The application of GA optimisation methods to the design of practical ventilation systems for multi-level metal mine operations

Abstract

This paper presents the results of a series of recent studies to investigate the improved optimal design and planning of the main ventilation systems of complex multi-level mine networks using a genetic algorithm (GA) routine. It is concluded that the method may be successfully used to investigate the benefits offered by alternative ventilation configurations and to determine the most practical and cost-effective ventilation system during the various mine planning stages (short-, medium- and long-term). In particular, the optimum number, location and duties of booster fans, and size and location of regulators may be evaluated and selected. The objective of the final ventilation design is to identify the ventilation system that operates in both a safe and energy-efficient manner. The method has been refined to include the selection of practical fan units that match the optimal fan operating duties determined by the GA routine. The paper also reviews general optimisation strategies that may be employed to enhance and maintain the performance of mine ventilation systems.

Keywords

VENTILATION DESIGN GENETIC ALGORITHM OPTIMISATION BOOSTER FAN ENERGY EFFICIENCY MULTI-LEVEL MINE

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