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Journal articles on the topic 'Flash smelting'

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Published: 4 June 2021

Last updated: 29 January 2023

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1

Xie, Sui, Xinhua Yuan, Fupeng Liu, and Baojun Zhao. "Control of Copper Content in Flash Smelting Slag and the Recovery of Valuable Metals from Slag—A Thermodynamic Consideration." Metals 13, no. 1 (January 11, 2023): 153. http://dx.doi.org/10.3390/met13010153.

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To determine slag properties and the factors influencing these properties for optimization of operating conditions in the copper flash smelting process, the composition and microstructures of the quenched smelting and converting slags have been analyzed. Thermodynamic software FactSage 8.2 has been used to investigate the effects of matte grade, SO2 partial pressure, and the Fe/SiO2 ratio on the liquidus temperature and the copper content of the smelting slag. The possibility to recover valuable metals from the smelting and converting slags through pyrometallurgical reduction by carbon is also discussed. It was found that the flash smelting slag temperature is usually higher than its liquidus temperature and the copper (1.2% Cu) is mainly present in the slag as dissolved copper. In the copper flash smelting process, the copper content in the slag can be decreased by decreasing the Fe/SiO2 ratio and temperature. In pyrometallurgical slag reduction, most Cu, Mo, and Ni can be recovered as an alloy. The conditions of recovery such as the ratio of smelting slag to converting slag, temperature, and reduction extent have been discussed.

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2

Jorgensen, F. R. A., and P. T. L. Koh. "Combustion in flash smelting furnaces." JOM 53, no. 5 (May 2001): 16–20. http://dx.doi.org/10.1007/s11837-001-0201-x.

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3

Taskinen, P., K. Seppälä, J. Laulumaa, and J. Poijärvi. "Oxygen pressure in the Outokumpu flash smelting furnace—Part 1: copper flash smelting settler." Mineral Processing and Extractive Metallurgy 110, no. 2 (August 2001): 94–100. http://dx.doi.org/10.1179/mpm.2001.110.2.94.

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4

Zaim, Ehsan Hassan, and Seyed Hossein Mansouri. "A new mathematical model for copper concentrate combustion in flash smelting furnaces." Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering 231, no. 2 (August 3, 2016): 119–30. http://dx.doi.org/10.1177/0954408915577545.

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A novel mathematical model for combustion of a single copper concentrate particle is presented. The model includes particle volatilization, fragmentation, smelting, and combustion phenomena. This model has been incorporated into a general computational fluid dynamics code to calculate flow field and particle trajectories needed to simulate the smelting process in flash furnaces. In this model, Lagrangian approach was used to handle solid particles and droplets of liquid fuel charged, while Eulerian framework was used to handle the gas phase flow field. The results show that the effect of particle fragmentation was remarkable in flash smelting process as compared with experimental data and should be considered in combustion modeling. Moreover, the flash smelting process simulation results show that the reaction shaft design should be optimized based on a combination of furnace dimension and type of concentrate burners.

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5

Lu, Hong. "An Neural Network Model for the Fe/SiO₂ Ratio in Copper Flash Smelting Slag Using Improved Back Propagation Algorithm." Advanced Materials Research 524-527 (May 2012): 1963–66. http://dx.doi.org/10.4028/www.scientific.net/amr.524-527.1963.

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The Fe/SiO2 ratio in slag is one of the important control parameters for copper flash smelting process, but it is difficult to describe the complex relationship between the technological parameters and the Fe/SiO2 ratio in slag using accurate mathematic formulae, because the copper flash smelting process is a complicated nonlinear system. An neural network model for the Fe/SiO2 ratio in copper flash smelting slag was developed, whose net structure is 8-15-12-1, and input nodes include the oxygen volume per ton concentrate, the oxygen grade, the flux rate, the quantity of Cu, S, Fe, SiO2 and MgO in concentrate. In order to avoid local minimum terminations when the model is trained by back propagation (BP) algorithm, a new algorithm called GA-BP is presented by using genetic algorithm (GA) to determine the initial weights and threshold values. The results show that the model can avoid local minimum terminations and accelerate convergence, and has high prediction precision and good generalization performance. The model can be used to optimize the copper flash smelting process control.

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6

Taskinen, Pekka, Ari Jokilaakso, Daniel Lindberg, and Jiliang Xia. "Modelling copper smelting – the flash smelting plant, process and equipment." Mineral Processing and Extractive Metallurgy 129, no. 2 (November 12, 2019): 207–20. http://dx.doi.org/10.1080/25726641.2019.1688904.

