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S. G. Zhang, Y. Z. Yao, K. Zhu, K. Y. Li, R. F. Zhang, S. Lu and X. D. Cheng (2016) Tunnelling And Underground Space Technology 53 13-21.
Date: 2017-03-09   Author: SKLFS  ,   Source: SKLFS  ,
 

S. G. Zhang, Y. Z. Yao, K. Zhu, K. Y. Li, R. F. Zhang, S. Lu and X. D. Cheng (2016) Prediction of smoke back-layering length under different longitudinal ventilations in the subway tunnel with metro train. Journal/Tunnelling And Underground Space Technology 53 13-21. [In English]
Web link: http://dx.doi.org/10.1016/j.tust.2015.12.013
Keywords: ,Smoke back-layering, Longitudinal ventilation, Subway tunnel, Metro, train, FDS, CRITICAL VELOCITY, NUMERICAL-SIMULATION, BACKLAYERING LENGTH, FIRE, BEHAVIOR, TEMPERATURE, BLOCKAGE, FLOW

Abstract: Due to the small width and the large train blockage ratio in subway tunnel, the smoke back-layering will be different from that in the wider road tunnel with small vehicle blockage ratio. In the train blockage region of tunnel, the velocity of longitudinal ventilated air-flow interacting with the back-flowed smoke gas is different from that in the upstream tunnel without train blockage. Then the back-flowed smoke gas might be prevented in the train blockage region with higher ventilation velocity, otherwise it would be stopped in the upstream tunnel without train blockage but with lower ventilation velocity. They were taken into consideration separately and an equivalent fire source was introduced by dividing the dimensionless heat release rate of fire source into two parts in the cases where the smoke back-layering length is longer than metro train length. A series of full-scale numerical simulations are carried out with FDS to investigate the smoke back-layering length in subway tunnel with different train lengths and longitudinal ventilation velocities. The simulation results indicate that the influence of metro train length on the smoke back-layering is great and cannot be ignored any more. A global correlation model is proposed based on the dimensionless analysis and simulation results. (C) 2015 Elsevier Ltd. All rights reserved.

 
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