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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Star cluster classification using deep transfer learning with PHANGS- HST

Currently available star cluster catalogues from the Hubble Space Telescope (HST) imaging of nearby galaxies heavily rely on visual inspection and classification of candidate clusters. Here, the time-consuming nature of this process has limited the production of reliable catalogues and thus also post-observation analysis. To address this problem, deep transfer learning has recently been used to create neural network models that accurately classify star cluster morphologies at production scale for nearby spiral galaxies (D ≲ 20 Mpc). Here, we use HST ultraviolet (UV)–optical imaging of over 20 000 sources in 23 galaxies from the Physics at High Angular resolution in Nearby GalaxieS (PHANGS) survey to train and evaluate two new sets of models: (i) distance-dependent models, based on cluster candidates binned by galaxy distance (9–12, 14–18, and 18–24 Mpc), and (ii) distance-independent models, based on the combined sample of candidates from all galaxies. We find that the overall accuracy of both sets of models is comparable to previous automated star cluster classification studies (~60–80 per cent) and shows improvement by a factor of 2 in classifying asymmetric and multipeaked clusters from PHANGS-HST. Somewhat surprisingly, while we observe a weak negative correlation between model accuracy and galactic distance, we find that training separate models for the three distance bins does not significantly improve classification accuracy. We also evaluate model accuracy as a function of cluster properties such as brightness, colour, and spectral energy distribution (SED)-fit age. Based on the success of these experiments, our models will provide classifications for the full set of PHANGS-HST candidate clusters (N ~ 200 000) for public release.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

High-accuracy emulators for observables in ΛCDM, N eff, Σ m ν, and w cosmologies

ABSTRACT We use the emulation framework CosmoPower to construct and publicly release neural network emulators of cosmological observables, including the cosmic microwave background (CMB) temperature and polarization power spectra, matter power spectrum, distance-redshift relation, baryon acoustic oscillation (BAO) and redshift-space distortion (RSD) observables, and derived parameters. We train our emulators on Einstein–Boltzmann calculations obtained with high-precision numerical convergence settings, for a wide range of cosmological models including ΛCDM, wCDM, ΛCDM + Neff, and ΛCDM + Σmν. Our CMB emulators are accurate to better than 0.5 per cent out to ℓ = 104, which is sufficient for Stage-IV data analysis, and our P(k) emulators reach the same accuracy level out to $k=50 \, \, \mathrm{Mpc}^{-1}$, which is sufficient for Stage-III data analysis. We release the emulators via an online repository (CosmoPower Organisation), which will be continually updated with additional extended cosmological models. Our emulators accelerate cosmological data analysis by orders of magnitude, enabling cosmological parameter extraction analyses, using current survey data, to be performed on a laptop. We validate our emulators by comparing them to class and camb and by reproducing cosmological parameter constraints derived from Planck TT, TE, EE, and CMB lensing data, as well as from the Atacama Cosmology Telescope Data Release 4 CMB data, Dark Energy Survey Year-1 galaxy lensing and clustering data, and Baryon Oscillation Spectroscopic Survey Data Release 12 BAO and RSD data.

Astronomy & Astrophysics↗
DOE OSTI2023

Accurate estimation of angular power spectra for maps with correlated masks

A common procedure when analyzing maps of the cosmic microwave background (CMB) or other cosmological signals is the need to remove ("mask") regions of the maps that are heavily contaminated, e.g., by non-cosmological foreground emission. After applying such a mask, one must account for its effect when inferring statistical properties of interest, such as the angular power spectrum of the field in the original map. A widely used approach to correct for such mask-induced effects was presented by Hivon et al. (2002), now widely known as the "MASTER" formalism. However, it is often the case that the map and mask are correlated in some way, such as point source masks used in CMB analyses, which have nonzero correlation with CMB secondary anisotropy fields and other mm-wave sky signals. In such situations, the MASTER approach gives biased results, as it assumes that the unmasked map and mask have zero correlation. While such effects have been discussed before with regard to specific physical models, here we derive a completely general formalism for any case where the map and mask are correlated. We show that our result ("reMASTERed") reconstructs ensemble-averaged angular power spectra to effectively exact precision, with significant improvements over traditional estimators for cases where the map and mask are correlated. An important consequence of our result is that for maps with correlated masks, it is no longer possible to invert a simple equation to obtain the true power spectrum from the observed (masked) power spectrum. Instead, our result necessitates the use of forward modeling from theory space into the observable domain of the masked power spectrum. We publicly release our software implementation of these results.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Model-agnostic likelihood for the reinterpretation of the 𝐵 + → 𝐾 + ⁢$𝑣\bar{𝑣}$ measurement at Belle II

