Nuclear Data Covariance Analysis in Radiation-Transport Simulations Utilizing SCALE Sampler and the IRDFF Nuclear Data Library
This article describes the nuclear data covariance analysis of an experimental design for a neutron energy-tuning assembly (ETA) created to shape a 14-MeV neutron point source to an objective spectrum. Underlying nuclear data uncertainties play a large role in the radiation transport and reaction rates for the range of responses to be expected from an experiment. The methodology leveraged the Standardized Computer Analysis for Licensing Evaluation (SCALE) Sampler module to determine the uncertainty in the neutron transport. The reaction uncertainty was perturbed with the International Reactor Dosimetry and Fusion File v.1.05 uncertainty, correlation matrix, and reaction cross section through multivariate normal distribution sampling to provide a final response metric. The resultant neutron fluence uncertainty for the ETA ranged from 2.7% to 6.2% in the energy range from 1.28 keV to 14.1 MeV, which contains 99.99% of the neutron fluence. The integrated uncertainties, including statistical and systematic nuclear data uncertainties, for the reaction products analyzed were 2.33% to 4.84% for most reactions, but 55Mn(n, γ), a less well-characterized reaction occurring in an energy domain with high flux uncertainty, was 19.7%. The mean of the reaction distributions was within 1.1% of the unperturbed nuclear data simulation. The experiment is planned for late 2019, where the predicted results will be compared against the experimental outcomes. The methodology presented can be utilized with alternate nuclear libraries in SCALE to develop uncertainty bounds and neutron flux spectra for many radiation-transport problems.
IEEE Transactions on Nuclear Science
N. J. Quartemont, A. A. Bickley and J. E. Bevins, "Nuclear Data Covariance Analysis in Radiation-Transport Simulations Utilizing SCALE Sampler and the IRDFF Nuclear Data Library," in IEEE Transactions on Nuclear Science, vol. 67, no. 3, pp. 482-491, March 2020, doi: 10.1109/TNS.2020.2970700.