A hybrid methodology for investigating DPM concentration distribution in underground mines

Abstract

A hybrid methodology is proposed to investigate the diesel particulate matter (DPM) concentration distribution in underground mines by using a ventilation network solver and computational fluid dynamics (CFD). Mine ventilation system, one of the most significant and energy-intensive parts of an underground mine, needs to be accurately studied to provide sufficient fresh air to the personnel working underground. Ventilation is used to dilute and remove the contaminants out of a mine to protect the personnel from being exposed to concentrations outside of regulatory requirements. Numerical modeling is increasingly being used to assist mine ventilation design and operation. Currently, there are two types of solvers used to calculate ventilation system solutions, which are network solvers and CFD. The hybrid methodology is proposed to provide improved diesel input to a ventilation network model using CFD. The hybrid methodology combines the two solvers through commonly shared boundary conditions, making it possible to conduct mine-scale ventilation simulations. The network solver simulates the whole mine ventilation system, and CFD simulates the active working faces. In this fashion, the ventilation model is computationally efficient but still produces accurate and detailed (e.g., three-dimensional DPM concentration distribution) results. Mining operations can benefit from the updated network model using the hybrid methodology and quickly assess different ventilation plans without additional capital investments.