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Evolutionary auto-design for aircraft engine cycle

delete2023-11-22
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OA
AI
X
Xudong Feng
Z
Zhening Liu
F
Feng Wu
H
Handing Wang *
DOI:10.1007/s40747-023-01274-2delete
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摘要

摘要

En 中文
Traditional engine cycle innovation is limited by human experiences, imagination, and currently available engine component performance expectations. Thus, the engine cycle innovation process is quite slow for the past 90 years. In this work, we propose a mixed variable multi-objective evolutionary optimization method for automatic engine cycle design. In the first, a simulation toolkit is developed for performance evaluation of potentially viable engine cycle solutions. Then, the engine cycle solutions are mixed encoded by the pins and the parameters of different engine components. The new engine cycle solutions are generated through the mutation operator. Finally, we construct two optimization objectives to drive the optimization process. Through the experimental research, new engine cycle solutions are discovered that exceed the performance of known turbojet and turbofan engines.
Keyword:
Multi-objective evolutionary algorithms
Engineering design
Mixed variable encoding

期刊

Complex and Intelligent Systems 封面图
Complex and Intelligent Systems
IF:
4.6
论文数:
2.1K
被引数:
6.6K

机构

N
Northwestern Polytechnical University
学者数:
4.6W
论文数: 3.7W
被引数: 5.3W
X
Xidian University
学者数:
2.4W
论文数: 1.9W
被引数: 9.7K
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