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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Influence of Nuclear Reaction Rate Uncertainties on Neutron Star Properties Extracted from X-Ray Burst Model–Observation Comparisons

We report that type-I X-ray bursts can be used to determine properties of accreting neutron stars via comparisons between model calculations and astronomical observations, exploiting the sensitivity of models to astrophysical conditions. However, the sensitivity of models to nuclear physics uncertainties calls into question the fidelity of constraints derived in this way. Using X-ray burst model calculations performed with the code MESA, we investigate the impact of uncertainties for nuclear reaction rates previously identified as influential and compare them to the impact of changes in astrophysical conditions, using the conditions that are thought to best reproduce the source GS 1826-24 as a baseline. We find that reaction rate uncertainties are unlikely to significantly change conclusions about the properties of accretion onto the neutron star surface for this source. However, we find that reaction rate uncertainties significantly hinder the possibility of extracting the neutron star mass–radius ratio by matching the modeled and observed light curves, due to the influence of reaction rates on the modeled light curve shape. Particularly influential nuclear reaction rates are 15 O(α, γ) and 23 Al(p, γ), though other notable impacts arise from 14 O(α, p), 18 Ne(α, p), 22 Mg(a, p), 24 Mg(α, γ), 59 Cu(p, g), and 61 Ga(p, γ). Additionally, we find that varying some nuclear reaction rates within their uncertainties has an impact on the neutron star crust composition and thermal structure that is comparable to relatively significant changes to the accretion conditions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

A bi-level spatiotemporal clustering approach and its application to drought extraction

We present a novel flexible bi-level spatiotemporal clustering algorithm to extract events based on their intensity and spatiotemporal structures. Our algorithm consists of using (i) a novel space-time k-means clustering to obtain spatiotemporally coherent intensity clusters, and (ii) a density-based spatial clustering of applications with noise (DBSCAN) to spatiotemporally section the intensity clusters into individual events. We discuss the development of the algorithm, the selection, tuning and meaning of the parameters within each step, as well as its validation. Finally, we apply the algorithm to a spatiotemporal drought index, standardized vapor pressure deficit drought index (SVDI), over the continental United States (US) from 1980–2021 and show that it captures historical drought events over the continental United States and their spatiotemporal extents.

17 WIND ENERGY↗
DOE OSTI2020

Decreasing wind speed extrapolation error via domain-specific feature extraction and selection

Abstract. Model uncertainty is a significant challenge in the wind energy industry and can lead to mischaracterization of millions of dollars' worth of wind resources. Machine learning methods, notably deep artificial neural networks (ANNs), are capable of modeling turbulent and chaotic systems and offer a promising tool to produce high-accuracy wind speed forecasts and extrapolations. This paper uses data collected by profiling Doppler lidars over three field campaigns to investigate the efficacy of using ANNs for wind speed vertical extrapolation in a variety of terrains, and it quantifies the role of domain knowledge in ANN extrapolation accuracy. A series of 11 meteorological parameters (features) are used as ANN inputs, and the resulting output accuracy is compared with that of both standard log-law and power-law extrapolations. It is found that extracted nondimensional inputs, namely turbulence intensity, current wind speed, and previous wind speed, are the features that most reliably improve the ANN's accuracy, providing up to a 65 % and 52 % increase in extrapolation accuracy over log-law and power-law predictions, respectively. The volume of input data is also deemed important for achieving robust results. One test case is analyzed in depth using dimensional and nondimensional features, showing that the feature nondimensionalization drastically improves network accuracy and robustness for sparsely sampled atmospheric cases.

17 WIND ENERGY↗
DOE OSTI2021

GUC CSU X-Band Precipitation Extracted Radar Columns and In-Situ Sensors (RadCLss)

For the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign, a scanning X-Band dual-polarimetric radar provided by Colorado State University (CSU) was deployed to estimate precipitation within the Upper Colorado River Basin. In order to evaluate precipitation estimates from the CSU X-Band Radar (XPRECIPRADAR), radar columns are extracted above field sites of interest to the SAIL campaign. These radar columns are then matched to in-situ sensors at these locations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Extracting the \(\Lambda \) Polarizing Fragmentation Function from Belle e + e − Data within the TMD Formalism

Data from the Belle Collaboration for associated production (with a light unpolarized hadron) and single-inclusive production of transversely polarized Λ-hyperons in e + e − annihilation processes allowed to extract within a TMD approach, for the first time, the Λ polarizing fragmentation function. Recent theoretical developments on the computation of cross sections for single-inclusive hadron production in e + e − annihilation processes, within a Soft Collinear Effective Theory approach, combined with the CSS formalism for the double-hadron production case, can be used to perform a renewed analysis, adopting a full TMD factorization scheme. Preliminary results and a comparison between the two analyses are presented.

CSS evolution equations↗
DOE OSTI2022

First Global Extraction of the Worm-gear TMD g 1 T

In these proceedings, we report on the first simultaneous extraction of the worm-gear function g 1 T , one of the eight leading-twist TMDs. The study analyzes COMPASS, HERMES and JLab semi-inclusive deep-inelastic scattering data using Monte Carlotechniques. We also provide a comparison of g 1 T obtained from this experimental data with a large N c analysis, the Wandzura–Wilczek-type approximation, and lattice QCD.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1967

Rigid-body motion extracted from total motion of a flexible body

Control system eliminates or reduces flexibility effects on the manual and automatic control of large flexible vehicles. It extracts rigid-body and flexible-body motion and adapts well when a flexible-body frequency coincides or nearly coincides with the control mode frequency.

Howard, J. C.↗