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SYNOPSIS Energy/power input in a flotation cell is an important parameter which, if optimised, can increase the flotation rate. The optimum energy/power input within a flotation cell is still a matter of conjecture and there is a need for a better understanding of the effect of energy input on flotation kinetics. This study investigates the effect of energy/power input on flotation kinetics in an oscillating grid flotation cell (OGC). The OGC decouples the processes of solid suspension and bubble generation as well as producing relatively isotropic and homogeneous turbulence with zero mean flow. Due to this, oscillating grids provide a potentially ideal environment for investigating the effects of energy input on flotation kinetics, which cannot be achieved in a mechanical flotation cell. The first objective of this thesis was to determine the effect of energy/power input on the flotation kinetics of sulphide minerals (galena, pyrite & pentlandite) and oxide minerals (apatite & hematite) in a laboratory scale oscillating grid flotation cell. The second objective was to compare the results from the laboratory OGC to comparative studies in the flotation literature and to fundamental models for particle-bubble contacting. The third objective was to determine whether the experimental results from the laboratory OGC are consistent with those from a pilot-scale OGC operating on a platinum ore. Galena, pyrite, pentlandite (-150 μm), apatite (-650 μm) and hematite (-75 μm) were floated in the laboratory OGC at energy inputs from 0.1 to 5.0 W/kg, using 0.13, 0.24, 0.58 and 0.82 mm bubble sizes (d₁₀), and at three collector dosages. Platinum ore (-75 μm) was floated in the pilot-scale OGC at energy inputs from 0 to 2.5 W/kg, using 0.71 and 1.47 mm bubble sizes (d₁₀). The effect of energy input on flotation kinetics was interpreted through trends in experimental flotation rate constants, simulated flotation rate constants and attachment-detachment flotation rate constants. Here, simulated flotation rate constants were calculated using a literature fundamental model for flotation in turbulent systems. This model is based on suitable expressions for the collision frequency, collision efficiency, attachment efficiency and stability efficiency, Attachment-detachment flotation rate constants were calculated using a kinetic model which allows for the two separate processes of bubble-particle collision/attachment and detachment. This model is based on kinetic expressions using empirical correlations for the attachment and detachment rate constants. Experimental flotation results show that the effect of energy input on the flotation rate is strongly dependent on the particle size and particle density and less dependent on bubble size and contact angle. Flotation rates generally increase with increasing particle size, decreasing bubble size and increasing contact angle, as is commonly found in the literature. Increasing energy input generally leads to an increase in the flotation rate for fine particles, an optimum flotation rate for intermediate particles and a decrease in the flotation rate for coarse particles. The optimum in the flotation rate for minerals with higher density is at a lower energy input than that for lower density minerals. The changes (increases/decreases) in the flotation rate with increasing energy input are very large for most of the conditions, indicating that this is an important parameter in flotation. Pilot scale results generally support the trends observed in the laboratory OGC. These findings are attributed to the effect of energy/power input on bubble-particle collection which is a balance between two competing effects, those of bubble-particle collision/attachment and those of bubble-particle detachment. Increasing energy input generally leads to significant increases in the flotation rate of fine particles, due to increased bubble-particle collision/attachment. Increasing energy input generally leads to an optimum flotation rate for intermediate particles, due to a combination of increased bubble-particle collision/attachment and detachment. For coarse particles, increasing energy input leads to significant increases in bubble-particle detachment. The relationship between the flotation rate and energy input is often described as k  ɛᴺ, in the absence of significant bubble-particle detachment. The typical values of N are in the range of 0.44-0.75 for theoretical studies and 0.7-1 for experimental studies. The values of N found in the current study are in the range of 0.7-1, which suggests that bubbleparticle collision/attachment has a stronger dependence on energy input than theory suggests. Simulated flotation results for fine particles compare well to the experimental data in terms of both trends and magnitude. This suggest that the turbulent collision