The basic oxygen furnace slag generated during steelmaking can be reused as aggregates in civil engineering because of its chemical composition and technological properties. However, the utilization of steel slag in practical applications is quite low due to its low volume stability. In this work, highly stable slag is obtained by the environmental-friendly self-disintegration high pressure (SDHP) process. In this method, the molten slag is initially crushed to form numerous small bulks. Subsequently, the slag bulks are treated by the self-disintegration process at a high pressure to obtain the highly stable steel slag. Thermodynamic evaluation and experimental investigation reveal that high pressure of steam promotes the hydration reaction. At a pressure of 0.2 MPa, the free lime (f-CaO) content and immersion expansion rate of the steel slag treated by this method are reduced to 1.5% and 0.9%, respectively. Both of these values satisfy the requirements specified in the national standards (GB/T 25029-2010 and GB/T 20491-2006). Moreover, the treatment time is reduced to 1.5 h, which is far lower than the treatment times required for traditional methods.
{"title":"Achieving stable steelmaking basic oxygen furnace slag through treatment by self-disintegration high pressure process","authors":"B. Peng, Wu Yuedong, C. Yue, Yu-Xiang Li","doi":"10.1051/METAL/2021020","DOIUrl":"https://doi.org/10.1051/METAL/2021020","url":null,"abstract":"The basic oxygen furnace slag generated during steelmaking can be reused as aggregates in civil engineering because of its chemical composition and technological properties. However, the utilization of steel slag in practical applications is quite low due to its low volume stability. In this work, highly stable slag is obtained by the environmental-friendly self-disintegration high pressure (SDHP) process. In this method, the molten slag is initially crushed to form numerous small bulks. Subsequently, the slag bulks are treated by the self-disintegration process at a high pressure to obtain the highly stable steel slag. Thermodynamic evaluation and experimental investigation reveal that high pressure of steam promotes the hydration reaction. At a pressure of 0.2 MPa, the free lime (f-CaO) content and immersion expansion rate of the steel slag treated by this method are reduced to 1.5% and 0.9%, respectively. Both of these values satisfy the requirements specified in the national standards (GB/T 25029-2010 and GB/T 20491-2006). Moreover, the treatment time is reduced to 1.5 h, which is far lower than the treatment times required for traditional methods.","PeriodicalId":18527,"journal":{"name":"Metallurgical Research & Technology","volume":"6 1","pages":"207"},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88325180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gui-peng Lu, Li-zhe Zhao, Wei Liu, Yu-meng Sun, W. Gong
The dissimilar connection between 6082 aluminum alloy and 304 stainless steel was realized by continuous drive friction welding. Microstructures of the joint were studied by optical microscopy (OM), scanning electron microscopy (SEM) and X-ray diffractometry (XRD). In the process of continuous drive welding, the intermetallic compounds (IMCs) Fe2Al5 phase was observed at the interface, the formation mechanism of IMC was discussed, and the corresponding analysis model was established. When the upset pressure in the range of 6–10 MPa, the element diffusion distance increases with the increase of upset pressure. The tensile strength of the joint increased firstly and then decreased with the increase of upset pressure. The joint’s maximum tensile strength can reach 234 MPa, and tensile fracture of the joint exhibited brittle-tough mixed fracture characteristics.
