Abstract
Though many studies pertaining to heap leaching have been carried out to study the reaction kinetics in cylindrical columns, in the scaled up variants the extraction efficiency has not always complemented the laboratory expectations. Since heap leaching is a hydrometallurgical process, the reactions are contingent on the effective interactions between the two main phases (i.e. solid and the fluid). Thus, this work attempts to elicit the understanding of the liquid flow without the focus on the reactions as the prior imparts higher importance. A pseudo 2-D packed bed of 266 mm in length, 200 mm in height and 100 mm in thickness was employed in this work and subjected to X-ray computed tomography (XCT) imaging. XCT is typically used to identify the solid structures in a study specimen. The current study explores the inter-particle flow behaviour and pore networks of two packing types, namely, glass beads and ore particles. The inter-particle flow development at varied flow rates using medical XCT was attempted in this work by the addition of a clinical contrast agent. The same packed beds were subjected to laboratory experiments to determine the respective liquid drainage distributions. The flow model was proposed on a weighted random walk (RW) approach to ascertain the probabilistic behaviour of the gravity dominated flow features in the examined packings using the pore networks inferred from the XCT images. The model was able to generate comparable liquid drainage profiles for the examined packings, though the effect of flow rate was not captured. This approach could be used to specify operational parameters, such as drip emitter spacing, particle size and agglomerate size in heap leaching to enhance the overall extraction of the valuable metal species.
Original language | English |
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Article number | 105451 |
Number of pages | 14 |
Journal | Hydrometallurgy |
Volume | 197 |
DOIs | |
Publication status | Published - Nov 2020 |
Keywords
- Fluid flow visualisation
- Heap hydrodynamics
- Liquid dispersal
- Pore network extraction
- Random walk
- X-ray imaging