Transactions of the Society for Mining, Metallurgy, and Exploration, Inc.
Transactions home

  SME FaceBook SME Twitter SME LinkedIn RSS Feed

New improvements to MFIRE to enhance fire-modeling capabilities

Mining Engineering , 2016, Vol. 68, No. 6, pp. 45-50

Zhou, L.; Smith, A.C.; Yuan, L.



MFIRE, the mine-fire simulation program of the U.S. National Institute for Occupational Safety and Health (NIOSH), is widely accepted as a standard for assessing and predicting the impact of a fire on the mine ventilation system and the spread of fire contaminants in coal and metal/nonmetal mines. MFIRE has been used by U.S. and international companies to simulate fires for planning and response purposes. It is a dynamic, transient-state, mine ventilation network simulation program that performs normal planning calculations. It can also be used to analyze ventilation networks under thermal and mechanical influence, such as changes in ventilation parameters; external influences, such as changes in temperature; and internal influences, such as a fire. The program output can be used to analyze the effects of these influences on the ventilation system. Since its original development by Michigan Technological University for the former U.S. Bureau of Mines in the 1970s, several updates have been released. In 2012, NIOSH completed a major redesign and restructuring of the program with the release of MFIRE 3.0. MFIRE’s outdated Fortran programming language was replaced with an object-oriented C++ language and packaged into a dynamic-link library. However, the MFIRE 3.0 release included no change or improvement to the fire-modeling algorithms inherited from its previous version, MFIRE 2.20. This paper reports on improvements that have been made to the fire-modeling capabilities of MFIRE 3.0 since its release. These improvements include the addition of the t-squared fire as a new fire-source model and the ability to include available heat-release-rate versus time data, the addition of a moving fire source for conveyor-belt fire simulations, improvement of the fire location algorithm, and the identification and prediction of smoke-rollback phenomena. All of the improvements discussed in this paper will be included in MFIRE 3.1 and released by NIOSH in the near future.