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• A new single-loop strategy for time-variant system reliability analysis is proposed. • The multiple response Gaussian process is adopted to depict the correlation between time-variant limit state functions. • The subset simulation is introduced into the proposed single-loop strategy to estimate the small failure probability. • The updated strategy and stopping criterion for the proposed single-loop time-variant reliability analysis are provided. This paper proposes a time-variant system reliability analysis method by combining multiple response Gaussian process (MRGP) and subset simulation (SS) to solve the small failure probability problem. One common method for time-variant reliability analysis is based on the double-loop procedure where the inner loop is the optimization for extreme values and the outer loop is extreme-value-based reliability analysis. In this paper, a new single-loop strategy is firstly proposed to decouple the double-loop procedure by using the best value in current initial samples to approximate the extreme value, thus the extremal optimization in inner loop can be avoided. Then the MRGP model is used to construct the surrogate model of extreme value response surface for time-variant system reliability analysis based on the approximated extremums. Meanwhile, the Kriging model is also constructed based on the initial samples to assist in searching the new sample point. Furthermore, for selecting the new point that resides as close to the extreme value response surface as possible from the Monte Carlo simulation (MCS) sample pool, three learning functions (U-function, EFF-function and H-function) are respectively used to find the new random variable sample point based on the MRGP model and the expected improvement (EI) function is used to find the new time sample point based on the Kriging model. Finally, for reducing the size of candidate sample pool and the computing burden, the SS method is combined with the MRGP model to deal with the small failure probability problem. The effectiveness of the proposed method is also demonstrated by several examples. [ABSTRACT FROM AUTHOR]

• Effects of multiple environmental stresses on fatigue performance of offshore wind turbine blades adhesive bonding are investigated. • The Cyclic cohesive zone model is improved by integrating a newly built multi-environmental degradation factor model. • Fatigue simulation considering the effects of multiple environmental stresses is performed. • The fatigue reliability of offshore wind turbine blades adhesive bonding is calculated. Offshore wind turbine blades (OWTBs) serve in harsh environments, such as high temperature, high humidity, salt fog, etc., and the various environmental stresses will have coupling effects on the OWTBs structural performance, in particular greatly accelerating the fatigue properties degradation and failure process of adhesive bonding. Thus, special consideration should be paid to the coupling effects of multiple environmental stresses on the fatigue reliability of adhesives. For this purpose, a fatigue reliability modeling method, which innovatively integrated fatigue analysis with multi-environmental stresses effect analysis, is proposed in this paper. Specifically, the fatigue damage process of adhesive bonding is characterized by Cyclic Cohesive Zone Model (CCZM); a multi-environmental degradation factor model (MEDFM) is built to quantify the coupling effects of environmental stresses on adhesive bonding fatigue lifetime, then the MEDFM is fused into the CCZM to realize the fatigue damage process simulation with the considerations of environmental stress. Finally, the fatigue reliability model considering multi-environmental stress coupling effects is built for adhesive bonding, and the feasibility and accuracy of the proposed method are verified by comparing it with the experimental results. The proposed method can be used for OWTBs fatigue analysis and structural design. [ABSTRACT FROM AUTHOR]