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Physicochemical principles of hydrogen metallurgy in blast furnace

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Journal of Iron and Steel Research International 2024年第1期31卷 46-63页

作者： han-jie guo School of Metallurgical and Ecological Engineering University of Science and Technology BeijingBeijing100083China Beijing Key Laboratory of Special Melting and Preparation of High-End Metal Materials Beijing100083China

Based on the stoichiometric method and the free energy minimization method,an ideal model for the reduction of iron oxides by carbon and hydrogen under blast furnace conditions was established,and the reduction efficiency and theoretical energy consumption of the all-carbon blast furnace and the hydrogen-rich blast furnace were *** results show that after the reduction reaction is completed at the bottom of the blast furnace,the gas produced by reduction at 1600℃still has a certain excessive reduction capacity,which is due to the hydrogen brought in by the hydrogen-rich blast as well as the excess carbon monoxide generated by the reaction of the coke and the oxygen brought in by the *** the process of the gas with excessive reduction capacity rising from the bottom of the blast furnace and gas reduction process,the excessive reduction capacity of the gas gradually decreases with the increase in the dydrogen content in the *** the all-carbon blast furnace,the excess gas reduction capacity is the strongest,and the total energy consumption per ton of iron reduction is the *** shows that,for the current operation mode of the blast furnace,adding hydrogen in the blast furnace cannot reduce the consumption of carbon required for reduction per ton of iron,but rather increases the consumption of carbon.

关键词： Hydrogen metallurgy Excess gas reduction capacity Theoretical energy consumption Hydrogen-rich blast furnace Thermodynamic model Gibbs minimum free energy method

Characteristics and stability of oxide+carbonitride in H13 steel at 1250℃

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Journal of Iron and Steel Research International 2024年第1期31卷 134-142页

作者： Xiao-lin Sun han-jie guo Jing guo Fei Wang Dong Xu Gao-yang Song Shuai Wang School of Materials Science and Engineering Hebei University of EngineeringHandan056038HebeiChina School of Metallurgical and Ecological Engineering University of Science and Technology BeijingBeijing100083China High Temperature Materials Research Institute Central Iron and Steel Research Institute Co.Ltd.Beijing100081China Technology Innovation Center for High Quality Cold Heading Steel of Hebei Province Hebei University of EngineeringHandan056038HebeiChina

The morphology,size,quantity,and composition of complex oxide+carbonitride in H13 steel held at 1250℃for 5,10,and 15 h were *** results show that the ratio and number of complex carbonitrides with cores in H13 steel are gradually increased when holding at 1250℃compared with those in the original H13 steel,and the core size *** are one or more oxide cores in(Ti_(x),V_(1-x))(Cy,N_(1-y)),including xCaO·zAl_(2)O_(3),xCaO·yMgO·zAl_(2)O_(3),and CaO after holding at 1250℃,in addition to MgO·Al_(2)O_(3)and Al_(2)O_(3)in the original *** equilibrium temperature for(Ti_(x),V_(1-x))(Cy,N_(1-y))precipitation at the solidification front and decomposition in the solid state was theoretically analyzed,which was affected by the x value and the product of Ti and N contents in H13 ***,the composition of(Ti_(x),V_(1-x))(Cy,N_(1-y))is influenced by the oxide *** is convinced that(Ti_(x),V_(1-x))(Cy,N_(1-y))with oxide cores has a higher stability,especially for oxides with a high Al_(2)O_(3)*** treatment at high temperature facilitates a more reasonable analysis of oxide+carbonitride,and the generation mechanism of oxide+carbonitride was discussed.

关键词： Complex carbonitride Decomposition Oxide core Characteristic Stability

Thermodynamic and experimental study of high-temperature roasting of blast furnace gas ash for recovery of metallic zinc and iron

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Journal of Iron and Steel Research International 2024年第1期31卷 108-120页

作者： Zi-han Wang Jing guo han-jie guo Bin Li School of Metallurgical Engineering University of Science and Technology BeijingBeijing100083China School of Metallurgical Engineering Xi’an University of Architecture and TechnologyXi’an710055ShaanxiChina

A high-temperature reduction roasting method was used to achieve metallic iron and zinc recovery from blast furnace gas ash(BFA).The reduction processes for Zn-containing and Fe-containing oxides were analyzed in detail by using ther-modynamic equilibrium calculation and the principle of minimum free *** results showed that the main reaction in the system is the reduction of ZnFe_(2)_(4)and iron *** the full temperature range,iron oxides were more easily reduced than zinc *** of the amount of CO contained in the system,the reduction of ZnO to Zn was difficult to proceed below the boiling point(906℃)of *** the reduction temperature is below 906℃,the reduction process of zinc ferrate was ZnFe_(2)_(4)→ZnO;when the reduction temperature is above 906℃,its reduction process becomed ZnFe_(2)_(4)→ZnO→Zn(g).The metallization and dezincification rates of the BFA gradually increased with increasing reaction *** the C/O ratio increased,the metallization and dezincification rates first increased and then *** effect of reduction time on BFA reduction was similar to that of reaction temperature.