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7

Bacedoni, María, Ignacio Moreno-Ventas, and Guillermo Ríos. "Copper Flash Smelting Process Balance Modeling." Metals 10, no. 9 (September 11, 2020): 1229. http://dx.doi.org/10.3390/met10091229.

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Process control in flash smelting is based on mass and energy balance from which the operational parameters (oxygen coefficient, oxygen enrichment, and flux demand) are obtained to achieve matte and slag with defined compositions and at defined temperatures. Mineral compositions of copper concentrates, and their blends, have been used in order to optimize the heat process balance. The classical balance methodology has been improved by using equations for molecular ratios and distribution coefficients that have been calculated using FactSage™. This paper describes the development of balance equations and compares their theoretical (equilibrium) results with industrial data logs of the smelting process.

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8

Solghar, Alireza Arab, and Morteza Abdolzadeh. "Thermochemical simulation of flash smelting furnace." Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering 229, no. 1 (November 2013): 11–24. http://dx.doi.org/10.1177/0954408913502168.

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9

Keyworth, B. "Flash smelting analysis, control and optimization." Minerals Engineering 2, no. 1 (January 1989): 137. http://dx.doi.org/10.1016/0892-6875(89)90072-1.

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10

Gao, Wei, Cheng Yan Wang, Fei Yin, Yong Qiang Chen, and Wei Jiao Yang. "Situation and Technology Progress of Lead Smelting in China." Advanced Materials Research 581-582 (October 2012): 904–11. http://dx.doi.org/10.4028/www.scientific.net/amr.581-582.904.

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The present paper reviews the situation and technology progress of lead smelting in China. According to the new lead smelting processes, this paper also presents a lead oxygen-enriched flash smelting technology, whose intellectual property rights are completely owned by China，it points out that lead smelting processes develop as follow: lower environmental pollution, higher metal recovery rate, more effective for complex low grade lead-bearing ore materials, lower energy consumption and higher automation degree.

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11

Shao, Yi Yuan, and Fei Shao. "Optimization of Operating Mode in Copper Flash Smelting Process." Advanced Materials Research 1046 (October 2014): 43–49. http://dx.doi.org/10.4028/www.scientific.net/amr.1046.43.

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A batch of operating parameters which need to be resolved on line are represented by operating modes.Operating mode optimization for copper flash smelting process based on fuzzy neural networks is presented. First of all, the optimal samples set is screened from the historical samples set. Then mode decomposition based on fuzzy neural networks is used, and chaos genetic algorithm is used to rake the optimal operating sub-pattern.This way is used to copper flash smelting process.The simulation result shows that this way can guide production.

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12

Arias, Luis, Sergio Torres, Carlos Toro, Eduardo Balladares, Roberto Parra, Claudia Loeza, Camilo Villagrán, and Pablo Coelho. "Flash Smelting Copper Concentrates Spectral Emission Measurements." Sensors 18, no. 7 (June 22, 2018): 2009. http://dx.doi.org/10.3390/s18072009.

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13

Varnas, S. R., and J. S. Truelove. "Simulating radiative transfer in flash smelting furnaces." Applied Mathematical Modelling 19, no. 8 (August 1995): 456–64. http://dx.doi.org/10.1016/0307-904x(95)00020-k.

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14

Caffery, G. A., T. R. Meadowcroft, J. R. Grace, I. V. Samarasekera, and A. A. Shook. "Comparisons between sulfide flash smelting and coal combustion—with implications for the flash smelting of high-grade concentrate." Metallurgical and Materials Transactions B 31, no. 5 (October 2000): 1005–12. http://dx.doi.org/10.1007/s11663-000-0076-1.

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15

Busolic, D., F. Parada, R. Parra, M. Sanchez, J. Palacios, and M. Hino. "Recovery of iron from copper flash smelting slags." Mineral Processing and Extractive Metallurgy 120, no. 1 (March 2011): 32–36. http://dx.doi.org/10.1179/037195510x12772935654945.

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16

Kemori, N., W. T. Denholm, and H. Kurokawa. "Reaction mechanism in a copper flash smelting furnace." Metallurgical and Materials Transactions B 20, no. 3 (June 1989): 327–36. http://dx.doi.org/10.1007/bf02696985.

