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Results 1 - 10 of 98
3/1/2012 - Peer reviewed journal articlesThe CART-based model that is given in this paper can be used to predict methane emission rates and to adjust operation parameters under ventilation constrains in longwall mining.
This NIOSH publication demonstrates how existing and new engineering controls can be used to reduce face methane levels.
Continuous Miner Spray Considerations for Optimizing Scrubber Performance in Exhaust Ventilation Systems2/1/2010 - Conference papersThis paper describes lab experiments to examine the effect of spray type, pressure, machine body blocking sprays, and scrubber airflow on dust and gas levels while using a 12.2 m (40 ft) exhaust ventilation curtain setback from the face.
3/1/2009 - Peer reviewed journal articlesThis study describes the development of an expert classification system used as a decision tool which can be used for degasification system selection using site- and mine-specific conditions.
A Numerical Evaluation on the Effects of Impermeable Faults on Degasification Efficiency and Methane Emissions During Underground Coal Mining9/1/2008 - Peer reviewed journal articlesThis study uses reservoir simulations to illustrate the effects of impermeable faults on the production performance of vertical and horizontal degasification boreholes.
The Borehole Monitoring Experiment: Field Measurements of Reservoir Conditions and Responses in Longwall Panel Overburden During Active Mining6/1/2008 - Conference papersThis paper describes the results of a NIOSH borehole monitoring experiment (BME) on an active longwall panel.
In this report, several practical guidelines are recommended for controlling longwall coalbed methane. All predictions are based on determinations made for the Pittsburgh Coalbed in southwestern Pennsylvania.
Modeling and Prediction of Ventilation Methane Emissions of U.S. Longwall Mines Using Supervised Artificial Neural Networks2/1/2008 - Peer reviewed journal articlesThis study proposes a principal component analysis (PCA) and artificial neural network (ANN)-based approach to predict the ventilation methane emission rates of U.S. longwall mines.
Development and Application of Reservoir Models and Artificial Neural Networks for Optimizing Ventilation Air Requirements in Development Mining of Coal Seams11/1/2007 - Peer reviewed journal articlesUsing coalbed methane reservoir modeling and an artificial neural network (ANN) design for prediction and optimization of methane inflows and ventilation air requirements to maintain methane concentrations below statutory limits.
9/1/2007 - Conference papersThis paper reviews how simultaneous application of three basic elements reduces the methane explosion hazard at coal mine working faces: (1) adequate ventilation, (2) regular monitoring of gas concentrations, and (3) elimination of ignition sources.