The prediction and control of furnace heat indicators are of great importance for improving the heat levels and conditions of the complex and difficult-to-operate hour-class delay blast furnace(BF)system.In this work,...The prediction and control of furnace heat indicators are of great importance for improving the heat levels and conditions of the complex and difficult-to-operate hour-class delay blast furnace(BF)system.In this work,a prediction and feedback model of furnace heat indicators based on the fusion of data-driven and BF ironmaking processes was proposed.The data on raw and fuel materials,process op-eration,smelting state,and slag and iron discharge during the whole BF process comprised 171 variables with 9223 groups of data and were comprehensively analyzed.A novel method for the delay analysis of furnace heat indicators was established.The extracted delay variables were found to play an important role in modeling.The method that combined the genetic algorithm and stacking efficiently im-proved performance compared with the traditional machine learning algorithm in improving the hit ratio of the furnace heat prediction model.The hit ratio for predicting the temperature of hot metal in the error range of±10℃ was 92.4%,and that for the chemical heat of hot metal in the error range of±0.1wt%was 93.3%.On the basis of the furnace heat prediction model and expert experience,a feedback model of furnace heat operation was established to obtain quantitative operation suggestions for stabilizing BF heat levels.These sugges-tions were highly accepted by BF operators.Finally,the comprehensive and dynamic model proposed in this work was successfully ap-plied in a practical BF system.It improved the BF temperature level remarkably,increasing the furnace temperature stability rate from 54.9%to 84.9%.This improvement achieved considerable economic benefits.展开更多
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....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.展开更多
Hydrogen-enriched blast furnace ironmaking has become an essential route to reduce CO_(2)emissions in the ironmaking process.However,hydrogen-enriched reduction produces large amounts of H_(2)O,which places new demand...Hydrogen-enriched blast furnace ironmaking has become an essential route to reduce CO_(2)emissions in the ironmaking process.However,hydrogen-enriched reduction produces large amounts of H_(2)O,which places new demands on coke quality in a blast furnace.In a hydrogen-rich blast furnace,the presence of H_(2)O promotes the solution loss reaction.This result improves the reactivity of coke,which is 20%-30%higher in a pure H_(2)O atmosphere than in a pure CO_(2)atmosphere.The activation energy range is 110-300 kJ/mol between coke and CO_(2)and 80-170 kJ/mol between coke and H_(2)O.CO_(2)and H_(2)O are shown to have different effects on coke degradation mechanisms.This review provides a comprehensive overview of the effect of H_(2)O on the structure and properties of coke.By exploring the interactions between H_(2)O and coke,several unresolved issues in the field requiring further research were identified.This review aims to provide valuable insights into coke behavior in hydrogen-rich environments and promote the further development of hydrogen-rich blast furnace ironmaking processes.展开更多
To realize the resource utilization of the valuable metals in the titanium-containing blast furnace slag,the process route of “hydrochloric acid leaching-electrolysis-carbonization and carbon dioxide capture-preparat...To realize the resource utilization of the valuable metals in the titanium-containing blast furnace slag,the process route of “hydrochloric acid leaching-electrolysis-carbonization and carbon dioxide capture-preparation of calcium carbonate” was proposed.In this study,the influences of process conditions on the leaching rates of calcium,magnesium,aluminum,and iron and the phases of the leaching residue were investigated for the leaching process.The experimental results show that the HCl solution could selectively leach the elements from the titanium-containing blast furnace slag.The better leaching conditions are the HCl solution concentration of 4 mol/L,the leaching time of 30 min,the ratio of liquid volume to solid gas of 10 mL/g,and the stirring paddle speed of 300 r/min.Under the conditions,the leaching rates of calcium,magnesium,aluminum,and iron can reach 85.87%,73.41%,81.35%,and 59.08%,and the leaching rate of titanium is 10.71%.The iron and the aluminum are removed from the leachate to obtain iron-aluminum water purification agents,and the magnesium is removed from the leachate to obtain magnesium hydroxide.The leaching residue phase is dominated by perovskite,followed by magnesium silicate and tricalcium aluminate,and the titaniumrich material could be obtained from the leaching residue by desiliconization.展开更多
The variation characteristics of bubble morphology and the thermal-physical properties of bubble boundary in the top-blown smelting furnace were explored by means of the computational fluid dynamics method.The essenti...The variation characteristics of bubble morphology and the thermal-physical properties of bubble boundary in the top-blown smelting furnace were explored by means of the computational fluid dynamics method.The essential aspects of the fluid phase(e.g.,splashing volume,dead zone of copper slag,and gas penetration depth)were explored together with the effect of sinusoidal pulsating gas intake on the momentum-transfer performance between phases.The results illustrated that two relatively larger vortices and two smaller vortices appear in the bubble waist and below the lance,respectively.The expansion of larger ones as well as the shrinking of smaller ones combine to cause the contraction of the bubble waist.Compared to the results of the case with a fixed gas injection velocity(V_(g)=58 m/s),the splashing volume and dead zone volume of the slag under the V_(g)=58+10sin(2πt)condition are reduced by 24.9%and 23.5%,respectively,where t represents the instant time.Gas penetration depth and slag motion velocity of the latter are 1.03 and 1.31 times high-er than those of the former,respectively.展开更多
Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss pos...Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.展开更多
Accurate positioning is one of the essential requirements for numerous applications of remote sensing data,especially in the event of a noisy or unreliable satellite signal.Toward this end,we present a novel framework...Accurate positioning is one of the essential requirements for numerous applications of remote sensing data,especially in the event of a noisy or unreliable satellite signal.Toward this end,we present a novel framework for aircraft geo-localization in a large range that only requires a downward-facing monocular camera,an altimeter,a compass,and an open-source Vector Map(VMAP).The algorithm combines the matching and particle filter methods.Shape vector and correlation between two building contour vectors are defined,and a coarse-to-fine building vector matching(CFBVM)method is proposed in the matching stage,for which the original matching results are described by the Gaussian mixture model(GMM).Subsequently,an improved resampling strategy is designed to reduce computing expenses with a huge number of initial particles,and a credibility indicator is designed to avoid location mistakes in the particle filter stage.An experimental evaluation of the approach based on flight data is provided.On a flight at a height of 0.2 km over a flight distance of 2 km,the aircraft is geo-localized in a reference map of 11,025 km~2using 0.09 km~2aerial images without any prior information.The absolute localization error is less than 10 m.展开更多
The paper proposes a biomass cross-upgrading process that combines hydrothermal carbonization and pyrolysis to produce high-quality blast furnace injection fuel.The results showed that after upgrading,the volatile con...The paper proposes a biomass cross-upgrading process that combines hydrothermal carbonization and pyrolysis to produce high-quality blast furnace injection fuel.The results showed that after upgrading,the volatile content of biochar ranged from 16.19%to 45.35%,and the alkali metal content,ash content,and specific surface area were significantly reduced.The optimal route for biochar pro-duction is hydrothermal carbonization-pyrolysis(P-HC),resulting in biochar with a higher calorific value,C=C structure,and increased graphitization degree.The apparent activation energy(E)of the sample ranges from 199.1 to 324.8 kJ/mol,with P-HC having an E of 277.8 kJ/mol,lower than that of raw biomass,primary biochar,and anthracite.This makes P-HC more suitable for blast furnace injection fuel.Additionally,the paper proposes a path for P-HC injection in blast furnaces and calculates potential environmental benefits.P-HC of-fers the highest potential for carbon emission reduction,capable of reducing emissions by 96.04 kg/t when replacing 40wt%coal injec-tion.展开更多
Blast furnace(BF)burden surface contains the most abundant,intuitive and credible smelting information and acquiring high-definition and high-brightness optical images of which is essential to realize precise material...Blast furnace(BF)burden surface contains the most abundant,intuitive and credible smelting information and acquiring high-definition and high-brightness optical images of which is essential to realize precise material charging control,optimize gas flow distribution and improve ironmaking efficiency.It has been challengeable to obtain high-quality optical burden surface images under high-temperature,high-dust,and extremelydim(less than 0.001 Lux)environment.Based on a novel endoscopic sensing detection idea,a reverse telephoto structure starlight imaging system with large field of view and large aperture is designed.Combined with a water-air dual cooling intelligent self-maintenance protection device and the imaging system,a starlight high-temperature industrial endoscope is developed to obtain clear optical burden surface images stably under the harsh environment.Based on an endoscope imaging area model,a material flow trajectory model and a gas-dust coupling distribution model,an optimal installation position and posture configuration method for the endoscope is proposed,which maximizes the effective imaging area and ensures large-area,safe and stable imaging of the device in a confined space.Industrial experiments and applications indicate that the proposed method obtains clear and reliable large-area optical burden surface images and reveals new BF conditions,providing key data support for green iron smelting.展开更多
The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the intera...The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the interaction among decision variables is intricate,leading to large group sizes and suboptimal optimization effects;hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables(MOEAWOD)is proposed in this paper.Initially,the decision variables are perturbed and categorized into convergence and diversity variables;subsequently,the convergence variables are subdivided into groups based on the interactions among different decision variables.If the size of a group surpasses the set threshold,that group undergoes a process of weighting and overlapping grouping.Specifically,the interaction strength is evaluated based on the interaction frequency and number of objectives among various decision variables.The decision variable with the highest interaction in the group is identified and disregarded,and the remaining variables are then reclassified into subgroups.Finally,the decision variable with the strongest interaction is added to each subgroup.MOEAWOD minimizes the interactivity between different groups and maximizes the interactivity of decision variables within groups,which contributed to the optimized direction of convergence and diversity exploration with different groups.MOEAWOD was subjected to testing on 18 benchmark large-scale optimization problems,and the experimental results demonstrate the effectiveness of our methods.Compared with the other algorithms,our method is still at an advantage.展开更多
