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Numerical simulation of fluid flow and alloy melting in RH process for electrical steels

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Journal of Iron and Steel Research(International) 2022年第9期29卷 1423-1433页

作者： Haijun Wang Rui Xu Hai-tao Ling Wei Zhong Li-zhong Chang sheng-tao qiu Anhui Province Key Laboratory of Metallurgical Engineering and Resources Reeyeling Anhui University of TechnologyMa'anshan 243002AnhuiChina School of Metalurgical Engineering Anhui University of Technology.Ma'anshan 243002AnhuiChina State Key Laboratory of Advanced Metallurgy University of Science and Technology BeijingBeijing 100083China Xinyu Iron and Steel Co. Ltd.Xinyu 338001JiangxiChina National Engineering and Research Centerfor Continuous Casting Technology Central Iron and Steel Research InstituteBeijing 100081China

Based on the Eulerian-Lagrangian approach,a mathematical model was established to describe the gas-liquid flow behavior in the Ruhrstahl-Heraeus(RH)degasser.The momentum source and the turbulent kinetic energy source due to the motion of gas bubbles were considered for the liquid flow.The effect of the expansion of gas bubbles on the liquid velocity,recirculation rate,and mixing time was quantitatively evaluated.After the fluid flow reached the steady state,the melting and mixing processes of aluminum alloys in the RH degasser were also investigated.The results indicate that the expansion of gas bubbles has a significant infuence on the recirculation rate and the mixing time in the RH process.Increasing the superheat of liquid steel and decreasing the initial diameter of alloy particles are beneficial to promote the melting and mixing of alloy particles.Due to the existence of solidified steel shells,the maximum diameter of the alloy particle is about 1.5 times its initial diameter.

关键词： Discrete particle model Multiphase flow Gas expansion-Mixing time Alloy melting Numerical simulation

High-yield production of porous carbon spheres derived from enzymatic hydrolysis lignin for zinc ion hybrid capacitors

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Frontiers of Chemical Science and Engineering 2024年第2期18卷 127-136页

作者： tao Huang Xihong Zu Jianhui Ma Wenbin Jian Xueqing qiu Wenli Zhang Guangdong Provincial Key Laboratory of Plant Resources Biorefinery School of Chemical Engineering and Light IndustryGuangdong University of TechnologyGuangzhou 510006China School of Advanced Manufacturing Guangdong University of TechnologyJieyang 522000China Jieyang Branch of Chemistry and Chemical Engineering Guangdong Laboratory(Rongjiang Laboratory) Jieyang 515200China

The widespread implementation of supercapacitors is hindered by the limited energy density and the pricey porous carbon electrode materials.The cost of porous carbon is a significant factor in the overall cost of supercapacitors,therefore a high carbon yield could effectively mitigate the production cost of porous carbon.This study proposes a method to produce porous carbon spheres through a spray drying technique combined with a carbonization process,utilizing renewable enzymatic hydrolysis lignin as the carbon source and KOH as the activation agent.The purpose of this study is to examine the relationship between the quantity of activation agent and the development of morphology,pore structure,and specific surface area of the obtained porous carbon materials.We demonstrate that this approach significantly enhances the carbon yield of porous carbon,achieving a yield of 22%in contrast to the conventional carbonization-activation method(9%).The samples acquired through this method were found to contain a substantial amount of mesopores,with an average pore size of 1.59 to 1.85 nm and a mesopore ratio of 25.6%.Additionally,these samples showed high specific surface areas,ranging from 1051 to 1831 m2·g^(−1).Zinc ion hybrid capacitors with lignin-derived porous carbon cathode exhibited a high capacitance of 279 F·g^(−1) at 0.1 A·g^(−1) and an energy density of 99.1 Wh·kg^(−1) when the power density was 80 kW·kg^(−1).This research presents a novel approach for producing porous carbons with high yield through the utilization of a spray drying approach.

