{"title":"MIDREX 静态热化学模型:遗传算法验证和注入氢气和焦炉煤气的绿色炼铁技术","authors":"Sunil Yadav, C. Srishilan, Ajay Kumar Shukla","doi":"10.1002/srin.202400082","DOIUrl":null,"url":null,"abstract":"<p>This work presents the development and validation of a static thermochemical model for predicting process parameters in the MIDREX shaft furnace, a method used for producing direct reduced iron from lump ore and pellets. Industrial plant data is used to validate the model. Furthermore, the model is utilized to analyze the process based on different parameters. Genetic algorithm (GA) is used to estimate the critical parameters of the process (like reaction factors and extent of reactions) and validate the model with industrial data. Further investigations are conducted to assess the possibility of replacing the reformer gas (bustle gas) with hydrogen and coke oven gas (COG) to make the process greener and almost free from carbon emissions, using a systematic approach of overall heat balance, using already developed coupled thermodynamics and kinetics-based model, and further using those data to estimate the reaction factors and extent of reactions using GA to be used in the static model. The results demonstrate the feasibility of replacing hydrogen and COG without much adverse effect on the process outcomes; however, this results in better metallization and reduced carbon footprint of the process effectively.</p>","PeriodicalId":21929,"journal":{"name":"steel research international","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Static Thermochemical Model of MIDREX: Genetic Algorithm Validation and Green Ironmaking with Hydrogen and Coke Oven Gas Injection\",\"authors\":\"Sunil Yadav, C. Srishilan, Ajay Kumar Shukla\",\"doi\":\"10.1002/srin.202400082\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This work presents the development and validation of a static thermochemical model for predicting process parameters in the MIDREX shaft furnace, a method used for producing direct reduced iron from lump ore and pellets. Industrial plant data is used to validate the model. Furthermore, the model is utilized to analyze the process based on different parameters. Genetic algorithm (GA) is used to estimate the critical parameters of the process (like reaction factors and extent of reactions) and validate the model with industrial data. Further investigations are conducted to assess the possibility of replacing the reformer gas (bustle gas) with hydrogen and coke oven gas (COG) to make the process greener and almost free from carbon emissions, using a systematic approach of overall heat balance, using already developed coupled thermodynamics and kinetics-based model, and further using those data to estimate the reaction factors and extent of reactions using GA to be used in the static model. The results demonstrate the feasibility of replacing hydrogen and COG without much adverse effect on the process outcomes; however, this results in better metallization and reduced carbon footprint of the process effectively.</p>\",\"PeriodicalId\":21929,\"journal\":{\"name\":\"steel research international\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2024-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"steel research international\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/srin.202400082\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"METALLURGY & METALLURGICAL ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"steel research international","FirstCategoryId":"88","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/srin.202400082","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"METALLURGY & METALLURGICAL ENGINEERING","Score":null,"Total":0}
引用次数: 0
摘要
这项工作介绍了用于预测 MIDREX竖炉工艺参数的静态热化学模型的开发和验证,MIDREX竖炉是一种利用块矿和球团矿生产直接还原铁的方法。工业设备数据用于验证模型。此外,该模型还可用于根据不同参数分析工艺。遗传算法(GA)用于估算工艺的关键参数(如反应因子和反应程度),并利用工业数据对模型进行验证。利用已开发的基于热力学和动力学的耦合模型,采用整体热平衡的系统方法,并进一步利用这些数据,使用 GA 估算反应因子和反应程度,将其用于静态模型中。结果表明,替代氢气和 COG 是可行的,不会对工艺结果产生太大的不利影响;不过,这将有效改善金属化效果并减少工艺的碳足迹。
Static Thermochemical Model of MIDREX: Genetic Algorithm Validation and Green Ironmaking with Hydrogen and Coke Oven Gas Injection
This work presents the development and validation of a static thermochemical model for predicting process parameters in the MIDREX shaft furnace, a method used for producing direct reduced iron from lump ore and pellets. Industrial plant data is used to validate the model. Furthermore, the model is utilized to analyze the process based on different parameters. Genetic algorithm (GA) is used to estimate the critical parameters of the process (like reaction factors and extent of reactions) and validate the model with industrial data. Further investigations are conducted to assess the possibility of replacing the reformer gas (bustle gas) with hydrogen and coke oven gas (COG) to make the process greener and almost free from carbon emissions, using a systematic approach of overall heat balance, using already developed coupled thermodynamics and kinetics-based model, and further using those data to estimate the reaction factors and extent of reactions using GA to be used in the static model. The results demonstrate the feasibility of replacing hydrogen and COG without much adverse effect on the process outcomes; however, this results in better metallization and reduced carbon footprint of the process effectively.
期刊介绍:
steel research international is a journal providing a forum for the publication of high-quality manuscripts in areas ranging from process metallurgy and metal forming to materials engineering as well as process control and testing. The emphasis is on steel and on materials involved in steelmaking and the processing of steel, such as refractories and slags.
steel research international welcomes manuscripts describing basic scientific research as well as industrial research. The journal received a further increased, record-high Impact Factor of 1.522 (2018 Journal Impact Factor, Journal Citation Reports (Clarivate Analytics, 2019)).
The journal was formerly well known as "Archiv für das Eisenhüttenwesen" and "steel research"; with effect from January 1, 2006, the former "Scandinavian Journal of Metallurgy" merged with Steel Research International.
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