Estimating underground mine ventilation friction factors from low density 3D data acquired by a moving LiDAR

Abstract

Ventilation system analysis for underground mines has remained mostly unchanged since the Atkinson method was made popular by McElroy in 1935. Data available to ventilation technicians and engineers is typically limited to the quantity of air moving through any given heading. Because computer-aided modelling, simulation, and ventilation system design tools have improved, it is now important to ensure that developed models have the most accurate information possible. This paper presents a new technique for estimating underground drift friction factors that works by processing 3D point cloud data obtained by using a mobile LiDAR. Presented are field results that compare the proposed approach with previously published algorithms, as well as with manually acquired measurements. Keywords: Mine ventilation, Mine design, Mobile mapping, Roughness estimation, Friction factors, LiDAR, 3D point clouds