Application of response surface methodology and central composite rotatable design for modeling and optimization of a multi-gravity separator for chromite concentration


Aslan N.

POWDER TECHNOLOGY, cilt.185, ss.80-86, 2008 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 185 Konu: 1
  • Basım Tarihi: 2008
  • Doi Numarası: 10.1016/j.powtec.2007.10.002
  • Dergi Adı: POWDER TECHNOLOGY
  • Sayfa Sayıları: ss.80-86

Özet

In this study, the application of response surface methodology (RSM) and central composite rotatable design (CCRD) for modeling and optimization of the influence of some operating variables on the performance of a multi-gravity separator (MGS) for chromite concentration is discussed. Three MGS operating variables, namely drum speed, tilt angle, and wash water flow rate were changed during the concentration tests based on CCRD. The range of values of the MGS variables used in the design were a drum speed of 133-217 rpm, tilt angle of 1.6 degrees-8.4 degrees, and wash water flow rate of 1.3-4.7 lpm. A total of 20 concentration tests were conducted using MGS on chromite ore obtained from Kangal/Eskikoy-Turkey. In order to optimize chromite concentration with MGS, mathematical model equations were derived by computer simulation programming applying least squares method using MATLAB 7.1. These equations that are second-order response functions representing concentrate grade and recovery were expressed as functions of three operating parameters of MGS. Predicted values were found to be in good agreement with experimental values (R-2 values of 0.96 and 0.98 for concentrate grade and recovery, respectively). In order to gain a better understanding of the three variables for optimal MGS performance, the models were presented as 3-D response surface graphs. This study has shown that the RSM and CCRD could efficiently be applied for the modeling of NIGS for chromite concentration and it is an economical way of obtaining the maximum amount of information in a short period of time and with the fewest number of experiments. (c) 2007 Elsevier B.V. All rights reserved.