关键词： enzymatic hydrolysis lignin porous carbon spheres spray drying zinc ion hybrid capacitors

Pharmacological Effects of Botanical Drugs on Myocardial Metabolism in Chronic Heart Failure

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Chinese Journal of Integrative Medicine 2024年第5期30卷 458-467页

作者： HU Yu-xuan qiu sheng-lei SHANG Ju-ju WANG Zi LAI Xiao-lei Beijing Hospital of Traditional Chinese Medicine Capital Medical UniversityBeijing 100010China

Although there have been significant advances in the treatment of heart failure in recent years,chronic heart failure remains a leading cause of cardiovascular disease-related death.Many studies have found that targeted cardiac metabolic remodeling has good potential for the treatment of heart failure.However,most of the drugs that increase cardiac energy are still in the theoretical or testing stage.Some research has found that botanical drugs not only increase myocardial energy metabolism through multiple targets but also have the potential to restore the balance of myocardial substrate metabolism.In this review,we summarized the mechanisms by which botanical drugs(the active ingredients/formulas/Chinese patent medicines)improve substrate utilization and promote myocardial energy metabolism by activating AMP-activated protein kinase(AMPK),peroxisome proliferator-activated receptors(PPARs)and other related targets.At the same time,some potential protective effects of botanical drugs on myocardium,such as alleviating oxidative stress and dysbiosis signaling,caused by metabolic disorders,were briefly discussed.

关键词： botanical drugs chronic heart failure myocardial metabolism pharmacological effects review

Clustering for Bivariate Functional Data

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Acta Mathematicae Applicatae Sinica 2024年第3期40卷 613-629页

作者： Shi-yun CAO Yan-qiu ZHOU Yan-ling WAN tao ZHANG School of Science Guangxi University of Science and TechnologyLiuzhou 545006China School of Marxism Guangxi University of Science and TechnologyLiuzhou 545006China Key Laboratory of Intelligent Information Processing and Graph Processing Guangxi University of Science and TechnologyLiuzhou 545006China

In this paper,we consider the clustering of bivariate functional data where each random surface consists of a set of curves recorded repeatedly for each subject.The k-centres surface clustering method based on marginal functional principal component analysis is proposed for the bivariate functional data,and a novel clustering criterion is presented where both the random surface and its partial derivative function in two directions are considered.In addition,we also consider two other clustering methods,k-centres surface clustering methods based on product functional principal component analysis or double functional principal component analysis.Simulation results indicate that the proposed methods have a nice performance in terms of both the correct classification rate and the adjusted rand index.The approaches are further illustrated through empirical analysis of human mortality data.

关键词： bivariate functional data -centres surface clustering functional principal component analysis partial derivative function

Joint Probability Analysis and Prediction of Sea Ice Conditions in Liaodong Bay

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Journal of Ocean University of China 2024年第1期23卷 57-68页

作者： LIAO Zhenkun DONG sheng tao Shanshan HUA Yunfei JIA Ning College of Engineering Ocean University of ChinaQingdao 266100China Shuifa Planning and Design Co. Ltd.Jinan 250100China National Hazards Mitigation Service Beijing 100194China

Sea ice conditions in Liaodong Bay of China are often described by sea ice grades,which classify annual sea ice conditions based on the annual maximum sea ice thickness(AM-SIT)and annual maximum floating ice extent(AM-FIE).The joint probability distribution of AM-SIT and AM-FIE was established on the basis of their data pairs from 1949/1950 to 2019/2020 in Liaodong Bay.The joint intensity index of the sea ice condition in the current year is calculated,and the joint classification criteria of the sea ice grades in past years are established on the basis of the joint intensity index series.A comparison of the joint criteria with the 1973 and 2022 criteria revealed that the joint criteria of the sea ice grade match well,and the joint intensity index can be used to quantify the sea ice condition over the years.A time series analysis of the sea ice grades and the joint intensity index sequences based on the joint criteria are then performed.Results show a decreasing trend of the sea ice condition from 1949/1950 to 2019/2020,a mutation in 1990/1991,and a period of approximately 91 years of the sea ice condition.In addition,the Gray-Markov model(GMM)is applied to predict the joint sea ice grade and the joint intensity index of the sea ice condition series in future years,and the error between the results and the actual sea ice condition in 2020/2021 is small.

