Reliability analysis on hybrid surrogate model of radial basis function and sparse polynomial chaos expansion (mt)

To resolve the poor universality and low accuracy of the existing surrogate models for reliability analysis, a hybrid surrogate model based on radial basis function（RBF） and sparse polynomial chaotic expansion（SPCE） was proposed. It realized rapid and accurate prediction of performance functions to improve the engineering applicability and the accuracy of structural reliability analysis. Importantly, the orthogonal matching pursuit technology was applied to obtain the important terms in PCE, and an SPCE model could be established directly to form the RBF-SPCE model for improving the prediction accuracy of surrogate model. Subsequently, the reliability analysis of complex structures is carried out based on Monte Carlo simulation（MCS）. In this work, three simulation cases were implemented to compare the performance of the proposed method with the traditional RBF model and augmented RBF model. The results illustrated that the proposed method has higher accuracy and efficiency for structural reliability analysis. Finally, a vehicle side impact engineering example illustrated that the proposed method has good engineering applicability for complex problems.