D. McBride

Simulation technology to support base metal ore heap leaching

Abstract A simulation framework is outlined for the analysis of the operation of both the heap and the associated water balance circuit for the leaching of primary metal ores. The heap simulation is based on a detailed computational model of the leaching process. The process chemistry, including reactants in the gas–liquid–solid matrix, gas flow, variably saturated liquid flow, species transport in both phases, heat transport, and biomass growth and catalysis, is accounted for in models that are equally applicable to simple and complex geometries. The leaching models are contained within the PHYSICA computational modelling environment that includes a powerful multiphase computational fluid dynamic (CFD) solver enabling reactive flow simulation through arbitrarily complex geometries. Tools have been developed in one-, two- and three-dimensions to capture a variety of aspects of the leaching process behaviour. By careful choice of tools, the framework can be applied to a wide range of leaching problems from small scale (e.g. analysis of column tests and drip emitter spacing) through to full scale heap simulation. An optimised version of the heap leach model is itself embedded within a simulation environment that exploits the BILCO mass balance software to enable dynamic simulation of the water balance within the whole plant circuit.

Computational modeling of mold filling and related free-surface flows in shape casting: An overview of the challenges involved

Accurate representation of the coupled effects between turbulent fluid flow with a free surface, heat transfer, solidification, and mold deformation has been shown to be necessary for the realistic prediction of several defects in castings and also for determining the final crystalline structure. A core component of the computational modeling of casting processes involves mold filling, which is the most computationally intensive aspect of casting simulation at the continuum level. Considering the complex geometries involved in shape casting, the evolution of the free surface, gas entrapment, and the entrainment of oxide layers into the casting make this a very challenging task in every respect. Despite well over 30 years of effort in developing algorithms, this is by no means a closed subject. In this article, we will review the full range of computational methods used, from unstructured finite-element (FE) and finite-volume (FV) methods through fully structured and block-structured approaches utilizing the cut-cell family of techniques to capture the geometric complexity inherent in shape casting. This discussion will include the challenges of generating rapid solutions on high-performance parallel cluster technology and how mold filling links in with the full spectrum of physics involved in shape casting. Finally, some indications as to novel techniques emerging now that can address genuinely arbitrarily complex geometries are briefly outlined and their advantages and disadvantages are discussed.

Finite volume method for the solution of flow on distorted meshes

Purpose – To improve flow solutions on meshes with cells/elements which are distorted/ non‐orthogonal.Design/methodology/approach – The cell‐centred finite volume (FV) discretisation method is well established in computational fluid dynamics analysis for modelling physical processes and is typically employed in most commercial tools. This method is computationally efficient, but its accuracy and convergence behaviour may be compromised on meshes which feature cells with non‐orthogonal shapes, as can occur when modelling very complex geometries. A co‐located vertex‐based (VB) discretisation and partially staggered, VB/cell‐centred (CC), discretisation of the hydrodynamic variables are investigated and compared with purely CC solutions on a number of increasingly distorted meshes.Findings – The co‐located CC method fails to produce solutions on all the distorted meshes investigated. Although more expensive computationally, the co‐located VB simulation results always converge whilst its accuracy appears to g...

Multi-component free surface flows and rotating devices in the context of minerals processing

In analysing the treatment and transport of slurries (i.e. particle loaded fluids) in minerals processing, it is common to come up against significant challenges from the perspective of the computational fluid dynamics (CFD) modelling, especially in trying to optimise their transport – to maintain uniformity of particle distribution or minimise their abrasive effects. These flows are essentially multi-component, non-Newtonian and their context is such that they may well involve complex free surfaces and also be in rotating equipment, as well, of course, involving rather complex geometrical configurations. Here we describe CFD models of some key slurry transport processes using a finite volume unstructured mesh-based code using a range of numerical procedures – algebraic slip models for capturing the particulate behaviour, scalar equation algorithms for the free surfaces and source-sink algorithms for the flow through rotating machinery. Applications of the above phenomena coupled are described together with some of the challenges in configuring CFD models.

Development of a radial ventricular assist device using numerical predictions and experimental haemolysis.

The objective of this study was to demonstrate the potential of Computational Fluid Dynamics (CFD) simulations in predicting the levels of haemolysis in ventricular assist devices (VADs). Three different prototypes of a radial flow VAD have been examined experimentally and computationally using CFD modelling to assess device haemolysis. Numerical computations of the flow field were computed using a CFD model developed with the use of the commercial software Ansys CFX 13 and a set of custom haemolysis analysis tools. Experimental values for the Normalised Index of Haemolysis (NIH) have been calculated as 0.020 g/100 L, 0.014 g/100 L and 0.0042 g/100 L for the three designs. Numerical analysis predicts an NIH of 0.021 g/100 L, 0.017 g/100 L and 0.0057 g/100 L, respectively. The actual differences between experimental and numerical results vary between 0.0012 and 0.003 g/100 L, with a variation of 5% for Pump 1 and slightly larger percentage differences for the other pumps. The work detailed herein demonstrates how CFD simulation and, more importantly, the numerical prediction of haemolysis may be used as an effective tool in order to help the designers of VADs manage the flow paths within pumps resulting in a less haemolytic device.

Computational Modelling of Metallurgical Processes: Achievements and Challenges

Extractive metallurgical processes rate amongst the most complex from the perspective of computational modeling. They typically involve multi-phase and multi-component fluid flow in very complex geometries, heat transfer driven by a number of interacting phenomena, solid-liquid-gaseous phase change and mass transfer together with complex thermodynamics and associated chemical reactions. Beyond the model building itself, key challenges have always involved being able to identify the phenomena present together with interactions to characterize processes and experimental laboratory and plant data to parameterize the arising models — it is in this milieu, which require considerable process understanding and subtlety of thought, that David Robertson has made his contributions.