关键词： sea ice grade ice thickness floating ice extent Liaodong Bay copula

A Two-Layer Encoding Learning Swarm Optimizer Based on Frequent Itemsets for Sparse Large-Scale Multi-Objective Optimization

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1342-1357页

作者： sheng Qi Rui Wang tao Zhang Xu Yang Ruiqing Sun Ling Wang College of Systems Engineering National University of Defense TechnologyChangsha 410073China Xiangjiang Laboratory Changsha 410205China College of Computer National University of Defense TechnologyChangsha 410073China Department of Automation Tsinghua UniversityBeijing 100084China IEEE

Traditional large-scale multi-objective optimization algorithms(LSMOEAs)encounter difficulties when dealing with sparse large-scale multi-objective optimization problems(SLM-OPs)where most decision variables are zero.As a result,many algorithms use a two-layer encoding approach to optimize binary variable Mask and real variable Dec separately.Nevertheless,existing optimizers often focus on locating non-zero variable posi-tions to optimize the binary variables Mask.However,approxi-mating the sparse distribution of real Pareto optimal solutions does not necessarily mean that the objective function is optimized.In data mining,it is common to mine frequent itemsets appear-ing together in a dataset to reveal the correlation between data.Inspired by this,we propose a novel two-layer encoding learning swarm optimizer based on frequent itemsets(TELSO)to address these SLMOPs.TELSO mined the frequent terms of multiple particles with better target values to find mask combinations that can obtain better objective values for fast convergence.Experi-mental results on five real-world problems and eight benchmark sets demonstrate that TELSO outperforms existing state-of-the-art sparse large-scale multi-objective evolutionary algorithms(SLMOEAs)in terms of performance and convergence speed.

关键词： Evolutionary algorithms learning swarm optimiza-tion sparse large-scale optimization sparse large-scale multi-objec-tive problems two-layer encoding.

Research on a Monte Carlo global variance reduction method based on an automatic importance sampling method

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Nuclear Science and Techniques 2024年第5期35卷 200-215页

作者： Yi-sheng Hao Zhen Wu Shen-Shen Gao Rui qiu Hui Zhang Jun-Li Li Department of Engineering Physics Tsinghua UniversityBeijing 100084China Key Laboratory of Particle and Radiation Imaging of Ministry of Education Beijing 100084China Nuctech Company Limited Beijing 100084China

Global variance reduction is a bottleneck in Monte Carlo shielding calculations.The global variance reduction problem requires that the statistical error of the entire space is uniform.This study proposed a grid-AIS method for the global variance reduction problem based on the AIS method,which was implemented in the Monte Carlo program MCShield.The proposed method was validated using the VENUS-Ⅲ international benchmark problem and a self-shielding calculation example.The results from the VENUS-Ⅲ benchmark problem showed that the grid-AIS method achieved a significant reduction in the variance of the statistical errors of the MESH grids,decreasing from 1.08×10^(-2) to 3.84×10^(-3),representing a 64.00% reduction.This demonstrates that the grid-AIS method is effective in addressing global issues.The results of the selfshielding calculation demonstrate that the grid-AIS method produced accurate computational results.Moreover,the grid-AIS method exhibited a computational efficiency approximately one order of magnitude higher than that of the AIS method and approximately two orders of magnitude higher than that of the conventional Monte Carlo method.

