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An adaptive algorithm to build up sparse polynomial chaos expansions for stochastic finite element analysis |
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| Authors: | Gé raud Blatman,Bruno Sudret |
| Affiliation: | 1. IFMA-LaMI, Campus des Cézeaux, BP 265, 63175 Aubière cedex, France;2. EDF R&D, Département Matériaux et Mécanique des Composants, site des Renardières, 77250 Moret-sur-Loing cedex, France;3. Phimeca Engineering S.A., Centre d’affaires du Zénith, 34 rue de Sarliève, 63800 Cournon d’Auvergne, France |
| Abstract: | Polynomial chaos (PC) expansions are used in stochastic finite element analysis to represent the random model response by a set of coefficients in a suitable (so-called polynomial chaos) basis. The number of terms to be computed grows dramatically with the size of the input random vector, which makes the computational cost of classical solution schemes (may it be intrusive (i.e.of Galerkin type) or non-intrusive) unaffordable when the deterministic finite element model is expensive to evaluate. |
| Keywords: | Adaptive stochastic finite elements Sequential experimental design Sparse polynomial chaos expansion Regression Structural reliability Response surfaces |
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