model used is appropriate for fine particles. For intermediate particles there are differences between the simulated flotation rate constants and the experimental data, primarily in terms of trends. For coarse particles there are very large differences between simulated flotation rate constants and the experimental data. This is attributed to under prediction of the collision frequency/efficiency and incorrect prediction of the stability efficiency. Here, the stability efficiency is considered to be under predicted at low energy inputs and over predicted at high energy inputs. This suggests that the stability efficiency has a much stronger dependence on energy input than theory suggests. Attachment-detachment results show that the attachment rate constant has a stronger dependence on energy input than theory suggest, supporting finding from the experimental results and simulated results for coarser particles. In addition, the detachment rate constant has a much stronger dependence on energy input than theory suggests, supporting findings from both the experimental and simulated results. Based on the objectives of this study and literature reviewed, the following hypotheses were made at the outset 1) Increasing energy/power input will increase the rate of flotation of fine particles but will result in an optimum for intermediate and coarse particles. The position of this optimum will depend on the particle density, bubble size and contact angle. 2) Fundamental models based on the RMS turbulent velocity will be appropriate for describing flotation kinetics as turbulence in the oscillating grid cell is relatively homogeneous and isotropic and 3) Trends in flotation results for a laboratory and pilot-scale oscillating grid flotation cell will be comparable as the distribution of turbulence in OGCs at equivalent specific power inputs is scale independent. Hypothesis 1 was found to be valid for both fine and intermediate particles, but for coarse particles increasing energy input resulted in sharp decreases in the flotation rate. In addition, the increase in the flotation rate with increasing energy input was found to be more dependent on the particle size and particle density than the bubble size and contact angle. Hypothesis 2 was found to be valid for fine particles but not for intermediate or coarse particles. Here, it was found that the processes of bubble-particle collision/attachment and detachment have a stronger dependence on energy input than theory suggests. Hypothesis 3 was supported by general trends in results for the laboratory and pilot-scale oscillating grid flotation cells, but was not convincingly demonstrated.

Diese Forschung zielt darauf ab, den Einsatz realistischer Mineralmikrostrukturen in Mineralverarbeitungssimulationen Simulationen von Aufbereitungsprozessen zu ermöglichen. Insbesondere Zerkleinerungsprozesse, wie z.B. das Brechen und Mahlen von mineralischen Rohmaterialien, werden stark von der mineralischen Mikrostruktur beeinflusst, da die Textur und die Struktur der vielen Körner und ihre mikromechanischen Eigenschaften das makroskopische Bruchverhalten bestimmen. Ein Beispiel: Stellen wir uns vor, wir haben ein mineralisches Material, das im Wesentlichen aus Körnern zweier verschiedener Mineralphasen, wie Quarz und Feldspat, besteht. Wenn die mikromechanischen Eigenschaften dieser beiden Phasen unterschiedlich sind, wird sich dies wahrscheinlich auf das makroskopische Bruchverhalten auswirken. Unter der Annahme, dass die Körner eines der Minerale bei geringeren Belastungen brechen, ist es wahrscheinlich, dass sich ein Riss durch einen Stein dieses Materials durch die schwächeren Körner ausbreitet. Tatsächlich ist dies eine wichtige Eigenschaft für die Erzaufbereitung. Um wertvolle Mineralien aus einem Erz zu gewinnen, ist es wichtig, sie aus dem kommerziell wertlosen Material, in dem sie vorkommen, zu befreien. Dazu ist es wichtig zu wissen und zu verstehen, wie das Material auf Korngrößenebene bricht. Um diesen Bruch simulieren zu können, ist es wichtig, realistische Modelle der mineralischen Mikrostrukturen zu verwenden. Diese Studie zeigt, wie solche realistischen zweidimensionalen Mikrostrukturen auf der Grundlage der quantitativen Mikrostrukturanalyse am Computer erzeugt werden können. Darüber hinaus zeigt die Studie, wie diese synthetischen Mikrostrukturen dann in die gut etablierte Diskrete-Elemente-Methode integriert werden können, bei der der Bruch von mineralischem Material auf Korngrößenebene simuliert werden kann.:List of Acronyms VII List of Latin Symbols IX List of Greek Symbols XV 1 Introduction 1 1.1 Motivation for using realistic microstructures in Discrete Element Method (DEM) 1 1.2 Possibilities for using realistic mineral microstructures in DEM simulations . 4 1.3 Objective and disposition of the thesis . . . . . . . . . . . . . . . . . . . . 