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| An efficient and accurate uncertainty propagation methodology for mechanics problems with random fields is developed in this paper. This methodology is based on the stochastic response surface method (SRSM) which has been previously proposed for problems dealing only with random variables. This paper extends SRSM to problems involving random fields or random processes fields. The favourable property of SRSM lies in that the deterministic computational model can be treated as a black box, as in the case of commercial finite element codes. Numerical examples are used to highlight the features of this technique and to demonstrate the accuracy and efficiency of the proposed method. A comparison with Monte Carlo simulation shows that the proposed method can achieve numerical results close to those from Monte Carlo simulation while dramatically reducing the number of deterministic finite element runs. |
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| Keywords:Stochastic Response surface, Karhunen-Loeve expansion, polynomial chaos, random field, stochastic finite elements, probabilistic collocation |
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