Journal of Engineering Mathematics

, Volume 87, Issue 1, pp 111–121 | Cite as

A control volume finite element method for adaptive mesh simulation of flow in heap leaching

  • Peyman Mostaghimi
  • Brendan S. Tollit
  • Stephen J. Neethling
  • Gerard J. Gorman
  • Christopher C. Pain


Accurate determination of fluid flow within heap leaching is crucial for understanding and improving performance of the process. Numerical methods have the potential to assist by modelling the process and studying the transport phenomena within the porous medium. This paper presents an adaptive mesh numerical scheme to solve for unsaturated incompressible flow in porous media with applications to heap leaching. The governing equations are Darcy’s law and the conservation of mass. An implicit pressure explicit saturation method is used to decouple the pressure and saturation equations. Pressure is discretized using a control volume (CV) finite element method, while for saturation a node-centred CV method is employed. The scheme is equipped with dynamic anisotropic mesh adaptivity to update the mesh resolution as the leaching solution infiltrates through the heap. This allows for high-fidelity modelling of multiscale features within the flow. The method is verified against the Buckley–Leverett problem where a quasi-analytical solution is available. It is applied for two-phase flow of air and leaching solution in a simplified two-dimensional heap geometry. We compare the accuracy and CPU efficiency of an adaptive mesh against a static mesh and demonstrate the potential to achieve high spatial accuracy at low computational cost through the use of anisotropic mesh adaptivity.


Adaptive mesh Control volume finite element method Heap leaching Multiphase flow  Porous media 


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Peyman Mostaghimi
    • 1
    • 2
  • Brendan S. Tollit
    • 2
  • Stephen J. Neethling
    • 1
  • Gerard J. Gorman
    • 2
  • Christopher C. Pain
    • 2
  1. 1.Rio Tinto Centre for Advanced Mineral Recovery, Department of Earth Science and EngineeringImperial CollegeLondonUK
  2. 2.Applied Modelling and Computational Group, Department of Earth Science and EngineeringImperial CollegeLondonUK

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