M5 model tree and Monte Carlo simulation for efficient structural reliability analysis

Highlights

• CFORM is proposed to enhance the robustness of FORM-based MPP search.

• M5Tree model with MCS is developed to improve the accuracy and efficiency of structural reliability analysis.

• The performances of CFORM and M5Tree+MC are illustrated using several reliability examples.

• The CFORM is more efficient than MCS and robust than the HL-RF method.

• The M5Tree+MC method provides an accurate result compared to CFORM, more efficiently.

Abstract

Practically, the performance of many engineering problems can be defined using a complex implicit limit state function. Approximation of the accurate failure probability is very time-consuming and inefficient based on Monte Carlo simulation (MCS) for complex performance functions. M5 model tree (M5Tree) model is robust approach for simulation and prediction phenomena, which provides ability to dealing with complex implicit problems by dividing them into smaller problems. By improving the efficiency of reliability method using accurate approximated failure probability, an efficient reliability method using the MCS and M5Tree is proposed to calibrate the performance function and estimate the failure probability, respectively. The superiorities including simplicity and accuracy of M5Tree meta-model are investigated to evaluate the actual performance function through five nonlinear complex mathematical and structural reliability problems. The proposed reliability method-based MCS and M5Tree improved the computational efforts for evaluating the performance function in reliability analysis. The M5Tree significantly increased the efficiency of reliability analysis with accurate failure probability.