[特邀报告]Optimized canopy air curtain dust protection using a two-level manifold and computational fluid dynamics
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[特邀报告]Optimized canopy air curtain dust protection using a two-level manifold and computational fluid dynamics

Optimized canopy air curtain dust protection using a two-level manifold and computational fluid dynamics
编号:503 稿件编号:463 访问权限:仅限参会人 更新:2024-05-20 14:57:19 浏览:564次 特邀报告

报告开始:2024年05月30日 16:40 (Asia/Shanghai)

报告时间:20min

所在会议:[S2] Safety Engineering and Occupational Health » [S2-2] Afternoon of May 30th-2

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摘要
Prolonged exposure to high concentrations of respirable coal mine dust causes coal workers’ pneumoconiosis and silicosis. Underground coal mine roof bolter operators are more prone to elevated exposure to coal and silica dust. The canopy air curtain (CAC) was developed by NIOSH to protect roof bolter operators from the exposure. The CAC supplies filtered air over the breathing zone of the operator. This dilutes the high coal dust concentrations and provides for an impenetrable air curtain. Many studies have been carried out to improve CAC efficiency. However, field test has shown variable dust control efficiencies indicating rooms to further improve due to the non-uniform airflow distribution across the plenum and ineffective perimeter flow. This study therefore redesigns the CAC with optimized flow distribution that effectively protects roof bolters from coal dust exposures. The Simplex Evolutionary Operational (EVOP) optimization algorithm was applied to optimize the configuration of the new CAC. Computational fluid dynamics (CFD) simulations are run at each iteration of the algorithm. The combination of these methodologies led to the optimization of the uniformity of airflow distribution across the plenum to achieve the best possible uniformity. A lab experiment using a physical model of the optimized CAC was used to validate the CFD model and confirm the ability of this design to protect roof bolter operators from excessive coal dust.
 
关键字
coal dust exposure, canopy air curtain, computational fluid dynamics, manifold optimization
报告人
Guang Xu
教授 Missouri University of Science and Technology

稿件作者
光/Xu Guang 徐 密苏里科学技术大学/Missouri University of Science and Technology
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