陆艺鑫,吕震宙,冯凯旋,何良莉

• 1:西北工业大学航空学院

摘要(Abstract)：

为保障涡轮轴在多种不确定性因素影响下的可靠性和寿命性能,建立了涡轮轴低周疲劳寿命可靠性分析与优化设计方法。搭建了涡轮轴结构分析、可靠性分析和可靠性优化设计的参数化平台,实现了设计参数的不同访问值处结构分析和可靠性分析的自主调用。提出了改进Monte Carlo结合自适应Kriging的算法(A-MCS-AK),通过多点加点和样本池缩减大幅提高了可靠性分析效率。针对极大化涡轮轴低周疲劳寿命均值和极小化涡轮轴低周疲劳寿命失效概率的可靠性优化模型,建立了基于自适应协作代理策略的类序列解耦算法。对选定涡轮轴的分析结果表明,搭建的参数化平台实现了分析数据的自主流动,提出的A-MCS-AK算法较传统的自适应Kriging结合MCS方法计算效率更高,建立的类序列解耦法实现了两种优化模型的高效求解,得到的优化方案显著提高了某型涡轮轴的寿命均值并降低了失效概率。

关键词(KeyWords)： 涡轮轴;低周疲劳;结构分析;可靠性分析;优化设计;参数化平台

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金（52075442）;; 两机重大专项（2017-IV-0009-0046）

