Quality Assurance Standards for Mine Ventilation Models and Ventilation Planning

摘要

Most mine ventilation engineers are involved in ventilation planning and design in some capacity. Ventilation modelling software used by a competent experienced ventilation engineer is extremely useful in developing good ventilation designs by allowing assessment of a wide range of potential options. Unfortunately, ventilation modelling undertaken by persons who do not have sufficient experience or knowledge usually results in a facade that covers up a fundamentally unsatisfactory design. Ventilation models are produced for a wide variety of purposes including: fault-finding of a problem area in a mine and options analysis for resolution of such problems; a complete review or optimisation exercise of an entire mine's ventilation system; or a much longer life-of-mine type of study. Models can be intended as the basis for studies with diverse purposes such as primary shaft or airway sizing, primary fan specification, examining re-entry times after blasting, resolving leakage or recirculation, or investigating the impact of fires or underground climate or cooling requirements. The concepts of 'materiality' and 'fitness for purpose' are essential to developing or using a ventilation model and serious mistakes have been made in wrongly using a ventilation model for purposes for which it was never intended, often because it is simply the most recent model on the mine site. Mistakes at this level often translate into faulty ventilation strategies and inefficient or ineffective use of scarce capital for ventilation projects. Validating a ventilation model is a time-consuming and expensive process and not every model must (or even should) be fully validated to meet the objectives at that time. This paper discusses the application of quality assurance in ventilation planning with particular respect to the 'basis of design' (BOD) as well as the standards for validating a ventilation model. It also provides a recommended way of dealing with non-conformances in measured versus modelled values of critical parameters in the model.