American Nuclear Society
Home

Home / Publications / Journals / Nuclear Science and Engineering / Volume 195 / Number 1

Methodology for Generating Covariance Data of Thermal Neutron Scattering Cross Sections

Chris W. Chapman, Goran Arbanas, Alexander I. Kolesnikov, Luiz Leal, Yaron Danon, Carl Wendorff, Kemal Ramić, Li Liu, Farzad Rahnema

Nuclear Science and Engineering / Volume 195 / Number 1 / January 2021 / Pages 13-32

Technical Paper / dx.doi.org/10.1080/00295639.2020.1792716

Received:April 20, 2020
Accepted:June 30, 2020
Published:December 16, 2020

This paper details and implements a framework for evaluating thermal neutron scattering cross sections that provide data and covariance data for hydrogen in light water. This methodology involves perturbing model parameters of molecular dynamics potentials and fitting the simulation results to experimental data. The framework is general and can be applied to any material or simulation method. The fit is made using the Unified Monte Carlo method to experimentally measure double-differential scattering cross sections of light water at the Spallation Neutron Source at Oak Ridge National Laboratory. Mean values and covariance data were generated for model parameters, phonon density of states, double-differential cross sections, and total scattering cross sections. These posterior parameter values were very similar to their prior values with a maximum relative error of 0.54%. This falls within in the Unified Monte Carlo–calculated uncertainties on the order of 2.7%. Additionally, posterior double-differential cross sections agree favorably with ENDF/B-VIII.0 cross sections. The new thermal scattering law was tested by comparing it against benchmarks from the International Criticality Safety Benchmark Evaluation Project Handbook, which showed a slight improvement over the ENDF/B-VIII.0 library. Additionally, the covariance matrix of the phonon density of states was validated to confirm that the spread of keff from the density of states used to generate the covariance matrix was similar to the spread of keff from the density of states of the sampled covariance matrix.