In recent years, composite laminated structures have been widely used in fields such as aerospace, military, and construction engineering. However, the uncertainty factors such as inaccuracies in geometric dimensions, variability in material properties, and fluctuations in loading environments may significantly impact the reliability and safety of composite laminated structures, as well as the output responses of the systems. Due to factors such as poor interlaminar bonding and external stress concentrations, delamination occurs in composite laminated structures when the rate of energy release reaches the interlaminar fracture toughness. Therefore, analyzing the delamination reliability of composite laminated structures is of significant importance. Currently, the reliability analysis of composite laminated structures mainly employs traditional methods such as first-order reliability method (FORM), second-order reliability method (SORM), and importance sampling (IS), often compared with Monte Carlo simulation (MCS). However, when the uncertainty dimensions and complexities of composite structures are high, these methods not only demonstrate low computational efficiency but also fail to ensure sufficient accuracy in their calculations.Compared to traditional reliability analysis methods, the integration of an adaptive Kriging model strategy and active learning functions combined with Monte Carlo simulation can be used for the reliability analysis of composite laminated structures. In particular, the Direct Probability Integral Method (DPIM) offers higher computational efficiency and accuracy, especially for high-dimensional and complex reliability analysis problems. Therefore, this study employs the AK-MCS method and DPIM to investigate the delamination reliability of composite laminated structures under Mode I, Mode II, and Mixed Mode I/II conditions. The results indicate that both DPIM and AK-MCS offer higher computational accuracy and efficiency compared to traditional reliability analysis methods. However, DPIM stands out due to its efficient computational performance. Although its accuracy is slightly lower than that of AK-MCS, DPIM demonstrates significant advantages in assessing the delamination reliability of laminated structures under the more complex and nonlinear conditions of Mixed Mode I/II. Considering the balance between accuracy and timeliness, DPIM can effectively evaluate the reliability of composite structures, ensuring their safe operation in fields such as aerospace and aviation equipment.
Key words
Composite laminates；Adaptive Kriging method；Direct probability integral method /
Reliability analysis
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