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Results for “98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL PROTECTION”

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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3,231 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Mapping the Microhardness of Al Matrix in U-7Mo/Al Dispersion Fuels at Medium and High Burn-up by in situ Nanoindentation

The mechanical degradation of the Al matrix in U-7Mo dispersion fuels was detected after irradiation in previous studies, but more details of the degradation mechanism are not clear yet to clarify the root cause. In this study, microhardness mapping in fresh and irradiated U-7Mo dispersion fuels coated with ZrN, with burn-up of 3.35 × 10 21 and 6.28 × 10 21 f/cm 3 , are measured to reveal the hardening of the Al matrix as a function of distance to fuel particles. Micro cubes were pulled by plasma focused ion beam scanning electron microscopy and tested by in situ nanoindenter with Berkovitch tip. Size effects are measured in medium and high burn-up samples. The higher burn-up specimen exhibits a more pronounced size effect when indent load is lower than 20 mN. Size effect correction models are also calculated by plots fitting, which predicts the true microhardness without size effect. Results shows that the hardness of the Al matrix near the ZrN coating has the highest value, then decreases moving away from the coating and become stable when the distance reaches ∼10 µm. The hardness starts increasing again getting closer to the next fuel particle, which makes the hardness distribution between two fuel particles to be “U” shape.

36 - MATERIALS SCIENCE↗
DOE OSTI2026

Optimization of the FRIB beam dump: a hybrid genetic algorithm and reinforcement learning approach

The operational envelope of high-power-density systems, such as particle accelerators and advanced nuclear energy systems, is critically constrained by the need to manage extreme thermal loads. To address this, we present a novel hybrid optimization framework combining a genetic algorithm (GA) with a soft actor-critic (SAC) deep reinforcement learning agent. This framework was applied to a practical high-heat-flux problem: redesigning the beam dump at the Facility for Rare Isotope Beams (FRIB) for a power upgrade from 20 kW to 50 kW. The resulting design, validated by three-dimensional conjugate heat transfer simulations, suppresses hazardous hot spots and yields a markedly more uniform temperature distribution. This provides a robust operating margin, increasing the average power-handling capability by 72% relative to the current design, demonstrating the framework’s potential to solve complex thermal management challenges in both accelerator technology and advanced nuclear systems.

Accelerator↗
DOE OSTI2024

Dark energy survey year 3 results: likelihood-free, simulation-based w CDM inference with neural compression of weak-lensing map statistics

We present simulation-based cosmological wcold dark matter (wCDM) inference using dark energy survey year 3 weak-lensing maps, via neural data compression of weak-lensing map summary statistics: power spectra, peak counts, and direct map-level compression/inference with convolutional neural networks (CNN). Using simulation-based inference, also known as likelihood-free or implicit inference, we use forward-modelled mock data to estimate posterior probability distributions of unknown parameters. This approach allows all statistical assumptions and uncertainties to be propagated through the forward-modelled mock data; these include sky masks, non-Gaussian shape noise, shape measurement bias, source galaxy clustering, photometric redshift uncertainty, intrinsic galaxy alignments, non-Gaussian density fields, neutrinos, and non-linear summary statistics. We include a series of tests to validate our inference results. This paper also describes the Gower Street simulation suite: 791 full-sky pkdgrav3 dark matter simulations, with cosmological model parameters sampled with a mixed active-learning strategy, from which we construct over 3000 mock dark energy survey lensing data sets. For wCDM inference, for which we allow –1 < w < –$\frac{1}{3}$⁠, our most constraining result uses power spectra combined with map-level (CNN) inference. Using gravitational lensing data only, this map-level combination gives Ω m = 0.283$^{+0.020}_{–0.027}$⁠, S 8 = 0.804$^{+0.025}_{–0.017⁠}$, and w < –0.80 (with a 68 per cent credible interval); compared to the power spectrum inference, this is more than a factor of two improvement in dark energy parameter (Ω⁠ DE , w⁠) precision.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

ORNL Report of Analysis for the Verification of NRMP CRM U030A

In support of the Certified Reference Material (CRM) program managed by the Nuclear Reference Material Program (NRMP), the Material Signatures and Isotopic Standards (MSIS) group of Oak Ridge National Laboratory (ORNL) was asked to prepare a set of CRM U030A units for use as standards for isotopic analysis using multicollector thermal ionization mass spectrometry (TIMS) and inductively coupled plasma mass spectrometry (ICP-MS) instruments. This report documents the results of the verification measurements performed on three randomly selected units by the MSIS group’s ISO/IEC 17025:2017 accredited operating procedure CSD-AM-CIMS-IN20, Determination of Uranium and Plutonium Isotopic Composition using Thermal Ionization Mass Spectrometry [1], and in accordance with the quality assurance plan as described in QAP-X-96-CSD/RML-001, Nuclear Analytical Chemistry Laboratory Section Quality Assurance Plan [2].

Mathew, Kattathu [Oak Ridge National Laboratory (O↗