7 2 Background 9 2.1 Discrete Element Method (DEM) . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1.1 Fundamentals of the Discrete Element Method (DEM) . . . . . . . . 9 2.1.2 Applications of DEM in comminution science . . . . . . . . . . . . . 21 2.1.3 Limitations of DEM in comminution science . . . . . . . . . . . . . . 26 2.2 Quantitative Microstructural Analysis . . . . . . . . . . . . . . . . . . . . . 29 2.2.1 Fundamentals of the Quantitative Microstructural Analysis . . . . . . 29 2.2.2 Applied QMA in mineral processing . . . . . . . . . . . . . . . . . . 49 2.2.3 Applicability of the QMA for the synthesis of realistic microstructures 49 3 Synthesis of realistic mineral microstructures for DEM simulations 51 3.1 Development of a computer-assisted QMA for the analysis of real and synthetic mineral microstructures . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.1.1 Fundamentals of the computer-assisted QMA . . . . . . . . . . . . 53 3.1.2 The requirements for the false-color image. . . . . . . . . . . . . . 54 3.1.3 The conversion of a given real mineral microstructure into a false-color image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 3.1.4 Implementation of the point, line, and area analysis . . . . . . . . . 59 3.1.5 Selection of appropriate QMA parameters for analyzing two-dimensional microstructures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 3.1.6 Summary of the principles of the adapted Quantitative Microstructural Analysis (QMA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 3.2 Analysis of possible strategies for the microstructure synthesis . . . . . . . . 71 3.3 Implementation of the drawing method . . . . . . . . . . . . . . . . . . . . 76 3.3.1 Drawing of a single grain . . . . . . . . . . . . . . . . . . . . . . . 77 XVIII List of Greek Symbols 3.3.2 Drawing of multiple grains, which form a synthetic microstructure . . 81 3.3.3 Synthesizing mineral microstructures consisting of multiple phases . 85 3.4 The final program for microstructure analysis and synthesis . . . . . . . . . 89 3.4.1 Synthesis and analysis of an example microstructure . . . . . . . . . 90 3.4.2 Procedure for generating a realistic synthetic microstructure of a given real microstructure . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 4 Validation of the synthesis approach 103 4.1 Methodical considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 4.1.1 The basic idea of the validation procedure . . . . . . . . . . . . . . 103 4.1.2 The experimental realizations . . . . . . . . . . . . . . . . . . . . . 108 4.2 Basic indenter test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 4.2.1 Considerations for the basic indenter test . . . . . . . . . . . . . . . 109 4.2.2 Realization and evaluation of the real basic indenter test . . . . . . . 114 4.2.3 Realization and evaluation of the simulated basic indenter test . . . 127 4.2.4 Conclusions on the basic indenter test . . . . . . . . . . . . . . . . . 138 4.3 Extended indenter test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 4.3.1 Basic considerations for the extended indenter test . . . . . . . . . . 139 4.3.2 Realization and evaluation of the real extended indenter test . . . . 142 4.3.3 Realization and evaluation of the simulated extended indenter test . 154 4.3.4 Conclusions on the extended indenter test . . . . . . . . . . . . . . 171 4.4 Particle bed test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 4.4.1 Basic considerations for the particle bed test . . . . . . . . . . . . . 173 4.4.2 Realization and evaluation of the real particle bed test . . . . . . . . 176 4.4.3 Realization and evaluation of the simulated particle bed test . . . . . 188 4.4.4 Conclusions on the particle bed test . . . . . . . . . . . . . . . . . . 203 5 Conclusions and directions for future development 205 6 References 211 List of Figures 229 List of Tables 235 Appendix 237 / This research aims to make it possible to use realistic mineral microstructures in simulations of mineral processing. In particular, comminution processes, such as the crushing and grinding of raw mineral materials, are highly aff ected by the mineral microstructure, since the texture and structure of the many grains and their micromechanical properties determine the macroscopic fracture behavior. To illustrate this, consider a mineral material that essentially consists of grains of two diff erent mineral phases, such as quartz and feldspar. If the micromechanical properties of these two phases are diff erent, this will likely have an impact on the macroscopic fracture behavior. Assuming that the grains of one of the minerals break at lower loads, it is likely that a crack through a stone of that material will spread through the weaker grains. In fact, this is an important property for ore processing. In order to extract valuable minerals from an ore, it is important to liberate them from