We recently measured the branching fraction of the 𝐵 + → 𝐾 + ⁢$𝑣\bar{𝑣}$ decay using 362 fb −1 of on-resonance 𝑒 + ⁢𝑒 − collision data under the assumption of Standard Model kinematics, providing the first evidence for this decay. To facilitate future reinterpretations and maximize the scientific impact of this measurement, we publicly release the full analysis likelihood along with all necessary material required for reinterpretation under arbitrary theoretical models sensitive to this measurement. In this work, we demonstrate how the measurement can be reinterpreted within the framework of the weak effective theory. Using a kinematic reweighting technique in combination with the published likelihood, we derive marginal posterior distributions for the Wilson coefficients, construct credible intervals, and assess the goodness of fit to the Belle II data. For the weak effective theory Wilson coefficients, the posterior mode of the magnitudes |𝐶 VL +𝐶 VR |, |𝐶 SL +𝐶 SR |, and |𝐶 TL | corresponds to the point (11.3, 0.0, 8.2). The respective 95% credible intervals are [1.9, 16.2], [0.0, 15.4], and [0.0, 11.2].

bottom quark↗
DOE OSTI2026

RADAI: A Large-Scale Realistic Dataset for Radiation Detection Algorithm Development

Open, realistic datasets are essential for developing and benchmarking radiation detection algorithms, yet they remain scarce. The Radiological Anomaly Detection and Identification (RADAI) project was develop to create datasets that meet the training and testing needs for sophisticated radiation detection algorithms. The RADAI dataset is a large-scale synthetic resource that integrates high-fidelity Monte Carlo simulations with realistic urban scenarios to capture both background variability and source signatures. RADAI models construction-material NORM, people and vehicles, urban clutter, and dynamic environmental effects such as cosmic-ray and rain-induced transients, and they provide list-mode detector data with motion and response modeling suitable for algorithm training and evaluation. The RADAI project resulted in three publicly-released complementary datasets together with an online scoring portal for standardized performance assessment and an open software toolkit that supports data access, augmentation, model development, and evaluation. These resources enable reproducible comparisons across methods and promote rigorous studies at the scale required by contemporary machine learning. By grounding algorithm development in realistic, well-documented conditions, RADAI supports progress toward more robust detection, identification, and localization in complex urban environments.

Ghawaly, James M. [Division of Computer Science an↗
DOE OSTI2024

OReole-FM: successes and challenges toward billion-parameter foundation models for high-resolution satellite imagery

While the pretraining of Foundation Models (FMs) for remote sensing (RS) imagery is on the rise, models remain restricted to a few hundred million parameters. Scaling models to billions of parameters has been shown to yield unprecedented benefits including emergent abilities, but requires data scaling and computing resources typically not available outside industry R&D labs. In this work, we pair high-performance computing resources including Frontier supercomputer, America's first exascale system, and high-resolution optical RS data to pretrain billion-scale FMs. Our study assesses performance of different pretrained variants of vision Transformers across image classification, semantic segmentation and object detection benchmarks, which highlight the importance of data scaling for effective model scaling. Moreover, we discuss construction of a novel TIU pretraining dataset, model initialization, with data and pretrained models intended for public release. By discussing technical challenges and details often lacking in the related literature, this work is intended to offer best practices to the geospatial community toward efficient training and benchmarking of larger FMs.

