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Effective averaging of stochastic radiative models based on Monte Carlo simulation

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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.

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Authors and Affiliations

  1. Institute of Computational Mathematics and Mathematical Geophysics, Siberian Branch, Russian Academy of Sciences, pr. Akademika Lavrent’eva 6, Novosibirsk, 630090, Russia

    A. Yu. Ambos & G. A. Mikhailov

Authors
  1. A. Yu. Ambos
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  2. G. A. Mikhailov
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Correspondence to A. Yu. Ambos.

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Original Russian Text © A.Yu. Ambos, G.A. Mikhailov, 2016, published in Zhurnal Vychislitel’noi Matematiki i Matematicheskoi Fiziki, 2016, Vol. 56, No. 5, pp. 896–908.

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Ambos, A.Y., Mikhailov, G.A. Effective averaging of stochastic radiative models based on Monte Carlo simulation. Comput. Math. and Math. Phys. 56, 881–893 (2016). https://doi.org/10.1134/S0965542516050055

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  • DOI: https://doi.org/10.1134/S0965542516050055

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