# Stochastic homogenization of nonconvex unbounded integral functionals with convex growth

1 MEPHYSTO - Quantitative methods for stochastic models in physics
Inria Lille - Nord Europe, ULB - Université Libre de Bruxelles [Bruxelles], LPP - Laboratoire Paul Painlevé - UMR 8524
Abstract : We consider the well-travelled problem of homogenization of random integral functionals. When the integrand has standard growth conditions, the qualitative theory is well-understood. When it comes to unbounded functionals, that is, when the domain of the integrand is not the whole space and may depend on the space-variable, there is no satisfactory theory. In this contribution we develop a complete qualitative stochastic homogenization theory for nonconvex unbounded functionals with convex growth. We first prove that if the integrand is convex and has p-growth from below (with p>d, the dimension), then it admits homogenization regardless of growth conditions from above. This result, that crucially relies on the existence and sublinearity at infinity of correctors, is also new in the periodic case. In the case of nonconvex integrands, we prove that a similar homogenization result holds provided the nonconvex integrand admits a two-sided estimate by a convex integrand (the domain of which may depend on the space-variable) that itself admits homogenization. This result is of interest to the rigorous derivation of rubber elasticity from polymer physics, which involves the stochastic homogenization of such unbounded functionals.
Type de document :
Article dans une revue
Archive for Rational Mechanics and Analysis, Springer Verlag, 2016, 221 (3), pp.1511--1584. 〈10.1007/s00205-016-0992-0〉
Domaine :

https://hal.inria.fr/hal-01192752
Contributeur : Antoine Gloria <>
Soumis le : jeudi 3 septembre 2015 - 14:27:58
Dernière modification le : jeudi 11 janvier 2018 - 06:25:39

### Citation

Mitia Duerinckx, Antoine Gloria. Stochastic homogenization of nonconvex unbounded integral functionals with convex growth. Archive for Rational Mechanics and Analysis, Springer Verlag, 2016, 221 (3), pp.1511--1584. 〈10.1007/s00205-016-0992-0〉. 〈hal-01192752〉

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