Prediction of cyanide recovery from silver leaching tailings with AVR using multivariable regression analysis

In this study, the tailings of the silver leaching plant, Eti Gumus AS, Turkey, containing high amounts of cyanide were tested to determine optimum recovery of cyanide, using packed columns for volatilization stage of AVR (acidification, volatilization or stripping, reneutralization). All recovery tests were performed in a pilot plant constructed using random packing with column internals and practised for mass transfer calculations. The main parametrical results of each test were measured in the laboratory and statistical analysis was performed using multivariable regression analysis. The parameters investigated were the viscosity of slurry, specific density, flow time of slurry in the funnel, air velocity, pulp density (wt%), pH, gas/liquid flow ratio (G/L), operating time, recovery rates and ambient temperature. The complex effects of the parameters were evaluated by multivariable linear regression analysis, favourable models then being corrected by using variance analysis. Verification of the predictive models to prove their practical validity and residual analysis of data were performed for preliminary treatment using the AVR process of leached tailings.