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17

Chen, Yujie, Zongwen Zhao, Pekka Taskinen, Yanjie Liang, Hongchuan Ouyang, Bing Peng, Ari Jokilaakso, et al. "Characterization of Copper Smelting Flue Dusts from a Bottom-Blowing Bath Smelting Furnace and a Flash Smelting Furnace." Metallurgical and Materials Transactions B 51, no. 6 (August 26, 2020): 2596–608. http://dx.doi.org/10.1007/s11663-020-01907-8.

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18

Yang, Shuang Ping, Jie Liu, Jian Wang, and Xin Du. "The Theoretical and Experimental Study on Making Low Iron Alloy from the Mixed Slag of Jinchuan Flash Smelting Furnace and JISCO Converter." Advanced Materials Research 803 (September 2013): 239–42. http://dx.doi.org/10.4028/www.scientific.net/amr.803.239.

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Jinchuan nickel-copper flash smelting slag is rich in iron, nickel, cobalt and copper, and JISCO converter slag is rich in iron, manganese and high CaO, etc., the two kind slags were blended, and then smelted into low-alloy iron containing nickel, cobalt, copper and manganese with smelting reduction method, which is a new comprehensive utilization methods for the Double slag. The thermodynamic calculation results of the equilibrium concentration of Fe, Cu and Ni in low-alloy iron obtained by smelting reduction under experimental condition are in good agreement with experimental results. Iron reduction rate of Fe, Cu and Ni can be elevated to above 90% by smelting reduction, thus the comprehensive utilization of valuable metals can come true.

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19

Zeng, Fan Rong, and Ping Zhang. "Prediction for Matte Grade in the Process of Copper Flash Smelting Based on QPSO-LSSVM." Advanced Materials Research 722 (July 2013): 535–40. http://dx.doi.org/10.4028/www.scientific.net/amr.722.535.

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According to the complexity of the reaction mechanism and the requirement of the craft indicator during the process of copper flash smelting, the prediction model of matte grade was proposed by combining quantum particle swarm optimization algorithm (QPSO) with least squares support vector machine (LS-SVM) in this paper. Firstly, the nonlinear relation model between matte grade and craft indicators in copper flash smelting process was established by using the LS-SVM. Secondly, the parameters of LS-SVM were optimized by using the QPSO algorithm. Finally, the simulation results show that the maximum relative error of the matte grade is 0.47% and the relative root mean square error is 0.33%.Results indicate that the model can satisfy the requirement of production process and can be used to guide the practical production.

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20

Jämsä-Jounela, S.-L., E. Vapaavuori, T. Salmi, M. Grönbärj, and M. Vermasvuori. "Fault diagnosis system for the Outokumpu flash smelting process." IFAC Proceedings Volumes 33, no. 22 (August 2000): 431–36. http://dx.doi.org/10.1016/s1474-6670(17)37033-7.

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21

Jämsä-Jounela, S.-L., M. Vermasvuori, S. Haavisto, and P. Endén. "Fault Diagnosis System for the Outokumpu Flash Smelting Process." IFAC Proceedings Volumes 34, no. 18 (September 2001): 65–70. http://dx.doi.org/10.1016/s1474-6670(17)33183-x.

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22

Higgins, D. R., N. B. Gray, and M. R. Davidson. "Simulating particle agglomeration in the flash smelting reaction shaft." Minerals Engineering 22, no. 14 (November 2009): 1251–65. http://dx.doi.org/10.1016/j.mineng.2009.07.005.

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23

Vapaavuori, E., S.-L. Jämsä-Jounela, and J. Yianatos. "Fault Diagnosis System for the Outokumpu Flash Smelting Process." IFAC Proceedings Volumes 32, no. 2 (July 1999): 7028–33. http://dx.doi.org/10.1016/s1474-6670(17)57199-2.

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24

Varnas, S. R., P. T. L. Koh, and N. Kemori. "Evaluation of nickel flash smelting through piloting and simulation." Metallurgical and Materials Transactions B 29, no. 6 (December 1998): 1329–43. http://dx.doi.org/10.1007/s11663-998-0057-3.

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25

Kojo, Ilkka V., Ari Jokilaakso, and Pekka Hanniala. "Flash smelting and converting furnaces: A 50 year retrospect." JOM 52, no. 2 (February 2000): 57–61. http://dx.doi.org/10.1007/s11837-000-0049-5.

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26

Wu, Jing, Hong Yao Wang, Yong Chun Shi, Hong Mei Fan, and Xiao Guang Li. "Large-Scale Rotary Steam Tube Drying System and Equipment for Copper Powder." Advanced Materials Research 402 (November 2011): 467–71. http://dx.doi.org/10.4028/www.scientific.net/amr.402.467.

