Development of Dilution Model of Diesel Particulate Matter (DPM) Using Computational Fluid Dynamics (CFD) Modelling for Blind Headings Using Pilot Scale Study
摘要
Indian underground coal mining is adapting to the increasing demand for coal. The underground mines are utilising diesel-powered vehicles for coal production and transportation, resulting in the generation of diesel particulate matter (DPM) and noxious diesel exhaust gases. The accumulation of DPM in the underground workings poses significant health risks to workers due to limited ventilation and pollutant dispersion. This study presents the development and validation of a computational fluid dynamics (CFD)-based dilution model to predict DPM dispersion in blind headings, with the aim of optimising the ventilation system and mitigating occupational exposure. To measure DPM levels in real time while airflow is controlled, a pilot-scale experiment was set up in the mine fire model gallery at CSIR-CIMFR, Dhanbad. This setup, which resembles a scaled blind heading, was created. The CFD model incorporated Reynolds-averaged Navier–Stokes (RANS) equations with a k-ε turbulence closure and discrete phase modelling to simulate particle transport while considering air velocity and emission rates. The CFD model was validated against the experimental data generated from the mine fire model gallery experiments, where a DPM source was provided using a diesel-powered truck available in-house. The models were simulated using different air velocities, viz. 0.5, 1.0, 1.5 and 2.0 m/s for optimisation using both main and auxiliary ventilation systems. The results revealed that an air velocity of 1.5 and 2.0 m/s can bring the DPM concentration below 100 µg/m3 at a 20% higher rate in the mine gallery as compared to the air velocities of 0.5 and 1.0 m/s. Further, an average increase in the ventilation rates by 57% reduced peak DPM concentrations by 32%. This study highlights the potential of CFD modelling as a predictive tool for designing targeted ventilation systems in confined mining environments. Results advocate for adaptive airflow management to minimise DPM exposure and offer actionable insights for improving occupational health standards in the mining industry.