The Experts below are selected from a list of 81 Experts worldwide ranked by ideXlab platform
I K Craig - One of the best experts on this subject based on the ideXlab platform.
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an ekf observer to estimate semi autogenous Grinding Mill hold ups
Journal of Process Control, 2017Co-Authors: J Le D Rou, Andreas Steinboeck, Andreas Kugi, I K CraigAbstract:The first author gratefully appreciates support from the University of Pretoria postgraduate study abroad bursary programme. The second author gratefully acknowledges financial support provided by the Austrian Academy of Sciences in the form of an APART-fellowship at the Automation and Control Institute of Vienna University of Technology. The third author gratefully acknowledges financial support provided by the Austrian Federal Ministry of Science, Research and Economy, and the National Foundation for Research, Technology and Development. The fourth author would like to acknowledge the support of the National Research Foundation of South Africa (Grant No.90533).
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reducing the number of size classes in a cumulative rates model used for process control of a Grinding Mill circuit
Powder Technology, 2013Co-Authors: J Le D Roux, I K CraigAbstract:The number of size classes in a cumulative rates model of a Grinding Mill circuit is reduced to determine the minimum number required to provide a reasonably accurate model of the circuit for process control. Each reduced size class set is used to create a non-linear cumulative rates model which is linearised to design a linear model predictive controller. The accuracy of a model is determined by the ability of the corresponding model predictive controller to control important process variables in the Grinding Mill circuit as represented by the full non-linear cumulative rates model. Results show that a model with 25 size classes that provides valuable information for plant design and scale-up, can be reduced to a model containing only a small number of size class sets and still be suitable for process control. Although as few as 3 size classes can be used to obtain a fairly accurate model for process control, the distribution of these 3 size classes inuences the accuracy of the model. For a model to be useful for process control, the model should at least provide the directions in which the process variables change.
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analysis and validation of a run of mine ore Grinding Mill circuit model for process control
Minerals Engineering, 2013Co-Authors: J Le D Roux, I K Craig, D G Hulbert, A L HindeAbstract:Abstract A simple and novel non-linear model of a run-of-mine ore Grinding Mill circuit, developed for process control and estimation purposes, is validated. The model makes use of the minimum number of states and parameters necessary to produce responses that are qualitatively accurate. It consists of separate feeder, Mill, sump and hydrocyclone modules that can be connected to model different circuit configurations. The model uses five states: rocks, solids, fines, water and steel balls. Rocks are defined as too large to be discharged from the Mill, whereas solids, defined as particles small enough to leave the Mill, consist of out-of-specification coarse ore and in-specification fine ore fractions. The model incorporates a unique prediction of the rheology of the slurry within the Mill. A new hydrocyclone model is also presented. The model parameters are fitted to an existing plant’s sampling campaign data and a step-wise procedure is given to fit the model to steady-state data. Simulation test results of the model are compared to sampling campaign data of the same plant at different steady-state conditions. The model shows promise in estimating important process variables such as Mill power and product particle size and is deemed suitable for process control studies.
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Grinding Mill circuits a survey of control and economic concerns
IFAC Proceedings Volumes, 2008Co-Authors: I K CraigAbstract:A worldwide survey on Grinding Mill circuits in the mineral processing industry was conducted. The aims of this survey are to determine how Milling circuits are currently controlled, and to find out how key process variables are linked to economic benefits. The survey involves background information on the circuits, the choice of controlled and manipulated variables, the economic impact of the controlled variables, adopted control technologies, and assessment of control performance. 68 responses were received as a whole. Survey results are contrasted to the Milling control literature.
Roberto Roma - One of the best experts on this subject based on the ideXlab platform.
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integrating photovoltaic solar energy and a battery energy storage system to operate a semi autogenous Grinding Mill
Journal of Cleaner Production, 2017Co-Authors: G Pamparana, W Krach, Jannik Haas, Gustavo Diazferra, Rodrigo Palmabehnke, Roberto RomaAbstract:Abstract The mining sector in Chile is facing a steady increase of energy consumption, which is mainly explained by the lower grades, the increase in rock hardness, and deeper mines. Although much of the mining activity in Chile is located in the Atacama Desert, where the solar radiation is high, the integration of solar energy in mining remains elusive. This work explores, through simulation, the use of a solar photovoltaic energy system (PV) and a battery energy storage system (BESS), combined with energy from the grid, to operate a semi-autogenous Grinding Mill (SAG). For this, a novel mixed-integer linear programming model was developed to optimize the operational costs of the joint SAG-PV-BESS operation, after which the best sizes of PV and BESS components are found through scenario inspection. Further, the implementation of a demand side management (DSM) option is considered by a proper sequencing of the SAG feed to make a more efficient use of the solar energy. The results show an interdependent behavior of the SAG-PV-BESS system and a strong influence of DSM. The use of both PV and BESS allows reducing the contracted power for the SAG, without incurring into overconsumption penalties. If DSM is implemented, the system allocates the higher consumption, associated to harder ore, during daytime to use the available PV energy. Overall, the combined effect of PV and BESS operation of SAG Mills allows reducing the energy-associated operational costs. This effect is exacerbated when DSM is implemented.
Jannik Haas - One of the best experts on this subject based on the ideXlab platform.