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Drying is a crucial step in the process of copper powder flash smelting for the direct influences on the quality of smelting. This paper proposes a unique system to match the special requirements of drying raw copper powder, such as large mass rate, small diameter dust and abrasion. On the bases of drying features and energy conservation, optimization design of drying system and equipment was also carried out. In site tests showed the satisfaction on working stability, energy thrift and quality of final product.

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27

Yu, Hai, Lian Yong Wang, and Tao Du. "Waste Heat Recovery and Reuse of Flue Gas in Copper Pyrometallurgy." Applied Mechanics and Materials 71-78 (July 2011): 2239–42. http://dx.doi.org/10.4028/www.scientific.net/amm.71-78.2239.

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In the paper, we take current relatively advanced, the most widely used flash smelting furnace, converter and rotary anode furnace as the examples, the waste heat resources of the process of matte smelting, the process of matte converting and the process of fire refining of blister copper in copper pyrometallurgy are analyzed respectively. Meanwhile, based on the way of using waste heat reasonably to suitable heat consumer in production process and the grade recovery principle of energy level matching, the model of waste heat recovery and reuse of flue gas in copper pyrometallurgy is constructed.

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28

Saxén, Henrik, Marco A. Ramírez-Argáez, Alberto N. Conejo, and Abhishek Dutta. "Special Issue on “Process Modeling in Pyrometallurgical Engineering”." Processes 9, no. 2 (January 29, 2021): 252. http://dx.doi.org/10.3390/pr9020252.

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This Special Issue on “Process Modeling in Pyrometallurgical Engineering” consists of 39 articles, including two review papers, and covers a wide range of topics related to process development and analysis based on modeling in ironmaking, steelmaking, flash smelting, casting, rolling operations, etc [...]

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29

Wan, Xingbang, Lotta Kleemola, Lassi Klemettinen, Hugh O’Brien, Pekka Taskinen, and Ari Jokilaakso. "On the Kinetic Behavior of Recycling Precious Metals (Au, Ag, Pt, and Pd) Through Copper Smelting Process." Journal of Sustainable Metallurgy 7, no. 3 (June 9, 2021): 920–31. http://dx.doi.org/10.1007/s40831-021-00388-6.

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Abstract The recycling and recovery of precious metals from secondary materials, such as waste-printed circuit boards, are an important area of circular economy research due to the limited existing resources and increasing amount of e-waste produced by the rapid development of technology. In this study, the kinetic behavior of precious metals Au, Ag, Pt, and Pd between copper matte and iron-silicate slag was investigated at a typical flash smelting temperature of 1300 °C in both air and argon atmospheres. SEM–EDS, EPMA, and LA-ICP-MS-advanced analysis methods were used for sample characterization. The results indicate that precious metals favor the matte phase over slag, and the deportment to matte occurred swiftly within a short time after the system had reached the experimental temperature. With increasing contact times, the precious metals were distributed increasingly into the sulfide matte. The distribution coefficients, based on experimentally measured element concentrations, followed the order of palladium > platinum > gold > silver in both air and argon, and the matte acted as an efficient collector of these precious metals. The obtained results can be applied to industrial copper matte smelting processes, and they also help in upgrading CFD models to simulate the flash smelting process more precisely. Graphical Abstract

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30

Zhang, Huibin, Yanan Wang, Yuzheng He, Shenghang Xu, Bin Hu, Huazhen Cao, Jun Zhou, and Guoqu Zheng. "Efficient and safe disposition of arsenic by incorporation in smelting slag through copper flash smelting process." Minerals Engineering 160 (January 2021): 106661. http://dx.doi.org/10.1016/j.mineng.2020.106661.

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31

Holtzer, M., A. Bydałek, W. Wołczyński, and A. Kmita. "Assessment of the Harmfulness of the Slags from Copper Smelting Processes, in an Aspect of their Management." Archives of Foundry Engineering 17, no. 3 (September 1, 2017): 191–95. http://dx.doi.org/10.1515/afe-2017-0114.

