Flotation is the separation process most used to recover valuable minerals from sulphide ores. The design of industrial flotation plants is a complex process involving many stages. Current design practice involves performing laboratory scale grinding and batch flotation tests, followed by a circuit design based on the scale-up of the laboratory kinetics and recovery-grade data. A pilot plant is then operated to evaluate the performance of the circuit based on recovery and grade, usually in the configuration of the intended full-scale plant. The circuit design is refined and economically evaluated after which the design of the full-scale plant is performed. A new approach to full-scale flotation plant design has been proposed by the Julius Kruttschnitt Mineral Research Centre and the Mineral Processing Research Unit of the University of Cape Town, as part of the Australian Minerals Industries Research Association (AMIRA) P9 Project. In this new methodology, the effects of the ore on plant performance are decoupled from the circuit effects. The ore properties are characterised by operating the pilot plant in as simple a configuration as possible. The pilot plant units are configured to perform a similar duty (in terms of mineral content and particle size) to the full-scale operation and their response measured. An important factor in the success of the methodology is having a pilot plant that is capable of accurately characterising the ore properties. For this purpose, the Wemco® Floatability Characterisation Test Rig (FCTR) was built. The FCTR is a self-contained, highly instrumented mobile pilot plant designed to develop and validate the new flotation plant design methodology. The aims of this thesis were to propose, develop and validate a methodology for using the FCTR to design industrial flotation plants. The hypothesis was that full-scale flotation plant design could be accurately performed using the P9 flotation model and modelling and scale-up methodologies, in conjunction with the FCTR. Test work was performed in three main areas: calibration of the ore characteristics and model parameters for the flotation model currently used by the AMIRA P9 Project; validation of the flotation model and modelling methodology; and prediction of full-scale plant performance using parameters determined on the FCTR. The ore floatability characteristics were calibrated using four FCTR circuits of increasing complexity. The ore floatability characteristics were determined for various models derived from data from one, two, three and four calibration circuits. Validation of the flotation model and modelling methodology was performed using three validation methods: internal validity tests, parameter sensitivity tests and predictive validation. From the internal validity tests, some of the models did not meet the validation criteria. The parameter sensitivity tests used Monte Carlo simulations to determine the sensitivity of the regressed model parameters. The tests produced small differences in the values determined from the models and the average values from the Monte Carlo simulations. The floatability characteristics appeared to be stable and unique. Predictive validation was performed using five FCTR circuits, different in configuration to the calibration circuits. The predictive validation was performed using the floatability characteristics determined from each of the calibration models, in conjunction with estimates of the model parameters. Overall, the predictions of the circuit performance were accurate and within experimental standard deviations for most streams in the circuits. The predictions of the key parameters of pentlandite and chalcopyrite recovery were accurate, especially for the final concentrate. The prediction of pyrrhotite recovery produced the largest errors. The prediction of pyrrhotite recovery appeared to be dependent on the addition of depressant to the cleaner and recleaner circuits of the circuit to be predicted. When the depressant addition rates were significantly different from those used in the calibration circuits, the prediction of pyrrhotite recovery was inaccurate. These errors were however reduced when experimental water recovery values were used. The extensive and robust validation of the flotation model and modelling methodology has shown that the flotation model and modelling methodology are valid under certain conditions. This test work represents the first comprehensive validation of the flotation model and modelling methodology incorporating changes in circuit configuration. Using the proposed modelling and scale-up methodology in conjunction with the FCTR, the metallurgical performance of three industrial flotation circuits were predicted. The predicted results were then compared to the experimentally determined results around the industrial circuits. In each case, a scale-up factor between the ore floatability characteristics determined on the FCTR, and the full-scale floatability characteristics, was required to achieve an accurate prediction. The scale-up factor ranged from 0.17 to 0.97 for the case studies investigated. In light of the results from each stage of test work, the proposed flotation plant design methodology was refined. With this methodology and the continual development of techniques for the measurement and prediction of the P9 flotation model parameters, accurate industrial plant design using the FCTR will become possible. With the addition of other unit operations, such as comminution, into the flowsheet, this methodology will eventually lead to the achievement of the ultimate goal of accurate plant design of green-field sites.

