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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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Machine Learning Surrogate Process Models for Efficient Performance Assessment of a Nuclear Waste Repository.
Abstract not provided.
Machine Learning Surrogate Process Models for Efficient Performance Assessment of a Nuclear Waste Repository.
Abstract not provided.
Physics-Informed Multi-Output Surrogate Modeling of Fusion Simulations.
Abstract not provided.
Optimization-based Approaches for Design of Chemical Process Families Using ReLU Surrogates.
Abstract not provided.
6DOF CFD Surrogate Models Compared to Axisymmetric Missile Concept From Mach 0.60 to 3.95.
Abstract not provided.
Improving Bayesian networks multifidelity surrogate construction with basis adaptation.
Abstract not provided.
TOWARDS AN ERA OF LOW-TEMPERATURE INTEGRAL CRITICAL EXPERIMENTS: SURROGATE TESTING OF LOW-TEMPERATURE TEX CONFIGURATIONS
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Paper-Biologically Inspired Acquisition Function for Training and Optimizing Fourier Neural Operator Surrogates of Physical Phenomena
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Milestone 1.2.14: Surface Characterization of Irradiated Surrogate Non-Native Corrosion Plumes on Aluminum 6061-T6 Specimens
The United States Department of Energy is seeking to evaluate the feasibility of extended dry storage of aluminum-clad spent nuclear fuel (ASNF) in helium-backfilled cannisters. A significant research effort has been devoted to determining the amount of radiation-induced molecular hydrogen generation from corrosion layers that would be present on the fuel assembly surfaces. However, to date, no evidence of radiation-induced changes in the microstructure of the corroded aluminum surfaces have been reported. This report provides surface characterization, in terms of corrosion layer composition and morphology, for aluminum alloy 6061-T6 “plume” samples subjected to one of three potential ASNF drying techniques—“vacuum only”, “vacuum + 4 hours at 100 oC”, and “vacuum + 4 hours at 220 oC”—and gamma irradiated (= 53 MGy) in the presence of helium gas with ~0% added relative humidity. At these high absorbed gamma doses, for the first time ever, radiation-induced circular defects were found on the sample surface, regardless of the drying regime employed. Additionally, large cracks that penetrated through the corrosion layer to expose bare aluminum metal were observed in irradiated “plume” specimens subjected to drying conditions of “vacuum + 4 hours at 220 oC”. The nature and implications of these defects on the extended dry storage of ASNF is unclear, requiring further study.
Biphasic Response Of Human IPSC-derived Neural Network Activity Following Exposure To A Sarin-surrogate Nerve Agent
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Polynomial Chaos Surrogate Construction for Stochastic Models with Parametric Uncertainty
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Multiple-charging effects on the CCN activity and hygroscopicity of surrogate black carbon particles
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OPNA surrogate exposure and risk assessment using a human-relevant brain microphysiological system
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DISSOLUTION OF SURROGATE U-Zr FUEL USING ALNIFLEX CONDITIONS
Non-aluminum clad spent nuclear fuel (NASNF) stored in L Basin at the Savannah River Site (SRS) is widely varied in fuel composition, design, packaging, and physical condition. The complexity of the NASNF inventory presents significant challenges, and technology development is necessary for successful disposition. One such fuel in the inventory is metallic uranium-zirconium (U-Zr) alloy fuel, the focus of this study. Electrolytic or nitric acid only dissolution of metallic U-Zr alloy can form insoluble zirconium oxide, which results in up to 52% loss of U to insoluble solids, and can be subject to potentially uncontrolled oxidation reactions [1, 2]. The AlNiflex process was determined to be a viable dissolution flowsheet for the U-Zr alloy fuel. Under a narrow set of solution concentrations, a combination of hydrofluoric acid (HF), nitric acid (HNO3), aluminum nitrate (Al(NO3)3), and hexavalent chromium can safely dissolve U-Zr intermetallic alloys, keep Zr soluble, and not significantly corrode stainless steel (SS) vessels [3, 4.
Soot Formation and Precursor Chemistry in Counterflow Flames of Aviation Fuels Surrogates
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Robust Assessment of Surrogate Model Credibility
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Surrogate Models for Analyzing Performance Behavior of HPC Applications Using the RAJA Performance Suite
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