{"title":"A hybrid data-driven approach for the analysis of hydrodynamic lubrication","authors":"Yang Zhao, Patrick P L Wong","doi":"10.1177/13506501231214584","DOIUrl":null,"url":null,"abstract":"The application of data mining technology has intensively advanced tribology research. While recent lubrication studies have highlighted the importance of data mining, researchers have not fully bridged the gap between massive lubrication data and intrinsic lubrication mechanisms. Thus, by revisiting lubrication modelling from the data-driven and physics-informed perspectives, we aim to construct a hybrid approach for hydrodynamic lubrication classification and prediction, where data-driven methods are combined with physics-informed approaches to achieve a fast and accurate prediction of the hydrodynamic lubrication scenario. Our approach will spur the application of data mining methods in lubrication studies.","PeriodicalId":20570,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology","volume":"40 11","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1177/13506501231214584","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 0
Abstract
The application of data mining technology has intensively advanced tribology research. While recent lubrication studies have highlighted the importance of data mining, researchers have not fully bridged the gap between massive lubrication data and intrinsic lubrication mechanisms. Thus, by revisiting lubrication modelling from the data-driven and physics-informed perspectives, we aim to construct a hybrid approach for hydrodynamic lubrication classification and prediction, where data-driven methods are combined with physics-informed approaches to achieve a fast and accurate prediction of the hydrodynamic lubrication scenario. Our approach will spur the application of data mining methods in lubrication studies.
期刊介绍：
The Journal of Engineering Tribology publishes high-quality, peer-reviewed papers from academia and industry worldwide on the engineering science associated with tribology and its applications.
"I am proud to say that I have been part of the tribology research community for almost 20 years. That community has always seemed to me to be highly active, progressive, and closely knit. The conferences are well attended and are characterised by a warmth and friendliness that transcends national boundaries. I see Part J as being an important part of that community, giving us an outlet to publish and promote our scholarly activities. I very much look forward to my term of office as editor of your Journal. I hope you will continue to submit papers, help out with reviewing, and most importantly to read and talk about the work you will find there." Professor Rob Dwyer-Joyce, Sheffield University, UK
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