Investigations of Ventilation Airflow Characteristics on a Longwall Face—A Computational Approach
AbstractMine ventilation has always been critical for underground mining operations to ensure operational efficiency and compliance with safety and health statutory requirements. To obtain a thorough understanding of the ventilation flow characteristics on a longwall face, innovative three dimensional (3D) models, incorporating key features of the longwall equipment and a zone of immediate goaf area, were developed. Mesh independent studies were conducted to determine the desirable mesh required for a mesh-independent solution. Then the model results were validated using field ventilation survey data. At both intersections of maingate/tailgate (MG/TG) and face where the flow boundary changes sharply, the occurrence of undesirable flow separation which causes additional energy loss was identified, as well as its extent of influence. The recirculation of airflow resulting from separation in the TG will lead to accumulation of high concentrations of mine gas, thus regular inspection or continuous monitoring of gas concentration in that area is highly recommended, especially when high gas emission is expected from the working seam. In addition, we also investigated the influence of shearer position and cutting sequence on longwall ventilation. Overall, the longwall models developed in this study together with the flow characteristics obtained will provide fundamental basis for the investigation of longwall gas and dust issues in the future. View Full-Text
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Wang, Z.; Ren, T.; Ma, L.; Zhang, J. Investigations of Ventilation Airflow Characteristics on a Longwall Face—A Computational Approach. Energies 2018, 11, 1564.
Wang Z, Ren T, Ma L, Zhang J. Investigations of Ventilation Airflow Characteristics on a Longwall Face—A Computational Approach. Energies. 2018; 11(6):1564.Chicago/Turabian Style
Wang, Zhongwei; Ren, Ting; Ma, Liqiang; Zhang, Jian. 2018. "Investigations of Ventilation Airflow Characteristics on a Longwall Face—A Computational Approach." Energies 11, no. 6: 1564.
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