Development of random geometry capability in RMC code for stochastic media analysis. (November 2015)

• Record Type: Journal Article
• Authors: Liu, Shichang; She, Ding; Liang, Jin-gang; Wang, Kan
• Is Part Of: Annals of nuclear energy. Volume 85(2015:Nov.)
• Page Start: 903
• Page End: 908
• Publication Date: 2015-11
• Subjects: Stochastic media -- Monte Carlo -- RMC -- Chord Length Sampling -- Random Sequential Addition; Nuclear energy -- Periodicals; Nuclear engineering -- Periodicals; 621.4805
• DOI: 10.1016/j.anucene.2015.07.008
• Languages: English
• ISSNs: 0306-4549

Abstract

Highlights: Monte Carlo method plays an important role in modeling of particle transport in random media. Three stochastic geometry modeling methods have been developed in RMC. The stochastic effects of the randomly dispersed fuel particles are analyzed. Investigation of accuracy and efficiency of three methods has been carried out. All the methods are effective, and explicit modeling is regarded as the best choice. Abstract: Simulation of particle transport in random media poses a challenge for traditional deterministic transport methods, due to the significant effects of spatial and energy self-shielding. Monte Carlo method plays an important role in accurate simulation of random media, owing to its flexible geometry modeling and the use of continuous-energy nuclear cross sections. Three stochastic geometry modeling methods including Random Lattice Method, Chord Length Sampling and explicit modeling approach with mesh acceleration technique, have been developed in RMC to simulate the particle transport in the dispersed fuels. The verifications of the accuracy and the investigations of the calculation efficiency have been carried out. The stochastic effects of the randomly dispersed fuel particles are also analyzed. The results show that all three stochastic geometry modeling methods can account for the effects of the random dispersion of fuel particles, and the explicit modeling method can be regarded as the best choice.