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AbstractThere are two methods to produce primary copper: hydrometallurgical and pyrometallurgical. Copper concentrates, from which copper matte is melted, constitute the charge at melting primary copper in the pyrometallurgical process. This process consists of a few stages, of which the basic ones are roasting and smelting. Smelting process may be bath and flash. Slag from copper production, on the end of process contain less 0,8%. It is treat as a waste or used other field, but only in a few friction. The slag amount for waste management or storage equaled 11 741 – 16 011 million tons in 2011. This is a serious ecological problem. The following slags were investigated: slag originated from the primary copper production process in the flash furnace of the Outtokumpuja Company in HM Głogów 2 (Sample S2): the same slag after the copper removal performed according the up to now technology (Sample S1): slag originated from the primary copper production process in the flash furnace of the Outtokumpuja Company in HM Głogów 2, after the copper removal performed according the new technology (Sample S3). In practice, all tested slags satisfy the allowance criteria of storing on the dumping grounds of wastes other than hazardous and neutral.

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32

Gui, Wei-Hua, Chun-Hua YANG, Yong-Gang LI, Jian-Jun HE, and Lin-Zi YIN. "Data-driven Operational-pattern Optimization for Copper Flash Smelting Process." Acta Automatica Sinica 35, no. 6 (August 14, 2009): 717–24. http://dx.doi.org/10.3724/sp.j.1004.2009.00717.

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33

KEMORI, Nobumasa, Harumasa KUROKAWA, and Zensaku KOZUKA. "Applications of Oxygen Probes to a Copper Flash Smelting Furnace." Journal of the Mining Institute of Japan 102, no. 1175 (1986): 41–47. http://dx.doi.org/10.2473/shigentosozai1953.102.1175_41.

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34

Ahokainen, T., and A. Jokilaakso. "Numerical Simulation of the Outokumpu Flash Smelting Furnace Reaction Shaft." Canadian Metallurgical Quarterly 37, no. 3-4 (October 1998): 275–83. http://dx.doi.org/10.1179/cmq.1998.37.3-4.275.

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35

Jong-Leng, Liow, and Neil B. Gray. "Experimental study of splash generation in a flash smelting furnace." Metallurgical and Materials Transactions B 27, no. 4 (August 1996): 633–46. http://dx.doi.org/10.1007/bf02915661.

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36

文, 燕. "Study on Leaching of Dust of Copper Flash Smelting Furnace." Metallurgical Engineering 02, no. 03 (2015): 151–57. http://dx.doi.org/10.12677/meng.2015.23022.

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37

龙, 鹏. "Numerical Simulation of Arsenic Distribution Behavior in Copper Flash Smelting." Metallurgical Engineering 05, no. 02 (2018): 85–92. http://dx.doi.org/10.12677/meng.2018.52012.

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38

González, A., O. Font, N. Moreno, X. Querol, N. Arancibia, and R. Navia. "Copper Flash Smelting Flue Dust as a Source of Germanium." Waste and Biomass Valorization 8, no. 6 (October 13, 2016): 2121–29. http://dx.doi.org/10.1007/s12649-016-9725-8.

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39

Dunn, J. G., and S. A. A. Jayaweera. "Applications of thermoanalytical methods to studies of flash smelting reactions." Thermochimica Acta 85 (April 1985): 115–18. http://dx.doi.org/10.1016/0040-6031(85)85543-x.

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40

Khan, Nadir Ali, and Ari Jokilaakso. "Flash Smelting Settler Design Modifications to Reduce Copper Losses Using Numerical Methods." Processes 10, no. 4 (April 16, 2022): 784. http://dx.doi.org/10.3390/pr10040784.

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A mathematical modeling approach was used to test different design modifications in a flash smelting settler to reduce the copper losses in slag, which is economically disadvantageous for copper processing using the pyrometallurgical route. The main purpose of this study was to find ways to reduce copper losses in slag by improving the settling and coalescence of copper matte droplets, in particular, the smallest droplet sizes of ≤100 µm. These improvements inside the flash smelting (FS) settler were targeted through different settler design modifications. Three different design schemes were tested using the commercial computational fluid dynamics (CFD) software, Ansys Fluent. These settler design modification schemes included the impact of various baffle types, positioning, the height inside the settler, and settler bottom inclinations. Simulations were carried out with and without coalescence and the results were compared with normal settler design. The results revealed that the settling phenomenon and coalescence efficiency were improved significantly with these design modifications. It was concluded that a single baffle design was optimal for reducing copper losses and increasing coalescence efficiency instead of using multiple baffle arrangements. The top-mounted baffle outperformed the bottom-mounted baffle and inclined settler design.

