Workshop for Applied Nuclear Data: WANDA2020
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Romano, Catherine↗
SEARCH · Engineering Papers
Results for “Nuclear data”
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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Calculating the impact of nuclear data changes with Crater
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Haeck, Wim↗
Nuclear data uncertainty challenges in Molten Salt Reactor safeguards
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Soares, Andre↗
Current Nuclear Data Needs for Applications
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Physics↗
FAUST - A Benchmark and Validation framework for Nuclear Data
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FAUST, benchmarks↗
Application of ML Interpretability to Augment Research in Nuclear Physics, Nuclear Data, and Inertial Confinement Fusion
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Grosskopf, Michael John↗
Sensitivity Tool Needs for Modern Nuclear Data Validation
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Rising, Michael Evan↗
From CAD to Nuclear Data S/U for Shielding Applications
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Kos, Bor↗
“Nuclear Data Adjustments and Impact to Applications” at WANDA2022
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Neudecker, Denise↗
LWR DECAY HEAT ANALYSIS WITH SCALE 6.3 AND ENDF/B-VIII.0 NUCLEAR DATA LIBRARIES
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Ilas, Germina↗
Nuclear Data Adjustment and Impact on Applications
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Neudecker, Denise↗
International Nuclear Data Evaluation Network (INDEN) on Actinide Evaluation in the Resonance Region (4) Summary Report of the IAEA Consultants’ Meeting IAEA Headquarters, Vienna Austria 1-4 November 2021
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Noguere, Gilles↗
252Cf Production at the High Flux Isotope Reactor: Nuclear Data Selection and LEU Conversion Impacts
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Hartanto, Donny↗
Nuclear Data Uncertainty Quantification of High Flux Isotope Reactor Low-Enriched Uranium Design
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Hartanto, Donny↗
easy_pert: A Python tool for using the PERT card to compute fixed source sensitivities to nuclear data
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Clark, Alexander Rich↗
Computing upper subcritical limits via Whisper using ENDF/B-VIII.0 nuclear data
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Clark, Alexander Rich↗
IMPACT OF RECENT ENDF NUCLEAR DATA ON BURNUP CREDIT CRITICALITY SAFETY ANALYSES
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Dupont, Mathieu↗
Methodology, verification, and performance of the continuous-energy nuclear data sensitivity capability in MCNP6
A continuous-energy sensitivity coefficient capability has been introduced into MCNP6. The methods for generating energy-resolved and energy-integrated sensitivity profiles are discussed. Results from the verification exercises that were performed are given, and these show that MCNP6 compares favorably with analytic solutions, direct density perturbations, and comparisons to TSUNAMI-3D and MONK. Run-time and memory requirements are assessed for typical applications, and these are shown to be reasonable with modern computing resources. (authors)
97 MATHEMATICS AND COMPUTING↗