A new approach for fatigue reliability analysis of thin‐walled structures with dc‐ilssvr

Fatigue analysis is of great significance for thin‐walled structures in the spacecraft indus-try to ensure their service reliability during operation. Due to the complex loadings of thin‐walled structures under thermal–structural–acoustic coupling conditions, the calculation cost of finite element (FE) simulations is relatively expensive. To improve the computational efficiency of dynamic reliability analysis on thin‐walled structures to within acceptable accuracy, a novel probabilistic approach named DC‐ILSSVR was developed, in which the rotation matrix optimization (RMO) method was used to initially search for the model parameters of least squares support vector regression (LS‐SVR). The distributed collaborative (DC) strategy was then introduced to enhance the efficiency of a component suffering from multiple failure modes. Moreover, a numerical example with respect to thin‐walled structures was used to validate the proposed method. The results showed that RMO performed on LS‐SVR model parameters provided competitive prediction accuracy, and hence the reliability analysis efficiency of thin‐walled pipe was significantly improved.