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Author:

Ren, Ming-Liang (Ren, Ming-Liang.) | Chen, Chao (Chen, Chao.) (Scholars:陈超) | Guo, Qiang (Guo, Qiang.) | Yang, Ying-Xia (Yang, Ying-Xia.) | Kang, Guo-Qing (Kang, Guo-Qing.) | Luo, Hai-Liang (Luo, Hai-Liang.)

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EI Scopus PKU CSCD

Abstract:

This paper analyzed the formation of piston-effect and the air flow characteristics in subway. Taking an operating subway in Beijing as a study object, the calculation results of SES and the commercial CFD software PHOENICS (3.6.1) were compared which shows well accordance. At the same time the SES results and the field measurement results were compared which shows well accordance too. Then the result of study was applied to a subway HVAC design in Beijing. A draft plan of the construction of ventilation shaft that can use the piston-effect effectively to reduce the HVAC energy consumption was put forward.

Keyword:

Computational fluid dynamics Pistons Optimization HVAC Computer simulation Railroads Subways Energy utilization

Author Community:

  • [ 1 ] [Ren, Ming-Liang]College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100022, China
  • [ 2 ] [Chen, Chao]College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100022, China
  • [ 3 ] [Guo, Qiang]College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100022, China
  • [ 4 ] [Yang, Ying-Xia]College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100022, China
  • [ 5 ] [Kang, Guo-Qing]College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100022, China
  • [ 6 ] [Luo, Hai-Liang]College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100022, China

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Source :

Journal of Shanghai Jiaotong University

ISSN: 1006-2467

Year: 2008

Issue: 8

Volume: 42

Page: 1376-1380,1391

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

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