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Solution of linear and nonlinear diffusion problems via stochastic differential equations

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The equation for nonlinear diffusion can be rearranged to a form that immediately leads to its stochastic analog. The latter contains a drift term that is absent when the diffusion coefficient is constant. The dependence of this coefficient on concentration (or temperature) is handled by generating many paths in parallel and approximating the derivative of concentration with respect to distance by the central difference. This method works for one-dimensional diffusion problems with finite or infinite boundaries and for diffusion in cylindrical or spherical shells. By mimicking the movements of molecules, the stochastic approach provides a deeper insight into the physical process. The parallel version of our algorithm is very efficient. The 99% confidence limits for the stochastic solution enclose the analytical solution so tightly that they cannot be shown graphically. This indicates that there is no systematic difference in the results for the two methods. Finally, we present a direct derivation of the stochastic method for cylindrical and spherical shells.
Wydawca
Czasopismo
Rocznik
Strony
415--428
Opis fizyczny
Bibliogr. 10 poz., rys., wykr., tab.
Twórcy
autor
  • AGH University of Science and Technology, Faculty of Computer Science, Electronics and Telecommunications, Department of Computer Science, Krakow, Poland
autor
  • Department of Mathematics and Computer Science, Mount Allison University, P.O. Box 6054, Sackville, NB, E4L 1G6, Canada
Bibliografia
  • [1] Bargie l M., Tory E.M.: Stochastic dynamic solution of nonlinear differential equations for transport phenomena. American Institute of Chemical Engineers Journal , vol. 42(3), pp. 889–891. doi:10.1002/aic.690420327, 1996.
  • [2] Crank J.: The Mathematics of Diffusion. Oxford University Press, second ed., 1975.
  • [3] Etheridge A.: A Course in Financial Calculus. Cambridge University Press, first ed., 2002.
  • [4] Gardiner C.W.: Handbook of Stochastic Methods: for Physics, Chemistry and the Natural Sciences . Springer-Verlag New York, second ed., 1985.
  • [5] Kloeden P.E., Platen E.: Numerical Solution of Stochastic Differential Equations . Springer-Verlag, Berlin–Heidelberg, first ed., 1992.
  • [6] Kolmogorov A.: ̈ Uber die analytischen Methoden in der Wahrscheinlichkeitsrechnung. Mathematische Annalen , vol. 104(1), pp. 415–458, 1931.
  • [7] Laso M.: Stochastic dynamic approach to transport phenomena. American Institute of Chemical Engineers Journal , vol. 40(8), pp. 1297–1311. doi: 10.1002/aic.690400804, 1994. ISSN 1547-5905.
  • [8] Øksendal B.K.: Stochastic Differential Equations: An Introduction with Applications . Springer-Verlag, Berlin–Heidelberg, sixth ed., 2003.
  • [9] Risken H.: The Fokker-Planck Equation: Methods of Solutions and Applications . Springer-Verlag, Berlin–Heidelberg, second ed., 1989.
  • [10] Van Kampen N.: Stochastic Processes in Physics and Chemistry . Elsevier Ams- terdam, third ed., 2007.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-60ec1bb7-e4e5-4408-a437-7543e3ec1d06
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