With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that consid...With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.展开更多
Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for rese...Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for researchers'visual perceptions of the evolution and interaction of events in the space environment.Methods A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time,and the corresponding relationships between data location features and other attribute features were established.A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data.The visualization process is optimized for rendering by merging materials,reducing the number of patches,and performing other operations.Results The results of sampling,feature extraction,and uniform visualization of the detection data of complex types,long duration spans,and uneven spatial distributions were obtained.The real-time visualization of large-scale spatial structures using augmented reality devices,particularly low-performance devices,was also investigated.Conclusions The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space,express the structure and changes in the spatial environment using augmented reality,and assist in intuitively discovering spatial environmental events and evolutionary rules.展开更多
The deformation and fracture evolution mechanisms of the strata overlying mines mined using sublevel caving were studied via numerical simulations.Moreover,an expression for the normal force acting on the side face of...The deformation and fracture evolution mechanisms of the strata overlying mines mined using sublevel caving were studied via numerical simulations.Moreover,an expression for the normal force acting on the side face of a steeply dipping superimposed cantilever beam in the surrounding rock was deduced based on limit equilibrium theory.The results show the following:(1)surface displacement above metal mines with steeply dipping discontinuities shows significant step characteristics,and(2)the behavior of the strata as they fail exhibits superimposition characteristics.Generally,failure first occurs in certain superimposed strata slightly far from the goaf.Subsequently,with the constant downward excavation of the orebody,the superimposed strata become damaged both upwards away from and downwards toward the goaf.This process continues until the deep part of the steeply dipping superimposed strata forms a large-scale deep fracture plane that connects with the goaf.The deep fracture plane generally makes an angle of 12°-20°with the normal to the steeply dipping discontinuities.The effect of the constant outward transfer of strata movement due to the constant outward failure of the superimposed strata in the metal mines with steeply dipping discontinuities causes the scope of the strata movement in these mines to be larger than expected.The strata in the metal mines with steeply dipping discontinuities mainly show flexural toppling failure.However,the steeply dipping structural strata near the goaf mainly exhibit shear slipping failure,in which case the mechanical model used to describe them can be simplified by treating them as steeply dipping superimposed cantilever beams.By taking the steeply dipping superimposed cantilever beam that first experiences failure as the key stratum,the failure scope of the strata(and criteria for the stability of metal mines with steeply dipping discontinuities mined using sublevel caving)can be obtained via iterative computations from the key stratum,moving downward toward and upwards away from the goaf.展开更多
In order to realize the OY Smelting Furnace disposal of solid waste,municipal waste,form a model of steel enterprises and urban integration,through the production practice of smelting furnace,analyzes the mechanism of...In order to realize the OY Smelting Furnace disposal of solid waste,municipal waste,form a model of steel enterprises and urban integration,through the production practice of smelting furnace,analyzes the mechanism of solid waste disposal,and proposed the disposal of solid waste desulfurization agent and disposal method:According to the theory to guide the actual production process,the test ton of iron with 10-15kg of desulfurizer in the production process does not affect the quality of molten iron and slag quality.展开更多
The financial aspects of large-scale engineering construction projects profoundly influence their success.Strengthening cost control and establishing a scientific financial evaluation system can enhance the project’s...The financial aspects of large-scale engineering construction projects profoundly influence their success.Strengthening cost control and establishing a scientific financial evaluation system can enhance the project’s economic benefits,minimize unnecessary costs,and provide decision-makers with a robust financial foundation.Additionally,implementing an effective cash flow control mechanism and conducting a comprehensive assessment of potential project risks can ensure financial stability and mitigate the risk of fund shortages.Developing a practical and feasible fundraising plan,along with stringent fund management practices,can prevent fund wastage and optimize fund utilization efficiency.These measures not only facilitate smooth project progression and improve project management efficiency but also enhance the project’s economic and social outcomes.展开更多