关键词： Blast furnace gas ash Thermodynamics Zinc removal Iron reduction High-temperature reduction roasting Integrated utilization

LAMDA-SSL:a comprehensive semi-supervised learning toolkit

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Science China(Information Sciences) 2024年第1期67卷 306-307页

作者： lin-han JIA Lan-Zhe guo Zhi ZHOU Yu-Feng LI National Key Laboratory for Novel Software Technology Nanjing University

Machine learning, particularly deep learning, has achieved remarkable success across a wide range of tasks. However,most of these tasks demand a substantial amount of labeled training data, which can be challenging to obtain in many real-world applications due to difficulties, costs, or time constraints associated with labeling. In this context,semi-supervised learning (SSL) has emerged as a promising paradigm to alleviate the dependency on large labeled datasets by harnessing the power of unlabeled data [1–3].

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A short review of antibacterial Cu-bearing stainless steel:antibacterial mechanisms,corrosion resistance,and novel preparation techniques

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Journal of Iron and Steel Research International 2024年第1期31卷 24-45页

作者： Shuai Liu han-jie guo School of Artificial Intelligence Beijing Technology and Business UniversityBeijing100048China Beijing Key Laboratory of Special Melting and Preparation of High-End Metal Materials University of Science and Technology BeijingBeijing100083China

Cu-bearing stainless steel is widely used in the fields of food,medical and household sanitary equipment because of its surface finish and corrosion ***,the growth of bacteria on stainless steel leads to the formation of biofilms,which causes ***,the antibacterial property of stainless steel is a worthy research *** of breakthroughs in the field of corrosion resistance and antimicrobial properties are still ***,due to the scarcity of publications on the antibacterial mechanisms and processing methods of antibacterial Cu-bearing stainless steel,we review the current state of relevant research and *** toxicity of Cu,corrosion resistance mechanism of stainless steel,and antibacterial mechanism and preparation method of antibacterial stainless steel are *** addition,alloying,surface modification and other methods are found to have limitations in balancing the toxicity and antibacterial properties of copper and the relationship between the antibacterial properties and corrosion resistance of Cu-bearing stainless steel.A new preparation method of antibacterial stainless steel associated with selective laser melting(SLM)is *** is becoming a powerful additive manufacturing technology that can be used to manufacture customized and complex *** research status of SLM applied in antibacterial stainless steel preparation is ***,the future research direction of Cu-bearing antibacterial stainless steel is discussed.

关键词： Cu-bearing stainless steel Antibacterial Processing Additive manufacturing Corrosion resistance

Crystal phase control and ignition properties of HNS/CL-20 composite microspheres prepared by microfluidics combined with emulsification techniques

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Particuology 2024年第2期85卷 241-251页

作者： Yi Liu Yunyan guo Rui Zhu Jinqiang Zhou Zhengxu lin Kai han Chongwei An Jingyu Wang Bidong Wu School of Environment and Safety Engineering North University of ChinaTaiyuan030051China School of Engineering Beijing Institute of TechnologyBeijing100081China Shanxi Province Ultrafine Powder Engineering Technology Research Center Taiyuan030051China

Improved controllability and energy density of ignition agents are of great significance for the devel-opment of energetic composite *** this study,droplet microfluidics and emulsification tech-niques were combined to prepare HNS/CL-20 composite microspheres with polyglycidyl azide polymer(GAP)as the *** influence of binder content on the morphology of microspheres was investi-gated,and the microspheres were characterized and tested for particle size,crystal structure,thermal decomposition,dispersibility,mechanical sensitivity,combustion behavior and detonation *** results showed that microspheres prepared with a binder content of 3%had higher sphericity and particle size *** microspheres retained the crystal structure of both HNS and CL-20(ε-type).Compared with raw HNS,the microspheres had higher apparent activation energy,better safety per-formance,and good *** ignition experiments and detonation performance tests show that HNS/CL-20 composite microspheres have excellent ignition performance,obvious combustion flame,and significant energy release effects,which are expected to achieve high energy and high-speed response of the igniter,thus improving the ignition reliability in special environments or systems.

关键词： Droplet microfluidics Emulsification technology Energetic materials Composite microspheres Crystal phase control Ignition

TSC prediction and dynamic control of BOF steelmaking with state-of-the-art machine learning and deep learning methods

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Journal of Iron and Steel Research International 2024年第1期31卷 174-194页

作者： Tian-yi Xie Cai-dong Zhang Quan-lin Zhou Zhi-qiang Tian Shuai Liu han-jie guo Material Technology Research Institute Hesteel GroupShijiazhuang050023HebeiChina Tangsteel Company Hesteel GroupTangshan063611HebeiChina School of Artificial Intelligence Beijing Technology and Business UniversityBeijing100048China School of Metallurgical and Ecological Engineering University of Science and Technology BeijingBeijing100083China

