{"title":"高强度集装箱钢在多道次变形条件下的流动应力模型","authors":"Xiaoguang Zhou, Shan Jiang, Xin Ma, Xin Li, Jinfan Zhao, Guangming Cao, Zhenyu Liu","doi":"10.1007/s12289-025-01929-0","DOIUrl":null,"url":null,"abstract":"<div><p>Multi-pass compression deformation experiments for a high-strength container steel have been conducted on the DIL805A/D thermal expansion instrument. The true stress- plastic strain curves of experimental steel were plotted. Three typical flow stress models are used to predict the flow stress of the first pass deformation, and Model-1 flow stress model with the highest fitting accuracy is selected as the basic model form. Also, high precision static recrystallization volume fraction model and austenite grain size model have been established. The genetic algorithm is used to optimize the parameters in Model-1 model according to the second pass flow stress data. The relationships between static recrystallization volume fraction, the initial austenite grain size, the dislocation density before deformation, the deformation temperature, the strain rate and the model parameters are established through the Support Vector Machine (SVM) algorithm. The established flow stress model not only has high accuracy but also conforms to physical metallurgical principles under multi-pass steel deformation conditions according to a maximum plastic strain of 0.25. The research results can provide an important theoretical guidance for the load distribution of the rolling mill for the production of high-strength container plate.</p></div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"18 3","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Flow stress model of high-strength container steel under multi-pass deformation conditions\",\"authors\":\"Xiaoguang Zhou, Shan Jiang, Xin Ma, Xin Li, Jinfan Zhao, Guangming Cao, Zhenyu Liu\",\"doi\":\"10.1007/s12289-025-01929-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Multi-pass compression deformation experiments for a high-strength container steel have been conducted on the DIL805A/D thermal expansion instrument. The true stress- plastic strain curves of experimental steel were plotted. Three typical flow stress models are used to predict the flow stress of the first pass deformation, and Model-1 flow stress model with the highest fitting accuracy is selected as the basic model form. Also, high precision static recrystallization volume fraction model and austenite grain size model have been established. The genetic algorithm is used to optimize the parameters in Model-1 model according to the second pass flow stress data. The relationships between static recrystallization volume fraction, the initial austenite grain size, the dislocation density before deformation, the deformation temperature, the strain rate and the model parameters are established through the Support Vector Machine (SVM) algorithm. The established flow stress model not only has high accuracy but also conforms to physical metallurgical principles under multi-pass steel deformation conditions according to a maximum plastic strain of 0.25. The research results can provide an important theoretical guidance for the load distribution of the rolling mill for the production of high-strength container plate.</p></div>\",\"PeriodicalId\":591,\"journal\":{\"name\":\"International Journal of Material Forming\",\"volume\":\"18 3\",\"pages\":\"\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2025-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Material Forming\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s12289-025-01929-0\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, MANUFACTURING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Material Forming","FirstCategoryId":"88","ListUrlMain":"https://link.springer.com/article/10.1007/s12289-025-01929-0","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
Flow stress model of high-strength container steel under multi-pass deformation conditions
Multi-pass compression deformation experiments for a high-strength container steel have been conducted on the DIL805A/D thermal expansion instrument. The true stress- plastic strain curves of experimental steel were plotted. Three typical flow stress models are used to predict the flow stress of the first pass deformation, and Model-1 flow stress model with the highest fitting accuracy is selected as the basic model form. Also, high precision static recrystallization volume fraction model and austenite grain size model have been established. The genetic algorithm is used to optimize the parameters in Model-1 model according to the second pass flow stress data. The relationships between static recrystallization volume fraction, the initial austenite grain size, the dislocation density before deformation, the deformation temperature, the strain rate and the model parameters are established through the Support Vector Machine (SVM) algorithm. The established flow stress model not only has high accuracy but also conforms to physical metallurgical principles under multi-pass steel deformation conditions according to a maximum plastic strain of 0.25. The research results can provide an important theoretical guidance for the load distribution of the rolling mill for the production of high-strength container plate.
期刊介绍:
The Journal publishes and disseminates original research in the field of material forming. The research should constitute major achievements in the understanding, modeling or simulation of material forming processes. In this respect ‘forming’ implies a deliberate deformation of material.
The journal establishes a platform of communication between engineers and scientists, covering all forming processes, including sheet forming, bulk forming, powder forming, forming in near-melt conditions (injection moulding, thixoforming, film blowing etc.), micro-forming, hydro-forming, thermo-forming, incremental forming etc. Other manufacturing technologies like machining and cutting can be included if the focus of the work is on plastic deformations.
All materials (metals, ceramics, polymers, composites, glass, wood, fibre reinforced materials, materials in food processing, biomaterials, nano-materials, shape memory alloys etc.) and approaches (micro-macro modelling, thermo-mechanical modelling, numerical simulation including new and advanced numerical strategies, experimental analysis, inverse analysis, model identification, optimization, design and control of forming tools and machines, wear and friction, mechanical behavior and formability of materials etc.) are concerned.