An improved model of continuous leaching systems using segregation approach

Document Type : Research Paper


1 Mining and Metallurgical Engineering Department, Yazd University, Yazd, Iran;

2 Department of Mining Engineering, Tarbiat Modares University, Tehran, Iran


In this study, a simplified dissolution model has been developed to evaluate the performance of continuous leaching reactors. The model considers continuous reduction of the surface area of particles using the distribution of their size and residence time. The model was validated by the bioleaching of a pyrite-arsenopyrite concentrate in the pilot plant scale, which resulted in good agreement between the experimental data and the predicted values. The developed model was also used to predict the outlet mass density function of particles, whose results showed that the mean particle size would not necessarily decrease as the mean residence time in the leaching process decreased. Using this model, the effect of operating parameters (e.g., particle size distribution, inlet flow, reagent concentration, kinetic parameters, and the type of residence time distribution) on the reactor performance can be predicted. Therefore, the model can be used for dynamic and static analyses of leaching circuits as well as designing and optimizing the processing plants.


[1] Papangelakis, V. & Demopoulos, G. (1993). Modeling, Simulation and Control of Hydrometallurgical Processes: Proceeding of the international symposium on Modeling, simulation and control of hydrometallurgical processes, Quebec City. Quebec, August 24-September2.
[2] Coelho, F.E.B., Balarini, J. C., Araújo, E.M.R., Miranda, T.L.S., Peres, A. E. C., Martins A.H., & Salum, A. (2018). Roasted zinc concentrate leaching: Population balance modeling and validation. Hydrometallurgy, 175(0), 208-217. doi:
[3] Crundwell, F. & Bryson, A. (1992). The Modeling of particulate leaching reactors-the population balance approach. Hydrometallurgy, 29(1-3), 275-295. doi:
[4] Sohn, H.Y. & Wadsworth, M.E. (2013). Rate processes of extractive metallurgy. Springer Science & Business Media. doi:
[5] Dixon, D.G. (1995). Improved methods for the design of multistage leaching systems. Hydrometallurgy, 39(1), 337- 351. doi:
[6] Peters, E. (1991). The mathematical modeling of leaching systems. JOM, 43(2), 20-26.
[7] Dixon, D.G. (1996). The multiple convolution integral: a new method for modeling multistage continuous leaching reactors. Chemical engineering science, 51(21), 4759-4767. doi:
[8] Kotsiopoulos, A., Hansford, G.S., & Rawatlal, R. (2008). An approach of segregation in modeling continuous flow tank bioleach systems. AIChE journal, 54(6), 1592-1599. doi:
[9] Drossou, M. (1986). The kinetics of the bioleaching of a refractory gold-bearing pyrite concentrate. University of Cape Town. doi: _kinetics_1982.pdf?sequence=1.
[10] McKibben, M.A. & Barnes, H.L. (1986). Oxidation of pyrite in low temperature acidic solutions: Rate laws and surface textures. Geochimica et Cosmochimica Acta, 50(7),1509- 1520. doi:
[11] Wiersma, C. & Rimstidt, J. (1984). Rates of reaction of pyrite and marcasite with ferric iron at pH 2. Geochimica et Cosmochimica Acta, 48(1), 85-92. doi:
[12] Boon, M.(1996). Theoretical and experimental methods in the Modeling of bio-oxidation kinetics of sulphide minerals. TU Delft, Delft University of Technology. doi: 807c192a2600.
[13] Vignes, A. (2013). Extractive metallurgy 3: Processing operations and routes. John Wiley & Sons. doi: 10.1002/9781118617106.
[14] Petersen, J.(2010). Modeling of bioleach processes: connection between science and engineering. Hydrometallurgy, 104(3- 4), 404-409. doi:
[15] Hansford, G. & Miller, D.(1993). Biooxidation of a gold‐ bearing pyrite‐arsenopyrite concentrate. FEMS microbiology reviews.,11(1‐3), 175-181. [16] de Andrade Lima, L. & Hodouin, D. (2005). Residence time distribution of an industrial mechanically agitated cyanidation tank. Minerals engineering, 18(6), 613-621. doi:
[17] Murphy, T. (2002). Residence Time Distribution of Solid Particles in a CSTR. McGill University Libraries. doi: http://digitool.Library.McGill.CA:80/R/-?func=dbin-jumpfull&object_id=79251&silo_library=GEN01
[18] Crundwell, F., Preez, N, Du. & Lloyd, J. (2013). Dynamics of particle-size distributions in continuous leaching reactors and autoclaves. Hydrometallurgy, 133, 44-50. doi:
[19] Saloojee, F. & Crundwell, F, K. (2016). Optimization of circuits for pressure leaching of sulphide ores and concentrates. Journal of the Southern African Institute of Mining and Metallurgy, 116(6), 517-524. doi: 10.17159/2411- 9717/2016/v116n6a5.