关键词： Monte Carlo Global variance reduction Reactor shielding Automatic importance sampling

Present-day movement characteristics of the Qinghai Nanshan fault and its surrounding area from GPS observation

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Geodesy and Geodynamics 2024年第2期15卷 133-141页

作者： Yang Liu Yuxuan qiu Jialiang Liu Luyun Xiong Caijun Xu Jianghui Geng Gang Zheng Tianchen sheng School of Geodesy and Geomatics Wuhan UniversityWuhan 430079China Key Laboratory of Geospace Environment and Geodesy Ministry of EducationWuhan UniversityWuhan 430079China Key Laboratory of Geophysical Geodesy Ministry of Natural ResourcesWuhan UniversityWuhan 430079China GNSS Research Center Wuhan UniversityWuhan 430079China School of Earth and Environment University of LeedsLeeds LS29JTUK Qinghai Basic Surveying and Mapping Institute Xining 810101China

The Qinghai Nanshan fault is a larger fault in the Northeastern Xizang Plateau.In previous studies,its movement characteristics are mainly investigated with geological and seismic observations,and the tectonic transformation role of the fault on its east is not yet clear.This study uses data fusion to obtain denser GPS observations near the Qinghai Nanshan fault.Based on tectonic characteristics,we establish a block model to investigate the fault slip rate,locking degree,and slip deficit.The results show that the Qinghai Nanshan fault slip rate is characterized by sinistral and convergent movement.Both the sinistral and convergent rates display a decreasing trend from west to east.The locking degree and slip deficit are higher in the western segment(with an average of about 0.74 and 1.1 mm/a)and lower in the eastern segment.Then,we construct a strain rate field using GPS observations to analyze the regional strain characteristics.The results indicate that along the fault,the western segment shows a larger shear strain rate and negative dilation rate.Regional earthquake records show that the frequency of earthquakes is lower near the fault.The joint results suggest that the western segment may have a higher earthquake risk.In addition,the insignificant fault slip rate in the eastern segment may indicate that it does not participate in the tectonic transformation among the Riyueshan,Lajishan,and West Qinling faults.

关键词： The Qinghai Nanshan fault Movement characteristics Block model Slip rate GPS

Multi-process production occurs in the iron and steel industry,supporting‘dual carbon'target:An in-depth study of CO_(2)emissions from different processes

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Journal of Environmental Sciences 2024年第6期140卷 46-58页

作者： Hongming Na Yuxing Yuan tao Du Tianbao Zhang Xi Zhao Jingchao Sun Ziyang qiu Lei Zhang SEP Key Laboratory of Eco-Industry Northeastern UniversityShenyang 110819China School of Metallurgy Northeastern UniversityShenyang 110819China

Reducing CO_(2)emissions of the iron and steel industry,a typical heavy CO_(2)-emitting sector is the only way that must be passed to achieve the‘dual-carbon’goal,especially in China.In previous studies,however,it is still unknown what is the difference between blast furnace basic oxygen furnace(BF-BOF),scrap-electric furnace(scrap-EF)and hydrogen metallurgy process.The quantitative research on the key factors affecting CO_(2)emissions is insufficient There is also a lack of research on the prediction of CO_(2)emissions by adjusting industria structure.Based on material flow analysis,this study establishes carbon flow diagrams o three processes,and then analyze the key factors affecting CO_(2)emissions.CO_(2)emissions of the iron and steel industry in the future is predicted by adjusting industrial structure The results show that:(1)The CO_(2)emissions of BF-BOF,scrap-EF and hydrogen metallurgy process in a site are 1417.26,542.93 and 1166.52 kg,respectively.(2)By increasing pellet ratio in blast furnace,scrap ratio in electric furnace,etc.,can effectively reduce CO_(2)emissions(3)Reducing the crude steel output is the most effective CO_(2)reduction measure.There is still 5.15×10^(8)-6.17×10^(8) tons of CO_(2)that needs to be reduced by additional measures.

关键词： Blast furnace-basic oxygen furnace process Scrap-electric furnace process Hydrogen metallurgy process Carbon flow diagram Influencing factors CO_(2)emission prediction