Headform and N95 filtering facepiece respirator interaction: contact pressure simulation and validation
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2012/01/01
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Description:This article presents a computational and experimental study of contact pressure between six N95 filtering facepiece respirators (FFRs) and five newly developed digital headforms (small, medium, large, long/narrow, and short/wide). Contact interaction is simulated using the finite element method and validated by experiments using a pressure mapping system. The headform model has multiple layers: a skin layer, muscle layer, fatty tissue layer, and bone layer. Each headform is divided into five parts (two parts for the cheeks, one part for the upper forehead, one part for the chin, and one part for the back side of the head). Each respirator model comprises multiple layers and two straps. The simulation process has two stages for each respirator/headform combination. The first stage is to wrap the straps around the back of the headform and pull the respirator away from the face. The second stage is to release the respirator so that the respirator moves toward the face. Strap forces and contact interactions are generated between the respirators and the headforms. Meanwhile, a real-time surface pressure mapping system is used to record the pressures at six key locations to validate the computational results. There is a strong correlation between computational and experimental results (R2 = 0.88). By comparing the pressure values from simulations and experiments, we have validated the simulation models. [Description provided by NIOSH]
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ISSN:1545-9624
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Pages in Document:46-58
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Volume:9
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Issue:1
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NIOSHTIC Number:nn:20040077
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Citation:J Occup Environ Hyg 2012 Jan; 9(1):46-58
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Contact Point Address:James Yang, Human-Centric Design Research Lab, Department of Mechanical Engineering, Texas Tech University, Lubbock, TX 79409
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Email:james.yang@ttu.edu
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Federal Fiscal Year:2012
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Peer Reviewed:True
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Source Full Name:Journal of Occupational and Environmental Hygiene
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Main Document Checksum:urn:sha-512:6c8bba1668feb2863c01a9bbb12d9b35ed6e56a439948b90888218ed1c5030887fc25a280b7e5e3eab83e95ca96694e5ae3ba4988eb03cf9be64cacdd5a08f2c
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