Estimation method of systematic uncertainties in Monte Carlo particle transport simulation based on analysis of variance. Issue 4 (3rd April 2019) - Hashimoto, Shintaro
ABSTRACT: In the present work, the authors propose a standard analytical method to estimate systematic uncertainties in the Monte Carlo particle transport simulation based on analysis of variance (ANOVA). As sample problems, two sets of neutron-shielding calculations for evaluating effective dose were performed using the Particle and Heavy Ion Transport code System coupled with ANOVA. In the simulation, we selected the total cross section and the water density in material as unclear physical quantities to induce systematic uncertainties. Systematic and statistical uncertainties were evaluated by changing the number of simulation conditions and trials per condition, where each condition is associated with one set of unclear quantities. Then, we analyzed the dependence of convergence of the systematic uncertainties on the number of conditions and trials. The analysis results show that simulations with only three conditions are adequate in the case where variations in the conditions have a monotonic effect on the calculation results, while more than 100 conditions are required in the other cases. In addition, we propose a useful criterion to determine the appropriate number of trials for converging systematic uncertainties.