高压涡轮机匣热固耦合下多目标优化方法

戴雄; 关玉璞; 赵振华; 陈伟; 刘璐璐

doi:10.13224/j.cnki.jasp.2017.08.024

高压涡轮机匣热固耦合下多目标优化方法

doi: 10.13224/j.cnki.jasp.2017.08.024

1.
南京航空航天大学能源与动力学院江苏省航空动力系统重点实验室,南京 210016
2.
先进航空发动机协同创新中心,北京 100191

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出版历程
- 收稿日期: 2015-05-19
- 刊出日期: 2017-08-28

Multi-objective optimization method for high pressure turbine casing based on thermal-structure coupling analysis

摘要

摘要: 建立了包含高压涡轮(HPT)机匣基本结构在内的轴对称参数化模型,基于热固耦合变形和结构参数灵敏度分析结果,选择了灵敏度高的12个关键结构参数作为优化设计变量,采用第2代非劣排序遗传算法(NSGA-Ⅱ),开展了以机匣等效质量和挂钩处径向平均位移为目标函数的多目标优化。优化结果表明：机匣加强肋结构朝着有利换热的方向发展,其他结构朝着机匣质量减轻的方向发展；优化后模型质量及径向位移量均有所减小。
- 高压涡轮机匣 /
- 多目标优化 /
- 参数化模型 /
- 热固耦合 /
- 遗传算法
Abstract: An axisymmetric parameterized high pressure turbine (HPT) casing model was established after HPT casing structure was analysed. Based on the thermal-structure coupling deformation and parameter sensitivity analysis result, 12 key structure parameters were selected as optimization variables. Taking the casing mass and the hook area average radial displacement as the multi-objective function, the second generation non-dominated sorting genetic algorithm (NSGA-Ⅱ) was adopted to solve this multi-objective optimization problem. The optimization result showed that the optimal strengthening ribs structure was more efficient at heat conduction, and other optimal structure was more efficient at losing weight. After the optimization, the model weight and radial displacement were lessened simultaneously.
- high pressure turbine casing /
- multi-objective optimization /
- parameterized model /
- thermal-structure coupling /
- genetic algorithm

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参考文献(18)

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