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

References

• Agioutantis, Z. , Luxbacher, K. , Dougherty, H. , & Karmis, M. (2015, June). Development and implementation of a data management platform for atmospheric data in underground coal mines . Paper presented at the 15th North American Mine Ventilation Symposium , Blacksburg, VA.
   Google Scholar
• Agioutantis, Z. , Luxbacher, K. , Dougherty, H. , Karmis, M. , & Schafrik, S. (2014). Development of an atmospheric data management system for underground coal mines, South Africa Institute of Mining and Metallurgy, 114, 1059–1063.
   Google Scholar
• Bahrami, D. , Yuan, L. , Zhou, L. , & Rowland, J. H. (2019). New mine fire location model utilizing real-time gas monitoring data. Proceedings of 17th North American Mine Ventilation Symposium , Montreal, QC, (pp. 30–37).
   Google Scholar
• Brake, D. J. (2013). Fire modeling in underground mines using Ventsim Visual VentFIRE Software. Proceedings of 2nd Australian Mine Ventilation Conference , Adelaide, South Australia, (pp. 265–276).
   Google Scholar
• Conti, R. S. , Chasko, L. L. , Wiehagen, W. J. , & Lazzara, C. P. (2005). Fire response preparedness for underground mines. NIOSH IC 9481, Department of Health and Human Services, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health.
   Google Scholar
• Ślęzak, D. , Grzegorowski, M. , Janusz, A. , Kozielski, M. , Nguyen, S. H. , Sikora, M. , Stawicki S , Wróbel Ł . (2018). A framework for learning and embedding multi-sensor forecasting models into a decision support system: A case study of methane concentration in coal mines. Information Sciences , 451–452, 112–133. https://doi.org/10.1016/j.ins.2018.04.026
   Web of Science ®Google Scholar
• Jahn, W. , Rein, G. , & Torero, J. L. (2008). The effect of model parameters on the simulation of fire dynamics. Fire Safety Science , 9(9), 1341–1352. https://doi.org/10.3801/IAFSS.FSS.9-1341
   Google Scholar
• Stewart, C. M. , Aminossadati, S. M. , & Kizil, M. S. (2017). Predictive network modelling with live sensor data. Proceedings of the 2nd international conference of fiber-optic and photonic sensors for industrial and safety applications , Brisbane, Australia, 64–69.
   Google Scholar
• Tewarson, A. (2002). Generation of heat and chemical compounds in fires: The SFPE handbook of fire protection engineering (3rd ed.). National Fire Protection Association and the Society of Fire Protection Engineers.
   Google Scholar
• Yuan, L. , Thomas, R. A. , & Zhou, L. (2017). Characterization of a mine fire using atmospheric monitoring system sensor data. Mining Engineering , 69(6), 57–62. https://doi.org/10.19150/me.7567
   Google Scholar
• Zhou, L. , Smith, A. C. , & Yuan, L. (2016). New improvements to MFIRE to enhance fire modeling capabilities. Mining Engineering , 68(6), 45–50. https://doi.org/10.19150/me.6628
   Google Scholar