تقرير
Methodology for physics-informed generation of synthetic neutron time-of-flight measurement data
| العنوان: | Methodology for physics-informed generation of synthetic neutron time-of-flight measurement data |
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| المؤلفون: | Walton, Noah, Brown, Jesse, Fritsch, William, Brown, Dave, Nobre, Gustavo, Sobes, Vladimir |
| المصدر: | Computer Physics Communications, Volume 294, 2024, 108927, ISSN 0010-4655 |
| سنة النشر: | 2023 |
| المجموعة: | Physics (Other) |
| مصطلحات موضوعية: | Physics - Computational Physics |
| الوصف: | Accurate neutron cross section data are a vital input to the simulation of nuclear systems for a wide range of applications from energy production to national security. The evaluation of experimental data is a key step in producing accurate cross sections. There is a widely recognized lack of reproducibility in the evaluation process due to its artisanal nature and therefore there is a call for improvement within the nuclear data community. This can be realized by automating/standardizing viable parts of the process, namely, parameter estimation by fitting theoretical models to experimental data. This automation effort could greatly benefit from a synthetic data resource. This work leverages problem-specific physics, Monte Carlo sampling, and a general methodology for data synthesis to generate unlimited, labelled experimental cross-section data that is statistically indistinguishable to the observed data. Heuristic and, where applicable, rigorous statistical comparisons to observed data support this claim. The demonstration is based on/limited to transmission measurements at Rensselaer Polytechnic Institute (RPI) and energy-differential cross sections in the resolved resonance region (RRR). An open-source software is published alongside this article that executes the complete methodology to produce high-utility synthetic datasets. The goal of this work is to provide an approach and corresponding tool that will allow the evaluation community to begin exploring more data-driven, ML-based solutions to long-standing challenges in the field. Comment: 14 pages, 5 figures |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1016/j.cpc.2023.108927 |
| URL الوصول: | http://arxiv.org/abs/2303.09698 |
| رقم الأكسشن: | edsarx.2303.09698 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.1016/j.cpc.2023.108927 |
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