Validation Of The AMIRA P9 Flotation Model Using The Floatability Characterisation Test Rig (FCTR) (42de3f2a-5b83-478d-9e10-9fa673cd825a)

The Floatability Characterisation Test Rig (FCTR) is a self-contained, highly instrumented, mobile pilot plant. It was developed as part of the AMIRA P9 project, primarily to determine ore floatability characteristics and to develop and validate flotation plant modelling, scale-up and simulation methodologies. This paper describes the use of the FCTR in validating the AMIRA P9 flotation model and modelling methodology. In 2001 the FCTR was installed and operated in parallel with WMC's (now BHP Billiton's) Kambalda Nickel Operation. The FCTR was operated using four different circuit configurations of increasing complexity. Metallurgical surveys, cell characterisation measurements and batch flotation tests were performed around each circuit. This allowed the calibration of a number of flotation models using a combination of data from one, two, three or four circuit configurations. The calibrated flotation models were then validated using predictive validation. To do this, data around a further five FCTR circuit configurations were collected (three of which are presented in this paper). The performance of each of the five circuit configurations was predicted using JKSimFloat V6.1 and the parameters from the various calibrated flotation models. The predicted performance was compared to the experimentally determined performance of each circuit. The validation of the AMIRA P9 model was shown to be largely successful except in the case where the reagent addition (depressant) to the validation circuit was different to that in the calibration circuits. The results also provided information regarding the required complexity of the calibration circuit and how many calibration circuits are required to obtain an accurate prediction of circuit performance. These results have increased the confidence in the AMIRA P9 flotation modelling methodology and have provided important information on what data must be collected to allow the accurate prediction of plant performance using the floatability component modelling approach.