The Experts below are selected from a list of 2001 Experts worldwide ranked by ideXlab platform
Zhang Meijie - One of the best experts on this subject based on the ideXlab platform.
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In situ synthesis of AlN whiskers in mullite-silicon carbide refractory under simulated coke Dry Quenching conditions
Ceramics International, 2018Co-Authors: Zhang Meijie, Han Cangjuan, Ao Huang, Yu ChangAbstract:Abstract AlN whiskers in mullite-silicon carbide refractories were synthesized under the simulated conditions of service temperature and nitrogen flow in a coke Dry Quenching (CDQ) furnace. Nanoscale Fe powder and Si 3 N 4 -Fe powder were added as catalysts to the raw materials of the mullite-silicon carbide refractory containing metallic Al powder. The correlation between the microstructures and the sample properties were studied; the results showed that the formation and interaction of AlN whiskers in situ in the matrix improved the strength, thermal shock resistance, and toughness of the refractory. Nanoscale Fe powder was more effective as a catalyst for the formation and growth of AlN whiskers. The formation temperature of AlN whiskers in the samples containing nanoscale Fe powder was successfully decreased from 1000 to 850 °C under nitrogen flow.
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Improving Mullite-Silicon Carbide Refractory in Coke Dry Quenching using Aluminum Nitride Whiskers Formed In Situ
Ceramics International, 2017Co-Authors: Zhang Meijie, Han Cangjuan, Ao Huang, Zhijun ShaoAbstract:Abstract The formation conditions and their influence on the properties of mullite-SiC refractory were studied by adding metallic Al powder to the raw materials to form AlN whiskers in a coke Dry Quenching furnace. The results show that the AlN whiskers were formed in situ and interacted to form networks in the matrix when the metallic Al powder was added into the mullite-SiC refractory after heat treatment above 850 °C for 8 h under nitrogen flow. The whiskers grew lengthwise as the firing temperature increased and the cold modulus of rupture, cold crushing strength, and hot modulus of rupture increased. The amount and particle size of the metallic Al powder also affected the properties of the refractory. The optimum amount of Al powder addition was determined to be 6 wt%, which provided the highest strength and excellent toughness after heat treatment at 1000 °C for 8 h under nitrogen. Reducing the particle size of the metallic Al powder could promote formation of the AlN whiskers and improve the strength of the refractory.
Jian-guo Wang - One of the best experts on this subject based on the ideXlab platform.
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Soft sensor development for improving economic efficiency of the coke Dry Quenching process
Journal of Process Control, 2019Co-Authors: Jian-guo Wang, Yuan Yao, Bang-hua Yang, Zhong-tao Xie, Li-lan LiuAbstract:Abstract Energy conservation and emission reduction in steelmaking have received significant attention owing to the high amount of fossil energy consumption and emissions. Many methods have been adopted for saving energy, among which coke Dry Quenching (CDQ) is a cost-effective option. In this work, a CDQ process in a steel plant in China is studied. Here, an economic efficiency index is adopted to handle the trade-off between the steam productivity and the coke burning loss. The operation data analysis indicates that the supplementary air flow rate in the CDQ operation does not follow the variation in the discharge rate of incandescent coke adequately, and this results in an increase in the concentration of combustible gas in the exhaust gas and a decrease in economic efficiency. The correlation analysis results show that it is necessary to introduce several derived variables into the data-driven model of this process because these derived variables are more useful than a few original variables for the prediction purposes. Based on these analyses, a soft sensor is proposed by integrating a nonnegative garrote variable selection algorithm with an autoregressive integrated moving average model, which provides a good solution for the real-time prediction of the economic efficiency of the CDQ process. Using this soft sensor, model-based optimization can be conducted, the performance of which is verified with a virtual implementation on the historical operation data and experiments performed in a real CDQ system. The results indicate that there is considerable room for improving the economic efficiency of this process.
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Stacked autoencoder for operation prediction of coke Dry Quenching process
Control Engineering Practice, 2019Co-Authors: Jian-guo Wang, Yuan Yao, Yu Wang, Bang-hua YangAbstract:Abstract Coke Dry Quenching (CDQ) is widely adopted for waste heat recovery in iron and steel plants. In this work, an economic benefit index was introduced to evaluate the performance of the CDQ system and stacked autoencoder (SAE) based deep neural networks are adopted for CDQ operation prediction. Based on the prediction results, a guidance is provided for online adjustment of the supplementary air flow rate, hence the efficiency and safety of the CDQ system can be improved. The case study on a real plant shows that the proposed method increases the economic efficiency of the CDQ process by 4.39%.
