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.

中文翻译：

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多组分结构动态概率分析的改进分解协调克里金建模策略

复杂结构的概率设计通常涉及众多组件、多学科、非线性和瞬态的特征，因此也需要大量的仿真。为了提高多组分结构动态概率分析的建模效率和仿真性能，我们提出了一种改进的分解协调克里金建模策略（IDCKMS），通过整合分解协调（DC）策略，极值响应面方法（ERSM），遗传算法 (GA) 和克里金代理模型。GA 用于求解最大似然方程并获得克里金超参数 θ 的最优值。ERSM 用于通过提取极值来解决代理建模中输出的响应过程。DC 策略用于协调分析目标的输出响应。通过考虑流体-热-结构相互作用，对具有叶片和盘的航空发动机高压涡轮叶盘进行概率分析，以验证该开发方法的有效性和可行性。在本次调查中，我们看到涡轮叶盘的可靠性为 0.9976，因为径向变形的允许值为 2.319 × 10-3 m。从敏感性分析来看，对涡轮叶盘径向变形影响最大的是气体温度，其次是角速度、入口速度、材料密度、出口压力和入口压力。通过对包括二次多项式的 DC 代理建模方法 (DCSMM)、克里金法的 DCSMM、和有限元模型的直接仿真，从模型拟合特性和仿真性能的角度，我们发现开发的IDCKMS在建模和仿真的精度和效率上优于其他三种方法。本文的努力为复杂结构的动态概率分析提供了一种高效、高精度的技术，丰富了可靠性理论。