Large deviation for a 2D Allen-Cahn-Navier-Stokes model under random influences

被引：3

作者：

Deugoue, G. ^{[1
]}

Medjo, T. Tachim ^{[1
,2
]}

机构：

[1] Univ Dschang, Dept Math & Comp Sci, POB 67, Dschang, Cameroon

[2] Florida Int Univ, Dept Math, DM413B Univ Pk, Miami, FL 33199 USA

来源：

ASYMPTOTIC ANALYSIS | 2021年 / 123卷 / 1-2期

关键词：

Allen-Cahn; Navier-Stokes; strong solutions; Gaussian noise; large deviations; PHASE-FIELD MODEL; EQUATIONS DRIVEN;

D O I：

10.3233/ASY-201625

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this article, we derive a large deviation principle for a 2D Allen-Cahn-Navier-Stokes model under random influences. The model consists of the Navier-Stokes equations for the velocity, coupled with an Allen-Cahn equation for the order (phase) parameter. The proof relies on the weak convergence method that was introduced in (Ann. Inst. Henri Poincare Probab. Stat. 47 (2011) 725-747) and based on a variational representation on infinite-dimensional Brownian motion.

引用

页码：41 / 78

页数：38

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