| Issue |
EPJ Web Conf.
Volume 247, 2021
PHYSOR2020 – International Conference on Physics of Reactors: Transition to a Scalable Nuclear Future
|
|
|---|---|---|
| Article Number | 15002 | |
| Number of page(s) | 8 | |
| Section | Sensitivity & Uncertainty Methods | |
| DOI | https://doi.org/10.1051/epjconf/202124715002 | |
| Published online | 22 February 2021 | |
https://doi.org/10.1051/epjconf/202124715002
UNCERTAINTY CHARACTERIZATION FRAMEWORK FOR STEADY-STATE AND TRANSIENT NEUTRONICS SIMULATIONS OF A CANDU REACTOR
1 Purdue University, School of Nuclear Engineering 205 Gates Rd., West Lafayette IN 47907
2 Canadian Nuclear Laboratories 1 Plant Road, Chalk River, Ontario, Canada, K0J 1P0
3 Canadian Nuclear Safety Commission 280 Slater, Ottawa, Ontario, K1P 5S9
abdelkhalik@purdue.edu
alexandre.trottier@cnl.ca
dumitru.serghiuta@canada.ca
huang714@purdue.edu
Published online: 22 February 2021
This paper reports on the development and testing of a comprehensive few-group cross section input uncertainty library for the NESTLE-C nodal diffusion-based nuclear reactor core simulator. This library represents the first milestone of a first-of-a-kind framework for the integrated characterization of uncertainties in steady-state and transient CANDU reactor simulations. The objective of this framework is to propagate, prioritize and devise a mapping capability for uncertainties in support of model validation of best-estimate calculations. A complete framework would factor both input and modeling uncertainty contributions. The scope of the present work is limited to the propagation of multi-group cross-section uncertainties through lattice physics calculations down to the few-group format, representing the input to the NESTLE-C core simulator, and finally to core responses of interest.
Key words: uncertainty characterization / CANDU neutronics core simulation / reduced order modeling
© The Authors, published by EDP Sciences, 2021
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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