Kinetics for reduction of iron ore based on the phase space reconstruction. (English) Zbl 1463.92089

Summary: A series of smelting reduction experiments has been carried out with high-phosphorus iron ore of the different bases and heating rates by thermogravimetric analyzer. The derivative thermogravimetric (DTG) data have been obtained from the experiments. After analyzing its phase space reconstruction, it is found that DTG phase portrait contains with a clear double “\(\infty\)” attractor characteristic by one-order delay. The statistical properties of the attractor inside and outside the double “\(\infty\)” structures are characterized with interface chemical reaction control and diffusion control stage in dynamic smelting process, respectively; the results are deserved to be a reference value on understanding of the mechanism and optimization and control of the process in smelting reduction of high-phosphorus iron ore.


92E20 Classical flows, reactions, etc. in chemistry
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[1] Wiendahl, H.-P.; Worbs, J., Simulation based analysis of complex production systems with methods of non-linear dynamics, Journal of Materials Processing Technology, 139, 1-3, 28-34 (2003)
[2] Yagiz, S.; Gokceoglu, C., Application of fuzzy inference system and nonlinear regression models for predicting rock brittleness, Expert Systems with Applications, 37, 3, 2265-2272 (2010)
[3] Deng, Z.; Yang, L.; Yu, J.; Luo, G., An inverse problem of identifying the coefficient in a nonlinear parabolic equation, Nonlinear Analysis, Theory, Methods and Applications, 71, 12, 6212-6221 (2009) · Zbl 1181.35325
[4] Shi, J.; Donskoi, E.; McElwain, D. L. S.; Wibberley, L. J., Modelling the reduction of an iron ore-coal composite pellet with conduction and convection in an axisymmetric temperature field, Mathematical and Computer Modelling, 42, 1-2, 45-60 (2005) · Zbl 1121.74354
[5] Tao, D., The kinetic models of chemical reaction of fluids on rough surfaces, Acta Metallurgica Sinica, 37, 10, 1073-1078 (2001)
[6] Tao, D. P., Fractal pore diffusion model of fluids in porous media, Acta Metallurgica Sinica, 13, 3, 877-883 (2000)
[7] Huang, D.; Yang, X.; Yang, T.; Kong, L., Kinetics and mathematical model for reduction process of iron ore briquette containing carbon, Acta Metallurgica Sinica, 32, 6, 629-636 (1996)
[8] Huang, D. B.; Kong, L. T., Kinetic model for firing hematite pellet containing solid fuel, Iron and Steelmaking, 30, 4, 1-6 (1995)
[9] Wang, Q.; Yang, Z.; Tian, J.; Li, W.; Sun, J., Mechanisms of reduction in iron ore-coal composite pellet, Ironmaking and Steelmaking, 24, 6, 457-460 (1997)
[10] Cross, M.; Croft, T. N.; Djambazov, G.; Pericleous, K., Computational modelling of bubbles, droplets and particles in metals reduction and refining, Applied Mathematical Modelling, 30, 11, 1445-1458 (2006) · Zbl 1375.76193
[11] Mark, P.; Cross, M.; Schwarz, P., A two-dimensional steady-state simulation model for a lead blast furnace, Proceedings of the 3rd International Conference on CFD in the Minerals and Process Industries, CSTRO
[12] Ma, X.; Jiang, M.; Wang, D., Kinetics and model of reaction process of iron ore-coal pellet, Journal of Northeastern University, 23, 5, 440-443 (2002)
[13] Fraser, A. M.; Swinney, H. L., Independent coordinates for strange attractors from mutual information, Physical Review A, 33, 2, 1134-1140 (1986) · Zbl 1184.37027
[14] Dippner, J. W.; Heerkloss, R.; Zbilut, J. P., Recurrence quantification analysis as a tool for characterization of non-linear mesocosm dynamics, Marine Ecology Progress Series, 242, 29-37 (2002)
[15] Chen, D.; Liu, Y.; Ma, X., Parameter joint estimation of phase space reconstruction in chaotic time series based on radial basis function neural networks, Acta Physica Sinica, 61, 10 (2012) · Zbl 1274.93253
[16] Chen, D.; Han, W., Prediction of multivariate chaotic time series via radial basis function neural network, Complexity, 18, 4, 55-66 (2013)
[17] Webber, C. L., Recurrence quantification analysis of nonlinear dynamical systems, COMMENT, 1, 1-94 (2005)
[18] Belaire-Franch, J.; Contreras, D., Recurrence plots in nonlinear time series analysis: free software, Journal of Statistical Software, 7, 1-18 (2002)
[19] Fan, G. F.; Qing, S.; Wang, H.; Hong, W.-C., The kinetic model of direct melting reduction process of huimin iron ore, Mineral Processing and Extractive Metallurgy, 122, 2, 1-8 (2013)
[20] Trzaskalik, T.; Sitarz, S., Discrete dynamic programming with outcomes in random variable structures, European Journal of Operational Research, 177, 3, 1535-1548 (2007) · Zbl 1102.90032
[21] van den Boom, T. J. J.; Heidergott, B.; de Schutter, B., Complexity reduction in MPC for stochastic max-plus-linear discrete event systems by variability expansion, Automatica, 43, 6, 1058-1063 (2007) · Zbl 1282.93180
[22] Iwankiewicz, R., Equations for probability density of response of dynamic systems to a class of non-Poisson random impulse process excitations, Probabilistic Engineering Mechanics, 23, 2-3, 198-207 (2008)
[23] Kontorovich, V.; Lyandres, V., Dynamic systems with random structure: an approach to the generation of nonstationary stochastic processes, Journal of the Franklin Institute, 336, 6, 939-954 (1999) · Zbl 0972.93064
[24] Hudson, E. R.; Ticknor, C.; Sawyer, B. C.; Taatjes, C. A.; Lewandowski, H. J.; Bochinski, J. R.; Bohn, J. L.; Ye, J., Production of cold formaldehyde molecules for study and control of chemical reaction dynamics with hydroxyl radicals, Physical Review A, 73, 6 (2006)
[25] Kundaliya, D. C.; Ogale, S. B.; Lofland, S. E.; Dhar, S.; Metting, C. J.; Shinde, S. R.; Ma, Z.; Varughese, B.; Ramanujachary, K. V.; Salamanca-Riba, L.; Venkatesan, T., On the origin of high-temperature ferromagnetism in the low-temperature-processed Mn-Zn-O system, Nature Materials, 3, 10, 709-714 (2004)
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