| Issue |
EPJ Nuclear Sci. Technol.
Volume 12, 2026
|
|
|---|---|---|
| Article Number | 17 | |
| Number of page(s) | 16 | |
| DOI | https://doi.org/10.1051/epjn/2026008 | |
| Published online | 12 June 2026 | |
https://doi.org/10.1051/epjn/2026008
Regular Article
Experimental uncertainty quantification using templates of expected measurement uncertainties for fast neutron-induced total, capture, and scattering cross sections
Los Alamos National Laboratory, Los Alamos, NM, USA
* e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Received:
27
August
2025
Received in final form:
24
December
2025
Accepted:
17
April
2026
Published online: 12 June 2026
Abstract
Careful experimental uncertainty quantification (UQ) is key for developing trustworthy evaluated nuclear data. Templates to account for missing or under-reported experimental uncertainties were recently developed by the covariance committee of Cross Section Evaluation Working Group (CSEWG). In this work, we illustrate the practical application and limitations of these templates for selected neutron-induced reactions, including (n, tot), (n, γ), and (n, xn) in the fast energy range, to illustrate their use in data analyses for nuclear data evaluations. We show that while the templates provide consistent framework, proper implementation still requires detailed knowledge of experimental conditions and careful treatment of nonlinear effects in cross section derivation. Case studies highlight how template-assisted UQ improves consistency with previous evaluations such as ENDF/B and reveals open challenges in propagating uncertainties across different energy regimes. The main contribution of this paper is to connect formal template recommendations with their use in practical evaluation workflows, clarifying both their benefits and current limitations.
© A. Khatiwada et al., Published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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