Yang Fei, Xiaoping Guan, Shibo Kuang, Aibing Yu and Ning Yang*,
{"title":"竖炉氢冶金建模与仿真综述:化学工程视角","authors":"Yang Fei, Xiaoping Guan, Shibo Kuang, Aibing Yu and Ning Yang*, ","doi":"10.1021/acsengineeringau.3c00033","DOIUrl":null,"url":null,"abstract":"<p >Hydrogen-based shaft furnace technology holds promise for low-carbon hydrogen metallurgy. Since hydrogen-assisted iron ore reduction is highly endothermic, inadequate heat supply relevant to the contact of gas and densely packed ores may reduce the rate and efficiency of reductions. The key to addressing this issue lies in understanding the competition among heat supply, heat transfer, and heat loss driven by the gas flow around ores and reactions within them. Modeling and simulation are crucial for revealing the underlying mechanisms and promoting process scale-up and intensification. This review summarizes previous efforts in physical modeling and model applications for improving the reduction performance. The discrete element method (DEM) and computational fluid dynamics (CFD)–DEM models have been used for particle-scale simulation to investigate inhomogeneous particle descent and relevant particle–particle interactions. For macroscale simulations, steady-state simplified models such as plug flow and REDUCTOR, as well as the Eulerian two-phase model, have been developed by considering heat and mass transfer. Based on these model applications, strategies including the optimization of operating conditions and gas-feeding methods have been proposed to improve the furnace performance. Further numerical efforts are needed to analyze the in-furnace heat evolution and reduction and reveal the competitiveness of flow, transport, and reaction by incorporating multiscale physics in shaft furnaces. Additionally, attention could be paid to the effects of particle sticking and degradation on reduction, which may be more serious when the proportion of lump ores increases. When evaluating relative optimization strategies, comprehensive comparisons are expected in terms of iron ore reduction degree, gas utilization rate, energy consumption, and economic feasibility under various reducing and cooling gas operating conditions and furnace profiles to offer practical guidelines for industrial design and intensification.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.3c00033","citationCount":"0","resultStr":"{\"title\":\"A Review on the Modeling and Simulation of Shaft Furnace Hydrogen Metallurgy: A Chemical Engineering Perspective\",\"authors\":\"Yang Fei, Xiaoping Guan, Shibo Kuang, Aibing Yu and Ning Yang*, \",\"doi\":\"10.1021/acsengineeringau.3c00033\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >Hydrogen-based shaft furnace technology holds promise for low-carbon hydrogen metallurgy. Since hydrogen-assisted iron ore reduction is highly endothermic, inadequate heat supply relevant to the contact of gas and densely packed ores may reduce the rate and efficiency of reductions. The key to addressing this issue lies in understanding the competition among heat supply, heat transfer, and heat loss driven by the gas flow around ores and reactions within them. Modeling and simulation are crucial for revealing the underlying mechanisms and promoting process scale-up and intensification. This review summarizes previous efforts in physical modeling and model applications for improving the reduction performance. The discrete element method (DEM) and computational fluid dynamics (CFD)–DEM models have been used for particle-scale simulation to investigate inhomogeneous particle descent and relevant particle–particle interactions. For macroscale simulations, steady-state simplified models such as plug flow and REDUCTOR, as well as the Eulerian two-phase model, have been developed by considering heat and mass transfer. Based on these model applications, strategies including the optimization of operating conditions and gas-feeding methods have been proposed to improve the furnace performance. Further numerical efforts are needed to analyze the in-furnace heat evolution and reduction and reveal the competitiveness of flow, transport, and reaction by incorporating multiscale physics in shaft furnaces. Additionally, attention could be paid to the effects of particle sticking and degradation on reduction, which may be more serious when the proportion of lump ores increases. When evaluating relative optimization strategies, comprehensive comparisons are expected in terms of iron ore reduction degree, gas utilization rate, energy consumption, and economic feasibility under various reducing and cooling gas operating conditions and furnace profiles to offer practical guidelines for industrial design and intensification.</p>\",\"PeriodicalId\":29804,\"journal\":{\"name\":\"ACS Engineering Au\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2023-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.3c00033\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Engineering Au\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://pubs.acs.org/doi/10.1021/acsengineeringau.3c00033\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, CHEMICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Engineering Au","FirstCategoryId":"1085","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acsengineeringau.3c00033","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
A Review on the Modeling and Simulation of Shaft Furnace Hydrogen Metallurgy: A Chemical Engineering Perspective
Hydrogen-based shaft furnace technology holds promise for low-carbon hydrogen metallurgy. Since hydrogen-assisted iron ore reduction is highly endothermic, inadequate heat supply relevant to the contact of gas and densely packed ores may reduce the rate and efficiency of reductions. The key to addressing this issue lies in understanding the competition among heat supply, heat transfer, and heat loss driven by the gas flow around ores and reactions within them. Modeling and simulation are crucial for revealing the underlying mechanisms and promoting process scale-up and intensification. This review summarizes previous efforts in physical modeling and model applications for improving the reduction performance. The discrete element method (DEM) and computational fluid dynamics (CFD)–DEM models have been used for particle-scale simulation to investigate inhomogeneous particle descent and relevant particle–particle interactions. For macroscale simulations, steady-state simplified models such as plug flow and REDUCTOR, as well as the Eulerian two-phase model, have been developed by considering heat and mass transfer. Based on these model applications, strategies including the optimization of operating conditions and gas-feeding methods have been proposed to improve the furnace performance. Further numerical efforts are needed to analyze the in-furnace heat evolution and reduction and reveal the competitiveness of flow, transport, and reaction by incorporating multiscale physics in shaft furnaces. Additionally, attention could be paid to the effects of particle sticking and degradation on reduction, which may be more serious when the proportion of lump ores increases. When evaluating relative optimization strategies, comprehensive comparisons are expected in terms of iron ore reduction degree, gas utilization rate, energy consumption, and economic feasibility under various reducing and cooling gas operating conditions and furnace profiles to offer practical guidelines for industrial design and intensification.
期刊介绍:
)ACS Engineering Au is an open access journal that reports significant advances in chemical engineering applied chemistry and energy covering fundamentals processes and products. The journal's broad scope includes experimental theoretical mathematical computational chemical and physical research from academic and industrial settings. Short letters comprehensive articles reviews and perspectives are welcome on topics that include:Fundamental research in such areas as thermodynamics transport phenomena (flow mixing mass & heat transfer) chemical reaction kinetics and engineering catalysis separations interfacial phenomena and materialsProcess design development and intensification (e.g. process technologies for chemicals and materials synthesis and design methods process intensification multiphase reactors scale-up systems analysis process control data correlation schemes modeling machine learning Artificial Intelligence)Product research and development involving chemical and engineering aspects (e.g. catalysts plastics elastomers fibers adhesives coatings paper membranes lubricants ceramics aerosols fluidic devices intensified process equipment)Energy and fuels (e.g. pre-treatment processing and utilization of renewable energy resources; processing and utilization of fuels; properties and structure or molecular composition of both raw fuels and refined products; fuel cells hydrogen batteries; photochemical fuel and energy production; decarbonization; electrification; microwave; cavitation)Measurement techniques computational models and data on thermo-physical thermodynamic and transport properties of materials and phase equilibrium behaviorNew methods models and tools (e.g. real-time data analytics multi-scale models physics informed machine learning models machine learning enhanced physics-based models soft sensors high-performance computing)