Ambrozio Dias, Philipe↗
DOE OSTI2025

NEPATEC2.0: NEPA Text Corpus v2.0

The National Environmental Policy Act of 1969, as amended (NEPA), is a major environmental law in the United States, requiring Federal agencies to consider and document potential environmental impacts before deciding on a proposed action. Modernization of NEPA and permitting processes faces significant challenges due to the lack of standardized formats and interoperable systems for organizing and sharing NEPA-related information across agencies. Much of the information gathered during NEPA reviews is written into documents such as categorical exclusions, environmental assessments, and environmental impact statements, then filed in predominately independent agency file stores that may or may not be publicly accessible. The application of metadata and data standards, such as those recommended by the Council on Environmental Quality (CEQ), to NEPA documents offers a shared vocabulary and structure for key entities like projects, processes, and documents that can streamline information exchange and enhance collaboration across systems. In this work, we publicly release NEPATEC2.0, an expanded corpus of NEPA documents with associated metadata. NEPATEC2.0 encompasses approximately 120,000 documents from 60,000 projects prepared by more than 60 different agencies. Modeled to align with CEQ metadata standards, NEPATEC2.0 promotes consistency in environmental reviews and supports the ongoing effort to modernize permitting technologies by facilitating more transparent, efficient, and data-driven decision-making. Importantly, NEPATEC2.0 demonstrates the possibilities and limitations of large language model-based prompting to extract information from NEPA documents at scale.

environmental review↗
DOE OSTI2022

Sample Code for "An automated approach to the alignment of compound refractive lenses"

This sample code is intended to be publicly released on DOECODE. It is an accompaniment to "n automated approach to the alignment of compoundrefractive lenses". It's two small, mostly self-contained scripts that include the complete details necessary to implement the to-be published article's algorithm at a scientific beamline.

Breckling, SeanR [Mission Support and Test Service↗
DOE OSTI2022

Development of a point kinetics subroutine for Molten Salt reactors in RELAP5-3D

RELAP5-3D has historically focused on accurate modeling of design-basis and beyond-design-basis accidents in solid fuel light-water reactors. The assumption used in solid fuel reactors that delayed neutron precursors remain at the location in which they were produced is inherently incorrect for a molten salt reactor with flowing fuel. Therefore, new methods for modeling MSR kinetics were required. Subroutine used in RELAP5-3D were updated to analyze point kinetics in a molten salt reactor during both steady state and transient analyses. The phenomena related to MSR kinetics that were added to RELAP5-3D include arrays to store previous values for independent and dependent variables, arrays to add terms to existing kinetics equations, and a new reactivity bias term. A custom MATLAB assessment code was used to establish a suite of verification tests. This capability is undergoing final documentation and testing for public release with a future version of RELAP5-3D.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

H3 StingRAY Final Design and Technical Report - Section 13 Appendices

These documents are referenced in the public version of the H3 StingRAY Final Design and Technical Report (Linked Dataset can be found in Resources section, below), and are submitted separately to allow for public release of head document. The display names have the corresponding section number for easy reference.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

EV Profile Capture

NextGen Profiles' EV profile capture efforts aimed to explore the variance in performance and evaluate how different operational conditions influence production EV charging behavior. Data were collected at a frequency of 10 Hz from both the EV and EVSE during each charge session. These charge session parameters were then entered into a time-series database for further analysis. The data were gathered under different operational conditions to examine the effects of various factors such as battery state of charge, battery temperature, vehicle condition, smart charge management, and EVSE limitations. The EV profile capture dataset includes extensive high-power charging data from 16 different EVs—comprising light-, medium-, and heavy-duty vehicles—along with EVSE from various suppliers. To protect confidentiality, the EV and EVSE metadata are anonymized, and the publicly released datasets are aggregated to 0.1-Hz frequency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

EVSE Characterization

NextGen Profiles' EVSE characterization efforts explored performance variability in production EVSE through the use of EV emulation equipment and assessed how different operational conditions influence charging behavior. Data were collected at a frequency of 10 Hz from both the EV emulator and EVSE during each charge session and stored in a time-series database for further analysis. As part of the NextGen Profiles project, characterization of high-power EVSE was performed on both conductive and wireless charging infrastructure; however, only conductive charging data are currently included in this repository. This EVSE characterization was performed over a range of DC output currents and voltages, covering both nominal and off-nominal test conditions. This EVSE characterization dataset includes high-power charging data from two types of 350-kW-capable EVSE using liquid-cooled Combined Charging System-1 (CCS1, North American version) cables and connectors. To protect confidentiality, all EVSE metadata are anonymized, and the publicly released datasets are metered at 10-Hz frequency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Fleet Utilization

