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Zhurnal Vychislitel'noi Matematiki i Matematicheskoi Fiziki, 2016, Volume 56, Number 5, Pages 896–908
DOI: https://doi.org/10.7868/S0044466916050057
(Mi zvmmf10387)
 

This article is cited in 7 scientific papers (total in 7 papers)

Effective averaging of stochastic radiative models based on Monte Carlo simulation

A. Yu. Ambos, G. A. Mikhailov

Institute of Computational Mathematics and Mathematical Geophysics, Siberian Branch, Russian Academy of Sciences, pr. Akademika Lavrent'eva 6, Novosibirsk, 630090, Russia
Full-text PDF (232 kB) Citations (7)
References:
Abstract: Based on the Monte Carlo simulation and probabilistic analysis, stochastic radiative models are effectively averaged; that is, deterministic models that reproduce the mean probabilities of particle passage through a stochastic medium are constructed. For this purpose, special algorithms for the double randomization and conjugate walk methods are developed. For the numerical simulation of stochastic media, homogeneous isotropic Voronoi and Poisson mosaic models are used. The parameters of the averaged models are estimated based on the properties of the exponential distribution and the renewal theory.
Key words: Poisson ensemble, random field, correlation length, radiation transfer, transmission function, penetration probability, maximum cross section method, double randomization.
Received: 06.07.2016
English version:
Computational Mathematics and Mathematical Physics, 2016, Volume 56, Issue 5, Pages 881–893
DOI: https://doi.org/10.1134/S0965542516050055
Bibliographic databases:
Document Type: Article
UDC: 519.676
Language: Russian
Citation: A. Yu. Ambos, G. A. Mikhailov, “Effective averaging of stochastic radiative models based on Monte Carlo simulation”, Zh. Vychisl. Mat. Mat. Fiz., 56:5 (2016), 896–908; Comput. Math. Math. Phys., 56:5 (2016), 881–893
Citation in format AMSBIB
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  • This publication is cited in the following 7 articles:
    Citing articles in Google Scholar: Russian citations, English citations
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