Corrosion and Hydrometallurgy
Evaluation of the corrosion behaviour and performance of metal alloys used and proposed for extended use in process engineering equipment to extract nickel from nickel sulfide flotation concentrate.
Development of an improved understanding of the corrosion processes and mechanisms that occur in environments with variable pressure, temperature, solution chemistry and atmosphere.
Research and development on the hydrometallurgical processes such as leaching, solvent-extraction, ion exchange and electrowinning proposed to dissolve, separate and extract metals such as nickel and metal by-products from flotation concentrate as a function of ore type and aqueous solution chemistry.
Process Control and Simulations
Objectives
- Development of a new process control and simulation research network at IIC while incorporating industrial partners. Currently the main partners are INCO and Honeywell.
- Development of advanced process control and simulation capacity for training highly qualified personnel for process industry. This will include development of undergraduate program for process engineering and graduate research in process control.
- Expansion of the research to key process industries across Canada, including refinery, oil and gas processing, mining and mineral processing and chemical industry.
Research
The process control group will develop advanced process control techniques and at the beginning this research focuses on Inco’s Hydrometallurgy plant. The research focuses on developing new control techniques for unit operations and also plant wide process control methodologies. Process industries aim at producing limited bulk volumes or continuous production of a wide range of products. The challenges include maintaining product quality and throughput, while maintaining other operating constraints such as waste, production demand, and material quality. Although unit operations aims at producing the best set-point control under given input conditions, the constraints imposed by other units forces them to operate at sub-optimal level. Meeting these objectives requires a high quality of technology in the fields of on-line optimization, advanced process control, and the integration of several control layers. The research in this area focuses on developing intelligent control techniques, particularly for multi-variable process control. The work includes number of control related topics, including multivariable controller design, optimization, adaptive and predictive control, nonlinear control, estimation and identification, process monitoring and diagnostics