涡扇发动机涡轮后框架结构/材料一体化优化设计方法

高希光; 刘兴国; 张华军; 宋迎东

涡扇发动机涡轮后框架结构/材料一体化优化设计方法

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.
中国人民解放军驻四二○厂军事代表室, 成都 610503
3.
南京航空航天大学机械结构力学及控制国家重点实验室, 南京 210016

基金项目: 国家自然科学基金(51075204,51105195);航空科学基金(2011ZB52024)

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出版历程
- 收稿日期: 2012-09-17
- 刊出日期: 2013-10-28

Concurrent structural and material optimization of turbine frame in turbo-fan engine

1.
Jiangsu Province Key Laboratory of Aerospace Power System, College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
2.
Representative Office Stationed 420 Factory, Chinese People's Liberation Army, Chengdu 610503
3.
State Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

摘要

摘要: 基于传统结构优化设计方法,综合考虑结构参数和材料性能对涡扇发动机涡轮后框架性能的影响,提出涡轮后框架结构/材料一体化优化设计方法.将原设计问题分解为结构级优化和材料级优化,分别应用可行方向法和并行遗传算法进行求解.应用C语言开发了分布式并行优化设计平台.应用该平台对某型涡扇发动机涡轮后框架进行结构/材料一体化优化设计,得到最佳材料组合和结构参数.优化结果表明:与单一材料的结构优化方法相比,提出的结构/材料一体化优化方法进一步减少了结构的质量,算例中最优选材比最差选材质量减少29.0%.
- 涡扇发动机 /
- 涡轮后框架 /
- 结构/材料一体化优化 /
- 分布式计算 /
- 并行遗传算法
Abstract: Based on the traditional structural optimization method,a structural/material optimization method for turbine frame was developed in consideration of the effects of structural parameters and properties of materials on the performance of turbine frame.The original optimization problem was decomposed into structure level and the material level.The first one was solved by feasible direction method while the second problem was solved by parallel genetic algorithms.A distributed computer system was designed by C language and employed to obtain the optimal material combination and structural parameters of one typical turbine frame.The result shows that the structure/material optimization may obtain better design than structure optimization.In the examples,compared with the worst material combination,the mass of the optimal material combination is reduced by 29.0%.
- turbo-fan engine /
- turbine frame /
- concurrent structural and material optimization /
- distributed computation /
- parallel genetic algorithm

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参考文献(15)

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