Criticality codes biases and associated uncertainties determination for fissile nuclear material transportation using different approaches

Abstract

International audienceCriticality safety analysis regarding fissile nuclear material transportation or operations requires, among many aspects, the experimental validation of the criticality codes with the associated cross-section libraries. The requirements for the experimental validation of the criticality code is to analyze the similarity between a selected set of critical experiments and the industrial configuration studied to determine the calculational biases and the associated uncertainties using different methods.The method currently used in France for addressing the bias and its associated uncertainty is mainly based on expert judgment and the knowledge of available experiments. This approach uses descriptive parameters (geometry, composition…) and some macroscopic calculated parameters to infer experiments potentially representative of an industrial case and the corresponding biases. The biases of the reference experiments are then transposed to the industrial case depending of the representativity of the experiments. This step can be facilitated by doing a linear regression of keff versus the parameter that best describes the configuration. An alternative method is to study the similarity between the selected experiments and the industrial case using the statistical approach based on the Generalized Linear Least Square Method (GLLSM). This method allows the propagation of uncertainties in nuclear data and discrepancies between calculations and reference benchmarks for a selection of experiments to linearly adjust the calculated keff values to reference values and therefore exhibit a bias and uncertainty due to nuclear data for an industrial case. The aim of the paper is to compare these two methodologies on an Orano TN transport and storage cask for BWR used fuel at around 15 GWD/MTU. A first selection of experiments was drawn using expert judgment. This selection was then restricted to experiments that were shown to be the closest to the industrial case regarding the Ck “similarity” parameter calculated with the SCALE 6.2.1 package. Applying both methodologies to the industrial case highlights that they both give comparable biases with regards to the uncertainties