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http://dx.doi.org/10.5762/KAIS.2017.18.2.443

Study on the optimal design of floor exhaust system using computational fluid dynamics for subway platform  

Namgung, Hyeong-Gyu (Transportation Environmental Research Team, Korea Railroad Research Institute(KRRI))
Park, Sechan (Transportation Environmental Research Team, Korea Railroad Research Institute(KRRI))
Kim, Minhae (Transportation Environmental Research Team, Korea Railroad Research Institute(KRRI))
Kim, Soo-Yeon (Transportation Environmental Research Team, Korea Railroad Research Institute(KRRI))
Kwon, Soon-Bark (Transportation Environmental Research Team, Korea Railroad Research Institute(KRRI))
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.18, no.2, 2017 , pp. 443-449 More about this Journal
Abstract
The imbalance of air supply and the exhaust on subway platforms has led to the installation of platform screen doors in underground subway stations. This imbalance causes the accumulation of pollutants on the platform and loss of comfort due to the lack of ventilation. In this study, a floor exhaust system was optimized using computational fluid dynamics (CFD) and an optimization program. The optimized floor exhaust system was manufactured and tested experimentally to evaluate the particle collection efficiency. CFX 17.0 and HEEDS were used to analyze the flow field and optimize the principal dimensions of the exhaust system. As a result of the three-step optimization, the optimized floor exhaust system had a total height of 1.78 m, pressure drop of 430 Pa, and particle collection capability of 61%. A fine dust particle collection experiment was conducted using a floor exhaust system that was manufactured at full scale based on the optimized design. The experiment indicated about 65% particle collection efficiency. Therefore, the optimized design can be applied to subway platforms to draw in exhaust air and remove particulate matter at the same time.
Keywords
CFD; Floor exhaust system; Indoor Air Quality; Optimization program; Subway station;
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Times Cited By KSCI : 6  (Citation Analysis)
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