Research output: Contribution to journal › Article › peer-review
Study of Superexponential Growth of the Mean Particle Flux by Monte Carlo Method. / Lotova, G. Z.; Mikhailov, G. A.
In: Numerical Analysis and Applications, Vol. 16, No. 3, 09.2023, p. 229-235.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - Study of Superexponential Growth of the Mean Particle Flux by Monte Carlo Method
AU - Lotova, G. Z.
AU - Mikhailov, G. A.
N1 - This work was performed under state assignment of Institute of Computational Mathematics and Mathematical Geophysics SB RAS (project no. 0251-2021-0002).
PY - 2023/9
Y1 - 2023/9
N2 - A comparative analysis of two algorithms (“by particles” and “by collisions”) for estimation of the weighted mean particle flux is made on the basis of a test problem solving for a single-speed particle propagation process with isotropic 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 fits better for assessment of the parameters of a possible superexponential growth of the flux. 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 turned out to be stronger for the layered mosaic.
AB - A comparative analysis of two algorithms (“by particles” and “by collisions”) for estimation of the weighted mean particle flux is made on the basis of a test problem solving for a single-speed particle propagation process with isotropic 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 fits better for assessment of the parameters of a possible superexponential growth of the flux. 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 turned out to be stronger for the layered mosaic.
KW - Voronoi mosaic
KW - flux of particles
KW - random media
KW - statistical simulation
KW - time asymptotics
UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85171582763&origin=inward&txGid=b5a55e2b97d53f1ee082152016d6be5f
UR - https://www.mendeley.com/catalogue/046204a5-49e0-3ac6-acd5-282d08981eb6/
U2 - 10.1134/S1995423923030047
DO - 10.1134/S1995423923030047
M3 - Article
VL - 16
SP - 229
EP - 235
JO - Numerical Analysis and Applications
JF - Numerical Analysis and Applications
SN - 1995-4239
IS - 3
ER -
ID: 55508558