Flotation is the separation process most used to recover valuable minerals from sulphide ores. The design of industrial flotation plants is a complex process involving many stages. Current design practice involves performing laboratory scale grinding and batch flotation tests, followed by a circuit design based on the scale-up of the laboratory kinetics and recovery-grade data. A pilot plant is then operated to evaluate the performance of the circuit based on recovery and grade, usually in the configuration of the intended full-scale plant. The circuit design is refined and economically evaluated after which the design of the full-scale plant is performed. A new approach to full-scale flotation plant design has been proposed by the Julius Kruttschnitt Mineral Research Centre and the Mineral Processing Research Unit of the University of Cape Town, as part of the Australian Minerals Industries Research Association (AMIRA) P9 Project. In this new methodology, the effects of the ore on plant performance are decoupled from the circuit effects. The ore properties are characterised by operating the pilot plant in as simple a configuration as possible. The pilot plant units are configured to perform a similar duty (in terms of mineral content and particle size) to the full-scale operation and their response measured. An important factor in the success of the methodology is having a pilot plant that is capable of accurately characterising the ore properties. For this purpose, the Wemco® Floatability Characterisation Test Rig (FCTR) was built. The FCTR is a self-contained, highly instrumented mobile pilot plant designed to develop and validate the new flotation plant design methodology. The aims of this thesis were to propose, develop and validate a methodology for using the FCTR to design industrial flotation plants. The hypothesis was that full-scale flotation plant design could be accurately performed using the P9 flotation model and modelling and scale-up methodologies, in conjunction with the FCTR. Test work was performed in three main areas: calibration of the ore characteristics and model parameters for the flotation model currently used by the AMIRA P9 Project; validation of the flotation model and modelling methodology; and prediction of full-scale plant performance using parameters determined on the FCTR. The ore floatability characteristics were calibrated using four FCTR circuits of increasing complexity. The ore floatability characteristics were determined for various models derived from data from one, two, three and four calibration circuits. Validation of the flotation model and modelling methodology was performed using three validation methods: internal validity tests, parameter sensitivity tests and predictive validation. From the internal validity tests, some of the models did not meet the validation criteria. The parameter sensitivity tests used Monte Carlo simulations to determine the sensitivity of the regressed model parameters. The tests produced small differences in the values determined from the models and the average values from the Monte Carlo simulations. The floatability characteristics appeared to be stable and unique. Predictive validation was performed using five FCTR circuits, different in configuration to the calibration circuits. The predictive validation was performed using the floatability characteristics determined from each of the calibration models, in conjunction with estimates of the model parameters. Overall, the predictions of the circuit performance were accurate and within experimental standard deviations for most streams in the circuits. The predictions of the key parameters of pentlandite and chalcopyrite recovery were accurate, especially for the final concentrate. The prediction of pyrrhotite recovery produced the largest errors. The prediction of pyrrhotite recovery appeared to be dependent on the addition of depressant to the cleaner and recleaner circuits of the circuit to be predicted. When the depressant addition rates were significantly different from those used in the calibration circuits, the prediction of pyrrhotite recovery was inaccurate. These errors were however reduced when experimental water recovery values were used. The extensive and robust validation of the flotation model and modelling methodology has shown that the flotation model and modelling methodology are valid under certain conditions. This test work represents the first comprehensive validation of the flotation model and modelling methodology incorporating changes in circuit configuration. Using the proposed modelling and scale-up methodology in conjunction with the FCTR, the metallurgical performance of three industrial flotation circuits were predicted. The predicted results were then compared to the experimentally determined results around the industrial circuits. In each case, a scale-up factor between the ore floatability characteristics determined on the FCTR, and the full-scale floatability characteristics, was required to achieve an accurate prediction. The scale-up factor ranged from 0.17 to 0.97 for the case studies investigated. In light of the results from each stage of test work, the proposed flotation plant design methodology was refined. With this methodology and the continual development of techniques for the measurement and prediction of the P9 flotation model parameters, accurate industrial plant design using the FCTR will become possible. With the addition of other unit operations, such as comminution, into the flowsheet, this methodology will eventually lead to the achievement of the ultimate goal of accurate plant design of green-field sites.

