626 5.2 Post-installation: Survey Following the successful installation and commissioning of the SK240 cell into the Ernest Henry Operations flotation circuit, a flotation survey was conducted to evaluate circuit performance during operation. Summary of the survey results is shown in Table 4. Table 4 – Survey results post-installation of SK240 cell Stream TPH Au Cu (g/t) Recovery (%) (%) Recovery (%) Rougher Feed 837.88 0.49 100 0.88 100 Rougher Concentrate 19.94 9.10 44.20 29.31 79.22 Scavenger Concentrate 91.18 2.03 1.44 SK240 Concentrate 3.93 34.78 33.35 21.58 11.51 Cleaner 3 Concentrate 22.66 9.00 49.68 27.40 84.16 Final Concentrate 26.59 12.81 83.03 26.54 95.67 Survey results indicated that the SK240 flash flotation cell recovered 74% of the gold and 65% of the copper reporting to the regrind circuit. Relative to pre‑installation performance, the SK240 substantially reduced the recirculation of valuable minerals within the regrind circuit, from 1750% prior to installation, the gold recirculating load has been reduced to 337% (based on the survey data), confirming the effectiveness of early recovery of liberated valuable particles. Table 5 presents the concentrate grades and associated recoveries from the post-installation survey and the simulation results from the previous section (4.2). Also shown in the table are the recoveries and grades for the Cleaner 3 concentrate and the final concentrate. Table 5 – Comparison of simulation and post-installation survey results Stream TPH Au Au Recovery Cu Cu Recovery (g/t) (%) (%) (%) Survey 3.93 34.78 33.35 21.58 11.51 SK240 Concentrate Pre_Sim #1 3.14 41.56 31.96 13.29 5.74 Pre_Sim #2 1.70 76.58 31.89 24.14 5.65 Survey 22.66 9.00 49.68 27.40 84.16 Cleaner 3 Concentrate Pre_Sim #1 22.34 9.60 52.50 29.09 89.39 Pre_Sim #2 22.44 9.57 52.56 28.99 89.47 Survey 26.59 12.81 83.03 26.54 95.67 Final Concentrate Pre_Sim #1 25.48 13.54 84.46 27.14 95.13 Pre_Sim #2 24.14 14.29 84.45 28.65 95.12 Pre‑simulation 1 (Pre_Sim #1) predicted a lower copper concentrate grade (13.29%) compared with the grade measured during the post‑installation survey (21.58%). This discrepancy was expected, as the simulation was based on performance data from the SK0.25 pilot unit rather than from a full‑scale cell. In addition to the considerable difference in scale between the pilot and installed units, the froth recovery characteristics observed in the pilot plant were not representative of those achieved in the full‑scale SK240. As a result, the pilot‑based model was unable to accurately predict full‑scale concentrate grade performance. However, the simulation results demonstrated that concentrate grade could be improved by adjusting the froth recovery factor (Pre‑Sim #2). This sensitivity analysis indicated that the model responded strongly to changes in froth recovery, highlighting the importance of accurately characterising full‑scale froth behaviour to improve predictive performance. Post-installation: Modeling and simulation to optimise performance A further objective of the campaign was to recalibrate the JKSimFloat model to support future simulations and optimisation of the Ernest Henry Operations flotation circuit. At this stage, the simulation work focused on identifying strategies to enhance overall flotation efficiency. The following simulation scenarios were evaluated to identify opportunities for improvement:
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