Integrated modelling of a smelter off-gas system

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In mineral and metallurgical industry, smelters process sulfide ores to produce nickel, copper, cobalt, and precious metals. Smelting and refining of the metals are usually accompanied by sulfur dioxide and other gas emissions, which may cause undesirable working environment and polluted air. Smelter off-gas cleaning systems treat the off-gas emissions and minimize the environmental impact of the smelter processes. With growing awareness of the importance of environmental protection and tightened environmental policy, extensive study on smelter off-gas system is necessary. Optimal operation of the smelter systems requires tight monitoring and automatic control of the processes. Reliable models of the smelter systems are necessary to improve control and monitoring of the operation. This project proposes to model the  smelter system in Falconbridge Ltd. using industrial operating data and fundamental principles. The smelter system includes many fundamental engineering unit operations. This project will investigate modelling techniques of these individual units, followed by plant-wide modelling with interactions of the engineering units. According to the dynamics of the variables, different model structures will be tested using conservation laws, semi-physical modelling or empirical identification. Model reduction will be conducted to generate the models that can be easily incorporated into process control development. An adaptive identification method with learning schemes will be investigated and developed specifically for modelling the time-varying characteristics of the smelter off-gas system. With the derived models, the control schemes for the smelter off-gas system will be investigated. Results of this project are expected to build necessary foundation to further improve the smelter operation and result in better environment and significant economic benefits.