CFD Modeling and Laboratory Studies of Dust Cleaning Efficacy of an Efficient Four Stage Non-Clogging Impingement Filter for Flooded-Bed Dust Scrubbers
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2022/03/22
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Description:Fibrous-type filters are used to capture dust particles in mining and other occupations where personnel are exposed for prolonged periods. Dust cleansing devices including flooded-bed dust scrubbers use these mesh-type multi-layered filters. These filters trap dust particles efficiently on their surface and inside their mesh. However, their continued operation leads to dust build-up and clogging. This results in increased resistance of the filter and lowered airflow rate through the scrubber. This could potentially enhance the exposure of the miners. A non-clogging self-cleaning impingement screen type dust filter was designed by the authors for use in mining and industrial dust cleansing applications. The filter guides dirt-laden air through rapidly turning paths which forces it to shed heavier particles. The particles impact one of the impermeable solid metallic filter surfaces and are removed from the airstream. A full cone water spray installed upstream prevents any surface build-up of dust. This paper summaried the computer models generated to show the filter operations and laboratory experiments including optical particle counting to establish the cleaning efficiency. [Description provided by NIOSH]
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ISSN:2095-8293
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Pages in Document:16
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Volume:9
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Issue:1
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NIOSHTIC Number:nn:20066361
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Citation:Int J Coal Sci Technol 2022 Mar; 9(1):16
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Contact Point Address:Ashish Ranjan Kumar, Department of Mining and Nuclear Engineering, Missouri University of Science and Technology, 1400 N. Bishop Ave, Rolla, MO, 65401, USA
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Email:arkxnf@mst.edu
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Federal Fiscal Year:2022
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Performing Organization:University of Kentucky
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Peer Reviewed:True
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Start Date:20190901
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Source Full Name:International Journal of Coal Science & Technology
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End Date:20210831
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Main Document Checksum:urn:sha-512:cc6762b610183648aafbf12e06371d890feabe068c8bbff788e5cd29a567fe1208d5bbd833dbaa81c4e131a3088574ab3c847ffd0790e1169d03585cca8be79f
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