Estimating the residual heat of blast furnace slag flushing in China,classifying and introducing the current proposed methods of slag flushing waste heat utilization,and listing existing cases.In order to better save ...Estimating the residual heat of blast furnace slag flushing in China,classifying and introducing the current proposed methods of slag flushing waste heat utilization,and listing existing cases.In order to better save energy and water in the slag flushing process of blast furnaces,an ideal comprehensive cascade utilization system scheme for annual recovery of waste heat is proposed.Based on the measured waste heat data of a steel plant,design calculations are carried out to further analyze the economic feasibility of the new scheme and provide reference for its promotion and application.展开更多
In ladle furnace, the prediction of the liquid steel temperature is always a hot topic for the researchers. The most of the existing temperature prediction models use small sample set. Today, the precision of them can...In ladle furnace, the prediction of the liquid steel temperature is always a hot topic for the researchers. The most of the existing temperature prediction models use small sample set. Today, the precision of them can not satisfy practical production. Fortunately, the large sample set is accumulated from the practical production process. However, a large sample set makes it difficult to build a liquid steel temperature model. To deal with the issue, the random forest method is preferred in this paper, which is a powerful regression method with low complexity and can be designed very quickly. It is with the parallel ensemble structure,uses sample subsets,and employs a simple learning algorithm of sub-models. Then, the random forest method is applied to establish a temperature model by using the data sampled from the production process. The experiments show that the random forest temperature model is more precise than other temperature models.展开更多
Considering some characteristics of large-scale standing quench furnace, such as great heat inertia, evident time lag, strong coupling influence, hard to establish exact mathematical models of plant and etc, an artifi...Considering some characteristics of large-scale standing quench furnace, such as great heat inertia, evident time lag, strong coupling influence, hard to establish exact mathematical models of plant and etc, an artificial intelligent fuzzy control algorithm is put forward in this paper. Through adjusting the on-off ratio of electric heating elements, the temperature in furnace is controlled accurately. This paper describes structure and qualities of the large-scale standing quench furnace briefly, introduces constitution of control system, and expounds principle and implementation of intelligent control algorithm. The applied results prove that the intelligent control system can completely satisfy the technological requirements. Namely, it can realize fast increasing temperature with a little overshoot, exact holding temperature, and well-distributed temperature in quench furnace. It has raised the output and quality of aluminum material, and brought the outstanding economic and social benefits.展开更多
The compositions, structures and properties of envi- ronmental-friendly ramming materials for mud package and taphole of large-scaled blast furnaces were studied. The results show that the formation of silica fibers m...The compositions, structures and properties of envi- ronmental-friendly ramming materials for mud package and taphole of large-scaled blast furnaces were studied. The results show that the formation of silica fibers makes structure of ramming materials dense. During the process of extruding mud and ramming materials, SiC is partly oxidized ; CaO , F% 03 and carbon penetrate towards the outer wall. The improvement of ramming materials can inhibit the penetration of molten slag, iron and carbon. The bulk density of environmental-friendly ramming ma- terials dried at 200 ℃ is 2.90 g · cm-3, the cold com- pressive strength of this kind of ramming materials dried at 200 ℃ is about 17. 0 MPa and fired at I 450 ℃ is about 39. 2 MPa.展开更多
The technical .wtors of castables innovation of matin iron trough in blust furnaces of WISCO in recent ten years were analyed, and corrosion process of dense corundum, sub-white corundum and brown corundum aggregates ...The technical .wtors of castables innovation of matin iron trough in blust furnaces of WISCO in recent ten years were analyed, and corrosion process of dense corundum, sub-white corundum and brown corundum aggregates in the castables for the main iron trough was researched. It is regarded tha.t there is no inevitable relation between castables properties and service life, and it must be considered that whether the normal technical in- dex in. the stan&trd can be used as judgment basis. Based on the improvement of matrix, the service hfe (once throughput of hot metal ) of castables used in main iron trough increases from 90 000 tons to 140 000 - 180 000 tons ; the properties of different raw materials are Jidly applied, and structure improvement of iron trough and progress of material technique are very important reasons.展开更多
