Prediction of dust loss from conveyors using computational fluid dynamics modelling

Abstract

Dust lift-off from conveyors forms a significant environmental and operational problem for operators in the mining, power generation and process industries. One means of reducing dust lift-off is to provide airflow deflectors or other aerodynamic modifications to the conveyor. A computational fluid dynamics (CFD) model has been developed to take into account the effect of wind direction, velocity and conveyor guarding on the dust loss from conveyors. The model is developed in the framework of CFX4. Experimental measurements of dust lift-off from the surface of a bed of ore in a wind tunnel at different wind velocities are used to characterise the dust. Based on the experimental data a model for predicting the mass and particle size distribution lifted from the bed surface at different air velocities is developed. The dust loss model is coupled to a Lagrangian particle-tracking model to predict particle trajectories. Validation of the model is undertaken by comparing CFD predictions against wind tunnel test work and shows good agreement. Results are presented for a typical conveyor design. The combination of experimental and CFD modelling is found to be a powerful tool for analysing dust loss from conveyors and can be extended to stockpiles and other situations where dust loss is a problem. The model can readily be extended to account for heat and moisture transfer in beds of porous materials.