{"title":"Effect of the upset pressure on Microstructure and Properties of Friction Welded Joints of 6082 aluminum alloy/304 stainless steel","authors":"Gui-peng Lu, Li-zhe Zhao, Wei Liu, Yu-meng Sun, W. Gong","doi":"10.1051/metal/2021067","DOIUrl":"https://doi.org/10.1051/metal/2021067","url":null,"abstract":"The dissimilar connection between 6082 aluminum alloy and 304 stainless steel was realized by continuous drive friction welding. Microstructures of the joint were studied by optical microscopy (OM), scanning electron microscopy (SEM) and X-ray diffractometry (XRD). In the process of continuous drive welding, the intermetallic compounds (IMCs) Fe2Al5 phase was observed at the interface, the formation mechanism of IMC was discussed, and the corresponding analysis model was established. When the upset pressure in the range of 6–10 MPa, the element diffusion distance increases with the increase of upset pressure. The tensile strength of the joint increased firstly and then decreased with the increase of upset pressure. The joint’s maximum tensile strength can reach 234 MPa, and tensile fracture of the joint exhibited brittle-tough mixed fracture characteristics.","PeriodicalId":18527,"journal":{"name":"Metallurgical Research & Technology","volume":"15 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73237843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Heng Zhou, Yifan Hu, Bingjie Wen, Shengli Wu, M. Kou, Yinsheng Luo
In COREX operation, the Si and S contents in hot metal are relatively high and easy-fluctuating, which is one of the problems affecting the practical operation. Accurate predictions of Si and S contents can provide theoretical references for stabilizing the fluctuations and decreasing the contents of Si and S in hot metal. Therefore, the present work established the prediction model of Si and S contents in hot metal in COREX based on BP neural network. The results show that the root-mean-square errors between the predicted value and actual value for Si and S are 0.098 and 0.0037, respectively. They are 0.070 and 0.0040 when the time-sequence lapse method is adopted, which turns out to be better. Therefore, the model is accurate and reliable to predict the Si and S contents in hot metal in COREX.
{"title":"BP neural network prediction for Si and S contents in hot metal of COREX process based on mathematical analysis and Deng’s correlation","authors":"Heng Zhou, Yifan Hu, Bingjie Wen, Shengli Wu, M. Kou, Yinsheng Luo","doi":"10.1051/metal/2021073","DOIUrl":"https://doi.org/10.1051/metal/2021073","url":null,"abstract":"In COREX operation, the Si and S contents in hot metal are relatively high and easy-fluctuating, which is one of the problems affecting the practical operation. Accurate predictions of Si and S contents can provide theoretical references for stabilizing the fluctuations and decreasing the contents of Si and S in hot metal. Therefore, the present work established the prediction model of Si and S contents in hot metal in COREX based on BP neural network. The results show that the root-mean-square errors between the predicted value and actual value for Si and S are 0.098 and 0.0037, respectively. They are 0.070 and 0.0040 when the time-sequence lapse method is adopted, which turns out to be better. Therefore, the model is accurate and reliable to predict the Si and S contents in hot metal in COREX.","PeriodicalId":18527,"journal":{"name":"Metallurgical Research & Technology","volume":"206 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76057715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Blast Furnace (BF) production methodology is one of the most complex process of iron & steel plants as it is dependent on multi-variable process inputs and disturbances to be modelled properly. Due to expensive investment costs, it is critical to operate a BF by reducing operational expenses, increasing the performance of raw material and fuel consumptions to optimize overall furnace efficiency and stability, also to maximize the lifetime. The chemical compositions and temperature of hot metal are important indicators while evaluating the operation, therefore, if the future values of hot metal temperature can be predicted in advance instead of subsequent measuring, then the BF staff can take earlier counteractions on several operational parameters such as coke to ore ratio, distribution matrix, oxygen enrichment rate, blast moisture rate, permeability, flame temperature, cold blast temperature, cold blast flow and pulverized coal injection rate, etc. to control the furnace optimally. In this study, Artificial Neural Networks (ANN) model is proposed combined with NARX (Nonlinear autoregressive exogenous model) time series approach to track and predict furnace hot metal temperature by selecting the most suitable process inputs and past values of hot metal temperatures using the real data which is collected from the BF operated in Turkey during 2 months of operation. Various data mining techniques are applied due to requirements of charge cycling and operating speed of the furnace which secures novelty and effectiveness of this study comparing previous articles. Furthermore, a statistical tool, Autoregressive Integrated Moving Average (ARIMA) model, is also executed for comparison. ANN prediction results of 0.92, 8.59 and 0.41 are found very satisfactory comparing ARIMA (1,1,1) model outputs of 0.73, 97.4 and 9.32 for R2 (Coefficient of determination), RMSE (Root mean squared error) and MAPE (Mean absolute percentage error) respectively. Consequently, an expert suggestion system is proposed using fuzzy if-then rules with 5 × 5 probability matrix design using the last predicted HMT value and the average of the last 5 HMT values to decide furnace’s warming or cooling movements state in mid-term and maintain the operational actions interactively in advance.
