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

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.

RÉSUMÉ

Au cours des dernières décennies, on a observé une augmentation constante de l’utilisation des systèmes de surveillance atmosphérique (SSA) dans les mines souterraines, car la technologie des capteurs a progressé et les coûts de cette technologie ont diminué. Le SSA est un outil fiable pour la détection précoce des incendies de mines en détectant les produits gazeux de combustion dans les mines souterraines. Lors d’une urgence liée à un incendie de mine, les décideurs de la mine comptent beaucoup sur une connaissance rapide et précise de la ventilation et de la situation d’incendie dans la mine, comme l’emplacement de l’incendie. la taille de l’incendie et la propagation de la fumée pour prendre des décisions efficaces et efficientes sur les stratégies de lutte contre l’incendie et l’évacuation des mineurs.Entre-temps, une prévision du potentiel de développement d’un incendie à un moment ultérieur, par exemple si les voies d’évacuation de la mine actuellement désignées seront contaminées par la fumée et les gaz toxiques avec la progression de l’incendie, est essentiel à la prise de décisions efficaces pour sauver des vies en danger. Les données de surveillance du SSA, y compris la concentration de monoxyde de carbone, le débit d’air, la propagation de la fumée, etc., peuvent fournir des renseignements quant à savoir si la fumée a atteint les endroits où des capteurs de SSA sont installés et si une propagation de la fumée à l’échelle de la mine s’est produite. Le National Institute for Occupational Safety and Health a entrepris d’intégrer les données de surveillance SSA en temps réel au programme de simulation des incendies de mines, MFIRE, afin de simuler et de prédire la propagation de la fumée et des gaz toxiques dans un réseau de ventilation à partir des données SSA en temps réel. Cet article fait état de la méthode développée en temps réel pour caractériser la taille et l’emplacement d’un incendie de mine souterraine et pour prédire la propagation des contaminants dans tout le réseau de ventilation de la mine à l’aide des données des capteurs de le SSA.

KEYWORDS:

• Atmospheric monitoring system (AMS)
• Carbon monoxide sensor
• Mine fire simulation
• Underground mine fire

MOTS CLÉS:

• capteur de monoxyde de carbone
• incendie de mine souterraine
• simulation d’incendie de mine
• système de surveillance atmosphèrique (SSA)

DISCLAIMER

The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention. Mention of any company or product does not constitute endorsement by NIOSH.

Additional information

Notes on contributors

L. Zhou

L. Zhou is a General Engineer of Pittsburgh Mining Research Division at NIOSH. She received her Ph.D. degree in Mining Engineering from West Virginia University. Her research interests are mainly in mine ventilation planning and simulation, mine fire simulation, and mine fire prevention. [email protected]

L. Yuan

L. Yuan is a Lead General Engineer of Fires & Explosions Branch at Pittsburgh Mining Research Division, NIOSH. He received his Ph.D. degree in Mechanical Engineering from University of Kentucky. His research focuses on mine fire prevention, detection and control, spontaneous combustion of coal, lithium-ion battery fires, and mine environmental monitoring and fire modeling.

D. Bahrami

D. Bahrami holds BS and MS degrees in Mining Engineering. He received his PhD in Geo-Engineering from University of Nevada, Reno (UNR). He has over 10 years of research experience at UNR in geothermal energy extraction, and underground ventilation. He is currently with NIOSH conducting research on underground mine fires.

R. A. Thomas

R. A. Thomas is an Electronics Technician for fires research. He has 30+ years of specialized technical research in fires and explosion research for the mining Industry. This includes installation, modifications, testing, and design of sensors used in monitoring gases produced during fires and explosion research. Experienced in installation and operation of fire suppression equipment during actual fire testing.

G. P. Cole

G. P. Cole graduated from Wright State University with a B.S. in Computer Engineering and has spent 30 years researching mining safety and health. His work has covered developing simulations for cable heating, mine fires and ventilation, and mine emergency response training. Other work areas included neural network-based arc detection and translating research findings into web, PC, and mobile applications.

J. H. Rowland

J. H. Rowland is a Research Physicist. He has worked at the Pittsburgh Mining Research Division at NIOSH for the past 30+ years. He has worked on projects dealing with desensitization and malfunction of coal mine explosives, permissible explosives testing, explosive accident investigations, and toxic fumes from blasting, mine-wide atmospheric monitoring systems, and conveyor belt fire detection, suppression, and modeling of conveyor belt fires.