Failure correlation evaluation for complex structural systems with cascaded synchronous regression. (November 2022) - Li, Xue-Qin; Song, Lu-Kai; Bai, Guang-Chen
Highlights: A cascaded synchronous regression (CSR) is proposed to evaluate failure correlation. The proposed CSR method can map multiple output responses simultaneously. The CSR-based system reliability model is established to grasp the failure correlation information. The Copula functions are applied to quantify the failure correlation relationships. The proposed method is validated to hold high computing accuracy and efficiency. Abstract: Failure correlation evaluation of complex structural systems is a complex analysis problem involving multiple disciplinary analyses and multiple response objectives, whose high-nonlinearity performance function makes the traditional methods are difficult to acquire acceptable computing accuracy and efficiency. In this case, a cascaded synchronous regression (CSR) method is proposed by combining the multi-level decomposition cooperation strategy and the random regression tree modeling algorithm. In CSR modeling, the multi-level and multi-stage complex structural system is first decomposed into several correlated single-level and single-stage distributed subsystems; moreover, based on the random regression tree algorithm, the corresponding nonlinear mapping model for each distributed subsystem are established; finally, by performing the CSR-based system reliability simulation and Copula functions, the failure correlation relationships can be quantified. The effectiveness of proposed method is validated by the multi-site and multi-mode failure correlation evaluation of aeroengine turbine disc. The current efforts open up an effective way to realize the high-accuracy failure correlation evaluation of complex structural systems, and shed a light on the structural reliability design theory.