基金financially supported by the General Program of the National Natural Science Foundation of China (No. 52274326)the Fundamental Research Funds for the Central Universities (No. N2425031)+3 种基金Seventh Batch of Ten Thousand Talents Plan (No. ZX20220553)China Baowu Low Carbon Metallurgy Innovation Foundation (No. BWLCF202109)The key technology research and development and application of digital transformation throughout the iron and steel production process (No. 2023JH2/101800058)Liaoning Province Science and Technology Plan Joint Program (Key Research and Development Program Project)
文摘The prediction and control of furnace heat indicators are of great importance for improving the heat levels and conditions of the complex and difficult-to-operate hour-class delay blast furnace(BF)system.In this work,a prediction and feedback model of furnace heat indicators based on the fusion of data-driven and BF ironmaking processes was proposed.The data on raw and fuel materials,process op-eration,smelting state,and slag and iron discharge during the whole BF process comprised 171 variables with 9223 groups of data and were comprehensively analyzed.A novel method for the delay analysis of furnace heat indicators was established.The extracted delay variables were found to play an important role in modeling.The method that combined the genetic algorithm and stacking efficiently im-proved performance compared with the traditional machine learning algorithm in improving the hit ratio of the furnace heat prediction model.The hit ratio for predicting the temperature of hot metal in the error range of±10℃ was 92.4%,and that for the chemical heat of hot metal in the error range of±0.1wt%was 93.3%.On the basis of the furnace heat prediction model and expert experience,a feedback model of furnace heat operation was established to obtain quantitative operation suggestions for stabilizing BF heat levels.These sugges-tions were highly accepted by BF operators.Finally,the comprehensive and dynamic model proposed in this work was successfully ap-plied in a practical BF system.It improved the BF temperature level remarkably,increasing the furnace temperature stability rate from 54.9%to 84.9%.This improvement achieved considerable economic benefits.
基金supported by the Scientific Research Project of Xiang Jiang Lab(22XJ02003)the University Fundamental Research Fund(23-ZZCX-JDZ-28)+5 种基金the National Science Fund for Outstanding Young Scholars(62122093)the National Natural Science Foundation of China(72071205)the Hunan Graduate Research Innovation Project(ZC23112101-10)the Hunan Natural Science Foundation Regional Joint Project(2023JJ50490)the Science and Technology Project for Young and Middle-aged Talents of Hunan(2023TJ-Z03)the Science and Technology Innovation Program of Humnan Province(2023RC1002)。
文摘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.
基金financially supported by the Young Elite Scientist Sponsorship Program by CAST(No.YESS20210090)the National Natural Science Foundation of China(No.51974019),Beijing Natural Science Foundation(J210017)China Baowu Low Carbon Metallurgy Innovation Foundation(Nos.BWLCF202119 and BWLCF 202117)。
文摘Hydrogen-enriched blast furnace ironmaking has become an essential route to reduce CO_(2)emissions in the ironmaking process.However,hydrogen-enriched reduction produces large amounts of H_(2)O,which places new demands on coke quality in a blast furnace.In a hydrogen-rich blast furnace,the presence of H_(2)O promotes the solution loss reaction.This result improves the reactivity of coke,which is 20%-30%higher in a pure H_(2)O atmosphere than in a pure CO_(2)atmosphere.The activation energy range is 110-300 kJ/mol between coke and CO_(2)and 80-170 kJ/mol between coke and H_(2)O.CO_(2)and H_(2)O are shown to have different effects on coke degradation mechanisms.This review provides a comprehensive overview of the effect of H_(2)O on the structure and properties of coke.By exploring the interactions between H_(2)O and coke,several unresolved issues in the field requiring further research were identified.This review aims to provide valuable insights into coke behavior in hydrogen-rich environments and promote the further development of hydrogen-rich blast furnace ironmaking processes.
基金Funded by the National Natural Science Foundation of China Youth Fund(No.52204419)the Liaoning Provincial Natural Science Foundation(No.2022-BS-076)the Guangxi Science and Technology Major Project(No.2021AA12013)。
文摘To realize the resource utilization of the valuable metals in the titanium-containing blast furnace slag,the process route of “hydrochloric acid leaching-electrolysis-carbonization and carbon dioxide capture-preparation of calcium carbonate” was proposed.In this study,the influences of process conditions on the leaching rates of calcium,magnesium,aluminum,and iron and the phases of the leaching residue were investigated for the leaching process.The experimental results show that the HCl solution could selectively leach the elements from the titanium-containing blast furnace slag.The better leaching conditions are the HCl solution concentration of 4 mol/L,the leaching time of 30 min,the ratio of liquid volume to solid gas of 10 mL/g,and the stirring paddle speed of 300 r/min.Under the conditions,the leaching rates of calcium,magnesium,aluminum,and iron can reach 85.87%,73.41%,81.35%,and 59.08%,and the leaching rate of titanium is 10.71%.The iron and the aluminum are removed from the leachate to obtain iron-aluminum water purification agents,and the magnesium is removed from the leachate to obtain magnesium hydroxide.The leaching residue phase is dominated by perovskite,followed by magnesium silicate and tricalcium aluminate,and the titaniumrich material could be obtained from the leaching residue by desiliconization.
