Stochastic homogenization of A-convex gradient flows

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Martin Heida - , Weierstrass Institute for Applied Analysis and Stochastics (Autor:in)
  • Stefan Neukamm - , Technische Universität München (Autor:in)
  • Mario Varga - , Technische Universität München (Autor:in)

Abstract

In this paper we present a stochastic homogenization result for a class of Hilbert space evolutionary gradient systems driven by a quadratic dissipation potential and a Lambda-convex energy functional featuring random and rapidly oscillating coefficients. Specific examples included in the result are Allen-Cahn type equations and evolutionary equations driven by the p-Laplace operator with p is an element of (1, infinity). The homogenization procedure we apply is based on a stochastic two-scale convergence approach. In particular, we define a stochastic unfolding operator which can be considered as a random counterpart of the well-established notion of periodic unfolding. The stochastic unfolding procedure grants a very convenient method for homogenization problems defined in terms of (Lambda-)convex functionals.

Details

OriginalspracheEnglisch
Seiten (von - bis)427-453
Seitenumfang27
FachzeitschriftDiscrete and continuous dynamical systems-Series s
Jahrgang14
Ausgabenummer1
PublikationsstatusVeröffentlicht - Jan. 2021
Peer-Review-StatusJa
Extern publiziertJa

Externe IDs

Scopus 85098882990

Schlagworte

Schlagwörter

  • Stochastic homogenization, stochastic unfolding, two-scale convergence, gradient system, 2-SCALE HOMOGENIZATION, GAMMA-CONVERGENCE, RANDOM-WALKS, HILBERT, SPACES

Bibliotheksschlagworte