{"title":"Performance analysis of hot metal temperature prediction in a blast furnace and expert suggestion system proposal using neural, statistical and fuzzy models","authors":"Erdoğan Bozkurt, I. M. Orak, Yasin Tunçkaya","doi":"10.1051/METAL/2021043","DOIUrl":"https://doi.org/10.1051/METAL/2021043","url":null,"abstract":"Blast Furnace (BF) production methodology is one of the most complex process of iron & steel plants as it is dependent on multi-variable process inputs and disturbances to be modelled properly. Due to expensive investment costs, it is critical to operate a BF by reducing operational expenses, increasing the performance of raw material and fuel consumptions to optimize overall furnace efficiency and stability, also to maximize the lifetime. The chemical compositions and temperature of hot metal are important indicators while evaluating the operation, therefore, if the future values of hot metal temperature can be predicted in advance instead of subsequent measuring, then the BF staff can take earlier counteractions on several operational parameters such as coke to ore ratio, distribution matrix, oxygen enrichment rate, blast moisture rate, permeability, flame temperature, cold blast temperature, cold blast flow and pulverized coal injection rate, etc. to control the furnace optimally. In this study, Artificial Neural Networks (ANN) model is proposed combined with NARX (Nonlinear autoregressive exogenous model) time series approach to track and predict furnace hot metal temperature by selecting the most suitable process inputs and past values of hot metal temperatures using the real data which is collected from the BF operated in Turkey during 2 months of operation. Various data mining techniques are applied due to requirements of charge cycling and operating speed of the furnace which secures novelty and effectiveness of this study comparing previous articles. Furthermore, a statistical tool, Autoregressive Integrated Moving Average (ARIMA) model, is also executed for comparison. ANN prediction results of 0.92, 8.59 and 0.41 are found very satisfactory comparing ARIMA (1,1,1) model outputs of 0.73, 97.4 and 9.32 for R2 (Coefficient of determination), RMSE (Root mean squared error) and MAPE (Mean absolute percentage error) respectively. Consequently, an expert suggestion system is proposed using fuzzy if-then rules with 5 × 5 probability matrix design using the last predicted HMT value and the average of the last 5 HMT values to decide furnace’s warming or cooling movements state in mid-term and maintain the operational actions interactively in advance.","PeriodicalId":18527,"journal":{"name":"Metallurgical Research & Technology","volume":"74 1","pages":"321"},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74309331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The effect of 1,5-diphenylthiocarbazone (dithizone) as an eco-friendly corrosion inhibitor for protection of AA7075 aluminium alloy in chloride containing aggressive environment was studied by means of weight-loss, electrochemical measurements and Raman spectroscopy. The results indicate that the addition of dithizone decreases significantly the corrosion rate of AA7075 alloy, with efficiency proportional to the inhibitor concentration. The polarization curves show that dithizone works as mixed-type inhibitor to slow down the anodic and cathodic reaction kinetic. The morphology revealed by scanning electron microscopy and the Raman spectroscopy analysis clearly shows that the inhibitor contributes in the formation of a stable protective film on the AA7075 alloy due to the adsorption of dithizone molecules on aluminium alloy surface obeying Langmuir adsorption isotherm.
