Access optimisation in underground mine design
In underground mines, ore is typically transported out of the mine along a network of gently sloping ramps or tunnels, horizontal drives and (possibly) vertical shafts. There are constraints on the ramps imposed by the limitations of the trucks that haul the ore. Typically the gradient may not be more than 1:7 and there is a lower limit on the radius of curves, which is typically 25 metres. Both the construction costs of the tunnels and shafts and the associated haulage costs along them are significant components of the overall mine costs.
The usual method of deciding on a design for a mining network is based on the mining engineer's expertise and experience. This generally involves detailing a small number of feasible networks and choosing the "most suitable" one. However, the difficulty of designing structures in three dimensions, the complexity of the possible connection schemes, and the combination of choices for ramp gradient, turning circle and mining levels means that these initial solutions have the potential to be dramatically improved by systematic optimisation. With kilometres of ramps and drives costing thousands of dollars per linear metre the potential savings are huge. Hence, optimising the layout of these ramps and drives can have a major impact on the economic efficiency and viability of the mine.
In earlier research, the research team developed algorithms for optimising the network of declines (systems of ramps) and drives which satisfy operational gradient and curvature constraints so that the cost of construction and haulage over the life of the mine is minimised. This approach has been implemented in the software tools DOT (Decline Optimisation Tool) and PUNO (Planar Underground Network Optimiser) which are being developed for commercial release. Our current research builds on this work by seeking to maximise the value of the mine with time discounting of value (the “cost of capital”) taken into account in accordance with standard industry practice. In order to achieve this aim, it is necessary to optimise both the access design and the operating schedule concurrently.
Leader: Doreen Thomas
Staff: Marcus Brazil, Peter Grossman
Students: Kashyapa Sirinanda
Collaborators: Hyam Rubinstein (Mathematics), David Lee (Mathematics) , Nick Wormald (Monash University)
Sponsors: Rand Mining, Tribune Resources
Optimisation of resources and infrastructure
optimisation; underground mine design