概率逻辑
参数统计
搭配(遥感)
计算机科学
算法
数学优化
数学
人工智能
机器学习
统计
作者
G.J.A. Loeven,Jeroen Witteveen,H. Bijl
出处
期刊:45th AIAA Aerospace Sciences Meeting and Exhibit
日期:2007-01-08
被引量:111
摘要
Complex o w and uid-structure interaction simulations require ecien t uncertainty quantication methods. In addition, a good property of an uncertainty quantication method is non-intrusiveness, meaning that existing deterministic solvers can be used for uncertainty quantication. In this paper the Probabilistic Collocation method is introduced, which combines the non-intrusiveness of the Stochastic Collocation method with the exponential convergence for arbitrary probability distributions of the Galerkin Polynomial Chaos method. Due to the non-intrusiveness and exponential convergence, the Probabilistic Collocation method requires only a few collocation points for a high accuracy. For the one dimensional piston problem the eciency of the Probabilistic Collocation method is compared with the Galerkin Polynomial Chaos method, the Non-Intrusive Polynomial Chaos method and the Stochastic Collocation method. The strength of the Probabilistic Collocation method is demonstrated by solving steady o w around a NACA0012 airfoil with an uncertain free stream velocity using a commercial o w solver. Dieren t possibilities of representing the stochastic solution are demonstrated to show the potential use of uncertainty quantication.
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