniques were more or less successful in recovering the known yield. It is, however, useful to be cognizant of requirements and calibrations, such as station coverage, emplacement conditions, propagation characterization, and uncertainties, to apply the methods to other areas with less complete information. We demonstrate that we can be successful at monitoring low-yield explosions using a variety of methods assuming that the signal-to-noise ratio is adequate at recording stations, and that the material properties are taken into account. Depth estimates are also important, particularly if one allows the possibility of a surface explosion.

Pasyanos, Michael E. [Lawrence Livermore National ↗
DOE OSTI2021

Towards improved guidelines for cost evaluation of carbon capture and storage

The white paper is an effort to draw up a set of CCS costing guidelines in three complementary areas where further guidelines and better practices are needed, and where efforts are underway to address those topics. The first area of study tackles the establishment of improved guidelines for cost evaluation of advanced low-carbon technology (such as a new CO 2 capture process or a novel power plant design). The second area of study focuses on CCS from non-power industries while the final area addresses quality assurance and uncertainty evaluations of data and models used in CCS cost analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Sequential Bayesian Methods for Analyzing Computer Models

Efficient analysis of computer models is essential for the validation and uncertainty quantification of those models. Surrogate models, and Gaussian processes in particular, are a common and powerful approach to analyzing computer models that treat computer models as a black-box function. Gaussian processes form a Bayesian model over a space of functions that gives a measure of uncertainty about the computer model output at unobserved locations and a framework for sequential sampling. This tutorial will show how to fit Gaussian processes on a series of test functions and apply sequential design techniques to estimate extrema, level sets, and reliabilities of those test functions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Benchmark Calculation for the Quad Cities Unit 1 Cycles 1-3 Using the SCALE 6.3/Polaris–PARCS v3.4.2 Code Package

In this study, benchmark calculations were performed for the Quad Cities Unit 1 cycles 1–3 to validate the SCALE 6.3/Polaris–PARCS v3.4.2 code package with the ENDF/B-VII.1 AMPX 56-group library by comparing the simulated results with the measured data. The benchmark results will be used in evaluating uncertainties of the SCALE/Polaris–PARCS code package for boiling water reactor physics analysis for key nuclear parameters such as reactivity and assembly power peaking factors. This report details plant and fuel design specifications and input data for SCALE/Polaris, GenPMAXS, and PARCS; additionally, detailed information is provided for all the input and output files produced for the benchmark calculations. The benchmark results are summarized herein so that they can be used to evaluate uncertainties with other benchmark results for key nuclear parameters.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Computational Modeling of Atmospheric Processes at Texas Southern University

Texas Southern University (TSU) is strengthening its research program in atmospheric chemistry and physics with a climate science emphasis by leveraging partnerships with the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Facility, Brookhaven National Laboratory (BNL), and the Tracking Aerosol Convection Interactions ExpeRiment (TRACER). This RDPP-supported program focuses on secondary organic aerosols (SOAs) and reactive atmospheric species that influence cloud formation, precipitation processes, and radiative forcing. SOAs play a critical role in cloud microphysics and Earth’s energy balance, yet the chemical and physical mechanisms governing SOA–cloud interactions remain a significant source of uncertainty in predictive climate models. Through computational modeling, observational data analysis, and national laboratory collaboration, this program develops a skilled cohort of students trained in atmospheric science, environmental data analysis, and climate-relevant modeling. These research experiences build technical competencies that are transferable to careers in government laboratories, academia, and industry. By engaging students from historically underrepresented communities in high-impact climate research, TSU expands participation in the atmospheric sciences workforce while contributing meaningful scientific insights to DOE-supported ARM research activities. This partnership strengthens national capacity in climate science and supports the development of the next generation of atmospheric researchers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Toward $\nu_{\mu}$CC $\eta$ Meson Cross Sections on Argon in SBND

The modeling of resonant neutrino interactions on argon is critical for achieving precision neutrino oscillation measurements and searching for physics beyond the Standard Model with both DUNE and the Short-Baseline Neutrino Program. Higher mass resonances beyond the $\Delta$(1232) baryon are particularly poorly constrained experimentally, and yet contribute a significant rate in multi-GeV interactions. The measurement of $\eta$(548) meson production from the decay of these resonances provides a unique probe, as well as the opportunity to measure observables sensitive to final state interactions with the nucleus. This poster will present progress towards the measurement of meson production with the Short-Baseline Near Detector (SBND) at Fermilab, leveraging the clean $\eta \rightarrow \gamma \gamma$ decay channel. The large statistics of the SBND dataset will provide high-precision measurements of this channel capable of constraining uncertainties in the modeling of higher order resonant interactions. This analysis further provides important handles on electromagnetic shower reconstruction performance through evaluation of the 548 MeV $\eta$ invariant mass peak.

