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Estimation of the average particle flux in a stochastically homogeneous medium by Monte Carlo method. / Lotova, Galiya Z.; Mikhailov, Gennady A.

в: Russian Journal of Numerical Analysis and Mathematical Modelling, Том 37, № 6, 01.12.2022, стр. 363-371.

Результаты исследований: Научные публикации в периодических изданияхстатьяРецензирование

Harvard

Lotova, GZ & Mikhailov, GA 2022, 'Estimation of the average particle flux in a stochastically homogeneous medium by Monte Carlo method', Russian Journal of Numerical Analysis and Mathematical Modelling, Том. 37, № 6, стр. 363-371. https://doi.org/10.1515/rnam-2022-0029

APA

Vancouver

Lotova GZ, Mikhailov GA. Estimation of the average particle flux in a stochastically homogeneous medium by Monte Carlo method. Russian Journal of Numerical Analysis and Mathematical Modelling. 2022 дек. 1;37(6):363-371. doi: 10.1515/rnam-2022-0029

Author

Lotova, Galiya Z. ; Mikhailov, Gennady A. / Estimation of the average particle flux in a stochastically homogeneous medium by Monte Carlo method. в: Russian Journal of Numerical Analysis and Mathematical Modelling. 2022 ; Том 37, № 6. стр. 363-371.

BibTeX

@article{b5bb5a2f4c15416fb143ad23acd5c1df,
title = "Estimation of the average particle flux in a stochastically homogeneous medium by Monte Carlo method",
abstract = "The paper is focused on the study of the superexponential growth of the average number of particles in a stochastically homogeneous propagating medium. A mosaic Voronoi field ('mosaic') is considered as a random density model. The notion of 'effective' correlation radius is introduced to compare the results with previously obtained estimates of superexponential parameters for a spherically symmetric layered mosaic. It is shown that transition from the layered random density model to a chaotic one preserving the correlation scale and one-dimensional distribution weakens the 'superexponential' property of the particle flux.",
keywords = "particle flow, random medium, Statistical simulation, time asymptotics, Voronoi mosaic",
author = "Lotova, {Galiya Z.} and Mikhailov, {Gennady A.}",
note = "Publisher Copyright: {\textcopyright} 2022 Walter de Gruyter GmbH, Berlin/Boston.",
year = "2022",
month = dec,
day = "1",
doi = "10.1515/rnam-2022-0029",
language = "English",
volume = "37",
pages = "363--371",
journal = "Russian Journal of Numerical Analysis and Mathematical Modelling",
issn = "0927-6467",
publisher = "Walter de Gruyter GmbH",
number = "6",

}

RIS

TY - JOUR

T1 - Estimation of the average particle flux in a stochastically homogeneous medium by Monte Carlo method

AU - Lotova, Galiya Z.

AU - Mikhailov, Gennady A.

N1 - Publisher Copyright: © 2022 Walter de Gruyter GmbH, Berlin/Boston.

PY - 2022/12/1

Y1 - 2022/12/1

N2 - The paper is focused on the study of the superexponential growth of the average number of particles in a stochastically homogeneous propagating medium. A mosaic Voronoi field ('mosaic') is considered as a random density model. The notion of 'effective' correlation radius is introduced to compare the results with previously obtained estimates of superexponential parameters for a spherically symmetric layered mosaic. It is shown that transition from the layered random density model to a chaotic one preserving the correlation scale and one-dimensional distribution weakens the 'superexponential' property of the particle flux.

AB - The paper is focused on the study of the superexponential growth of the average number of particles in a stochastically homogeneous propagating medium. A mosaic Voronoi field ('mosaic') is considered as a random density model. The notion of 'effective' correlation radius is introduced to compare the results with previously obtained estimates of superexponential parameters for a spherically symmetric layered mosaic. It is shown that transition from the layered random density model to a chaotic one preserving the correlation scale and one-dimensional distribution weakens the 'superexponential' property of the particle flux.

KW - particle flow

KW - random medium

KW - Statistical simulation

KW - time asymptotics

KW - Voronoi mosaic

UR - http://www.scopus.com/inward/record.url?scp=85143981200&partnerID=8YFLogxK

U2 - 10.1515/rnam-2022-0029

DO - 10.1515/rnam-2022-0029

M3 - Article

AN - SCOPUS:85143981200

VL - 37

SP - 363

EP - 371

JO - Russian Journal of Numerical Analysis and Mathematical Modelling

JF - Russian Journal of Numerical Analysis and Mathematical Modelling

SN - 0927-6467

IS - 6

ER -

ID: 40960157