Journal of Korean Society of Occupational and Environmental Hygiene (한국산업보건학회지)

Korean Industrial Hygiene Association (한국산업보건학회)
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A Study on Indirect Prediction of Welding Fume Concentrations Using Computational Fluid Dynamics

전산유체역학을 이용한 용접흄농도 간접적 예측가능성 연구

  • Piao, Cheng Xu (Department of Environmental Engineering, Changwon National University) ;
  • Kim, Tae Hyeung (Department of Environmental Engineering, Changwon National University) ;
  • Seo, Jeoung Yoon (Department of Environmental Engineering, Changwon National University) ;
  • He, Rong Bin (Department of Environmental Engineering, Changwon National University) ;
  • Lim, Jung Ho (Department of Environmental Engineering, Changwon National University) ;
  • Kang, Dae Woong (Department of Environmental Engineering, Changwon National University) ;
  • Ha, Hyun Chul (Ventech Corp.)
  • Received : 2009.08.29
  • Accepted : 2009.11.20
  • Published : 2009.12.30
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Abstract

There are various methods for welding fume control. These methods can be divided into local exhaust system, general ventilation system and integrated control system. With the general ventilation system, we should have a good prediction tool for testing various appropriate control options. But, until now there are not many studies about how to predict the welding fume concentrations. Especially, the prediction of welding fume concentration is not a very easy task because welding fume is the particulate matters. In this study, we tried to measure $CO_2$ concentrations and welding fume concentrations in a small single room with a small ventilation opening. Using commercially available CFD (Computational Fluid Dynamics) software, we tried to predict $CO_2$ concentrations under the exactly same conditions. Then, we tried to compare the numerical $CO_2concentrations$ with the experimental results to know whether we could predict $CO_2$ concentrations. Then we tried to compare $CO_2$ concentrations with experimental welding fume concentrations to know whether we can use the numerical $CO_2concentrations$ to predict the welding fume concentration indirectly.

Keywords

Acknowledgement

Supported by : 창원대학교

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