Modeling carbon monoxide spread in underground mine fires.

Area of Science:

• Mine safety engineering
• Fire dynamics
• Computational fluid dynamics

Background:

• Carbon monoxide (CO) poisoning is a primary cause of fatalities in underground mine fires.
• Accurate prediction of CO spread is essential for mitigating risks in mine environments.

Purpose of the Study:

• To model and analyze the spread of carbon monoxide (CO) in underground mine fires.
• To investigate the impact of airflow leakage on CO concentration reduction.
• To compare simulation results from Fire Dynamics Simulator (FDS) and MFIRE models.

Main Methods:

• Utilized the Fire Dynamics Simulator (FDS) to model a section of the mine ventilation network.
• Calibrated the FDS model with full-scale mine fire test data for CO concentrations.
• Employed the MFIRE program to predict CO spread throughout the entire mine ventilation network.
• Investigated the effect of airflow leakage on CO reduction using FDS simulations.
• Compared MFIRE simulations using constant and dynamic heat release rates (derived from FDS).

Main Results:

• Airflow leakage into mine entries was found to significantly reduce CO concentrations.
• FDS simulations provided valuable data for calibrating and improving the MFIRE model.
• MFIRE simulations predicted CO spread across the entire ventilation network, incorporating dynamic fire source data.

Conclusions:

• Accurate modeling of CO spread is vital for underground mine fire safety.
• Airflow leakage is an effective mechanism for reducing CO hazards.
• Integrated modeling approaches (FDS and MFIRE) enhance the prediction capabilities for mine fire scenarios.