Print Email Facebook Twitter Reliable Computational Predictions by Modeling Uncertainties Using Arbitrary Polynomial Chaos Title Reliable Computational Predictions by Modeling Uncertainties Using Arbitrary Polynomial Chaos Author Witteveen, J.A.S. Bijl, H. Faculty Aerospace Engineering Date 2006-09-06 Abstract Inherent physical uncertainties can have a significant influence on computational predictions. It is therefore important to take physical uncertainties into account to obtain more reliable computational predictions. The Galerkin polynomial chaos method is a commonly applied uncertainty quantification method. However, the polynomial chaos expansion has some limitations. Firstly, the polynomial chaos expansion based on classical polynomials can achieve exponential convergence for a limited set of standard distributions only. Secondly, the application of polynomial chaos to nonlinearities can be difficult. These two limitations of the polynomial chaos expansion are discussed in this paper. Subject uncertainty quantificationpolynomial chaosorthogonal polynomials To reference this document use: http://resolver.tudelft.nl/uuid:9dc0f511-0ba5-4b4b-9591-9e34a49fc476 Publisher Delft University of Technology; European Community on Computational Methods in Applied Sciences (ECCOMAS) ISBN 90-9020970-0 Source ECCOMAS CFD 2006: Proceedings of the European Conference on Computational Fluid Dynamics, Egmond aan Zee, The Netherlands, September 5-8, 2006 Part of collection Institutional Repository Document type conference paper Rights (c) 2006 The Author(s) Files PDF Witteveen.pdf 653.25 KB Close viewer /islandora/object/uuid:9dc0f511-0ba5-4b4b-9591-9e34a49fc476/datastream/OBJ/view