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Daykin Schnell, a Ph.D. candidate in the Department of Mining Engineering, recently finished in the top three of the Pittsburgh Coal Mining Institute of America and Society for Mining, Metallurgy & Exploration (SME), Pittsburgh Section's Short Presentation Contest for his presentation, "Full-scale and small-scale modeling and testing of underground methane explosions."

After a competitive first round of eliminations, seven students advanced to the live presentation session, where they delivered compelling research presentations and skillfully addressed questions from the jury panel. Schnell, an SME Ph.D. Fellowship Grant recipient, placed third and will have his abstract published in an upcoming issue of SME's Mining Engineering Magazine.

Presentation Summary

Accidental methane explosions are of concern in underground coal mines in the United States. Significant work has gone into reducing the risk associated with methane explosions and helping to ensure the safety of the underground coal miner. 

However, the potential for accidental methane explosions still exists. Many studies have been conducted to better understand how methane explosions impact underground mining environments and to determine what steps can be taken to protect miners. Current research includes modeling methane explosions from field testing and past mine incidents. Additionally, predictive models have been developed that can effectively estimate the effects of potential methane explosions. Work is currently ongoing to develop, test and validate multiple computational fluid dynamic (CFD) models for estimating air overpressures from methane explosions in underground mining environments. Full-scale CFD models have been validated against field test data from National Institute for Occupation Safety and Health (NIOSH) testing at the Lake Lynn Experimental Mine. An additional 1/10 small-scale CFD model has been developed concurrently with a 1/10 small-scale physical mine network to establish procedures for full-scale methane explosion impacts through smallscale field testing.