(2023) The simulation of the emission of iron fumes caused by shielded metal arc welding using a computational fluid dynamics method. Toxicology and Industrial Health. pp. 36-48. ISSN 0748-2337
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Abstract
Computational fluid dynamics (CFD) is an indispensable simulation tool for predicting the emission of pollutants in the work environment. Welding is one of the most common industrial processes that might expose the operators and surrounding workers to certain hazardous gaseous metal fumes. In the present study, we used computational fluid dynamics (CFD) methodology for simulating the emission of iron fumes from the shielded metal arc welding (SMAW) procedure. A galvanized steel chamber was fabricated to measure the pollutant concentration and identify the size of the fume created by the SMAW. Then, the emission of welding aerosol was simulated using a method of computational fluid-particle dynamics with the ANSYS 2020 R1 software. The highest amount of welding fumes concentration was related to iron fumes (i.e., 3045 mu g/m(3) with a diameter of 0.25 mu m). The results of the current study indicated that the local exhaust and general ventilation system can prevent the spreading of welding fumes to the welder's breathing zone and the surrounding environment. CFD was also found to be an efficient method for predicting the emission of the iron fumes created by SMAW as well as for selecting an appropriate ventilation system. However, further studies that take the modeling of welding-generated emission of additional metal particles and gases into account will need to be undertaken.
Item Type: | Article | ||||||||
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Keywords: | Fluid simulation computational dynamics welding fume shielded metal arc welding computational fluid dynamics cfd simulation numerical-simulation subject-variability particle-transport air-flow ventilation exposure deposition model responses Public, Environmental & Occupational Health Toxicology | ||||||||
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Page Range: | pp. 36-48 | ||||||||
Journal or Publication Title: | Toxicology and Industrial Health | ||||||||
Journal Index: | ISI | ||||||||
Volume: | 39 | ||||||||
Number: | 1 | ||||||||
Identification Number: | https://doi.org/10.1177/07482337221144143 | ||||||||
ISSN: | 0748-2337 | ||||||||
Depositing User: | مهندس مهدی شریفی | ||||||||
URI: | http://eprints.medilam.ac.ir/id/eprint/4224 |
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