{"title":"Study of the influence of dithizone as an eco-friendly corrosion inhibitor on the corrosion behaviour of AA7075 aluminium alloy in neutral chloride solution","authors":"M. Acila, H. Bensabra, M. Santamaría","doi":"10.1051/METAL/2021002","DOIUrl":"https://doi.org/10.1051/METAL/2021002","url":null,"abstract":"The effect of 1,5-diphenylthiocarbazone (dithizone) as an eco-friendly corrosion inhibitor for protection of AA7075 aluminium alloy in chloride containing aggressive environment was studied by means of weight-loss, electrochemical measurements and Raman spectroscopy. The results indicate that the addition of dithizone decreases significantly the corrosion rate of AA7075 alloy, with efficiency proportional to the inhibitor concentration. The polarization curves show that dithizone works as mixed-type inhibitor to slow down the anodic and cathodic reaction kinetic. The morphology revealed by scanning electron microscopy and the Raman spectroscopy analysis clearly shows that the inhibitor contributes in the formation of a stable protective film on the AA7075 alloy due to the adsorption of dithizone molecules on aluminium alloy surface obeying Langmuir adsorption isotherm.","PeriodicalId":18527,"journal":{"name":"Metallurgical Research & Technology","volume":"151 1","pages":"203"},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74291181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The evolution of the microstructure and texture of CSP thin-gauge non-oriented silicon steel was investigated by OM, XRD and EBSD. Results show: (1) the equiaxed surface grains with 28.13 µm average grains size accounted for 19.14% of through-thickness, while deformed band structure dominated the center layer and the other maintained at a composite structure with the first two. With the cold-rolled reduction rate enhancing to 91.15%, the stratification structure transformed into a complete fibrous structure. Annealing from 925 °C to 975 °C, the average grain size of the annealing plate similarly increased, which begins with 67.3 µm and ends at 80.58 µm. (2) The texture of the hot-rolled sheets mainly located at Cube and Goss texture, while with the cold-rolled process executing, the type and volume of texture change and finally stabilize at α fiber texture ({110}//RD) with the peak at {114}<110> at 91.15% reductions rate. The {411}<148> texture on the α* fiber line throughout maintained the strongest texture at different annealing temperatures. (3) The initial re-crystallization temperature is in the range of 600–620 °C, and the re-crystallization is roughly completed at 700 °C. Part of {411}<148> oriented grains nucleated at {411}<148> sub-grains originated from α fiber deformed structure, and the others nucleate at the grains boundaries of the deformed α fiber grains or in the inner of {111}<110> and {111}<112> grains. When the re-crystallization was accomplished at 750 °C, {411}<148> oriented grains are significantly larger than other oriented grains compared to 680 °C or the less. (4) Best magnetic properties were obtained at 975 °C with the B50 = 1.506 T and P10/400 = 16.19 W/kg.
{"title":"Evolution of microstructure and texture of ultra-thin non-oriented electrical steel manufactured by CSP","authors":"L. Fan, Meili Qin, Xingyuan Zhao, Zheng-hai Zhu, Li-jun Xiao, Jiao-Huang, Feng-Guo","doi":"10.1051/metal/2021079","DOIUrl":"https://doi.org/10.1051/metal/2021079","url":null,"abstract":"The evolution of the microstructure and texture of CSP thin-gauge non-oriented silicon steel was investigated by OM, XRD and EBSD. Results show: (1) the equiaxed surface grains with 28.13 µm average grains size accounted for 19.14% of through-thickness, while deformed band structure dominated the center layer and the other maintained at a composite structure with the first two. With the cold-rolled reduction rate enhancing to 91.15%, the stratification structure transformed into a complete fibrous structure. Annealing from 925 °C to 975 °C, the average grain size of the annealing plate similarly increased, which begins with 67.3 µm and ends at 80.58 µm. (2) The texture of the hot-rolled sheets mainly located at Cube and Goss texture, while with the cold-rolled process executing, the type and volume of texture change and finally stabilize at α fiber texture ({110}//RD) with the peak at {114}<110> at 91.15% reductions rate. The {411}<148> texture on the α* fiber line throughout maintained the strongest texture at different annealing temperatures. (3) The initial re-crystallization temperature is in the range of 600–620 °C, and the re-crystallization is roughly completed at 700 °C. Part of {411}<148> oriented grains nucleated at {411}<148> sub-grains originated from α fiber deformed structure, and the others nucleate at the grains boundaries of the deformed α fiber grains or in the inner of {111}<110> and {111}<112> grains. When the re-crystallization was accomplished at 750 °C, {411}<148> oriented grains are significantly larger than other oriented grains compared to 680 °C or the less. (4) Best magnetic properties were obtained at 975 °C with the B50 = 1.506 T and P10/400 = 16.19 W/kg.","PeriodicalId":18527,"journal":{"name":"Metallurgical Research & Technology","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83165717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper introduces a linear quadratic sliding mode control (LQ-SMC) scheme into a looper control system. First, according to a 1700 mm tandem hot mill, the state-space dynamic model of the looper system was established, and then, the optimal control law of the looper system was obtained based on the established model. Finally, the optimal sliding mode and optimal sliding mode control law of the LQ-SMC scheme were designed such that the sliding motion could satisfy the optimal value of the quadratic performance index. Simulation results show that the proposed control scheme has complete robustness to external disturbances that satisfies certain conditions, and the coupling between the looper angle dynamic and strip tension dynamic is also minimized.
