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Model coefficients for barite.

Table 3 Model coefficients for barite.

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Fig. 1. Illustration of current methods to determine the relationship between process water chemistry and flotation performance.
Fig. 1. Illustration of current methods to determine the relationship between process water chemistry and flotation performance.
Fig. 2. Process sensitivity analysis to the process water composition as per- formed in HSC Sim.
Fig. 2. Process sensitivity analysis to the process water composition as per- formed in HSC Sim.
Baseline Synthetic Water composition. Table 1
Baseline Synthetic Water composition. Table 1
Model coefficients for fluorite.
Model coefficients for fluorite.
Fig. 3. Modeling of fluorite flotation kinetics data with the three-component batch flotation equation under baseline conditions and with magnesium-rich water (10 mmol/1 MgCl»). To parametrize the flotation kinetics under varying water compo- sitions, a flotation model first has to be selected. As is commonly done when modeling the flotation rate of minerals (Ruuska et al., 2012), a first order kinetic equation was preferred. The model selected in this case is a so-called three-component batch flotation model since it provides a relatively good fit between experimental and modeled data, as illu- strated in Fig. 3 with the flotation of the fluorite ore in the BSW and in water containing 10 mmol/l MgCl. (Mg-rich water). This model links
Fig. 3. Modeling of fluorite flotation kinetics data with the three-component batch flotation equation under baseline conditions and with magnesium-rich water (10 mmol/1 MgCl»). To parametrize the flotation kinetics under varying water compo- sitions, a flotation model first has to be selected. As is commonly done when modeling the flotation rate of minerals (Ruuska et al., 2012), a first order kinetic equation was preferred. The model selected in this case is a so-called three-component batch flotation model since it provides a relatively good fit between experimental and modeled data, as illu- strated in Fig. 3 with the flotation of the fluorite ore in the BSW and in water containing 10 mmol/l MgCl. (Mg-rich water). This model links
Model coefficients for quartz.
Model coefficients for quartz.
In Fig. 4, the composition of the ore is defined in a regular mineral processing stream (named Feed (solids)) while the water throughput and composition are defined separately in a hydrometallurgical stream (named Feed (water)). Those two streams are mixed in the rod mill unit to produce a new stream (named Milled feed) that simultaneously car- ries the information related to the solid and the aqueous phases. This stream information is then carried to the conditioner unit, where Fig. 4. Simple HSC Sim flowsheet including water composition as an input.
In Fig. 4, the composition of the ore is defined in a regular mineral processing stream (named Feed (solids)) while the water throughput and composition are defined separately in a hydrometallurgical stream (named Feed (water)). Those two streams are mixed in the rod mill unit to produce a new stream (named Milled feed) that simultaneously car- ries the information related to the solid and the aqueous phases. This stream information is then carried to the conditioner unit, where Fig. 4. Simple HSC Sim flowsheet including water composition as an input.
Calculated values for the model parameters my, m,, ky, and k, when the Baseline Synthetic Water (BSW) is used as process water.
Calculated values for the model parameters my, m,, ky, and k, when the Baseline Synthetic Water (BSW) is used as process water.
Fig. 5. Fluorite recovery (a) and concentrate grade (b) as a function of [Ca2*] and [Mg*], where [F~] = Ommol/] and [SO,2~] = 0mmol/1. The sensitivity analysis in Fig. 5 highlights that magnesium and calcium ions have a fundamentally different effect on the flotation of the fluorite ore. Although both cations slightly decrease the purity of the concentrate, Mg”* has an adverse effect on the fluorite recovery whereas Ca?* tends to increase said recovery. In addition, it can be observed that the negative effect produced by the presence of Mg”* in
Fig. 5. Fluorite recovery (a) and concentrate grade (b) as a function of [Ca2*] and [Mg*], where [F~] = Ommol/] and [SO,2~] = 0mmol/1. The sensitivity analysis in Fig. 5 highlights that magnesium and calcium ions have a fundamentally different effect on the flotation of the fluorite ore. Although both cations slightly decrease the purity of the concentrate, Mg”* has an adverse effect on the fluorite recovery whereas Ca?* tends to increase said recovery. In addition, it can be observed that the negative effect produced by the presence of Mg”* in
Calculated process performance under baseline conditions.
Calculated process performance under baseline conditions.
Fig. 6. Fluorite recovery (a) and concentrate grade (b) as a function of [F~] and [SO,42~], where [Ca2*] = Ommol/] and [Mg?*] = 0 mmol/l.
Fig. 6. Fluorite recovery (a) and concentrate grade (b) as a function of [F~] and [SO,42~], where [Ca2*] = Ommol/] and [Mg?*] = 0 mmol/l.
Constraints for the optimization problem. Table 7
Constraints for the optimization problem. Table 7
Fig. 7. Consideration of two water sources as process water in HSC Sim.
Fig. 7. Consideration of two water sources as process water in HSC Sim.
Composition of the two available water sources on the mine site. Table 9
Composition of the two available water sources on the mine site. Table 9
Fig. 8. Variation of process performance as a function of tailings water re- circulation intensity.
Fig. 8. Variation of process performance as a function of tailings water re- circulation intensity.
Fig. 9. Integration of HSC Sim in the processing plant to help deciding on the fate of the currently used process water. The control platform is used to de- termine the best option to minimize water rejection while maintaining suffi- cient process performance.
Fig. 9. Integration of HSC Sim in the processing plant to help deciding on the fate of the currently used process water. The control platform is used to de- termine the best option to minimize water rejection while maintaining suffi- cient process performance.
Water composition fed to the processing plant and resulting process perfor- mance based on the selected option for the fate of the process water. References
Water composition fed to the processing plant and resulting process perfor- mance based on the selected option for the fate of the process water. References
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