Antonakis, Alexander [UC, Santa Barbara]↗
DOE OSTI2023

Considering the Variability of Soiling in Long-Term PV Performance Forecasting: Preprint

This study presents the development of a methodology for evaluating the variability associated with soiling on long-term PV forecasting. Independent engineering firms typically build P50 forecasts for large PV plants through the use of the PVsyst software, where monthly soiling losses are one of many inputs to the P50 model. Subsequently, long-term performance distributions, or Pvalues, are constructed through a Monte Carlo analysis that includes various factors such as: satellite irradiance modeling uncertainty, uncertainty in the PVsyst model, and long-term irradiance variability. Often the PVsyst model uncertainty is increased to account for sites with significant soiling concerns but no systematic method has been presented in the literature to specifically include soiling variability within Pvalues. In this work soiling information from 16 sites in the U.S. Southwest are combined with 20 years of rainfall data to generate 20 years of energy production with soiling losses and then subsequently generate Pvalues. The results show that the spread of Pvalues (P1-P99) can increase from 0-13% when interannual soiling variability is included.

interannual variability↗
DOE OSTI2022

An independent analysis of bias sources and variability in wind plant pre-construction energy yield estimation methods

The wind resource assessment community has long had the goal of reducing the bias between wind plant pre-construction energy yield assessment (EYA) and the observed annual energy production (AEP). This comparison is typically made between the 50% probability of exceedance (P50) value of the EYA and the long-term corrected operational AEP (hereafter OA P50), and is known as the P50 bias. The industry has critically lacked an independent analysis of bias reduction investigated across multiple consultants to identify the greatest sources of uncertainty and variance in the EYA process and the best opportunities for uncertainty reduction. The present study addresses this gap by benchmarking consultant methodologies against each other and against operational data at a scale not seen before in industry collaborations. We consider data from 10 wind plants and evaluate discrepancies between eight consultancies in the steps taken from estimates of gross to net energy. Consultants tend to overestimate the gross energy produced at the turbines and then compensate by further overestimating downstream losses, leading to a mean P50 bias near zero, still with significant variability among the individual wind plants. Within our data sample, we find that consultant estimates of all loss categories, except environmental losses, tend to reduce the project-to-project variability of the P50 bias. The disagreement between consultants, however, remains flat throughout the addition of losses. Finally, we find that differences in consultants’ estimates of project performance can lead to differences up to $10/MWh in the levelized cost of energy for a wind plant.

Todd, Austin C.↗
DOE OSTI2024

Benchmark Calculation for Surry Unit 1 Cycles 1-3 Using the SCALE 6.3/Polaris–PARCS v3.4.2 Code Package

The benchmark calculations were performed for Surry Unit 1 cycles 1–3 to validate the SCALE 6.3/Polaris–Purdue Advanced Reactor Core Simulator (PARCS) v3.4.2 with the ENDF/B–VII.1 56–group library by comparing the simulated results with the measured data. The benchmark results will be used to evaluate uncertainties of the SCALE/Polaris–PARCS code package for pressurized water reactor physics analysis for key nuclear parameters such as reactivity, control bank worth, temperature coefficients, and pin and assembly power peaking factors. This report details plant and fuel design specifications and input data for SCALE/Polaris, GenPMAXS, and PARCS. Additional details are provided for the input and output files produced for the benchmark calculations. The benchmark results were summarized such that they can be used in evaluating uncertainties with other benchmark results for key nuclear parameters.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Benchmark Calculation for the Watts Bar Unit 1 Cycles 1-3 Using the SCALE 6.3/Polaris–PARCS v3.4.2 Code Package

Benchmark calculations for the Watts Bar Unit 1 cycles 1–3 were performed to validate the SCALE 6.3/Polaris–PARCS v3.4.2 with the ENDF/B-VII.1 56-group library by comparing the simulated results with the measured data. The benchmark results are used in evaluating uncertainties of the SCALE/Polaris–PARCS code package for pressurized water reactor physics analysis for key nuclear parameters such as reactivity, control bank worth, temperature coefficients, and pin and assembly power peaking factors. This report details plant and fuel design specifications and input data for SCALE/Polaris, GenPMAXS, and PARCS. Additional details are provided for the input and output files produced for the benchmark calculations. The benchmark results were summarized such that they can be used in evaluating uncertainties for key nuclear parameters with other benchmark results.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Measuring the β-decay Properties of Neutron-rich Exotic Pm, Sm, Eu, and Gd Isotopes to Constrain the Nucleosynthesis Yields in the Rare-earth Region

Abstract The β -delayed neutron-emission probabilities of 28 exotic neutron-rich isotopes of Pm, Sm, Eu, and Gd were measured for the first time at RIKEN Nishina Center using the Advanced Implantation Detector Array (AIDA) and the BRIKEN neutron detector array. The existing β -decay half-life ( T 1/2 ) database was significantly increased toward more neutron-rich isotopes, and uncertainties for previously measured values were decreased. The new data not only constrain the theoretical predictions of half-lives and β -delayed neutron-emission probabilities, but also allow for probing the mechanisms of formation of the high-mass wing of the rare-earth peak located at A ≈ 160 in the r -process abundance distribution through astrophysical reaction network calculations. An uncertainty quantification of the calculated abundance patterns with the new data shows a reduction of the uncertainty in the rare-earth peak region. The newly introduced variance-based sensitivity analysis method offers valuable insight into the influence of important nuclear physics inputs on the calculated abundance patterns. The analysis has identified the half-lives of 168 Sm and of several gadolinium isotopes as some of the key variables among the current experimental data to understand the remaining abundance uncertainty at A = 167–172.

79 ASTRONOMY AND ASTROPHYSICS↗