One important issue in uncertainty analysis is to find an effective way for propagating uncertainty through engineering systems which have significant random variation parameters in space or time. In this paper, the polynomial chaos expansion (PCE) was selected since this approach can reduce the computational effort in large-scale engineering design applications. An implementation of PCE, which includes different probability distributions, is the focus of this paper. Two existing techniques, a generalized PCE algorithm and transformation methods, are investigated and verified for their accuracy and efficiency for non-normal random variable cases. A nonlinear structural model of an uninhabitated joined-wing aircraft and a three pin-connected rod structure are used for demonstrating the method.
Reliability Analysis of a Large Computational Model Using Polynomial Chaos Expansion
Sae Technical Papers
SAE 2003 World Congress & Exhibition ; 2003
2003-03-03
Conference paper
English
Reliability analysis of a large computational model using polynomial chaos expansion
Automotive engineering | 2003
|2003-01-0465 Reliability Analysis of a Large Computational Model Using Polynomial Chaos Expansion
British Library Conference Proceedings | 2003
|2003-01-0465 Reliability Analysis of a Large Computational Model Using Polynomial Chaos Expansion
British Library Conference Proceedings | 2003
|