Automated Resonance Fitting for Nuclear Data Evaluation

Walton, Noah A. W.; Zivenko, Oleksii; Lewis, Amanda M.; Fritsch, William; Forbes, Jacob; Brown, Jesse M.; Brown, David A.; Nobre, Gustavo A.; Sobes, Vladimir

doi:10.1080/00295639.2024.2439700

Title: Automated Resonance Fitting for Nuclear Data Evaluation

Journal Article · 26 January 2025 · Nuclear Science and Engineering

DOI: https://doi.org/10.1080/00295639.2024.2439700 · OSTI ID:2538389

^[1]; Zivenko, Oleksii ^[1]; Lewis, Amanda M. ^[1]; Fritsch, William ^[1]; Forbes, Jacob ^[1]; Brown, Jesse M. ^[2]; Brown, David A. ^[3]; Nobre, Gustavo A. ^[3]; Sobes, Vladimir ^[1]

University of Tennessee, Knoxville, TN (United States)
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Brookhaven National Laboratory (BNL), Upton, NY (United States)

Global and national efforts to deliver high-quality nuclear data to users have a wide-ranging impact, affecting applications in national security, reactor operations, basic science, medicine, and more. Cross-section evaluation is a major part of this effort, combining theory and experimentation to produce recommended values and uncertainties for reaction probabilities. Resonance region evaluation is a specialized type of nuclear data evaluation that can require significant manual effort and months of time from expert scientists. Here, in this article, nonconvex, nonlinear optimization methods are combined with concepts of inferential statistics to infer a resonance model from experimental data in an automated manner that is not dependent on prior evaluation(s). This methodology aims to enhance the workflow of a resonance evaluator by minimizing time, effort, and the potential for bias from prior assumptions, while enhancing reproducibility and documentation, thereby addressing well-known challenges in the field.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA), Nuclear Criticality Safety Program (NCSP); USDOE Office of Science (SC), Nuclear Physics (NP); USDOE Office of Science (SC), Office of Workforce Development for Teachers & Scientists (WDTS)

Grant/Contract Number:: AC05-00OR22725; NA0003996; SC0012704

OSTI ID:: 2538389

Journal Information:: Nuclear Science and Engineering, Journal Name: Nuclear Science and Engineering Journal Issue: 7 Vol. 199; ISSN 0029-5639

Publisher:: Taylor & FrancisCopyright Statement

Country of Publication:: United States

Language:: English

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