Histogram of statistical data for optimizing the prompt fission neutron spectrum of 239Pu(n, f) via criticality benchmarking

In this study, the PFNS for 239Pu are evaluated using both differential and integral experimental data. A method that leverages integral criticality benchmark experiments to constrain the PFNS data is introduced. The measured central values of the PFNS are perturbed by constructing a covariance matrix. The PFNS are sampled using two types of covariance matrices; either generated with an assumed correlation matrix and incorporating experimental uncertainties, or derived directly from experimental reports. The joint Monte Carlo transport (JMCT) code is employed to perform transport simulations on five criticality benchmark assemblies by utilizing perturbed PFNS data. Extensive simulations result in an optimized PFNS that shows improved agreement with the integral criticality benchmark experiments. This study introduces a novel approach for optimizing differential experimental data through integral experiments, particularly when a covariance matrix is not provided. These data show the bin centers and counts of the sampled statistical histograms.