Development of an analytical model for copper heap leaching from secondary sulfides in chloride media in an industrial environment Technical paper

Main Article Content

Manuel Saldaña
https://orcid.org/0000-0001-9265-1529
Eleazar Salinas-Rodríguez
https://orcid.org/0000-0002-0510-3266
Jonathan Castillo
https://orcid.org/0000-0002-7794-4291
Felipe Peña-Graf
https://orcid.org/0000-0002-1921-4055
Francisca Roldán

Abstract

In multivariate analysis, a predictive model is a mathematical/statistical model that relates a set of independent variables to dependent or response variable(s). This work presents a descriptive model that explains copper recovery from secondary sulfide minerals (chalcocite) taking into account the effects of time, heap height, superficial velocity of leaching flow, chloride concentration, particle size, porosity, and effective diffusivity of the solute within particle pores. Copper recovery is then modelled by a system of first-order differential equations. The results indicated that the heap height and superficial velocity of leaching flow are the most critical independent variables while the others are less influential under operational conditions applied. In the present study representative adjustment parameters are obtained, so that the model could be used to explore copper recovery in chloride media as a part of the extended value chain of the copper sulfides processing.

Article Details

How to Cite
[1]
M. Saldaña, E. Salinas-Rodríguez, J. Castillo, F. Peña-Graf, and F. Roldán, “Development of an analytical model for copper heap leaching from secondary sulfides in chloride media in an industrial environment: Technical paper”, Hem Ind, vol. 76, no. 4, pp. 183–195, Sep. 2022, doi: 10.2298/HEMIND220214015S.
Section
Chemical Engineering - Simulation and Optimization

How to Cite

[1]
M. Saldaña, E. Salinas-Rodríguez, J. Castillo, F. Peña-Graf, and F. Roldán, “Development of an analytical model for copper heap leaching from secondary sulfides in chloride media in an industrial environment: Technical paper”, Hem Ind, vol. 76, no. 4, pp. 183–195, Sep. 2022, doi: 10.2298/HEMIND220214015S.

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