多源不确定性下叶盘结构疲劳可靠性分析与优化设计  

Fatigue Reliability Analysis and Optimization Design of Turbine Blade Disks under Multi-Source Uncertainties

作　　者：牛晓鹏 朱顺鹏 高杰维[1] 廖鼎 何金超 NIU Xiao-peng;ZHU Shun-peng;GAO Jie-wei;LIAO Ding;HE Jin-chao(School of Mechanical and Electrical Engineering,University of Electronic Science and Technology of China,Chengdu 611731,China;Centre for System Reliability and Safety,University of Electronic Science and Technology of China,Chengdu 611731,China)

机构地区：[1]电子科技大学机械与电气工程学院,四川成都611731 [2]电子科技大学系统可靠性与安全性研究中心,四川成都611731

出　　处：《推进技术》2022年第2期222-230,共9页Journal of Propulsion Technology

基　　金：国家自然科学基金(11972110;11672070);四川省重点研发计划(2021YFG0210)。

摘　　要：为了更好地满足叶盘结构的设计需求,针对叶盘结构疲劳寿命分散和几何参数众多等问题,基于随机有限元法构建了融合多源不确定性的叶盘结构疲劳可靠性分析与优化设计框架。首先,采用应力敏感因子分析筛选叶盘结构关键尺寸;然后,将关键尺寸、材料属性及载荷定义为随机变量,基于其分布规律进行拉丁超立方抽样以开展随机有限元分析和寿命预测;最后,结合寿命预测结果,分别运用插值法、概率累积疲劳寿命法以及Kriging代理模型进行了叶盘结构可靠性优化设计。结果显示,经上述三种方法优化后,叶盘结构中值疲劳寿命分别提升了27%,1.4%和108%。其中,基于Kriging代理模型建立的优化方法效果最佳,显著提升了叶盘结构的使役可靠性。Fatigue life scatter caused by material variability,load variation and geometrical uncertainty must be considered in engineering design to enable the structural integrity of turbine blade disk. Accordingly,a framework for fatigue reliability analysis and optimal design,coupling with multi-source uncertainties,was developed based on stochastic finite element method. Firstly,the critical dimensions were determined in view of the stress altering factor. Then,the critical dimensions,material property and load were defined as random variables,and the Latin hypercube sampling approach was employed to provide datasets for the following stochastic finite element simulation. Based on the predicted lifetime after simulated data processing,three reliability optimization strategies were raised by employing interpolation method,probabilistic cumulative fatigue life method and Kriging surrogate model,respectively. Results show that the median fatigue lifetime of the turbine blade disk respectively increases 27%,1.4%,and 108% using three optimization methods. Particularly,the optimization model based on the Kriging surrogate model works best,by which the turbine bladed disk’s reliability is improved significantly.

关 键 词：疲劳可靠性 叶盘结构 不确定性 随机有限元 优化设计 

分 类 号：V231.95[航空宇航科学与技术—航空宇航推进理论与工程]