The Effect of Turbulence and Scalar Transport Models on Prediction of Worker Exposure to Aerosols
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2003/07/06
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Description:The present study is concerned with the relative concentrations of contaminants in the breathing-zone (BZ) when toxic airborne contaminants are released within an armlength in front of a worker, a common location that often leads to high exposures. Three-dimensional turbulent flow around a modeled human body in a wind tunnel has been simulated numerically and the results from various models are compared with each other. A model was built using a mesh generator to represent a real human body as closely as possible. Four different turbulence models, namely, standard k-e turbulence model, RNG k-e turbulence model, Reynolds Stress turbulence model (RSM) and Large Eddy Simulation (LES), were used to evaluate their effect on the predicted concentration levels used in assessing the exposure of the worker. Results from Eulerian scalar transport method and Lagrangian particle tracking method are also compared. Concentration levels are calculated at various sampling locations in the vicinity of the human face. It is found that the predicted concentration varies significantly from model to model: at the breathing zone the coefficient of variation for predicted concentration is 30%. [Description provided by NIOSH]
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ISBN:0791836975
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Volume:2
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NIOSHTIC Number:nn:20053041
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Citation:Proceedings of ASME FEDSM'03: ASME/JSME 2003 4th Joint Fluids Engineering Conference, July 6-10, 2003, Honolulu, Hawaii. New York: The American Society of Mechanical Engineers, 2003 Jul; :1813-1818
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Federal Fiscal Year:2003
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Performing Organization:College of Egineering and Mineral Resources, West Virginia University
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Peer Reviewed:False
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Start Date:20010701
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Source Full Name:Proceedings of ASME FEDSM'03: ASME/JSME 2003 4th Joint Fluids Engineering Conference, July 6-10, 2003, Honolulu, Hawaii
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End Date:20050630
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Main Document Checksum:urn:sha-512:3ff17ede28c618284c30a691be91549c3218b2b5351e6b57469a04da9608d497f0de8635c9bd3ad4dd1e16e54418a38a1f7a49c6f6f9c282f63437e0969ac441
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