基金the Applied Basic Research Project of Yunnan Province,China(No.202301 AT070411).
文摘The variation characteristics of bubble morphology and the thermal-physical properties of bubble boundary in the top-blown smelting furnace were explored by means of the computational fluid dynamics method.The essential aspects of the fluid phase(e.g.,splashing volume,dead zone of copper slag,and gas penetration depth)were explored together with the effect of sinusoidal pulsating gas intake on the momentum-transfer performance between phases.The results illustrated that two relatively larger vortices and two smaller vortices appear in the bubble waist and below the lance,respectively.The expansion of larger ones as well as the shrinking of smaller ones combine to cause the contraction of the bubble waist.Compared to the results of the case with a fixed gas injection velocity(V_(g)=58 m/s),the splashing volume and dead zone volume of the slag under the V_(g)=58+10sin(2πt)condition are reduced by 24.9%and 23.5%,respectively,where t represents the instant time.Gas penetration depth and slag motion velocity of the latter are 1.03 and 1.31 times high-er than those of the former,respectively.
文摘Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.
文摘Accurate positioning is one of the essential requirements for numerous applications of remote sensing data,especially in the event of a noisy or unreliable satellite signal.Toward this end,we present a novel framework for aircraft geo-localization in a large range that only requires a downward-facing monocular camera,an altimeter,a compass,and an open-source Vector Map(VMAP).The algorithm combines the matching and particle filter methods.Shape vector and correlation between two building contour vectors are defined,and a coarse-to-fine building vector matching(CFBVM)method is proposed in the matching stage,for which the original matching results are described by the Gaussian mixture model(GMM).Subsequently,an improved resampling strategy is designed to reduce computing expenses with a huge number of initial particles,and a credibility indicator is designed to avoid location mistakes in the particle filter stage.An experimental evaluation of the approach based on flight data is provided.On a flight at a height of 0.2 km over a flight distance of 2 km,the aircraft is geo-localized in a reference map of 11,025 km~2using 0.09 km~2aerial images without any prior information.The absolute localization error is less than 10 m.
基金the National Key R&D Program of China(No.2022YFE0208100)the National Natural Science Foundation of China(No.5274316)+1 种基金the Key Research and Development Plan of Anhui Province,China(No.202210700037)the Major Science and Technology Project of Xinjiang Uygur Autonomous Region,China(No.2022A01003).
文摘The paper proposes a biomass cross-upgrading process that combines hydrothermal carbonization and pyrolysis to produce high-quality blast furnace injection fuel.The results showed that after upgrading,the volatile content of biochar ranged from 16.19%to 45.35%,and the alkali metal content,ash content,and specific surface area were significantly reduced.The optimal route for biochar pro-duction is hydrothermal carbonization-pyrolysis(P-HC),resulting in biochar with a higher calorific value,C=C structure,and increased graphitization degree.The apparent activation energy(E)of the sample ranges from 199.1 to 324.8 kJ/mol,with P-HC having an E of 277.8 kJ/mol,lower than that of raw biomass,primary biochar,and anthracite.This makes P-HC more suitable for blast furnace injection fuel.Additionally,the paper proposes a path for P-HC injection in blast furnaces and calculates potential environmental benefits.P-HC of-fers the highest potential for carbon emission reduction,capable of reducing emissions by 96.04 kg/t when replacing 40wt%coal injec-tion.
基金the National Natural Science Foundation of China(62273359)the General Project of Hunan Natural Science Foundation of China(2022JJ30748)the National Major Scientific Research Equipment of China(61927803)。
文摘Blast furnace(BF)burden surface contains the most abundant,intuitive and credible smelting information and acquiring high-definition and high-brightness optical images of which is essential to realize precise material charging control,optimize gas flow distribution and improve ironmaking efficiency.It has been challengeable to obtain high-quality optical burden surface images under high-temperature,high-dust,and extremelydim(less than 0.001 Lux)environment.Based on a novel endoscopic sensing detection idea,a reverse telephoto structure starlight imaging system with large field of view and large aperture is designed.Combined with a water-air dual cooling intelligent self-maintenance protection device and the imaging system,a starlight high-temperature industrial endoscope is developed to obtain clear optical burden surface images stably under the harsh environment.Based on an endoscope imaging area model,a material flow trajectory model and a gas-dust coupling distribution model,an optimal installation position and posture configuration method for the endoscope is proposed,which maximizes the effective imaging area and ensures large-area,safe and stable imaging of the device in a confined space.Industrial experiments and applications indicate that the proposed method obtains clear and reliable large-area optical burden surface images and reveals new BF conditions,providing key data support for green iron smelting.
