An efficient finite element analysis method for aero engine gear reliability combining co-simulation and surrogate model

Oftentimes, finite element analysis (FEA) is an essential part of structural system reliability analysis. Using simulation software to perform FEA improves the efficiency with its powerful simulation ability, although the characteristics of multivariable and large-scale still pose a severe challenge to the efficiency, which in turn affects the overall efficiency of reliability analysis. The high automation of FEA is achieved through a co-simulation to bypass the human errors presenting in the manual operation. Computational cost is reduced by approximately replacing the finite element model (FEM) with a surrogate model. Aiming at the application of aero engine gear, this paper uses the MATLAB- ANSYS co-simulation to improve the efficiency of multivariable analysis and uses the Kriging surrogate model to improve the efficiency of large-scale analysis with the help of sensitivity-based variable reduction and quasi-Monte Carlo-based sampling. The results demonstrate the remarkable efficiency and practicability of the proposed method in improving the aero engine gear FEA.