This paper presents a review of the current state-of-the-art of numerical methods for stochastic computations. The focus is on efficient high-order methods suitable for practical applications, with a particular emphasis on those based on generalized polynomial chaos (gPC) methodology. The framework of gPC is reviewed, along with its Galerkin and collocation approaches for solving stochastic equations. Properties of these methods are summarized by using results from literature. This paper also attempts to present the gPC based methods in a unified framework based on an extension of the classical spectral methods into multi-dimensional random spaces.
机构:
Department of Mathematics, Kookmin University, Seoul 136-702, Korea, Republic ofDepartment of Mathematics, Kookmin University, Seoul 136-702, Korea, Republic of
Park, Taehoon
Kim, Pok-Son
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机构:
Fachbereich Informatik, Johan Wolfgang Goethe-Universitaet, Postfach 11 19 32, D-60054 Frankfurt/Main, GermanyDepartment of Mathematics, Kookmin University, Seoul 136-702, Korea, Republic of
机构:
St Petersburg State Univ, Univ Skaya Nab 7-9, St Petersburg 199034, RussiaSt Petersburg State Univ, Univ Skaya Nab 7-9, St Petersburg 199034, Russia