Wei-gang It , Chao Liu , Yun-tao Zhao , Bin Liu , Xiang-hua Liu
{"title":"Modeling deformation resistance for hot rolling based on generalized additive model","authors":"Wei-gang It , Chao Liu , Yun-tao Zhao , Bin Liu , Xiang-hua Liu","doi":"10.1016/S1006-706X(18)30015-3","DOIUrl":null,"url":null,"abstract":"<div><p>A model of deformation resistance during hot strip rolling was established based on generalized additive model. Firstly, a data modeling method based on generalized additive model was given. It included the selection of dependent variable and independent variables of the model, the link function of dependent variable and smoothing functional form of each independent variable, estimating process of the link function and smooth functions, and the last model modification. Then, the practical modeling test was carried out based on a large amount of hot rolling process data. An integrated variable was proposed to reflect the effects of different chemical compositions such as carbon, silicon, manganese, nickel, chromium, niobium, etc. The integrated chemical composition, strain, strain rate and rolling temperature were selected as independent variables and the cubic spline as the smooth function for them. The modeling process of deformation resistance was realized by SAS software, and the influence curves of the independent variables on deformation resistance were obtained by local scoring algorithm. Some interesting phenomena were found, for example, there is a critical value of strain rate, and the deformation resistance increases before this value and then decreases. The results confirm that the new model has higher prediction accuracy than traditional ones and is suitable for carbon steel, microalloyed steel, alloyed steel and other steel grades.</p></div>","PeriodicalId":64470,"journal":{"name":"Journal of Iron and Steel Research(International)","volume":"24 12","pages":"Pages 1177-1183"},"PeriodicalIF":3.1000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1006-706X(18)30015-3","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Iron and Steel Research(International)","FirstCategoryId":"1087","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1006706X18300153","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"METALLURGY & METALLURGICAL ENGINEERING","Score":null,"Total":0}
引用次数: 1
Abstract
A model of deformation resistance during hot strip rolling was established based on generalized additive model. Firstly, a data modeling method based on generalized additive model was given. It included the selection of dependent variable and independent variables of the model, the link function of dependent variable and smoothing functional form of each independent variable, estimating process of the link function and smooth functions, and the last model modification. Then, the practical modeling test was carried out based on a large amount of hot rolling process data. An integrated variable was proposed to reflect the effects of different chemical compositions such as carbon, silicon, manganese, nickel, chromium, niobium, etc. The integrated chemical composition, strain, strain rate and rolling temperature were selected as independent variables and the cubic spline as the smooth function for them. The modeling process of deformation resistance was realized by SAS software, and the influence curves of the independent variables on deformation resistance were obtained by local scoring algorithm. Some interesting phenomena were found, for example, there is a critical value of strain rate, and the deformation resistance increases before this value and then decreases. The results confirm that the new model has higher prediction accuracy than traditional ones and is suitable for carbon steel, microalloyed steel, alloyed steel and other steel grades.