{"title":"用于加成制造哈氏合金 X 超级合金疲劳寿命预测的多物理信息集成神经网络","authors":"Haijie Wang, Bo Li, Liming Lei, Fuzhen Xuan","doi":"10.1080/17452759.2024.2368652","DOIUrl":null,"url":null,"abstract":"The inherent ‘black-box’ characteristic of neural networks renders the physical interpretability of fatigue life prediction challenging, resulting in physically inconsistent prediction results. In ...","PeriodicalId":23756,"journal":{"name":"Virtual and Physical Prototyping","volume":"9 20 1","pages":""},"PeriodicalIF":10.2000,"publicationDate":"2024-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-physics information-integrated neural network for fatigue life prediction of additively manufactured Hastelloy X superalloy\",\"authors\":\"Haijie Wang, Bo Li, Liming Lei, Fuzhen Xuan\",\"doi\":\"10.1080/17452759.2024.2368652\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The inherent ‘black-box’ characteristic of neural networks renders the physical interpretability of fatigue life prediction challenging, resulting in physically inconsistent prediction results. In ...\",\"PeriodicalId\":23756,\"journal\":{\"name\":\"Virtual and Physical Prototyping\",\"volume\":\"9 20 1\",\"pages\":\"\"},\"PeriodicalIF\":10.2000,\"publicationDate\":\"2024-07-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Virtual and Physical Prototyping\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1080/17452759.2024.2368652\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MANUFACTURING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Virtual and Physical Prototyping","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/17452759.2024.2368652","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
Multi-physics information-integrated neural network for fatigue life prediction of additively manufactured Hastelloy X superalloy
The inherent ‘black-box’ characteristic of neural networks renders the physical interpretability of fatigue life prediction challenging, resulting in physically inconsistent prediction results. In ...
期刊介绍：
Virtual and Physical Prototyping (VPP) offers an international platform for professionals and academics to exchange innovative concepts and disseminate knowledge across the broad spectrum of virtual and rapid prototyping. The journal is exclusively online and encourages authors to submit supplementary materials such as data sets, color images, animations, and videos to enrich the content experience.
Scope:
The scope of VPP encompasses various facets of virtual and rapid prototyping.
All research articles published in VPP undergo a rigorous peer review process, which includes initial editor screening and anonymous refereeing by independent expert referees. This ensures the high quality and credibility of published work.
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