The probabilistic design of complex structure usually involves the features of numerous components, multiple disciplines, nonlinearity, and transients and, thus, requires lots of simulations as well. To enhance the modeling efficiency and simulation performance for the dynamic probabilistic analysis of the multicomponent structure, we propose an improved decomposed-coordinated Kriging modeling strategy (IDCKMS), by integrating decomposed-coordinated (DC) strategy, extremum response surface method (ERSM), genetic algorithm (GA), and Kriging surrogate model. The GA is used to resolve the maximum-likelihood equation and achieve the optimal values of the Kriging hyperparameter θ. The ERSM is utilized to resolve the response process of outputs in surrogate modeling by extracting the extremum values. The DC strategy is used to coordinate the output responses of analytical objectives. The probabilistic analysis of an aeroengine high-pressure turbine blisk with blade and disk is conducted to validate the effectiveness and feasibility of this developed method, by considering the fluid–thermal–structural interaction. In respect of this investigation, we see that the reliability of turbine blisk is 0.9976 as the allowable value of radial deformation is 2.319 × 10−3 m. In terms of the sensitivity analysis, the highest impact on turbine blisk radial deformation is of gas temperature, followed by angular speed, inlet velocity, material density, outlet pressure, and inlet pressure. By the comparison of methods, including the DC surrogate modeling method (DCSMM) with quadratic polynomial, the DCSMM with Kriging, and the direct simulation with finite-element model, from the model-fitting features and simulation performance perspectives, we discover that the developed IDCKMS is superior to the other three methods in the precision and efficiency of modeling and simulation. The efforts of this article provide a highly efficient and highly accurate technique for the dynamic probabilistic analysis of complex structure and enrich reliability theory.

Purpose: The purpose of this paper is to briefly summarize and review the theories and methods of complex structures’ dynamic reliability. Complex structures are usually assembled from multiple components and subjected to time-varying loads of aerodynamic, structural, thermal and other physical fields; its reliability analysis is of great significance to ensure the safe operation of large-scale equipment such as aviation and machinery.Design/methodology/approach: In this paper for the single-objective dynamic reliability analysis of complex structures, the calculation can be categorized into Monte Carlo (MC), outcrossing rate, envelope functions and extreme value methods. The series-parallel and expansion methods, multi-extremum surrogate models and decomposed-coordinated surrogate models are summarized for the multiobjective dynamic reliability analysis of complex structures.Findings: The numerical complex compound function and turbine blisk are used as examples to illustrate the performance of single-objective and multiobjective dynamic reliability analysis methods. Then the future development direction of dynamic reliability analysis of complex structures is prospected.Originality/value: The paper provides a useful reference for further theoretical research and engineering application.