Print Email Facebook Twitter Reliable Computational Predictions by Modeling Uncertainties Using Arbitrary Polynomial Chaos Part of: ECCOMAS CFD 2006: Proceedings of the European Conference on Computational Fluid Dynamics· list the conference papers Title Reliable Computational Predictions by Modeling Uncertainties Using Arbitrary Polynomial Chaos Author Witteveen, J.A.S. Bijl, H. 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:f7f6ec25-2e29-498c-b919-95c2181ad716 Part of collection Conference proceedings Document type conference paper Rights (c) 2006 Witteveen, J.A.S.; Bijl, H. Files PDF Witteveen.pdf 653.25 KB Close viewer /islandora/object/uuid:f7f6ec25-2e29-498c-b919-95c2181ad716/datastream/OBJ/view