Variance reduction techniques for MCNP applied to PBMR

Abstract

The applicability of the Monte Carlo N-Particle code (MCNP) to evaluate reactor shielding applications is greatly improved through the use of variance reduction techniques. This study deals with the analysis of variance reduction methods, more specifically, variance reduction methods applied in MCNP such as weight windows, geometry splitting and source biasing consistent with weight windows. Furthermore, different cases are presented to show how to improve the Figure of Merit (FOM) of an MCNP calculation when weight windows and source biasing consistent with weight windows are used. Various methodologies to generate weight windows are clearly defined in this dissertation. All the above-mentioned concepts are used to analyse a system similar to the upper part of the Pebble Bed Modular Reactor's (PBMR) bottom reflector.