STRUCTURAL RELIABILITY ANALYSIS METHOD BASED ON COLLABORATION-MEAN POINT CONSTRAINED ACTIVE LEARNING SURROGATE MODEL (Jixie qiangdu)
The reliability of mechanical structures is crucial for their safe operation,to address the problem of low accuracy and low efficiency in reliability analysis of complex mechanical structures,a new active learning surrogate model based reliability analysis method was proposed.The spatial location characteristics of excellent fitting samples were studied and three constraints,such as surface constraint,distance constraint,and domain constraint,were proposed accordingly.Correspondingly,three control functions were established to achieve the three constraints.Then,three control functions were organically collaborated,and an effective new learning function,collaboration-mean point constrained learning(CPCL)function was proposed.Combined with the augmented radial basis function(ARBF),a collaboration-mean point constrained active learning surrogate model(ARBF+CPCL)reliability analysis method was established.Finally,three cases were employed to verify the high computational accuracy and computational efficiency of ARBF+CPCL reliability analysis method,and the application ability of ARBF+CPCL method in practical engineering cases was proved through the reliability analysis example of the turbine disk.