S-Space College of Engineering/Engineering Practice School (공과대학/대학원) Dept. of Civil & Environmental Engineering (건설환경공학부) ICASP13
Global sensitivity analysis in high dimensions with partial least squares-driven PCEs
- Ehre, Max; Papaioannou, Iason; Straub, Daniel
- Issue Date
- 13th International Conference on Applications of Statistics and Probability in Civil Engineering(ICASP13), Seoul, South Korea, May 26-30, 2019
- We develop an efficient method for the computation of variance-based sensitivity indices using a recently introduced latent-variable-based polynomial chaos expansion, which is particularly suitable for high dimensional problems. By back-transforming the surrogate from its latent variable space-basis to the original input variable space-basis, we derive analytical expressions for these sensitivities that only depend on the model coefficients. Thus, once the surrogate model is built, the variance-based sensitivities can be computed at negligible computational cost as no additional sampling is required. The accuracy of the method is demonstrated with a numerical experiment of an elastic truss.