Comparison of variance-reduction techniques for gamma dose rate determination

Abstract

Three-dimensional computer simulation and virtual reality technology enable the visualization of dose encountered by workers during dismantling operations by using simplified real-time dose computation tools. Such tools generally use a macroscopic approach for gamma dose rate calculation, namely the point kernel integration method with build-up factors. This simplified physical model enhances calculation performance but presents also some restrictions. In contrast, stochastic Monte Carlo methods enable a precise estimation of gamma dose rate, but computing time is prohibitive for real-time dose applications. To speed up the simulation, Monte Carlo codes can be used in combination with variance-reduction techniques, which have to be used very cautiously to stay within their limits of validity. This paper presents a comparison between two variance-reduction techniques implemented in the Monte Carlo code TRIPOLI-4 $$\circledR $$ , the exponential transform and the adaptive multilevel splitting, testing their efficiency in dismantling-like configurations.Both methods behave better in deep penetration problems but require a good amount of user experience in the creation of the importance map. This study shows the need to develop a new type of algorithm capable to tackle configurations where the lack of collisions can limit the efficiency of the current VRT.