基金supported in part by the Central Government Guides Local Science and TechnologyDevelopment Funds(Grant No.YDZJSX2021A038)in part by theNational Natural Science Foundation of China under(Grant No.61806138)in part by the China University Industry-University-Research Collaborative Innovation Fund(Future Network Innovation Research and Application Project)(Grant 2021FNA04014).
文摘The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the interaction among decision variables is intricate,leading to large group sizes and suboptimal optimization effects;hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables(MOEAWOD)is proposed in this paper.Initially,the decision variables are perturbed and categorized into convergence and diversity variables;subsequently,the convergence variables are subdivided into groups based on the interactions among different decision variables.If the size of a group surpasses the set threshold,that group undergoes a process of weighting and overlapping grouping.Specifically,the interaction strength is evaluated based on the interaction frequency and number of objectives among various decision variables.The decision variable with the highest interaction in the group is identified and disregarded,and the remaining variables are then reclassified into subgroups.Finally,the decision variable with the strongest interaction is added to each subgroup.MOEAWOD minimizes the interactivity between different groups and maximizes the interactivity of decision variables within groups,which contributed to the optimized direction of convergence and diversity exploration with different groups.MOEAWOD was subjected to testing on 18 benchmark large-scale optimization problems,and the experimental results demonstrate the effectiveness of our methods.Compared with the other algorithms,our method is still at an advantage.
基金The work was supported by Humanities and Social Sciences Fund of the Ministry of Education(No.22YJA630119)the National Natural Science Foundation of China(No.71971051)Natural Science Foundation of Hebei Province(No.G2021501004).
文摘With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.
文摘Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for researchers'visual perceptions of the evolution and interaction of events in the space environment.Methods A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time,and the corresponding relationships between data location features and other attribute features were established.A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data.The visualization process is optimized for rendering by merging materials,reducing the number of patches,and performing other operations.Results The results of sampling,feature extraction,and uniform visualization of the detection data of complex types,long duration spans,and uneven spatial distributions were obtained.The real-time visualization of large-scale spatial structures using augmented reality devices,particularly low-performance devices,was also investigated.Conclusions The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space,express the structure and changes in the spatial environment using augmented reality,and assist in intuitively discovering spatial environmental events and evolutionary rules.
基金Financial support for this work was provided by the Youth Fund Program of the National Natural Science Foundation of China(No.42002292)the General Program of the National Natural Science Foundation of China(No.42377175)the General Program of the Hubei Provincial Natural Science Foundation,China(No.2023AFB631).We are very grateful for the foundations’continued support and to our colleagues for their valuable help with this research.
文摘The deformation and fracture evolution mechanisms of the strata overlying mines mined using sublevel caving were studied via numerical simulations.Moreover,an expression for the normal force acting on the side face of a steeply dipping superimposed cantilever beam in the surrounding rock was deduced based on limit equilibrium theory.The results show the following:(1)surface displacement above metal mines with steeply dipping discontinuities shows significant step characteristics,and(2)the behavior of the strata as they fail exhibits superimposition characteristics.Generally,failure first occurs in certain superimposed strata slightly far from the goaf.Subsequently,with the constant downward excavation of the orebody,the superimposed strata become damaged both upwards away from and downwards toward the goaf.This process continues until the deep part of the steeply dipping superimposed strata forms a large-scale deep fracture plane that connects with the goaf.The deep fracture plane generally makes an angle of 12°-20°with the normal to the steeply dipping discontinuities.The effect of the constant outward transfer of strata movement due to the constant outward failure of the superimposed strata in the metal mines with steeply dipping discontinuities causes the scope of the strata movement in these mines to be larger than expected.The strata in the metal mines with steeply dipping discontinuities mainly show flexural toppling failure.However,the steeply dipping structural strata near the goaf mainly exhibit shear slipping failure,in which case the mechanical model used to describe them can be simplified by treating them as steeply dipping superimposed cantilever beams.By taking the steeply dipping superimposed cantilever beam that first experiences failure as the key stratum,the failure scope of the strata(and criteria for the stability of metal mines with steeply dipping discontinuities mined using sublevel caving)can be obtained via iterative computations from the key stratum,moving downward toward and upwards away from the goaf.
