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Monte Carlo Methods and Applications

Managing Editor: Sabelfeld, Karl K.

Editorial Board: Binder, Kurt / Bouleau, Nicolas / Chorin, Alexandre J. / Dimov, Ivan / Dubus, Alain / Egorov, Alexander D. / Ermakov, Sergei M. / Halton, John H. / Heinrich, Stefan / Kalos, Malvin H. / Lepingle, D. / Makarov, Roman / Mascagni, Michael / Mathe, Peter / Niederreiter, Harald / Platen, Eckhard / Sawford, Brian R. / Schmid, Wolfgang Ch. / Schoenmakers, John / Simonov, Nikolai A. / Sobol, Ilya M. / Spanier, Jerry / Talay, Denis

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CiteScore 2016: 0.70

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1569-3961
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Volume 15, Issue 1

Issues

Stochastic simulation of particle transport by a random Darcy flow through a porous cylinder

K. Sabelfeld
  • ICMMG, Russian Academy of Sciences, Siberian Branch, Lavrentiev street 6, 630090 Novosibirsk, Russia. Email:
  • Other articles by this author:
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/ O. Kurbanmuradov
  • Center for Phys. Math. Research, Turkmenian State University, Turkmenbashy av. 31, 744000 Ashgabad, Turkmenistan. Email:
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ A. Levykin
  • ICMMG, Russian Academy of Sciences, Siberian Branch, Lavrentiev street 6, 630090 Novosibirsk, Russia. Email:
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Published Online: 2009-05-14 | DOI: https://doi.org/10.1515/MCMA.2009.004

Abstract

A stochastic simulation method is developed for a numerical study of particle transport in random porous medium. The hydraulic conductivity is assumed to be a random field of a given statistical structure, the flow is modelled in a cylinder with prescribed boundary conditions. Numerical experiments are carried out by solving the random Darcy equation for each sample of the hydraulic conductivity by a SOR iteration method, and tracking Lagrangian trajectories in the simulated flow.

Keywords.: Darcy equation; random hydraulic conductivity; flow in a cylinder; Lagrangian trajectory; randomized spectral models; lognormal random fields

About the article

Received: 2007-11-07

Revised: 2008-12-15

Published Online: 2009-05-14

Published in Print: 2009-05-01


Citation Information: Monte Carlo Methods and Applications, Volume 15, Issue 1, Pages 63–90, ISSN (Online) 1569-3961, ISSN (Print) 0929-9629, DOI: https://doi.org/10.1515/MCMA.2009.004.

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[1]
Orazgeldi Kurbanmuradov, Karl Sabelfeld, and Peter R. Kramer
Journal of Computational Physics, 2013, Volume 245, Page 218

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