Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-26T08:41:17.388Z Has data issue: false hasContentIssue false

Probabilistic Approximation of a Nonlinear Parabolic Equation Occurring in Rheology

Published online by Cambridge University Press:  14 July 2016

Mohamed Ben Alaya*
Affiliation:
Université Paris 13
Benjamin Jourdain*
Affiliation:
CERMICS
*
Postal address: LAGA, Institut Galilée, Université Paris 13, 93430 Villetaneuse, France. Email address: [email protected]
∗∗ Postal address: CERMICS, École des Ponts, ParisTech, 6–8 avenue Blaise Pascal, 77455 Marne la Vallée, France. Email address: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

In this paper we are interested in a nonlinear parabolic evolution equation occurring in rheology. We give a probabilistic interpretation to this equation by associating a nonlinear martingale problem with it. We prove the existence of a unique solution, P, to this martingale problem. For any t, the time marginal of P at time t admits a density ρ(t,x) with respect to the Lebesgue measure, where the function ρ is the unique weak solution to the evolution equation in a well-chosen energy space. Next we introduce a simulable system of n interacting particles and prove that the empirical measure of this system converges to P as n tends to ∞. This propagation-of-chaos result ensures that the solution to the equation of interest can be approximated using a Monte Carlo method. Finally, we illustrate the convergence in some numerical experiments.

Type
Research Article
Copyright
Copyright © Applied Probability Trust 2007 

References

Bass, R. F. and Pardoux, E. (1987). Uniqueness for diffusions with piecewise constant coefficients. Prob. Theory Relat. Fields 76, 557572.CrossRefGoogle Scholar
Cancès, E., Catto, I. and Gati, Y. (2005). Mathematical analysis of a nonlinear parabolic equation arising in the modelling of non-Newtonian flows. SIAM J. Math. Anal. 37, 6082.CrossRefGoogle Scholar
Cancès, E., Catto, I., Gati, Y. and Le Bris, C. (2005). Well-posedness of a multiscale model for concentrated suspensions. SIAM J. Multiscale Modeling Simul. 4, 10411058.CrossRefGoogle Scholar
Hébraux, P. and Lequeux, F. (1998). Mode-coupling theory for the pasty rheology of soft glassy materials. Phys. Rev. Lett. 81, 29342937.CrossRefGoogle Scholar
Krylov, N. V. (1974). Some estimates of the probability density of a stochastic integral. Ser. Mat. 38, 233254.Google Scholar
Lepeltier, J. P. and Marchal, B. (1976). Problème des martingales et équations différentielles stochastiques associées à un opérateur intégro-différentiel. Ann. Inst. H. Poincaré B 12, 43103.Google Scholar
Méléard, S. (1995). Asymptotic behaviour of some interacting particle systems; McKean–Vlasov and Boltzmann models. In Probabilistic Models for Nonlinear Partial Differential Equations (Lecture Notes Math. 1627; Montecatini Terme, 1995), Springer, Berlin, pp. 4295.Google Scholar
Revuz, D. and Yor, M. (1991). Continuous martingales and Brownian motion. Springer, Berlin.CrossRefGoogle Scholar
Stroock, D. W. and Varadhan, S. R. S. (1979). Multidimensional Diffusion Processes. Springer, Berlin.Google Scholar
Sznitman, A.-S. (1991). Topics in propagation of chaos. In Ecole d'Été de Probabilités de Saint-Flour XIX—1989 (Lecture Notes Math. 1464), Springer, New York.Google Scholar