AN EFFICIENT RESPONSE SURFACE TECHNIQUE FOR SENSITIVITY ESTIMATION IN STRUCTURAL RELIABILITY ANALYSIS

Abstract

The RSM is a powerful structural reliability method using the values of the function at specific points that approximates the limit state function with a polynomial expression. The analytical function replaces the exact limit state function which the computational time required for the assessment of the reliability of structural systems can be reduced significantly. However, the location of the sample points has been investigated by several authors and the performance of the response surface method is still under discussion. Therefore, this study proposes a new response surface method for sensitivity estimation of parameters in structural reliability analysis. A first oder polynomial without cross terms is adopted to approximate the limit-state function, and the sensitivity vector of the limit state function can be obtained. A experimental design with 4n+1 sampling points includes 2n+1 sampling points are chosen along the coordinate axes of the U-space of standard normal random variables, as in the classic RSM and 2n sampling points is rotated according to the sensitivity vector of the limit state function is built. A quadratic polynomial is adopted to approximate the limit-state function, and the most probable point (MPP) can be obtained by conducting HL-RF algorithm based on the created RS. To further improve the precision of reliability analysis, Monte Carlo Simulation (MCS) is conducted on the established polynomial to compute the probability of failure. Three numerical models are considered to demonstrate the advantages of the proposed method.