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A soft sensing method for operation optimization of coke Dry Quenching process
2017 36th Chinese Control Conference (CCC), 2017Co-Authors: Jian-guo Wang, Bang-hua Yang, Li-lan Liu, Zhi-duo Cao, Min-rui Fei, Zhi-fu Deng, Yuan YaoAbstract:Based on the actual data analysis, it is found in this paper that the supplementary air flow rate in the CDQ operation didn't follow the variation of the discharge rate of incandescent coke well, which results in the concentration increase of combustible gas in the exhaust gas and the decrease of economic efficiency. The correlation analysis results show that the introduced derived variables are more useful than some plain variables for the purpose of prediction. Next, to handle the contradiction between the steam productivity and the coke burning loss, a new economic efficiency index is introduced by synthesizing the two competing aspects. A kind of soft sensor of economic efficiency is put forward by combining nonnegative garrote (NNG) variable selection algorithm with the autoregressive integrated moving average (ARIMA) model, which gives a good solution to the economic efficiency real-time prediction problem of CDQ system. Then, the implementation of model-based optimization is studied based on the actual operation data. The results show that there exists large room for economic efficiency promotion.
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Deep learning-based soft-sensing method for operation optimization of coke Dry Quenching process
2016 35th Chinese Control Conference (CCC), 2016Co-Authors: Jian-guo Wang, Tiao Shen, Yuan Yao, Tao Chen, Jing-hui Zhao, Shi-wei Ma, Bing Shen, Yi-ping WuAbstract:In the modern industrial process control, the development of distributed control system (DCS) makes the application of data-driven soft-sensing methods available. Deep learning (DL), as a novel training strategy of deep neural networks, has large potential for soft sensor modeling. In comparison with shallow neural network, because DL can make full use of massive process by greedy layer-wise training approach, deep structure of neural network has better representation and generalization ability. Compared with the traditional coke wet Quenching, coke Dry Quenching (CDQ) has the advantage of waste heat recovery, which is advanced, energy saving and environmentally friendly, and is the main coke Quenching method adopted in iron and steel plant. A deep learning-based soft-sensing method for operation optimization of coke Dry Quenching process is put forward in this paper. By defining the economic efficiency, the data with high economic efficiency is used for modeling and optimizing the CDQ operating variable, i.e. supplementary air flow rate (F SA ). The experimental results show that, adopting the adjusted optimal operation, a remarkable raise (1.58%) of economic efficiency can be acquired on average. Thus, the presented deep learning-based soft-sensing method for operation optimization is effective and feasible for improving the waste heat recovery in CDQ system.
Yu Chang - One of the best experts on this subject based on the ideXlab platform.
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In situ synthesis of AlN whiskers in mullite-silicon carbide refractory under simulated coke Dry Quenching conditions
Ceramics International, 2018Co-Authors: Zhang Meijie, Han Cangjuan, Ao Huang, Yu ChangAbstract:Abstract AlN whiskers in mullite-silicon carbide refractories were synthesized under the simulated conditions of service temperature and nitrogen flow in a coke Dry Quenching (CDQ) furnace. Nanoscale Fe powder and Si 3 N 4 -Fe powder were added as catalysts to the raw materials of the mullite-silicon carbide refractory containing metallic Al powder. The correlation between the microstructures and the sample properties were studied; the results showed that the formation and interaction of AlN whiskers in situ in the matrix improved the strength, thermal shock resistance, and toughness of the refractory. Nanoscale Fe powder was more effective as a catalyst for the formation and growth of AlN whiskers. The formation temperature of AlN whiskers in the samples containing nanoscale Fe powder was successfully decreased from 1000 to 850 °C under nitrogen flow.
Han Cangjuan - One of the best experts on this subject based on the ideXlab platform.
