651 A full factorial experimental program was conducted to quantify the influence of baffling and superficial gas velocity (Jg). The cell was operated in two baffle configurations: a conventional rotor-stator assembly, or a stator-free mode with four flat baffles mounted close to the walls. Four levels of Jg were tested for each baffling mode, resulting in 8 experiments, with an additional 2 repeats to estimate experimental error. Table 1 summarizes the tested factors and levels. Table 1 – Experimental design Factor Levels Baffling Stator, Baffles Jg (cm/s) 0.0, 0.5, 1.0, 1.5 Particle settling at the tank bottom was monitored using a camera positioned beneath the cell. To trace suspension behaviour, 1 kg of +106-150 µm silica was added into the cell. The cell was operated at low percent solids, with the tracer being the only solid material. The critical impeller speed for just suspension (Njs) was measured by incrementally increasing the impeller speed until no particles remained settled for more than one second (Zwietering, 1958). The system was then set at the observed Njs. Power draw was measured using a power meter that recorded the electrical energy consumption of the flotation mechanism. To isolate the energy required to agitate the pulp, measurements were corrected by subtracting the no-load power. A Guided Radar Laser (GRL) was utilized to measure the position of the surface (Lewis, 2007; Morrison, 2017). Using a Fast Fourier Transform (FFT), the variation of surface position over time was converted into an interface oscillation parameter. The oscillation parameter corresponded to the largest amplitude in the frequency spectrum generated by the FFT (Morrison, 2023). The amplitude produced by the FFT does not represent physical displacement directly. It is the result of a mathematical transformation of the time domain signal into the frequency domain. FFT magnitudes are useful for studying relative changes in signal strength across frequencies, but they do not correspond to actual physical dimensions. 3. RESULTS AND DISCUSSION The experimental data were analyzed using statistical regression modelling to evaluate the effects of the studied variables on the critical impeller speed (Njs), power draw (Pjs), and interface oscillations (Θjs). The Means of Means method was applied to identify key trends, which were interpreted in relation to the likely underlying mechanisms. 3.1 Effect of baffling and airflow rate on the critical impeller speed (Njs) A statistical regression model was developed to assess the influence of the variables on Njs. The derived model is shown in Equation 1. The model achieved an adjusted R2 of 97%, as summarized in Table 2. Njs = 465.9 + 689.9 Jg - 102.8 Baffling - 203.0 Jg2 - 180.3 Baffling*Jg (1)
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