Mine Conveyor Belt Fire Classification

Details

• Personal Author:
  Barros-Daza MJ ; Hodges JL ; Lattimer BY ; Luxbacher, Kray D.
• Description:
  This article presents a conveyor belt fire classification model that allows for the determination of the most effective firefighting strategy. In addition, the effect of belt design parameters on the fire classification was determined. A methodology that involves the use of numerical simulations and artificial neural networks was implemented. An approach previously proposed for modeling fires over conveyor belts was used. With the objective of obtaining some required modeling input parameter and verifying the capacity of this approach to get realistic results, computational fluid dynamics model calibration and validation were carried out using experimental test results available in the literature. Results indicated that scenarios with belt positions closer to the mine roof and greater tunnel heights require a higher longitudinal air velocity to be attacked directly. Furthermore, the belt fire classification model provided by the artificial neural network had an accuracy around 95% when test scenarios were classified. [Description provided by NIOSH]
• Subjects:
  Emergencies Firefighters Fires Occupational Health Safety
• Keywords:
  Author Keywords: Artificial Neural Network Neural Network Belt Fires Coal Mines Critical Velocity Emergency Response Fire Fighters Fire Fighting Mine Fire Classification Mine Firefighters Mine Fires Neural Networks Simulation Methods

  More +
• ISSN:
  0734-9041
• Document Type:
  Text
• Funding:
  Contract
• Genre:
  Journal Article
• Place as Subject:
  OSHA Region 3 ; Virginia
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  44-69
• Volume:
  40
• Issue:
  1
• NIOSHTIC Number:
  nn:20067990
• Citation:
  J Fire Sci 2022 Jan; 40(1):44-69
• Contact Point Address:
  Manuel J. Barros-Daza, Department of Mining and Minerals Engineering, Virginia Tech, 117A Surge Building, 400 Stanger Street (MC 0239), Blacksburg, VA 24061, USA
• Email:
  manuel1@vt.edu
• Federal Fiscal Year:
  2022
• Performing Organization:
  Virginia Polytechnic Institute & State University
• Peer Reviewed:
  True
• Start Date:
  20140901
• Source Full Name:
  Journal of Fire Sciences
• End Date:
  20190831
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:cd7280303dec0255afe85b4373b71b76a4d61f190495e775d34de89874eef24dd1456c93d32120de12e94fe5fdc24616342f729b0857013a3c5512590862c25f
• Download URL:
  https://stacks.cdc.gov/view/cdc/230221/cdc_230221_DS1.pdf
• File Type:
  [PDF - 2.29 MB ]