Advancing Flotation Process Optimization: Integration of Hydrodynamic Measurement, Bubble Size Characterization, and Drift Flux Modeling for Industrial Applications
Thesis event information
Date and time of the thesis defence
Place of the thesis defence
L5
Topic of the dissertation
Advancing Flotation Process Optimization: Integration of Hydrodynamic Measurement, Bubble Size Characterization, and Drift Flux Modeling for Industrial Applications
Doctoral candidate
Master of Minery Contracts Management Claudio Leiva Hurtubia
Faculty and unit
University of Oulu Graduate School, Faculty of Technology, Oulu Mining School
Subject of study
Mineral processing
Opponent
PhD in Process and Chemical Engineering Martin Rudolph , Helmholtz Institute Freiberg for Resource Technology
Custos
PhD in Physical Chemistry Saija Luukkanen, Oulu Mining School
Improving the Flotation Process by Measuring Water and Air Flow, Bubble Sizes, and Predicting Bubble Behavior for Industry Use.
Flotation is a key method for separating valuable minerals from gangue in mineral processing. However, the recovery of fine hydrophilic gangue is a challenge that negatively impacts the grade of the concentrate. This study aims to improve the flotation process by focusing on the transport medium of mineral particles and water. The research incorporates an innovative sensor-based approach for evaluating the performance of flotation circuits and the impact of surfactants on bubble hydrodynamics and their effect on bubble size distribution prediction.
The study proposes a new methodology for holdup measurement, which improves the accuracy of gas velocity calculation using a new algorithm. Experimental results and industrial device validation indicate that the new system can measure superficial gas velocity (Jg) online and self-calibrate, with a 2 [%] error and the froth depth error being +/- 1 [cm]. Furthermore, the research introduces a multiparameter sensor for measuring gas dispersion in industrial flotation cells, which has been experimentally designed and validated in an industrial environment (TRL 8).
In addition, the study incorporates a surfactant-type parameter in the drift flux model to consider the impact of surfactants on bubble hydrodynamics. This modification aims to improve the accuracy of bubble size distribution prediction. The results show that the confidence interval for bubble size estimation based on drift flux in column flotation is reduced, contributing to a better understanding of surfactant impact on bubble swarm hydrodynamics.
The proposed online gas dispersion sensor and the new algorithms for bubble size distribution measurements are expected to optimize the flotation process as they improve the accuracy of bubble size distribution measurements. The study also includes a comparison of bubble size distributions using bubble viewer algorithms, which predict bubble size distributions with an error of less than 5 [%] and derivations close to 0.1 mm in the determination of D32.
In conclusion, this PhD thesis significantly contributes to mineral processing, specifically the development of the online Jg and froth depth sensor and the bubble viewer sensor location process. The research enhances the understanding of surfactant impact on bubble hydrodynamics. It provides innovative solutions that can significantly improve the accuracy of gas dispersion measurement and bubble size distribution prediction in industrial flotation cells.
The study proposes a new methodology for holdup measurement, which improves the accuracy of gas velocity calculation using a new algorithm. Experimental results and industrial device validation indicate that the new system can measure superficial gas velocity (Jg) online and self-calibrate, with a 2 [%] error and the froth depth error being +/- 1 [cm]. Furthermore, the research introduces a multiparameter sensor for measuring gas dispersion in industrial flotation cells, which has been experimentally designed and validated in an industrial environment (TRL 8).
In addition, the study incorporates a surfactant-type parameter in the drift flux model to consider the impact of surfactants on bubble hydrodynamics. This modification aims to improve the accuracy of bubble size distribution prediction. The results show that the confidence interval for bubble size estimation based on drift flux in column flotation is reduced, contributing to a better understanding of surfactant impact on bubble swarm hydrodynamics.
The proposed online gas dispersion sensor and the new algorithms for bubble size distribution measurements are expected to optimize the flotation process as they improve the accuracy of bubble size distribution measurements. The study also includes a comparison of bubble size distributions using bubble viewer algorithms, which predict bubble size distributions with an error of less than 5 [%] and derivations close to 0.1 mm in the determination of D32.
In conclusion, this PhD thesis significantly contributes to mineral processing, specifically the development of the online Jg and froth depth sensor and the bubble viewer sensor location process. The research enhances the understanding of surfactant impact on bubble hydrodynamics. It provides innovative solutions that can significantly improve the accuracy of gas dispersion measurement and bubble size distribution prediction in industrial flotation cells.
Last updated: 9.4.2025