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  5. Experimental Study on the Maximum Ceiling Gas Temperature Driven by Double Fires in a Tunnel with Natural Ventilation

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Preprint
English
2023

Experimental Study on the Maximum Ceiling Gas Temperature Driven by Double Fires in a Tunnel with Natural Ventilation

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English
2023
DOI: 10.2139/ssrn.4503642

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Long Shi
Long Shi

University Of Science And Technology Of China

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Kun He
Ying Zhen Li
Haukur Ingason
+2 more

Abstract

The maximum gas temperature below the ceiling is an important parameter for tunnel safety. The present study analyzed the characteristics of the maximum excess ceiling gas temperature driven by double fire sources in a naturally ventilated tunnel. A series of reduced-scale tunnel fire experiments were carried out with different fire separation distances and heat release rates. Theoretical analysis based on the equivalent virtual origin was also undertaken. The results showed that there exists only one peak gas temperature when the two fire plumes are merged before reaching the ceiling, while two peak gas temperatures can be observed for when the two fire plumes are completely separated. The maximum excess gas temperature below the tunnel ceiling gradually decreases with an increasing fire separation distance in the plume merging region (S < Scp). When the fire separation distance increases further (S > Scp), the effect of the fire separation distance on the maximum gas temperature below the ceiling is very limited. Furthermore, a model using an equivalent fire source was proposed to predict the maximum excess gas temperature below the ceiling, considering different plume merging states. The present study benefits to the understanding of the maximum excess gas temperature characteristics of the smoke flow driven by double fires with an equal heat release rate in naturally ventilated tunnels.

How to cite this publication

Kun He, Ying Zhen Li, Haukur Ingason, Long Shi, Xudong Cheng (2023). Experimental Study on the Maximum Ceiling Gas Temperature Driven by Double Fires in a Tunnel with Natural Ventilation. , DOI: 10.2139/ssrn.4503642.

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Publication Details

Type

Preprint

Year

2023

Authors

5

Datasets

0

Total Files

0

Language

English

DOI

10.2139/ssrn.4503642

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