| Issue |
EPJ Web Conf.
Volume 211, 2019
WONDER-2018 – 5th International Workshop On Nuclear Data Evaluation for Reactor applications
|
|
|---|---|---|
| Article Number | 07008 | |
| Number of page(s) | 7 | |
| Section | Uncertainties And Covariance Matrices (Methodology and Impact on Reactor Calculations) | |
| DOI | https://doi.org/10.1051/epjconf/201921107008 | |
| Published online | 05 June 2019 | |
https://doi.org/10.1051/epjconf/201921107008
Examples of Monte Carlo techniques applied for nuclear data uncertainty propagation
1 Department of Energy Engineering, Universidad Politécnica de Madrid, 28006 Madrid, Spain
2 OECD/Nuclear Energy Agency, Boulogne-Billancourt, 92100, France
* Corresponding author: oscar.cabellos@upm.es
Published online: 5 June 2019
The aim of this work is to review different Monte Carlo techniques used to propagate nuclear data uncertainties. Firstly, we introduced Monte Carlo technique applied for Uncertainty Quantification studies in safety calculations of large scale systems. As an example, the impact of nuclear data uncertainty of JEFF-3.3 235U, 238U and 239Pu is demonstrated for the main design parameters of a typical 3-loop PWR Westinghouse unit. Secondly, the Bayesian Monte Carlo technique for data adjustment is presented. An example for 235U adjustment using criticality and shielding integral benchmarks shows the importance of performing joint adjustment based on different set of integral benchmarks.
© The Authors, published by EDP Sciences, 2019
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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