{"title":"Dynamic modelling and linear quadratic sliding mode control of a multivariable looper system in hot strip mills","authors":"Yin Fang-chen, Wu Xiang-Cheng","doi":"10.1051/METAL/2020095","DOIUrl":"https://doi.org/10.1051/METAL/2020095","url":null,"abstract":"This paper introduces a linear quadratic sliding mode control (LQ-SMC) scheme into a looper control system. First, according to a 1700 mm tandem hot mill, the state-space dynamic model of the looper system was established, and then, the optimal control law of the looper system was obtained based on the established model. Finally, the optimal sliding mode and optimal sliding mode control law of the LQ-SMC scheme were designed such that the sliding motion could satisfy the optimal value of the quadratic performance index. Simulation results show that the proposed control scheme has complete robustness to external disturbances that satisfies certain conditions, and the coupling between the looper angle dynamic and strip tension dynamic is also minimized.","PeriodicalId":18527,"journal":{"name":"Metallurgical Research & Technology","volume":"118 1","pages":"215"},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86885953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chengying Cao, Gao-feng Wang, Jie Li, Qianghua Tian, Qi Zhu, Ke-nan Ai, Jianxun Fu
At present, the effective ways to improve the cleanliness of S50C die steel are Ca or Mg-Al treatment processes. In order to explore the effect difference of two kinds of modification process of S50C killed steel, evaluate the industrial application prospect of the two processes, and clarify the modification mechanism. In this paper, the advantages of Mg-Al modification are demonstrated from the aspects of theoretical basis and actual sample modification effect. The thermodynamics and kinetics of inclusion precipitation, composition, morphology, and distribution are analyzed. The results show that: the precipitation temperature of MnS in S50C die steel is 1686 K, the corresponding solid-phase rate is 0.98. In Mg-Al modification, when the Al content is 332 ppm, the Mg content should be controlled below 14.1 ppm. When the Al content is higher than 0.02%, the Ca content should be controlled below 28.7 ppm. Kinetic calculations show that the equilibrium shape size of MnS is in the range of 0.3‑1.4 µm. Both modifications increase the nucleation rate of inclusions and control the shape and size of inclusions by pre-precipitation. Ca treatment is preventing the formation of large inclusions by forming calcium aluminate. Mg can provide more uniform nucleation sites and form smaller inclusions.
{"title":"Comparative analysis of the effect of Ca and Mg-Al modification on the composite inclusions in S50C Die steel","authors":"Chengying Cao, Gao-feng Wang, Jie Li, Qianghua Tian, Qi Zhu, Ke-nan Ai, Jianxun Fu","doi":"10.1051/metal/2021049","DOIUrl":"https://doi.org/10.1051/metal/2021049","url":null,"abstract":"At present, the effective ways to improve the cleanliness of S50C die steel are Ca or Mg-Al treatment processes. In order to explore the effect difference of two kinds of modification process of S50C killed steel, evaluate the industrial application prospect of the two processes, and clarify the modification mechanism. In this paper, the advantages of Mg-Al modification are demonstrated from the aspects of theoretical basis and actual sample modification effect. The thermodynamics and kinetics of inclusion precipitation, composition, morphology, and distribution are analyzed. The results show that: the precipitation temperature of MnS in S50C die steel is 1686 K, the corresponding solid-phase rate is 0.98. In Mg-Al modification, when the Al content is 332 ppm, the Mg content should be controlled below 14.1 ppm. When the Al content is higher than 0.02%, the Ca content should be controlled below 28.7 ppm. Kinetic calculations show that the equilibrium shape size of MnS is in the range of 0.3‑1.4 µm. Both modifications increase the nucleation rate of inclusions and control the shape and size of inclusions by pre-precipitation. Ca treatment is preventing the formation of large inclusions by forming calcium aluminate. Mg can provide more uniform nucleation sites and form smaller inclusions.","PeriodicalId":18527,"journal":{"name":"Metallurgical Research & Technology","volume":"26 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77554332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the presented work, desulfurization process parameters and the lime utilization ratio were correlated by data-driven technique, and a convolutional neural network was applied to predict the lime utilization ratio in the Kambara Reactor (KR) desulfurization process. The results show that compared with the support vector regression model and random forest model, the convolutional neural network model achieves the best performance with correlation coefficient value of 0.9964, mean absolute relative error of 0.01229 and root mean squared error of 0.3392%. The sensitivity analysis was carried out to investigate the influence of process parameters on the lime utilization ratio, which shows that the lime weight and the initial sulfur content have the significant effect on the lime utilization ratio. By analyzing the influence of the lime weight on the lime utilization ratio under the current desulfurization process parameters, it can be concluded that decreasing the lime weight from 3256 kg to 2332 kg can increase the lime utilization ratio by about 5%.