the commercially worthless material in which they are found. For this, it is essential to know and understand how the material breaks at grain-size level. To be able to simulate this breakage, it is important to use realistic models of the mineral microstructures. This study demonstrates how such realistic two-dimensional microstructures can be generated on the computer based on quantitative microstructural analysis. Furthermore, the study shows how these synthetic microstructures can then be incorporated into the well-established discrete element method, where the breakage of mineral material can be simulated at grain-size level.:List of Acronyms VII List of Latin Symbols IX List of Greek Symbols XV 1 Introduction 1 1.1 Motivation for using realistic microstructures in Discrete Element Method (DEM) 1 1.2 Possibilities for using realistic mineral microstructures in DEM simulations . 4 1.3 Objective and disposition of the thesis . . . . . . . . . . . . . . . . . . . . 7 2 Background 9 2.1 Discrete Element Method (DEM) . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1.1 Fundamentals of the Discrete Element Method (DEM) . . . . . . . . 9 2.1.2 Applications of DEM in comminution science . . . . . . . . . . . . . 21 2.1.3 Limitations of DEM in comminution science . . . . . . . . . . . . . . 26 2.2 Quantitative Microstructural Analysis . . . . . . . . . . . . . . . . . . . . . 29 2.2.1 Fundamentals of the Quantitative Microstructural Analysis . . . . . . 29 2.2.2 Applied QMA in mineral processing . . . . . . . . . . . . . . . . . . 49 2.2.3 Applicability of the QMA for the synthesis of realistic microstructures 49 3 Synthesis of realistic mineral microstructures for DEM simulations 51 3.1 Development of a computer-assisted QMA for the analysis of real and synthetic mineral microstructures . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.1.1 Fundamentals of the computer-assisted QMA . . . . . . . . . . . . 53 3.1.2 The requirements for the false-color image. . . . . . . . . . . . . . 54 3.1.3 The conversion of a given real mineral microstructure into a false-color image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 3.1.4 Implementation of the point, line, and area analysis . . . . . . . . . 59 3.1.5 Selection of appropriate QMA parameters for analyzing two-dimensional microstructures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 3.1.6 Summary of the principles of the adapted Quantitative Microstructural Analysis (QMA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 3.2 Analysis of possible strategies for the microstructure synthesis . . . . . . . . 71 3.3 Implementation of the drawing method . . . . . . . . . . . . . . . . . . . . 76 3.3.1 Drawing of a single grain . . . . . . . . . . . . . . . . . . . . . . . 77 XVIII List of Greek Symbols 3.3.2 Drawing of multiple grains, which form a synthetic microstructure . . 81 3.3.3 Synthesizing mineral microstructures consisting of multiple phases . 85 3.4 The final program for microstructure analysis and synthesis . . . . . . . . . 89 3.4.1 Synthesis and analysis of an example microstructure . . . . . . . . . 90 3.4.2 Procedure for generating a realistic synthetic microstructure of a given real microstructure . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 4 Validation of the synthesis approach 103 4.1 Methodical considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 4.1.1 The basic idea of the validation procedure . . . . . . . . . . . . . . 103 4.1.2 The experimental realizations . . . . . . . . . . . . . . . . . . . . . 108 4.2 Basic indenter test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 4.2.1 Considerations for the basic indenter test . . . . . . . . . . . . . . . 109 4.2.2 Realization and evaluation of the real basic indenter test . . . . . . . 114 4.2.3 Realization and evaluation of the simulated basic indenter test . . . 127 4.2.4 Conclusions on the basic indenter test . . . . . . . . . . . . . . . . . 138 4.3 Extended indenter test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 4.3.1 Basic considerations for the extended indenter test . . . . . . . . . . 139 4.3.2 Realization and evaluation of the real extended indenter test . . . . 142 4.3.3 Realization and evaluation of the simulated extended indenter test . 154 4.3.4 Conclusions on the extended indenter test . . . . . . . . . . . . . . 171 4.4 Particle bed test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 4.4.1 Basic considerations for the particle bed test . . . . . . . . . . . . . 173 4.4.2 Realization and evaluation of the real particle bed test . . . . . . . . 176 4.4.3 Realization and evaluation of the simulated particle bed test . . . . . 188 4.4.4 Conclusions on the particle bed test . . . . . . . . . . . . . . . . . . 203 5 Conclusions and directions for future development 205 6 References 211 List of Figures 229 List of Tables 235 Appendix 237