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New Monte Carlo algorithms for investigation of criticality fluctuations in the particle scattering process with multiplication in stochastic media. / Ambos, Andrey Yu; Lotova, Galiya; Mikhailov, Guennady.

в: Russian Journal of Numerical Analysis and Mathematical Modelling, Том 32, № 3, 27.06.2017, стр. 165-172.

Результаты исследований: Научные публикации в периодических изданияхстатьяРецензирование

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Ambos AY, Lotova G, Mikhailov G. New Monte Carlo algorithms for investigation of criticality fluctuations in the particle scattering process with multiplication in stochastic media. Russian Journal of Numerical Analysis and Mathematical Modelling. 2017 июнь 27;32(3):165-172. doi: 10.1515/rnam-2017-0014

Author

Ambos, Andrey Yu ; Lotova, Galiya ; Mikhailov, Guennady. / New Monte Carlo algorithms for investigation of criticality fluctuations in the particle scattering process with multiplication in stochastic media. в: Russian Journal of Numerical Analysis and Mathematical Modelling. 2017 ; Том 32, № 3. стр. 165-172.

BibTeX

@article{e8905e4d75f447cb80d5f517e7adbe1c,
title = "New Monte Carlo algorithms for investigation of criticality fluctuations in the particle scattering process with multiplication in stochastic media",
abstract = "A Monte Carlo algorithm admitting parallelization is constructed for estimation of probability moments of the spectral radius of the operator of the integral equation describing transfer of particles with multiplication in a random medium. A randomized homogenization method is developed with the same aim on the base of the theory of small perturbations and diffusive approximation. Test calculations performed for a one-group spherically symmetric model system have shown a satisfactory concordance of results obtained from two models.",
keywords = "effective multiplication factor, Monte Carlo method, probability distribution, radiative transfer., Statistical modelling",
author = "Ambos, {Andrey Yu} and Galiya Lotova and Guennady Mikhailov",
year = "2017",
month = jun,
day = "27",
doi = "10.1515/rnam-2017-0014",
language = "English",
volume = "32",
pages = "165--172",
journal = "Russian Journal of Numerical Analysis and Mathematical Modelling",
issn = "0927-6467",
publisher = "Walter de Gruyter GmbH",
number = "3",

}

RIS

TY - JOUR

T1 - New Monte Carlo algorithms for investigation of criticality fluctuations in the particle scattering process with multiplication in stochastic media

AU - Ambos, Andrey Yu

AU - Lotova, Galiya

AU - Mikhailov, Guennady

PY - 2017/6/27

Y1 - 2017/6/27

N2 - A Monte Carlo algorithm admitting parallelization is constructed for estimation of probability moments of the spectral radius of the operator of the integral equation describing transfer of particles with multiplication in a random medium. A randomized homogenization method is developed with the same aim on the base of the theory of small perturbations and diffusive approximation. Test calculations performed for a one-group spherically symmetric model system have shown a satisfactory concordance of results obtained from two models.

AB - A Monte Carlo algorithm admitting parallelization is constructed for estimation of probability moments of the spectral radius of the operator of the integral equation describing transfer of particles with multiplication in a random medium. A randomized homogenization method is developed with the same aim on the base of the theory of small perturbations and diffusive approximation. Test calculations performed for a one-group spherically symmetric model system have shown a satisfactory concordance of results obtained from two models.

KW - effective multiplication factor

KW - Monte Carlo method

KW - probability distribution

KW - radiative transfer.

KW - Statistical modelling

UR - http://www.scopus.com/inward/record.url?scp=85021384857&partnerID=8YFLogxK

U2 - 10.1515/rnam-2017-0014

DO - 10.1515/rnam-2017-0014

M3 - Article

AN - SCOPUS:85021384857

VL - 32

SP - 165

EP - 172

JO - Russian Journal of Numerical Analysis and Mathematical Modelling

JF - Russian Journal of Numerical Analysis and Mathematical Modelling

SN - 0927-6467

IS - 3

ER -

ID: 9286942