作者(Author): 陆艺鑫,吕震宙,冯凯旋,何良莉

DOI: 10.13675/j.cnki.tjjs.210510

参考文献(References)：

• [1]陶春虎，钟培道，王仁智，等.航空发动机转动部件的失效与预防[M].北京：国防工业出版社，2008.
• [2]丁亮亮.某型航空发动机风扇轴疲劳寿命预测及可靠性分析[D].成都：电子科技大学，2014.
• [3] Sacks J,Schiller S B,Welch W J. Design for Computer Experiment[J]. Technometrics,1989,31(1):41-47.
• [4]刘丁玮.航空发动机涡轮轴疲劳可靠性建模与分析方法研究[D].成都：电子科技大学，2019.
• [5]程宏伟.航空发动机涡轮轴概率疲劳寿命预测与可靠性分析[D].成都：电子科技大学，2020.
• [6] Nikolaidis E,Burdisso R. Reliability-Based Design Optimization Using Probabilistic Sufficiency Factory[J].Computers&Structures,1988,28(6):781-788.
• [7] Chen Huitao,Fan Junkai,Jing Shuangxi,et al. Probabilistic Design Optimization of Wind Turbine Gear Transmission System Based on Dynamic Reliability[J]. Journal of Mechanical Science and Technology,2019,33(2):579-589.
• [8] Li Huaxia,Cho Hyunkyoo,Sugiyama Hiroyuki. Reliability-Based Design Optimization of Wind Turbine Drive Train with Integrated Multibody Gear Dynamics Simulation Considering Wind Load Uncertainty[J]. Structural and Multidis-Ciplinary Optimization,2017,56:183-201.
• [9] Kuschel N,Rackwitz R. Optimal Design under TimeVariant Reliability Constraints[J]. Structural Safety,2000,22(2):113-127.
• [10] Royset J O, Kiureghian A D, Polak E. ReliabilityBased Optimal Structural Design by the Decoupling Approach[J]. Reliability Engineering System Safety,2001,73(3):213-221.
• [11] Cheng Gengdong,Xu Lin,Jiang Lei. A Sequential Approximate Programming Strategy for Reliability-Based Structural Optimization[J]. Computers&Structures,2006,84(21):1353-1367.
• [12] LehkyD,Slowik O,Novák D. Reliability-Based Design:Artificial Neural Networks and Double-Loop Reliability-Based Optimization Approaches[J]. Advances in Engineering Software,2018,117(4):123-135.
• [13] Shi Lei, Lin Shih-Po. A New RBDO Method Using Adaptive Response Surface and First-Order Score Function for Crashworthiness Design[J]. Reliability Engineering&System Safety,2016,156:125-133.
• [14] Wu Y T,Wang W. Efficient Probabilistic Design by Converting Reliability Constraints to Equivalent Approximate Deterministic Constraints[J]. Society for Design and Process Science,1996,2(4):13-21.
• [15] Du XP,Chen W. Sequential Optimization and Reliability Assessment Method for Efficient Probabilistic Design[J]. Journal of Mechanical Design,2004,126(2):871-880.
• [16]吕震宙，宋述芳，李璐祎，等.结构/机构可靠性设计基础[M].西安：西北工业大学出版社，2019.
• [17] Liao Kuowei,Ha Christopher. Application of ReliabilityBased Optimization to Earth-Moving Machine:Hydraulic Cylinder Components Design Process[J]. Structural&Multidisciplinary Optimization,2008,36(5):523-536.
• [18] Tu J,Choi K K,Park Y H. A New Study on ReliabilityBased Design Optimization[J]. Journal of Mechanical Design,1999,121(4):557-564.
• [19] Kuschel N,Rackwitz R. Two Basic Problems in Reliability-Based Structural Optimization[J]. Mathematical Methods of Operations Research,1997,46(3):309-333.
• [20] Aoues Y,Chateauneuf A. Benchmark Study of Numerical Methods for Reliability-Based Design Optimization[J]. Structural and Multidisciplinary Optimization,2010,41(2):277-294.
• [21] Ching J,Hsu W C. Transforming Reliability Limit-State Constraints into Deterministic Limit-State Constraints[J]. Structural Safety,2008,30(1):11-33.
• [22]贾贝熙，吕震宙，雷婧宇.涡轮叶片寿命可靠性分析的参数化仿真平台[J].航空学报，DOI:10. 7527/S1000-6893. 2020. 24747.
• [23]陈浩.某型涡扇航空发动机涡轮轴有限元及寿命分析[D].成都：电子科技大学，2016.
• [24]郭正，何勇，刘君.网格变形与局部重构相结合的非结构动网格实现[C].西安：第十二届全国计算流体力学会议，2004:461-465.
• [25]王延荣.航空发动机零件可靠性安全性设计[M].北京：航空工业出版社，2018.
• [26]丁如昌.航空发动机涡轮盘疲劳可靠性建模和分析[D].成都：电子科技大学，2019.
• [27]王荣桥，胡殿印.发动机结构可靠性设计理论及应用[M].北京：科学出版社，2017.
• [28]贾瑞.基于蚁群算法的结构疲劳可靠性优化方法研究[D].南京：南京航空航天大学，2008.
• [29]王卫国.轮盘低循环疲劳寿命预测和实验评估方法研究[D].南京：南京航空航天大学，2006.
• [30]高阳，白广忱，张瑛莉.涡轮盘低循环疲劳寿命的概率分析[J].航空动力学报，2009,24(4):804-809.
• [31]姚卫星.结构疲劳寿命分析[M].北京：国防工业出版社，2004.
• [32] Miner M A. Cumulative Damage in Fatigue[J]. Journal of Applied Mechanics,1945,67:159-164.
• [33] Echard B,Gayton N,Lemaire M. AK-MCS:An Active Learning Reliability Method Combining Kriging and Monte Carlo Simulation[J]. Structural Safety,2011,33(2):145-154.
• [34] Park Hae-Sang,Jun Chi-Hyuck. A Simple and Fast Algorithm for K-Medoids Clustering[J]. Expert Systems with Applications,2008,36(2):3336-3341.
• [35] Couckuyt Ivo,Dhaene Tom,Demeester Piet. ooDACE Toolbox:A Flexible Object-Oriented Kriging Implementation[J]. Journal of Machine Learning Research,2014,15:3183-3186.
• [36] Feng Kaixuan,Lu Zhenzhou,Wang Lu. A Novel DualStage Adaptive Kriging Method for Profust Reliability Analysis[J]. Journal of Computational Physics,2020,419(4).