基于POD-PCE-Kriging模型的航空发动机高维多目标优化  

High-dimensional multi-objective optimization of aero-engine based on POD-PCE-Kriging model

作　　者：马跃 郭明明[1,2] 孙博伦 田野 宋文艳 乐嘉陵[1,2] MA Yue;GUO Mingming;SUN Bolun;TIAN Ye;SONG Wenyan;LE Jialing(School of Information Engineering,Southwest University of Science and Technology,Mianyang Sichuan 621010,China;Science and Technology on Scramjet Laboratory,China Aerodynamics Research and Development Center,Mianyang Sichuan 621000,China;School of Power and Energy,Northwestern Polytechnical University,Xi’an 710129,China)

机构地区：[1]西南科技大学信息工程学院,四川绵阳621010 [2]中国空气动力研究与发展中心高超声速冲压发动机技术重点实验室,四川绵阳621000 [3]西北工业大学动力与能源学院,西安710129

出　　处：《航空动力学报》2023年第7期1604-1614,共11页Journal of Aerospace Power

基　　金：四川省科技计划项目(2023YFG0336)。

摘　　要：针对于传统的航空发动机燃烧室设计过程计算周期长,加工和试验成本高,制约发动机设计周期的问题,基于航空发动机燃烧室模型,结合POD-PCE-Kriging(本征正交分解-多项式混沌展开-Kriging)模型和粒子群优化(PSO)算法开展了燃烧性能代理模型的构建和多目标优化设计。通过试验,应用POD-PCE-Kriging模型预测结果与一维程序计算结果进行对比分析,针对于燃烧效率和总压损失预测值的方均根误差分别为0.006 3%和0.122 7%。对设计变量参数开展寻优,并对获取的Pareto最优解集进行了分析,为满足性能指标的先进航空发动机燃烧室设计提供了物理见解,可以快速准确获得满足最优性能的设计参数,缩短航空发动机的研制周期。In view of the traditional aero-engine combustor design process with long calculation cycle,high processing test and cost which restricts the engine design cycle,based on the aero-engine combustor model,POD-PCE-Kriging(proper orthogonal decomposition-polynomial chaotic expansion-Kriging)model and particle swarm optimization(PSO)algorithms were combined to construct the combustion performance surrogate model and carry out multi-objective optimization design.Through the test,the predicted results of POD-PCE-Kriging model were compared with the calculated results of one-dimensional program,and the root mean square errors of the predicted values of combustion efficiency and total pressure loss were 0.0063%and 0.1227%,respectively.Optimization search was carried out for the design variables,and the obtained Pareto optimal solution set was analyzed to provide physical insight into the design of advanced aero-engine combustor to meet the performance specifications,which can quickly and accurately obtain the design parameters to meet the optimal performance and accelerate the development cycle of aero-engine.

关 键 词：航空发动机燃烧室设计 代理模型 POD-PCE-Kriging模型 粒子群优化算法 多目标优化 

分 类 号：V231[航空宇航科学与技术—航空宇航推进理论与工程]