A key goal of NextGen Profiles' fleet utilization study was to conduct a comprehensive, strategic, and standardized assessment of the operational behavior and utilization patterns across EV and EVSE production-ready fleets. These data-driven insights were intended to inform current fleet management strategies and support future infrastructure planning, ensuring the effective adoption and adaptation of the growing EV fleet market. The study applied a series of metrics defined in NextGen Profiles to evaluate diverse fleet operations across various use cases, emphasizing trends in charging, routing, and other critical behaviors. The fleet utilization dataset includes these three sets of metrics from 17 EV fleets, each consisting of a wide range of vehicle types and operational categories, as well as two EVSE fleets. Data were collected from a variety of sources and reformatted into a unified structure before metric computation, ensuring consistency and comparability across all fleets. To protect confidentiality, all fleet metadata are anonymized, and the publicly released metric datasets are aggregated to an hourly cadence.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

An Exact Algorithm for the Linear Tape Scheduling Problem

Magnetic tapes are often considered as an outdated storage technology, yet they are still used to store huge amounts of data. Their main interests are a large capacity and a low price per gigabyte, which come at the cost of a much larger file access time than on disks. With tapes, finding the right ordering of multiple file accesses is thus key to performance. Moving the reading head back and forth along a kilometer long tape has a non-negligible cost and unnecessary movements thus have to be avoided. However, the optimization of tape request ordering has rarely been studied in the scheduling literature, much less than I/O scheduling on disks. For instance, minimizing the average service time for several read requests on a linear tape remains an open question. Therefore, in this paper, we aim at improving the quality of service experienced by users of tape storage systems, and not only the peak performance of such systems. To this end, we propose a reasonable polynomial-time exact algorithm while this problem and simpler variants have been conjectured NP-hard. We also refine the proposed model by considering U-turn penalty costs accounting for inherent mechanical accelerations. Then, we propose a low-cost variant of our optimal algorithm by restricting the solution space, yet still yielding an accurate suboptimal solution. Finally, we compare our algorithms to existing solutions from the literature on logs of the mass storage management system of a major datacenter. This allows us to assess the quality of previous solutions and the improvement achieved by our low-cost algorithm. Aiming for reproducibility, we make available the complete implementation of the algorithms used in our evaluation, alongside the dataset of tape requests that is, to the best of our knowledge, the first of its kind to be publicly released.

Honoré, Valentin↗
DOE OSTI2020

Cooperative Research and Development Agreement (CRADA) NFE-18-07194 with TerraPower LLC (Final Report)

Because of the potential economic and safety benefits of the molten salt reactor (MSR) concept, development of several designs has been initiated around the world over the past decade. New international nuclear safeguards needs and verification challenges are likely to arise because of the commercial interests in MSRs and the number of MSR design variants. As a result, work was undertaken to explore the cross-cutting issues specific to the application of international nuclear safeguards (i.e., safeguards) to liquid-fueled molten salt reactors (LFMSRs). Through a public-private partnership, a report was developed that focuses on the TerraPower Molten Chloride Fast Reactor (MCFR) design that has received a funding award from the US Department of Energy (DOE), Office of Nuclear Energy. The report is intended to provide a preliminary analysis for a safeguards-by-design (SBD) effort to inform designers about how safeguards could be applied to LFMSRs by the International Atomic Energy Agency (IAEA).Although the report specifically focuses on the TerraPower design, the conclusions are applicable to the main design features of LFMSRs and can be used to extrapolate how existing IAEA safeguards measures for other fuel cycle facilities can be appropriately applied or modified. The report evaluates the appropriate safeguards approaches for LFMSRs, presents existing safeguards inspection technologies are still valid for LFMSRs, and identifies new challenges that will require novel measurement instruments to meet verification standards of the IAEA and the international safeguards regime. This document summarizes the results of the work performed under the full report developed as part of the Cooperative Research and Development Agreement (CRADA). This summary does not contain any protected CRADA information and is intended for public release.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Offshore Wind Resource Assessment for the California Pacific Outer Continental Shelf (2020)

This report presents a state-of-the-art wind resource data set produced by the National Renewable Energy Laboratory (NREL) for the California Pacific Outer Continental Shelf (OCS). This data set replaces NREL's Wind Integration National Dataset (WIND) Toolkit for the California OCS, which was produced and released publicly in 2013 and is currently the principal data set used by stakeholders for wind resource assessment in the continental United States.

17 WIND ENERGY↗