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In situ synthesis of AlN whiskers in mullite-silicon carbide refractory under simulated coke Dry Quenching conditions
Ceramics International, 2018Co-Authors: Zhang Meijie, Han Cangjuan, Ao Huang, Yu ChangAbstract:Abstract AlN whiskers in mullite-silicon carbide refractories were synthesized under the simulated conditions of service temperature and nitrogen flow in a coke Dry Quenching (CDQ) furnace. Nanoscale Fe powder and Si 3 N 4 -Fe powder were added as catalysts to the raw materials of the mullite-silicon carbide refractory containing metallic Al powder. The correlation between the microstructures and the sample properties were studied; the results showed that the formation and interaction of AlN whiskers in situ in the matrix improved the strength, thermal shock resistance, and toughness of the refractory. Nanoscale Fe powder was more effective as a catalyst for the formation and growth of AlN whiskers. The formation temperature of AlN whiskers in the samples containing nanoscale Fe powder was successfully decreased from 1000 to 850 °C under nitrogen flow.
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Improving Mullite-Silicon Carbide Refractory in Coke Dry Quenching using Aluminum Nitride Whiskers Formed In Situ
Ceramics International, 2017Co-Authors: Zhang Meijie, Han Cangjuan, Ao Huang, Zhijun ShaoAbstract:Abstract The formation conditions and their influence on the properties of mullite-SiC refractory were studied by adding metallic Al powder to the raw materials to form AlN whiskers in a coke Dry Quenching furnace. The results show that the AlN whiskers were formed in situ and interacted to form networks in the matrix when the metallic Al powder was added into the mullite-SiC refractory after heat treatment above 850 °C for 8 h under nitrogen flow. The whiskers grew lengthwise as the firing temperature increased and the cold modulus of rupture, cold crushing strength, and hot modulus of rupture increased. The amount and particle size of the metallic Al powder also affected the properties of the refractory. The optimum amount of Al powder addition was determined to be 6 wt%, which provided the highest strength and excellent toughness after heat treatment at 1000 °C for 8 h under nitrogen. Reducing the particle size of the metallic Al powder could promote formation of the AlN whiskers and improve the strength of the refractory.
Ao Huang - One of the best experts on this subject based on the ideXlab platform.
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In situ synthesis of AlN whiskers in mullite-silicon carbide refractory under simulated coke Dry Quenching conditions
Ceramics International, 2018Co-Authors: Zhang Meijie, Han Cangjuan, Ao Huang, Yu ChangAbstract:Abstract AlN whiskers in mullite-silicon carbide refractories were synthesized under the simulated conditions of service temperature and nitrogen flow in a coke Dry Quenching (CDQ) furnace. Nanoscale Fe powder and Si 3 N 4 -Fe powder were added as catalysts to the raw materials of the mullite-silicon carbide refractory containing metallic Al powder. The correlation between the microstructures and the sample properties were studied; the results showed that the formation and interaction of AlN whiskers in situ in the matrix improved the strength, thermal shock resistance, and toughness of the refractory. Nanoscale Fe powder was more effective as a catalyst for the formation and growth of AlN whiskers. The formation temperature of AlN whiskers in the samples containing nanoscale Fe powder was successfully decreased from 1000 to 850 °C under nitrogen flow.
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Improving Mullite-Silicon Carbide Refractory in Coke Dry Quenching using Aluminum Nitride Whiskers Formed In Situ
Ceramics International, 2017Co-Authors: Zhang Meijie, Han Cangjuan, Ao Huang, Zhijun ShaoAbstract:Abstract The formation conditions and their influence on the properties of mullite-SiC refractory were studied by adding metallic Al powder to the raw materials to form AlN whiskers in a coke Dry Quenching furnace. The results show that the AlN whiskers were formed in situ and interacted to form networks in the matrix when the metallic Al powder was added into the mullite-SiC refractory after heat treatment above 850 °C for 8 h under nitrogen flow. The whiskers grew lengthwise as the firing temperature increased and the cold modulus of rupture, cold crushing strength, and hot modulus of rupture increased. The amount and particle size of the metallic Al powder also affected the properties of the refractory. The optimum amount of Al powder addition was determined to be 6 wt%, which provided the highest strength and excellent toughness after heat treatment at 1000 °C for 8 h under nitrogen. Reducing the particle size of the metallic Al powder could promote formation of the AlN whiskers and improve the strength of the refractory.
