Study on integration of real-time atmospheric monitoring system data and MFIRE simulation

Abstract

ABSTRACT The past several decades have seen a steady increase in the use of atmospheric monitoring systems (AMS) in underground mines as sensor technology has advanced and costs for this technology have decreased. The AMS is a reliable tool for early mine fire warning by detecting gaseous products of combustion in underground mines. During a mine fire emergency, mine decision makers rely heavily on prompt and accurate knowledge of the ventilation and fire situation in the mine, such as fire location, fire size, and the spread of smoke to make effective and efficient decisions on firefighting strategies and miner evacuation. Meanwhile, a prediction of the potential for fire development at a later time, such as whether the currently designated mine escapeways will be contaminated by smoke and toxic gases with the progress of the fire, is critical for effective decision making to save lives that are in danger. The AMS monitoring data, including carbon monoxide concentration, airflow rate, smoke spread, etc., can provide information as to whether the smoke has reached the locations where AMS sensors are installed and if a mine-wide smoke spread has occurred. The National Institute for Occupational Safety and Health has undertaken a task to integrate real-time AMS monitoring data with the mine fire simulation program, MFIRE, to simulate and predict the spread of smoke and toxic gas in a ventilation network based on the real-time AMS data. This article reports the developed real-time method for characterizing the size and location of an underground mine fire and for predicting the spread of contaminants throughout the mine ventilation network using sensor data from the AMS.