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Witteveen, J.A.S. (author), Bijl, H. (author)
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...
conference paper 2006
document
Loeven, A. (author), Witteveen, J.A.S. (author), Bijl, H. (author)
In this paper a Two Step approach with Chaos Collocation for efficient uncertainty quantification in computational fluid-structure interactions is followed. In Step I, a Sensitivity Analysis is used to efficiently narrow the problem down from multiple uncertain parameters to one parameter which has the largest influence on the solution. In Step...
conference paper 2006
document
Witteveen, J.A.S. (author), Bijl, H. (author)
conference paper 2008
document
Witteveen, J.A.S. (author), Bijl, H. (author)
A monomial chaos approach is proposed for efficient uncertainty quantification in nonlinear computational problems. Propagating uncertainty through nonlinear equations can still be computationally intensive for existing uncertainty quantification methods. It usually results in a set of nonlinear equations which can be coupled. The proposed...
conference paper 2006
document
Witteveen, J.A.S. (author), Bijl, H. (author)
A robust and efficient uncertainty quantification method is presented for resolving the effect of uncertainty on the behavior of multi-physics systems. The extrema diminishing method in probability space maintains a bounded error due to the interpolation of deterministic samples at constant phase in a transonic airfoil flutter problem.
conference paper 2009
document
Witteveen, J.A.S. (author), Bijl, H. (author)
A monomial chaos approach is proposed for efficient uncertainty quantification in nonlinear computational problems. Propagating uncertainty through nonlinear equations can still be computationally intensive for existing uncertainty quantification methods. It usually results in a set of nonlinear equations which can be coupled. The proposed...
conference paper 2006
document
Witteveen, J.A.S. (author), Bijl, H. (author)
An explicit mesh motion algorithm based on inverse distance weighting interpolation is presented. The explicit formulation leads to a fast mesh motion algorithm and an easy implementation. In addition, the proposed point-by-point method is robust and flexible in case of large deformations, hanging nodes, and parallelization. Mesh quality results...
conference paper 2009
document
Witteveen, J.A.S. (author), Bijl, H. (author)
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...
conference paper 2006
document
Witteveen, J.A.S. (author), Bijl, H. (author)
An efficient uncertainty quantification method for unsteady problems is presented in order to achieve a constant accuracy in time for a constant number of samples. The approach is applied to the aeroelastic problems of a transonic airfoil flutter system and the AGARD 445.6 wing benchmark with uncertainties in the flow and the structure.
conference paper 2009
document
Witteveen, J.A.S. (author), Bijl, H. (author)
conference paper 2008
document
Witteveen, J.A.S. (author), Bijl, H. (author)
conference paper 2008
document
Loeven, A. (author), Witteveen, J.A.S. (author), Bijl, H. (author)
In this paper a Two Step approach with Chaos Collocation for efficient uncertainty quantification in computational fluid-structure interactions is followed. In Step I, a Sensitivity Analysis is used to efficiently narrow the problem down from multiple uncertain parameters to one parameter which has the largest influence on the solution. In Step...
conference paper 2006
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