{"title":"面向增材制造的翼肋拓扑优化","authors":"Q.S. Wang, S.Y. Wang, A. H. Li","doi":"10.4273/ijvss.15.2.16","DOIUrl":null,"url":null,"abstract":"This paper describes the design of a lightweight wing rib structure by combining topology optimisation with additive manufacturing. In addition, a deep feed-forward neural network model is proposed to perform the load prediction for the constructed wing structure incorporated with this optimised rib. The strain energy of the front rib has a minimum strain energy 1330 J for the initial volume state when the topology is not optimised for lightweighting. The relative error of the load prediction values obtained by the output layer of the deep feed-forward neural network is less than 0.02%. The absolute error of the small load prediction was less than 0.30 N. The presented results demonstrate the viability of additive manufactured rib and its implementation in global wing load prediction model for faster designs.","PeriodicalId":14391,"journal":{"name":"International Journal of Vehicle Structures and Systems","volume":"57 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Topology Optimization of Wing Ribs for Additive Manufacturing\",\"authors\":\"Q.S. Wang, S.Y. Wang, A. H. Li\",\"doi\":\"10.4273/ijvss.15.2.16\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes the design of a lightweight wing rib structure by combining topology optimisation with additive manufacturing. In addition, a deep feed-forward neural network model is proposed to perform the load prediction for the constructed wing structure incorporated with this optimised rib. The strain energy of the front rib has a minimum strain energy 1330 J for the initial volume state when the topology is not optimised for lightweighting. The relative error of the load prediction values obtained by the output layer of the deep feed-forward neural network is less than 0.02%. The absolute error of the small load prediction was less than 0.30 N. The presented results demonstrate the viability of additive manufactured rib and its implementation in global wing load prediction model for faster designs.\",\"PeriodicalId\":14391,\"journal\":{\"name\":\"International Journal of Vehicle Structures and Systems\",\"volume\":\"57 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Vehicle Structures and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4273/ijvss.15.2.16\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Vehicle Structures and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4273/ijvss.15.2.16","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
Topology Optimization of Wing Ribs for Additive Manufacturing
This paper describes the design of a lightweight wing rib structure by combining topology optimisation with additive manufacturing. In addition, a deep feed-forward neural network model is proposed to perform the load prediction for the constructed wing structure incorporated with this optimised rib. The strain energy of the front rib has a minimum strain energy 1330 J for the initial volume state when the topology is not optimised for lightweighting. The relative error of the load prediction values obtained by the output layer of the deep feed-forward neural network is less than 0.02%. The absolute error of the small load prediction was less than 0.30 N. The presented results demonstrate the viability of additive manufactured rib and its implementation in global wing load prediction model for faster designs.
期刊介绍:
The International Journal of Vehicle Structures and Systems (IJVSS) is a quarterly journal and is published by MechAero Foundation for Technical Research and Education Excellence (MAFTREE), based in Chennai, India. MAFTREE is engaged in promoting the advancement of technical research and education in the field of mechanical, aerospace, automotive and its related branches of engineering, science, and technology. IJVSS disseminates high quality original research and review papers, case studies, technical notes and book reviews. All published papers in this journal will have undergone rigorous peer review. IJVSS was founded in 2009. IJVSS is available in Print (ISSN 0975-3060) and Online (ISSN 0975-3540) versions. The prime focus of the IJVSS is given to the subjects of modelling, analysis, design, simulation, optimization and testing of structures and systems of the following: 1. Automotive vehicle including scooter, auto, car, motor sport and racing vehicles, 2. Truck, trailer and heavy vehicles for road transport, 3. Rail, bus, tram, emerging transit and hybrid vehicle, 4. Terrain vehicle, armoured vehicle, construction vehicle and Unmanned Ground Vehicle, 5. Aircraft, launch vehicle, missile, airship, spacecraft, space exploration vehicle, 6. Unmanned Aerial Vehicle, Micro Aerial Vehicle, 7. Marine vehicle, ship and yachts and under water vehicles.