Flotation is a physicochemical process and its success is governed by a number of factors; including the ore mineral association and particle size distribution, the pulp chemistry, as well as the hydrodynamics and gas dispersion of flotation machines. Due to the interactions occurring, it is difficult to characterize the effect of a specific factor and the scale up of flotation behavior from laboratory cell to industrial scale. In particular, generating the equivalent hydrodynamic condition in laboratory flotation cells to that in industrial cell has always been a great challenge as variation in flotation cell hydrodynamics strongly influences flotation kinetics and product quality.
Considerable effort has been made over the years to find a suitable way to mathematically model flotation performance in order to design and optimise flotation circuits using both fundamental and applied approaches. The AMIRA P9 model (k = P × Sb × Rf), has been developed as a practical model with measurable parameters that has been widely used by industrial plants to improve and optimize their performance. In these flotation simulations the applied bubble surface area flux (Sb) is the only hydrodynamic parameter to take variation of the hydrodynamic condition of flotation cells into account. In the scale up from laboratory to plant scale, a scale up number is needed. A review of the fundamental approach has revealed that more hydrodynamic parameters need to be incorporated to improve the predictive capacity of the equation. The objective of this thesis is “to develop and incorporate measurable and appropriate turbulence parameters into the AMIRA P9 model (k = P × Sb × Rf), thus enabling P to be a more consistent measure of the ore properties and the model to be more accurate for predictions including scale up”.
In the first step of this study, the possibility of applying practical measurements to characterise the hydrodynamic conditions of flotation cells of any size was tested. Several measurement instruments such as power meter, hot-wire anemometer, bubble sizer, air flow meter and viscometer were used to characterise the hydrodynamic condition inside two different flotation cells (5 L and 60 L). As a result, power input, energy dissipation rate, turbulent kinetic energy, bubble size and air flow parameters could be obtained for 12 different hydrodynamic conditions in the cells.
The influence of impeller speed on bubble size distribution reported in the published literature in different flotation cells is inconsistent, for some cases, bubble size reduces with increasing impeller speed and in others it remains unchanged. The effect of impeller speed on bubble size was tested in the flotation cells with different sizes in this study and the relationship differed for the results obtained in the 5 L and 60 L cell. However by using the turbulent kinetic energy (TKE) instead of impeller speed, the relationship was consistent. The results show that the turbulent kinetic energy (TKE) should be kept above a minimum value to get the finest bubble size distribution regardless of the impeller diameter or the scale of the flotation cell. Thus it was possible to account for the inconsistency in the published literature in regard to the influence of impeller speed on bubble size.
The AMIRA P9 model has floatability (P) as the property of the ore which is considered to remain constant in different flotation cell sizes with different hydrodynamic conditions. However in this study, increasing the power input increased the P value especially in finer particle size classes (-75 µm) in both the studied flotation cells To improve the accuracy of the AMIRA P9 flotation model in predicting k and to improve the consistency of the P value, measurable and appropriate turbulence parameters were sought to be incorporated into the model. Dimensionless turbulent parameters, ӕ and EVF were formulated and used for modelling purposes. The parameters improved the consistency of ore property P’’. The new ore property values obtained from flotation experiments with 5 L flotation cell were used to predict the flotation rate constant in the 60 L cell at different hydrodynamic conditions. The accuracy of the predictions was enhanced when these dimensionless parameters were used, with the exception of the coarse particle behaviour.
Further work is recommended to evaluate the turbulence parameters in a continuous system, at a larger scale and for industrial flotation circuits. More study on coarse particle flotation is also recommended as this study indicated that the new ore property value may reduce with increasing energy dissipation rate due to intensifying detachment in the high turbulent region in a flotation cell. Finally, incorporating more components such as mineral liberation to the P9 model could increase the accuracy of the predictions.