Prediction of barite recovery and grade by multiple linear regression (MLR) analysis in concentrating of barite tailings by using multi-gravity separator (MGS)
Künye
Deniz, V. (2021). Prediction of barite recovery and grade by multiple linear regression (MLR) analysis in concentrating of barite tailings by using multi-gravity separator (MGS). Particulate Science and Technology, 39(6), 748-756.Özet
Multi-gravity separator (MGS) is a very effective separator for very fine-sized minerals. In this study, for the first time in the literature, the concentrability of a typical barite plant fines (tailing) was investigated by using anMGS. For this purpose, the effects of different operating parameters such as the solids ratio of feed pulp, the rotational drum speed, the wash water flow rate, and the tilt angle were studied in detail. Additionally, multiple linear regression (MLR) analyses were performed to understand the effect of operating parameters on the separator (MGS) performance for barite tailings, and the equations were developed to predict the recovery and the grade of barite concentrate fraction. As a result of experiments, a barite concentrate from the barite tailing containing 38.40% BaSO(4)was obtained with 92.55% BaSO(4)grade and a total barite recovery of 78.41%.MLRstudies also showed that there were good correlations between the experimental results and predicted values (R(2)values of 0.928 and 0.853 for the recovery and grade of barite concentrate, respectively). Based on the results obtained from this study, it can be concluded that while the solids ratio of feed pulp showed an important effect on the BaSO(4)grade, the tilt angle had an effect on the recovery of the barite concentrate.