Galerkin Solution for Linear Stochastic Algebraic Equations

Algebraic equations with random coefficients, referred to as stochastic algebraic equations, are used extensively to solve approximately differential equations describing mechanics problems with uncertain material properties and applied loads. This paper (1) constructs optimal and suboptimal Galerkin solutions for linear stochastic algebraic equations, (2) reviews current procedures for deriving stochastic algebraic equations from stochastic differential equations and proposes alternative methods, (3) demonstrates the implementation of the proposed Galerkin method by numerical examples, and (4) calculates statistics of the displacement field for a plate on random elastic foundation. The optimal Galerkin solution coincides with the conditional expectation of the exact solution with respect to a σ-field coarser than the σ-field relative to which the exact solution is measurable, and is unbiased. Generally, suboptimal Galerkin solutions are biased but may provide approximations for the tails of the distribution of the exact solution that are superior to those by the optimal Galerkin solution.