| Issue |
EPJ Web Conf.
Volume 302, 2024
Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo (SNA + MC 2024)
|
|
|---|---|---|
| Article Number | 07017 | |
| Number of page(s) | 9 | |
| Section | High Performance Computing for Nuclear Data Processing – Benchmarking | |
| DOI | https://doi.org/10.1051/epjconf/202430207017 | |
| Published online | 15 October 2024 | |
https://doi.org/10.1051/epjconf/202430207017
Preliminary Generation of Windowed Multipole Covariance Data
Massachusetts Institute of Technology
* e-mail: jebarlow@mit.edu
** e-mail: bforget@mit.edu
Published online: 15 October 2024
A methodology for the generation of covariance data in the windowed multipole formalism for resolved resonance data was developed. Using this process, covariance matrices were created for oxygen-16, uranium-235, and uranium-238, such that sampled cross-sections would match a user-selected average standard deviation, set at 5% ± 0.5% for this work. Windowed multipole datasets were then sampled and used on a simple critical benchmark to demonstrate the use of WMP data in conjunction with the Total Monte Carlo method of uncertainty propagation.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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