Abstract
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.
Original language | English |
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State | Published - 2019 |
Event | 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019 - Seoul, Korea, Republic of Duration: 26 May 2019 → 30 May 2019 |
Conference
Conference | 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019 |
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Country/Territory | Korea, Republic of |
City | Seoul |
Period | 26/05/19 → 30/05/19 |