Brune, Jürgen F.Bogin, Gregory E.Juganda, Aditya2020-04-062022-02-032020-04-062022-02-032020https://hdl.handle.net/11124/174069Includes bibliographical references.2020 Spring.Longwall face ignitions from accumulated methane gas are known to be among the most common causes of methane explosions at underground coal operations. Current industry practice relies on point-type methane sensors reading installed on the shearer body and other fixed location, such as the tailgate drive, to prevent face ignition in the longwall face area. However, this practice is not reliable in detecting and preventing explosion hazard in the longwall face, as shown by numerous face ignition cases, including the 2010 Upper Big Branch mine explosion in West Virginia, U.S. Computational Fluid Dynamics (CFD) can be used to simulate ventilation conditions in the longwall face for different ventilation scenario. This approach has the advantages of allowing visualization of the aerodynamics of airflow and formation of hazardous gas mixtures which are not detectable using traditional monitoring and ventilation survey methods, which can be used to develop a more reliable methane monitoring practices to improve methane explosion safety in longwall coal mines.CFD modeling results show that the current regulatory requirements and industry practice of maintaining a minimum amount of airflow at the tailgate corner in combination with methane reading from two single point-based sensors installed on the shearer body and tailgate drive is not adequate to warn of and prevent methane ignition hazards at the face. This research has demonstrated that the proposed multi-sensor warning system that relies on multiple sensors reading installed on the tip of the shield’s roof provides a more reliable and more accurate representation of potential explosive methane concentrations around the shearer drums compared to the current monitoring practice.born digitaldoctoral dissertationsengCopyright of the original work is retained by the author.longwall coal minecomputational fluid dynamics modelingventilationText