Mathematical(data-driven)models based on state-of-the-art(SOTA)machine learning and deep learning models and data collected from 12,786 heats were established to predict the values of temperature,sample,and carbon(TSC)test,including temperature of molten steel(TSC-Temp),carbon content(TSC-C)and phosphorus content(TSC-P),which made prepa-ration for eliminating the TSC *** maximize the prediction accuracy of the proposed approach,various models with different inputs were implemented and compared,and the best models were applied to the production process of a Hesteel Group steelmaking plant in China in the *** number of tabular features(hot metal information,scrap,additives,blowing practices,and preset values)was expanded,and time series(off-gas profiles and blowing practice curves)that could reflect the entire steelmaking process were introduced as ***,the latest machine learning models(LightGBM,CatBoost,TabNet,and NODE)were used to make predictions with tabular features,and the best coefficient of determination R^(2)values obtained for TSC-P,TSC-C and TSC-Temp predictions were 0.435(LightGBM),0.857(Cat-Boost)and 0.678(LightGBM),respectively,which were higher than those of classic models(backpropagation and support vector machine).Then,making predictions was performed by using SOTA time series regression models(SCINet,Dlinear,Informer,and MLSTM-FCN)with original time series,SOTA image regression models(NesT,CaiT,ResNeXt,and GoogLeNet)with resized time series,and the proposed Concatenate-Model and Parallel-Model with both tabular features and time *** optimization and comparisons,it was finally determined that the Concatenate-Model with MLSTM-FCN,SCINet and Informer as feature extractors performed the best,and its R^(2)values for predicting TSC-P,TSC-C and TSC-Temp reached 0.470,0.858 and 0.710,*** field test accuracies for TSC-P,TSC-C and TSC-Temp were 0.459,0.850 and 0.685,respectively.A related importance analysis was carri

关键词： BOF steelmaking In-blow prediction TSC test Machine learning Deep learning Field application

A Survey on Distributed Network Localization from a Graph Laplacian Perspective

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Journal of Systems Science & Complexity 2024年第1期37卷 273-293页

作者： han Zhimin lin Zhiyun FU Minyue Artificial Intelligence Institute School of AutomationHangzhou Dianzi UniversityHangzhou 310018China Shenzhen Key Laboratory of Control Theory and Intelligent Systems School of System Design and Intelligent ManufacturingSouthern University of Science and TechnologyShenzhen 518055China Peng Cheng Laboratory Shenzhen 518000China

Network localization serves as a fundamental component for enabling various position based operations in multi-agent systems,facilitating tasks like target searching and formation control by providing accurate position information for all nodes in the *** localization focuses on the challenge of determining the positions of nodes within a network,relying on the known positions of anchor nodes and internode relative *** the past few decades,distributed network localization has garnered significant attention from *** paper aims to provide a review of main results and advancements in the field of distributed network localization,with a particular focus on the perspective of graph *** to its favorable characteristics,graph Laplacian unifies various network localization,even when dealing with diverse types of internode relative measurements,into a unified protocol framework,which can be constructed by a linear method and ensure the global convergence.

关键词： Distributed network localization graph Laplaian sensor network

Interactive effect of thermal aging and proton irradiation on microstructural evolution and hardening ofδ-ferrite in 308L stainless steel weld metal

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Journal of Materials Science & Technology 2024年第3期170卷 140-155页

作者： Xiaodong Gao Xiaodong lin Tao guo lining Xu Yaolei han Baolong Jiang Xingyuan Mei Qunjia Peng Lijie Qiao Beijing Advanced Innovation Center for Materials Genome Engineering Institute of Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijing 100083China Institute of Materials Shanghai UniversityShanghai 200072China School of Materials Science and Engineering University of Science and Technology BeijingBeijing 100083China Suzhou Nuclear Power Research Institute Suzhou 215004China State Key Laboratory for Advanced Metals and Materials University of Science and Technology BeijingBeijing 100083China

In the harsh service environment of high temperature and intense neutron irradiation in water-cooled nuclear reactors,the austenitic stainless steel weld overlay cladding on the inner surface of the reactor pressure vessel suffers from thermal aging and irradiation damage simultaneously,which can induce microstructural evolution and hardening of the *** it is quite difficult to achieve this simul-taneous process out of the pile,two kinds of combined experiments,i.e.,post-irradiation thermal aging and post-aging irradiation were performed on 308 L stainless steel weld metals in this *** interactive effect of thermal aging and proton irradiation on microstructural evolution and hardening ofδ-ferrite in 308 L weld metal was investigated by combining atom probe tomography,transmission elec-tron microscopy and nanoindentation *** results revealed that thermal aging could eliminate the dislocation loops induced by irradiation and affect the phase transition process by accelerating spinodal decomposition and G-phase precipitation,thus enhancing hardening of irradiatedδ-*** the effect of irradiation on the microstructure and hardening of thermally agedδ-ferrite,however,intensive collision cascades can intensify G-phase precipitation and dislocation loop formation but decrease spinodal decomposition,leading to a limited effect on hardening of thermally agedδ-***,the interaction of thermal aging and irradiation can promote G-phase ***,the interaction can causeδ-ferrite hardening,which is mainly influenced by spinodal decomposition,followed by G-phase and dislocation loops,where spinodal decomposition and G-phase cause hardening by inducing strain fields.

关键词： Austenitic stainless steel weld metals Thermal aging Proton irradiation Interaction Microstructural evolution Hardening