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41

Wang, Guohua, Yaru Cui, Xiaoming Li, Shufeng Yang, Junxue Zhao, Hongliang Tang, and Xuteng Li. "Molecular Dynamics Simulation on Microstructure and Physicochemical Properties of FexO-SiO2-CaO-MgO-“NiO” Slag in Nickel Matte Smelting under Modulating CaO Content." Minerals 10, no. 2 (February 10, 2020): 149. http://dx.doi.org/10.3390/min10020149.

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To improve the conditions of extracting iron from nickel smelting residues, the composition modulating from FexO-SiO2-CaO-MgO-“NiO” slag source for matte smelting using high MgO nickel sulfide concentrate was carried out. Based on the molecular dynamics simulation and experimental characterization, the effect of CaO content in nickel slags on the physicochemical properties, the microstructure evolution, and the feasibility of subsequent iron extraction were analyzed. The results showed that, for nickel smelting slag with 9 wt.% MgO, 13–15 wt.% CaO and Fe/SiO2 ratio of 1.2, the melting temperature of nickel slag was lower than 1200 °C, and the viscosity was lower than 0.22 Pa·s at 1350 °C. The electric conductivity was similar to that of the industrial slag, and the interfacial tension between slag and matte was relatively large, which ensured a good separating characteristic. It not only met the requirements for the slag performances in the existing flash smelting process but also improved conditions for the subsequent iron extraction. Additionally, it could be adapted to the current situation where an increasing MgO content exists in the nickel sulfide concentrate.

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42

KEMORI, Nobumasa, Teiji AONO, Harumasa KUROKAWA, and Mutsuo TOMONO. "The Application of Equilibrium Calculations to a Copper Flash Smelting Furnace." Journal of the Mining Institute of Japan 103, no. 1191 (1987): 315–23. http://dx.doi.org/10.2473/shigentosozai1953.103.1191_315.

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43

Stefanova, V., K. Genevski, and B. Stefanov. "Mechanism of Oxidation of Pyrite, Chalcopyrite and Bornite During Flash Smelting." Canadian Metallurgical Quarterly 43, no. 1 (January 2004): 78–88. http://dx.doi.org/10.1179/cmq.2004.43.1.78.

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44

CZKOWSKI, A. ZAJA, J. BOTOR, and J. CZERNECKI. "THERMODYNAMICS OF COPPER AND LEAD IN ALUMINA SATURATED FLASH SMELTING SLAG." Canadian Metallurgical Quarterly 43, no. 3 (January 2004): 417–29. http://dx.doi.org/10.1179/cmq.2004.43.3.417.

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45

GENEVSKI, K., and V. STEFANOVA. "DISPERSED MATTE DROPLETS IN INDUSTRIAL SLAG MELTS FROM FLASH SMELTING FURNACE." Canadian Metallurgical Quarterly 47, no. 1 (January 2008): 51–58. http://dx.doi.org/10.1179/cmq.2008.47.1.51.

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46

GUI, Wei-hua, Ling-yun WANG, Chun-hua YANG, Yong-fang XIE, and Xiao-bo PENG. "Intelligent prediction model of matte grade in copper flash smelting process." Transactions of Nonferrous Metals Society of China 17, no. 5 (October 2007): 1075–81. http://dx.doi.org/10.1016/s1003-6326(07)60228-3.

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47

SASAKI, Yukihito, Yoshiaki MORI, and Yasumasa HATTORI. "Numerical Study of Combustion Phenomena of Concentrate Particles in Flash Smelting Furnace." Journal of MMIJ 125, no. 1 (2009): 31–37. http://dx.doi.org/10.2473/journalofmmij.125.31.

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ASAKI, Zenjiro. "Analyses of reactions in fluidized bed roasting furnace and flash smelting furnace." Journal of the Society of Powder Technology, Japan 23, no. 7 (1986): 510–17. http://dx.doi.org/10.4164/sptj.23.510.

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JOKILAAKSO, ARI, TAPIO AHOKAINEN, OSMO TEPPO, YONGXIANG YANG, and KAJ LILIUS. "Experimental and Computational-Fluid-Dynamics Simulation of the Outokumpu Flash Smelting Process." Mineral Processing and Extractive Metallurgy Review 15, no. 1-4 (December 1995): 217–34. http://dx.doi.org/10.1080/08827509508914200.

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WANG, Jin-liang, Ya-zhou CHEN, Wen-hai ZHANG, and Chuan-fu ZHANG. "Furnace structure analysis for copper flash continuous smelting based on numerical simulation." Transactions of Nonferrous Metals Society of China 23, no. 12 (December 2013): 3799–807. http://dx.doi.org/10.1016/s1003-6326(13)62932-5.

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