文摘In order to realize the OY Smelting Furnace disposal of solid waste,municipal waste,form a model of steel enterprises and urban integration,through the production practice of smelting furnace,analyzes the mechanism of solid waste disposal,and proposed the disposal of solid waste desulfurization agent and disposal method:According to the theory to guide the actual production process,the test ton of iron with 10-15kg of desulfurizer in the production process does not affect the quality of molten iron and slag quality.
文摘The financial aspects of large-scale engineering construction projects profoundly influence their success.Strengthening cost control and establishing a scientific financial evaluation system can enhance the project’s economic benefits,minimize unnecessary costs,and provide decision-makers with a robust financial foundation.Additionally,implementing an effective cash flow control mechanism and conducting a comprehensive assessment of potential project risks can ensure financial stability and mitigate the risk of fund shortages.Developing a practical and feasible fundraising plan,along with stringent fund management practices,can prevent fund wastage and optimize fund utilization efficiency.These measures not only facilitate smooth project progression and improve project management efficiency but also enhance the project’s economic and social outcomes.
文摘Estimating the residual heat of blast furnace slag flushing in China,classifying and introducing the current proposed methods of slag flushing waste heat utilization,and listing existing cases.In order to better save energy and water in the slag flushing process of blast furnaces,an ideal comprehensive cascade utilization system scheme for annual recovery of waste heat is proposed.Based on the measured waste heat data of a steel plant,design calculations are carried out to further analyze the economic feasibility of the new scheme and provide reference for its promotion and application.
基金supported by the National Natural Science Foundation of China(61702070)
文摘In ladle furnace, the prediction of the liquid steel temperature is always a hot topic for the researchers. The most of the existing temperature prediction models use small sample set. Today, the precision of them can not satisfy practical production. Fortunately, the large sample set is accumulated from the practical production process. However, a large sample set makes it difficult to build a liquid steel temperature model. To deal with the issue, the random forest method is preferred in this paper, which is a powerful regression method with low complexity and can be designed very quickly. It is with the parallel ensemble structure,uses sample subsets,and employs a simple learning algorithm of sub-models. Then, the random forest method is applied to establish a temperature model by using the data sampled from the production process. The experiments show that the random forest temperature model is more precise than other temperature models.
基金Supported by The National Natural Science Foundation of China (No. 59835170).
文摘Considering some characteristics of large-scale standing quench furnace, such as great heat inertia, evident time lag, strong coupling influence, hard to establish exact mathematical models of plant and etc, an artificial intelligent fuzzy control algorithm is put forward in this paper. Through adjusting the on-off ratio of electric heating elements, the temperature in furnace is controlled accurately. This paper describes structure and qualities of the large-scale standing quench furnace briefly, introduces constitution of control system, and expounds principle and implementation of intelligent control algorithm. The applied results prove that the intelligent control system can completely satisfy the technological requirements. Namely, it can realize fast increasing temperature with a little overshoot, exact holding temperature, and well-distributed temperature in quench furnace. It has raised the output and quality of aluminum material, and brought the outstanding economic and social benefits.
文摘The compositions, structures and properties of envi- ronmental-friendly ramming materials for mud package and taphole of large-scaled blast furnaces were studied. The results show that the formation of silica fibers makes structure of ramming materials dense. During the process of extruding mud and ramming materials, SiC is partly oxidized ; CaO , F% 03 and carbon penetrate towards the outer wall. The improvement of ramming materials can inhibit the penetration of molten slag, iron and carbon. The bulk density of environmental-friendly ramming ma- terials dried at 200 ℃ is 2.90 g · cm-3, the cold com- pressive strength of this kind of ramming materials dried at 200 ℃ is about 17. 0 MPa and fired at I 450 ℃ is about 39. 2 MPa.
文摘The technical .wtors of castables innovation of matin iron trough in blust furnaces of WISCO in recent ten years were analyed, and corrosion process of dense corundum, sub-white corundum and brown corundum aggregates in the castables for the main iron trough was researched. It is regarded tha.t there is no inevitable relation between castables properties and service life, and it must be considered that whether the normal technical in- dex in. the stan&trd can be used as judgment basis. Based on the improvement of matrix, the service hfe (once throughput of hot metal ) of castables used in main iron trough increases from 90 000 tons to 140 000 - 180 000 tons ; the properties of different raw materials are Jidly applied, and structure improvement of iron trough and progress of material technique are very important reasons.