Flotation is the separation process most used to recover valuable minerals from sulphide ores. The design of industrial flotation plants is a complex process involving many stages. Current design practice involves performing laboratory scale grinding and batch flotation tests, followed by a circuit design based on the scale-up of the laboratory kinetics and recovery-grade data. A pilot plant is then operated to evaluate the performance of the circuit based on recovery and grade, usually in the configuration of the intended full-scale plant. The circuit design is refined and economically evaluated after which the design of the full-scale plant is performed. A new approach to full-scale flotation plant design has been proposed by the Julius Kruttschnitt Mineral Research Centre and the Mineral Processing Research Unit of the University of Cape Town, as part of the Australian Minerals Industries Research Association (AMIRA) P9 Project. In this new methodology, the effects of the ore on plant performance are decoupled from the circuit effects. The ore properties are characterised by operating the pilot plant in as simple a configuration as possible. The pilot plant units are configured to perform a similar duty (in terms of mineral content and particle size) to the full-scale operation and their response measured. An important factor in the success of the methodology is having a pilot plant that is capable of accurately characterising the ore properties. For this purpose, the Wemco® Floatability Characterisation Test Rig (FCTR) was built. The FCTR is a self-contained, highly instrumented mobile pilot plant designed to develop and validate the new flotation plant design methodology. The aims of this thesis were to propose, develop and validate a methodology for using the FCTR to design industrial flotation plants. The hypothesis was that full-scale flotation plant design could be accurately performed using the P9 flotation model and modelling and scale-up methodologies, in conjunction with the FCTR. Test work was performed in three main areas: calibration of the ore characteristics and model parameters for the flotation model currently used by the AMIRA P9 Project; validation of the flotation model and modelling methodology; and prediction of full-scale plant performance using parameters determined on the FCTR. The ore floatability characteristics were calibrated using four FCTR circuits of increasing complexity. The ore floatability characteristics were determined for various models derived from data from one, two, three and four calibration circuits. Validation of the flotation model and modelling methodology was performed using three validation methods: internal validity tests, parameter sensitivity tests and predictive validation. From the internal validity tests, some of the models did not meet the validation criteria. The parameter sensitivity tests used Monte Carlo simulations to determine the sensitivity of the regressed model parameters. The tests produced small differences in the values determined from the models and the average values from the Monte Carlo simulations. The floatability characteristics appeared to be stable and unique. Predictive validation was performed using five FCTR circuits, different in configuration to the calibration circuits. The predictive validation was performed using the floatability characteristics determined from each of the calibration models, in conjunction with estimates of the model parameters. Overall, the predictions of the circuit performance were accurate and within experimental standard deviations for most streams in the circuits. The predictions of the key parameters of pentlandite and chalcopyrite recovery were accurate, especially for the final concentrate. The prediction of pyrrhotite recovery produced the largest errors. The prediction of pyrrhotite recovery appeared to be dependent on the addition of depressant to the cleaner and recleaner circuits of the circuit to be predicted. When the depressant addition rates were significantly different from those used in the calibration circuits, the prediction of pyrrhotite recovery was inaccurate. These errors were however reduced when experimental water recovery values were used. The extensive and robust validation of the flotation model and modelling methodology has shown that the flotation model and modelling methodology are valid under certain conditions. This test work represents the first comprehensive validation of the flotation model and modelling methodology incorporating changes in circuit configuration. Using the proposed modelling and scale-up methodology in conjunction with the FCTR, the metallurgical performance of three industrial flotation circuits were predicted. The predicted results were then compared to the experimentally determined results around the industrial circuits. In each case, a scale-up factor between the ore floatability characteristics determined on the FCTR, and the full-scale floatability characteristics, was required to achieve an accurate prediction. The scale-up factor ranged from 0.17 to 0.97 for the case studies investigated. In light of the results from each stage of test work, the proposed flotation plant design methodology was refined. With this methodology and the continual development of techniques for the measurement and prediction of the P9 flotation model parameters, accurate industrial plant design using the FCTR will become possible. With the addition of other unit operations, such as comminution, into the flowsheet, this methodology will eventually lead to the achievement of the ultimate goal of accurate plant design of green-field sites.

Thesis (Ph.D.)--University of Tulsa, 1990. / Bibliography: leaves 69-71.

Thesis (Ph.D.)--University of Tulsa, 1990. / Includes index. Bibliography: leaves 143-147.

Thesis (Ph. D.)--Ohio University, June, 1994. / Title from PDF t.p.

Thesis (Ph.D.)--University of Wollongong, 2005. / Typescript. Includes bibliographical references: leaf 159-168.

Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1994. / Vita. Abstract. Includes bibliographical references (leaves 98-101). Also available via the Internet.

Thesis (M. App. Sc.)--Carleton University, 2005. / Includes bibliographical references (p. 110-114). Also available in electronic format on the Internet.

Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1994. / Vita. Abstract. Includes bibliographical references (leaves 106-113). Also available via the Internet.