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A Galerkin-based formulation of the probability density evolution method for general stochastic finite element systems

机译:基于Galerkin的通用随机有限元系统的概率密度演化方法

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The present paper proposes a Galerkin finite element projection scheme for the solution of the partial differential equations (pde's) involved in the probability density evolution method, for the linear and nonlinear static analysis of stochastic systems. According to the principle of preservation of probability, the probability density evolution of a stochastic system is expressed by its corresponding Fokker-Planck (FP) stochastic partial differential equation. Direct integration of the FP equation is feasible only for simple systems with a small number of degrees of freedom, due to analytical and/or numerical intractability. However, rewriting the FP equation conditioned to the random event description, a generalized density evolution equation (GDEE) can be obtained, which can be reduced to a one dimensional pde. Two Galerkin finite element method schemes are proposed for the numerical solution of the resulting pde's, namely a time-marching discontinuous Galerkin scheme and the StreamlineUpwind/Petrov Galerkin (SUPG) scheme. In addition, a reformulation of the classical GDEE is proposed, which implements the principle of probability preservation in space instead of time, making this approach suitable for the stochastic analysis of finite element systems. The advantages of the FE Galerkin methods and in particular the SUPG over finite difference schemes, like the modified Lax-Wendroff, which is the most frequently used method for the solution of the GDEE, are illustrated with numerical examples and explored further.
机译:本文提出了一种Galerkin有限元投影方案,用于求解概率密度演化方法中涉及的偏微分方程(pde),用于随机系统的线性和非线性静态分析。根据概率保留原理,随机系统的概率密度演化由相应的Fokker-Planck(FP)随机偏微分方程表示。由于分析和/或数值难处理性,FP方程的直接积分仅适用于具有少量自由度的简单系统。但是,通过重写以随机事件描述为条件的FP方程,可以获得广义密度演化方程(GDEE),可以将其简化为一维pde。针对所得pde的数值解,提出了两种Galerkin有限元方法,即时间行进不连续Galerkin方案和StreamlineUpwind / Petrov Galerkin(SUPG)方案。另外,提出了经典GDEE的重新表述,该表述实现了空间而不是时间中的概率保留原理,从而使该方法适合于有限元系统的随机分析。有限元方法(尤其是SUPG)相对于有限差分方案的优势,例如改进的Lax-Wendroff,它是GDEE求解的最常用方法,其优点已通过数值示例进行了说明并作了进一步探讨。

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