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Stochastic system for generalized polytropic filtration

机译:广义多细胞过滤的随机系统

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In this paper, we study a certain class of stochastic quasilinear parabolic equations describing a generalized polytropic elastic filtration in the framework of variable exponents Lebesgue and Sobolev spaces. We establish an existence result in the infinite dimensional framework of weak probabilistic solutions when the forcing terms do not satisfy Lipschitz conditions, and the governing equations are subjected to cylindrical Wiener processes. We use a Galerkin method, derive crucial a priori estimates for the approximate solutions, and combine profound analytic and probabilistic compactness results in order to pass to the limit. Several difficulties arise in obtaining these uniform bounds and passing to the limit since the nonlinear elliptic part of the leading operator admits nonstandard growth. Apart from adapting the above essential tools, we extend classical methods of monotonicity to the present situation.
机译:在本文中,我们研究了一定类的随机拟线性抛物方程,其描述了可变指数Lebesgue和Soboleev空间的框架中的广义多细胞性弹性过滤。 当迫使术语不满足Lipschitz条件时,我们建立弱概率解决方案无限尺寸框架的存在结果,并且控制方程经受圆柱形维纳工艺。 我们使用Galerkin方法,为近似解决方案推导至关重要,并结合深刻的分析和概率紧凑率,以便传递给极限。 由于领先运营商的非线性椭圆形部分承认非线性椭圆部分,因此在获得这些均匀的边界并传递到极限时出现了几个困难。 除了调整上述必要工具之外,我们将展示对目前情况的古典单调性方法。

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