Uncertainty propagation across different domains is of fundamental importance in stochastic simulations. In this work, we develop a novel stochastic domain decomposition method for steady-state partial differential equations (PDEs) with random inputs. The Variable-separation (VS) method is one of the most accurate and efficient approaches to solving the stochastic partial differential equation (SPDE). We extend the VS method to stochastic algebraic systems, and then integrate its essence with the deterministic domain decomposition method (DDM). It leads to the stochastic domain decomposition based on the Variable-separation method (SDD-VS) that we investigate in this paper. A significant merit of the proposed SDD-VS method is that it is competent to alleviate the "curse of dimensionality", thanks to the explicit representation of stochastic functions deduced by physical systems. The SDD-VS method aims to get a separated representation of the solution to the stochastic interface problem. To this end, an offline-online computational decomposition is introduced to improve efficiency. The main challenge in the offline phase is to obtain the affine representation of stochastic algebraic systems, which is crucial to the SDD-VS method. This is accomplished through the successive and flexible applications of the VS method. In the online phase, the interface unknowns of SPDEs are estimated using the quasi-optimal separated representation, making it easier to construct efficient surrogate models of subproblems. At last, three concrete examples are presented to illustrate the effectiveness of the proposed method.
翻译:对于横跨不同领域的不确定传播在随机仿真中具有基础意义。本文针对随机输入的稳态偏微分方程(PDEs),开发了一种新颖的随机域分解方法。变量分离(Variable-separation,VS)方法是解决随机偏微分方程(SPDE)最准确和高效的方法之一。我们将VS方法扩展到随机代数系统,并将其要点与确定性域分解方法(DDM)集成。这导致了我们在本文中研究的基于变量分离方法(SDD-VS)的随机域分解。所提出的SDD-VS方法的一个重要优点是,由于通过物理系统推导出随机函数的显式表示,它能够有效地减缓“维度诅咒”。SDD-VS方法旨在获得解决随机界面问题的分离表示。为此,引入了离线-在线计算分解以提高效率。离线阶段的主要挑战是获得随机代数系统的仿射表示,这对于SDD-VS方法至关重要。这是通过连续和灵活地应用VS方法来实现的。在在线阶段,使用准最优分离表示估计SPDE的接口未知数,以便更容易地构造子问题的高效代理模型。最后,提供了三个具体的示例,以说明所提出的方法的有效性。