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Mining Publication: A New Methane Control and Prediction Software Suite for Longwall Mines
Keywords: Gas emissions Gob gas vent holes Longwall mining Methane Ventilation
Original creation date: September 2011
Authors: HN Dougherty, C� Karacan
Peer Reviewed Journal Article - September 2011
Download PDF Document (1.59 MB)
NIOSHTIC2 Number: 20039497
Comput Geosci 2011 Sep; 37(9):1490-1500
This paper presents technical and application aspects of a new software suite, MCP (Methane Control and Prediction), developed for addressing some of the methane and methane control issues in longwall coal mines. The software suite consists of dynamic link library (DLL) extensions to MS-AccessTM, written in C++. In order to create the DLLs, various statistical, mathematical approaches, prediction and classification artificial neural network (ANN) methods were used. The current version of MCP suite (version 1.3) discussed in this paper has four separate modules that (a) predict the dynamic elastic properties of coal-measure rocks, (b) predict ventilation emissions from longwall mines, (c) determine the type of degasification system that needs to be utilized for given situations and (d) assess the production performance of gob gas ventholes that are used to extract methane from longwall gobs. These modules can be used with the data from basic logs, mining, longwall panel, productivity, and coal bed characteristics. The applications of these modules separately or in combination for methane capture and control related problems will help improve the safety of mines. The software suite’s version 1.3 is discussed in this paper.
Image of publication A New Methane Control and Prediction Software Suite for Longwall MinesPeer Reviewed Journal Article - September 2011
Download PDF Document (1.59 MB)
NIOSHTIC2 Number: 20039497
Comput Geosci 2011 Sep; 37(9):1490-1500
See Also
Comparisons Between Cross-Measure Boreholes and Surface Gob Holes
Longwall Gob Degasification With Surface Ventilation Boreholes Above the Lower Kittanning Coalbed
Methane Emission Rate Studies in a Central Pennsylvania Mine
Modeling and Prediction of Ventilation Methane Emissions of U.S. Longwall Mines Using Supervised Artificial Neural Networks
Numerical Analysis of the Impact of Longwall Panel Width on Methane Emissions and Performance of Gob Gas Ventholes
Probabilistic Modeling Using Bivariate Normal Distributions for Identification of Flow and Displacement Intervals in Longwall Overburden
Technology News 465 - Method for Predicting Methane Emissions on Extended Longwall Faces
Page last reviewed: September 21, 2012
Page last updated: September 21, 2012
Content source: National Institute for Occupational Safety and Health, Mining Program
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