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integrating photovoltaic solar energy and a battery energy storage system to operate a semi autogenous Grinding Mill
Journal of Cleaner Production, 2017Co-Authors: G Pamparana, W Krach, Jannik Haas, Gustavo Diazferra, Rodrigo Palmabehnke, Roberto RomaAbstract:Abstract The mining sector in Chile is facing a steady increase of energy consumption, which is mainly explained by the lower grades, the increase in rock hardness, and deeper mines. Although much of the mining activity in Chile is located in the Atacama Desert, where the solar radiation is high, the integration of solar energy in mining remains elusive. This work explores, through simulation, the use of a solar photovoltaic energy system (PV) and a battery energy storage system (BESS), combined with energy from the grid, to operate a semi-autogenous Grinding Mill (SAG). For this, a novel mixed-integer linear programming model was developed to optimize the operational costs of the joint SAG-PV-BESS operation, after which the best sizes of PV and BESS components are found through scenario inspection. Further, the implementation of a demand side management (DSM) option is considered by a proper sequencing of the SAG feed to make a more efficient use of the solar energy. The results show an interdependent behavior of the SAG-PV-BESS system and a strong influence of DSM. The use of both PV and BESS allows reducing the contracted power for the SAG, without incurring into overconsumption penalties. If DSM is implemented, the system allocates the higher consumption, associated to harder ore, during daytime to use the available PV energy. Overall, the combined effect of PV and BESS operation of SAG Mills allows reducing the energy-associated operational costs. This effect is exacerbated when DSM is implemented.
J Le D Roux - One of the best experts on this subject based on the ideXlab platform.
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reducing the number of size classes in a cumulative rates model used for process control of a Grinding Mill circuit
Powder Technology, 2013Co-Authors: J Le D Roux, I K CraigAbstract:The number of size classes in a cumulative rates model of a Grinding Mill circuit is reduced to determine the minimum number required to provide a reasonably accurate model of the circuit for process control. Each reduced size class set is used to create a non-linear cumulative rates model which is linearised to design a linear model predictive controller. The accuracy of a model is determined by the ability of the corresponding model predictive controller to control important process variables in the Grinding Mill circuit as represented by the full non-linear cumulative rates model. Results show that a model with 25 size classes that provides valuable information for plant design and scale-up, can be reduced to a model containing only a small number of size class sets and still be suitable for process control. Although as few as 3 size classes can be used to obtain a fairly accurate model for process control, the distribution of these 3 size classes inuences the accuracy of the model. For a model to be useful for process control, the model should at least provide the directions in which the process variables change.
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analysis and validation of a run of mine ore Grinding Mill circuit model for process control
Minerals Engineering, 2013Co-Authors: J Le D Roux, I K Craig, D G Hulbert, A L HindeAbstract:Abstract A simple and novel non-linear model of a run-of-mine ore Grinding Mill circuit, developed for process control and estimation purposes, is validated. The model makes use of the minimum number of states and parameters necessary to produce responses that are qualitatively accurate. It consists of separate feeder, Mill, sump and hydrocyclone modules that can be connected to model different circuit configurations. The model uses five states: rocks, solids, fines, water and steel balls. Rocks are defined as too large to be discharged from the Mill, whereas solids, defined as particles small enough to leave the Mill, consist of out-of-specification coarse ore and in-specification fine ore fractions. The model incorporates a unique prediction of the rheology of the slurry within the Mill. A new hydrocyclone model is also presented. The model parameters are fitted to an existing plant’s sampling campaign data and a step-wise procedure is given to fit the model to steady-state data. Simulation test results of the model are compared to sampling campaign data of the same plant at different steady-state conditions. The model shows promise in estimating important process variables such as Mill power and product particle size and is deemed suitable for process control studies.
G Pamparana - One of the best experts on this subject based on the ideXlab platform.
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integrating photovoltaic solar energy and a battery energy storage system to operate a semi autogenous Grinding Mill
Journal of Cleaner Production, 2017Co-Authors: G Pamparana, W Krach, Jannik Haas, Gustavo Diazferra, Rodrigo Palmabehnke, Roberto RomaAbstract:Abstract The mining sector in Chile is facing a steady increase of energy consumption, which is mainly explained by the lower grades, the increase in rock hardness, and deeper mines. Although much of the mining activity in Chile is located in the Atacama Desert, where the solar radiation is high, the integration of solar energy in mining remains elusive. This work explores, through simulation, the use of a solar photovoltaic energy system (PV) and a battery energy storage system (BESS), combined with energy from the grid, to operate a semi-autogenous Grinding Mill (SAG). For this, a novel mixed-integer linear programming model was developed to optimize the operational costs of the joint SAG-PV-BESS operation, after which the best sizes of PV and BESS components are found through scenario inspection. Further, the implementation of a demand side management (DSM) option is considered by a proper sequencing of the SAG feed to make a more efficient use of the solar energy. The results show an interdependent behavior of the SAG-PV-BESS system and a strong influence of DSM. The use of both PV and BESS allows reducing the contracted power for the SAG, without incurring into overconsumption penalties. If DSM is implemented, the system allocates the higher consumption, associated to harder ore, during daytime to use the available PV energy. Overall, the combined effect of PV and BESS operation of SAG Mills allows reducing the energy-associated operational costs. This effect is exacerbated when DSM is implemented.
