Estimation of biases and uncertainties on PWR nuclide inventories for severe accidents analyses

Abstract

The work presented in this paper deals with bias and uncertainty quantification on nuclear fuel inventory in a pressurized water reactors core during normal operation. This actinides and fission products inventory is used as input data for radiological releases evaluation in case of a severe accident. The different sources of bias and uncertainty, as well as their impacts for UO2 and MOX fuel at the assembly and core levels, are discussed. Uncertainty sources include technological uncertainties (e.g. dimensions, irradiation history, temperatures), modeling assumptions, uncertainties related to the resolution methods used in the calculation tools and nuclear data uncertainties. For each source of uncertainty investigated in this paper, an evaluation of the associated biases and uncertainties on nuclide inventory is performed. It is shown that, among the sources of bias and uncertainties studied, spread due to nuclear data as well as the bias and uncertainties due to “infinite lattice approximation” are the most significant ones, for the isotopes of interest.

Fast Uncertainty Quantification of Spent Nuclear Fuel with Neural Networks

“…It was found that the cooling time affects the decay https://doi.org/10.1016/j.anucene.2023.110204 Received 7 September 2023; Received in revised form 25 October 2023; Accepted 25 October 2023 heat uncertainty, while nuclear data and assembly design parameters contribute the most to the uncertainty, with a few nuclides playing a significant role. Uncertainty sources from technological uncertainties, modeling assumptions, modeling resolution and nuclear data uncertainties on PWR nuclide inventories for severe accidents were analyzed in Ichou et al (2023). They found that the nuclear data and the ''infinite lattice approximation'' have the biggest influence on the bias and uncertainties.…”