Proximity Detection of Explosive Methane Clouds in Longwall Mines

Details

• Personal Author:
  Bogin GE ; Brune, Jürgen F. ; Demirkanr C ; Düzgün HS ; Isleyen E ; Juganda A ; Nguyen T ; Strebinger C
• Description:
  Methane detection in underground coal and other gassy mines traditionally done with point-type sensors or by certified examiners using handheld meters. To provide a sufficient margin of safety, machine-mounted point sensors shut down equipment at methane concentrations of 1 or 1.5%, yet many mine fires and explosions have shown that point sensors may not be capable of detecting explosive methane clouds. The 2010 explosion at the Upper Big Branch mine in West Virginia, USA, is one such example that killed 29 miners. Researchers are using multi-point methane readings, CFD, and 3-D modeling to produce the real-time methane distribution cloud and visualization through virtual and augmented reality (VR and AR). Knowing the position of the shearer, shields and other ignition sources creates a proximity detection model for the methane cloud that will automatically shut off the shearer or other equipment before an explosion can happen. [Description provided by NIOSH]
• Subjects:
  Explosions Mining Occupational Health Safety
• Keywords:
  Coal Mines Explosive Gases Longwall Mining Methane Control Mine Fires Sensors Underground Mines Virtual Reality
• ISBN:
  9780367336042
• ISSN:
  2639-7749
• Publisher:
  CRC Press
• Document Type:
  Text
• Funding:
  Contract
• Genre:
  Book
• Place as Subject:
  Colorado ; OSHA Region 3 ; OSHA Region 8 ; West Virginia
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  3
• NIOSHTIC Number:
  nn:20068520
• Citation:
  Mining goes digital: proceedings of the 39th International Symposium 'Application of Computers and Operations Research in the Mineral Industry' (APCOM 2019), June 4-6, 2019, Wroclaw, Poland. Proceedings in earth and geosciences series. Mueller C, Assibey-Bonsu, Baafi E, Dauber C, Doran C, Jaszczuk M, Nagovitsyn O, eds. London: CRC Press, 2019 May; 3:620-626
• CAS Registry Number:
  Methane (CAS RN 74-82-8)
• Editor(s):
  Mueller C; Assibey-Bonsu; Baafi E; Dauber C; Doran C; Jaszczuk M; Nagovitsyn O
• Federal Fiscal Year:
  2019
• Performing Organization:
  Tustees of the Colorado School of Mines
• Peer Reviewed:
  True
• Start Date:
  20140901
• Source Full Name:
  Mining goes digital: proceedings of the 39th International Symposium 'Application of Computers and Operations Research in the Mineral Industry' (APCOM 2019), June 4-6, 2019, Wroclaw, Poland. Proceedings in earth and geosciences series, volume 3
• End Date:
  20190831
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:8ca3af0ee66fb4ad7be6d13692493a8748c57be93ed2fffe1d69b04017e29d70fabe67e24ed1c24a5e3600d5b1c3d115b360b750b43c148b0256387ced88b4e6
• Download URL:
  https://stacks.cdc.gov/view/cdc/207136/cdc_207136_DS1.pdf
• File Type:
  [PDF - 4.18 MB ]