An effective sensitivity analysis methodology for the reliability-based structural optimization design to high temperature components

Most of physical parameters of high temperature components are usually correlated with the temperature parameter, which makes the reliability-based structural optimization design more complicated. So far, few efficient sensitivity analysis methods adapted to highly nonlinear performance function with correlated non-normal variables have been invented. An effective simulation approach is presented to perform reliability sensitivity analysis with the aid of Cholesky factorization and curve fitting. Moreover, in order to improve the programming and computational efficiency, the mixed programming technique of Visual Basic and MATLAB was employed to develop a reliability sensitivity analysis program. The numerical case shows that the results are consistent with those from other traditional methods, and the engineering cases indicate that the proposed method can be effectively used in highly nonlinear function with correlated non-normal parameters. Meanwhile, the results also demonstrate that the correlation coefficient parameter of high temperature components is very important in the reliability-based structural optimization design; hence, this parameter should be fully taken into consideration to ensure that the analysis results are accurate and reasonable.