{"title":"A convolutional neural network-based model for predicting lime utilization ratio in the KR desulfurization process","authors":"Size Wu, Jian Yang","doi":"10.1051/metal/2021074","DOIUrl":"https://doi.org/10.1051/metal/2021074","url":null,"abstract":"In the presented work, desulfurization process parameters and the lime utilization ratio were correlated by data-driven technique, and a convolutional neural network was applied to predict the lime utilization ratio in the Kambara Reactor (KR) desulfurization process. The results show that compared with the support vector regression model and random forest model, the convolutional neural network model achieves the best performance with correlation coefficient value of 0.9964, mean absolute relative error of 0.01229 and root mean squared error of 0.3392%. The sensitivity analysis was carried out to investigate the influence of process parameters on the lime utilization ratio, which shows that the lime weight and the initial sulfur content have the significant effect on the lime utilization ratio. By analyzing the influence of the lime weight on the lime utilization ratio under the current desulfurization process parameters, it can be concluded that decreasing the lime weight from 3256 kg to 2332 kg can increase the lime utilization ratio by about 5%.","PeriodicalId":18527,"journal":{"name":"Metallurgical Research & Technology","volume":"58 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76583831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This work describes the mechanical properties and metallurgical characterization of Friction Stir Processing (FSP) on TIG welded dissimilar AA5052-H32 and AA5083-H111 alloys using ER5356 filler wire. A comparison is drawn between unprocessed TIG weld and FS Processed (FSPed) TIG welded specimen with the identical combination. The fabricated welded joints were investigated By Optical Microscope (OM), Scanning Electron Microscope (SEM) Analysis, Tensile Strength Analysis, and Micro-Hardness testing. The results illustrate the improvement in mechanical properties after FSPed of the TIG welded joint resulting in enhanced tensile strength (224.5 MPa) and hardness (104 HV) in contrast to the unprocessed TIG weld joints with (192.5 MPa) and (70 Hv). In addition, during the mechanical characterization, the FSPed TIG welds show fine grain at the Friction Stir (FS) processed zone with fine grain structures which improves the hardness at the FS zone. The mechanical property of FS joint is superior when compared to the unprocessed TIG weld joint.
{"title":"Mechanical properties and metallurgical characterization of FSPed TIG and TIG welded AA5052-H32/AA5083-H111 dissimilar aluminium alloys","authors":"Antony Prabu Dhanaraj, S. Kumarasamy","doi":"10.1051/METAL/2021005","DOIUrl":"https://doi.org/10.1051/METAL/2021005","url":null,"abstract":"This work describes the mechanical properties and metallurgical characterization of Friction Stir Processing (FSP) on TIG welded dissimilar AA5052-H32 and AA5083-H111 alloys using ER5356 filler wire. A comparison is drawn between unprocessed TIG weld and FS Processed (FSPed) TIG welded specimen with the identical combination. The fabricated welded joints were investigated By Optical Microscope (OM), Scanning Electron Microscope (SEM) Analysis, Tensile Strength Analysis, and Micro-Hardness testing. The results illustrate the improvement in mechanical properties after FSPed of the TIG welded joint resulting in enhanced tensile strength (224.5 MPa) and hardness (104 HV) in contrast to the unprocessed TIG weld joints with (192.5 MPa) and (70 Hv). In addition, during the mechanical characterization, the FSPed TIG welds show fine grain at the Friction Stir (FS) processed zone with fine grain structures which improves the hardness at the FS zone. The mechanical property of FS joint is superior when compared to the unprocessed TIG weld joint.","PeriodicalId":18527,"journal":{"name":"Metallurgical Research & Technology","volume":"35 1","pages":"304"},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84544876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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