Study of superexponential growth of the mean partile flux by Monte Carlo method

G. Z. Lotova^ab, G. A. Michailov<sup>ba

a</sup> Institute of Computational Mathematics and Mathematical Geophysics of Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia
^b Novosibirsk State University

Abstract: A comparative analysis of two algorithms for estimation of weighted mean particle flux - «by particles» and «by collisions» - is made on the basis of test problem solving for a single-speed particle propagation process with scattering and multiplication in a random medium. It is shown that the first algorithm is preferable for a simple estimation of the mean flux and the second one, for estimation of the parameters of a possible superexponential flux growth. Two models of the random medium are considered: a chaotic «Voronoi mosaic» and «a spherically layered mosaic». For a fixed mean correlation radius, the superexponential growth has been stronger for the layered mosaic.

Key words: statistical simulation, time asymptotics, random media, particle flux, Voronoi mosaic.

UDC: 519.245

Received: 18.11.2022
Revised: 23.12.2022
Accepted: 10.04.2023

DOI: 10.15372/SJNM20230304

 English version: Numerical Analysis and Applications, 2023, 16:3, 229–235