航空发动机循环演化自动设计

IF 5 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Complex & Intelligent Systems Pub Date : 2023-11-22 DOI:10.1007/s40747-023-01274-2
Xudong Feng, Zhening Liu, Feng Wu, Handing Wang
{"title":"航空发动机循环演化自动设计","authors":"Xudong Feng, Zhening Liu, Feng Wu, Handing Wang","doi":"10.1007/s40747-023-01274-2","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":10524,"journal":{"name":"Complex & Intelligent Systems","volume":"29 3","pages":""},"PeriodicalIF":5.0000,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evolutionary auto-design for aircraft engine cycle\",\"authors\":\"Xudong Feng, Zhening Liu, Feng Wu, Handing Wang\",\"doi\":\"10.1007/s40747-023-01274-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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.</p>\",\"PeriodicalId\":10524,\"journal\":{\"name\":\"Complex & Intelligent Systems\",\"volume\":\"29 3\",\"pages\":\"\"},\"PeriodicalIF\":5.0000,\"publicationDate\":\"2023-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Complex & Intelligent Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1007/s40747-023-01274-2\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Complex & Intelligent Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s40747-023-01274-2","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

摘要

传统的发动机循环创新受到人类经验、想象力和现有发动机部件性能预期的限制。因此,在过去的90年里,发动机循环创新的过程相当缓慢。本文提出了一种用于自动发动机循环设计的混合变量多目标进化优化方法。首先,开发了一个模拟工具包,用于评估潜在可行的发动机循环解决方案的性能。然后,利用引脚和不同发动机部件的参数对发动机循环解进行混合编码。通过变异算子生成新的发动机循环解。最后,我们构建了两个优化目标来驱动优化过程。通过实验研究,发现了超越已知涡喷发动机和涡扇发动机性能的新的发动机循环解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Evolutionary auto-design for aircraft engine cycle

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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Complex & Intelligent Systems
Complex & Intelligent Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
9.60
自引率
10.30%
发文量
297
期刊介绍: Complex & Intelligent Systems aims to provide a forum for presenting and discussing novel approaches, tools and techniques meant for attaining a cross-fertilization between the broad fields of complex systems, computational simulation, and intelligent analytics and visualization. The transdisciplinary research that the journal focuses on will expand the boundaries of our understanding by investigating the principles and processes that underlie many of the most profound problems facing society today.
期刊最新文献
Large-scale multiobjective competitive swarm optimizer algorithm based on regional multidirectional search Towards fairness-aware multi-objective optimization Low-frequency spectral graph convolution networks with one-hop connections information for personalized tag recommendation A decentralized feedback-based consensus model considering the consistency maintenance and readability of probabilistic linguistic preference relations for large-scale group decision-making A dynamic preference recommendation model based on spatiotemporal knowledge graphs
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1