Conceptual Multidisciplinary Design Optimization of Commercial Aero-engine System

被引:0
|
作者
Guo, Fushui [1 ]
Zhao, Shiqi [1 ]
Zhou, Xiaodong [2 ]
Fan, Jun [3 ]
Mi, Dong [4 ]
机构
[1] AECC Commercial Aircraft Engine Co Ltd, Shanghai, Peoples R China
[2] State Grid Gen Aviat Co Ltd, Beijing, Peoples R China
[3] Army Aviat Inst, Beijing, Peoples R China
[4] AECC Hunan Aviat Powerplant Res Inst, Zhuzhou, Peoples R China
关键词
D O I
10.1088/1757-899X/685/1/012021
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
Commercial aero-engine design is a complicated task, which involves many disciplines, such as thermodynamics, aerodynamics, solid mechanics, heat transfer and materials science. Besides, for the sake of market requirements, designing a commercial aero-engine should not only consider the performance, fuel consumption, thrust and weight, but also pay special attention to noise, emissions and other environmental indices. In order to balance conflicts among various discipline indicators, and design an aero-engine with high comprehensive performance, we apply the multidisciplinary design optimization (MDO) technology to the conceptual design of an aero-engine system in this paper. Particularly, the system conceptual design of a high-bypass-ratio turbofan aero-engine is selected as a case study. A total of five disciplines, including thermal cycle, aerodynamics, structural mechanics, emission and noise, are considered. Meanwhile, six modules are integrated and analysed carefully. These modules include performance evaluation at the design point, performance evaluation at fifteen different off-design points, engine size assessment, engine weight assessment, engine emission assessment as well as engine noise assessment. On the basis of these modules, a MDO platform is set up. In addition, one optimization study with a single target of fuel burn is carried out by utilizing the adaptive simulated annealing (ASA) algorithm. Moreover, another optimization with multiple targets of fuel burn as well as nitrogen oxide emission is also studied by employing the non-dominated sorting genetic (NSGA-II) algorithm. The results shows that the MDO method for the commercial aero-engine can obtain better solutions for the system by fully taking into account the mutual effects among different disciplines.
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页数:8
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