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Full-scale fire tests in the underwater tunnel section model with sidewall smoke extraction
Highlights Eight groups of fire tests up to 6.6 MW in a 150-m long full-scale underwater tunnel model. Fire and smoke dynamics are revealed in tunnel with a unique sidewall extraction. Sidewall extraction slows down the smoke spread and keeps a good stratification. Propose a framework of establishing full-scale tunnel fire database for smart fire system.
Abstract The Hong Kong–Zhuhai–Macau Bridge (HZMB) is a 55-km bridge-tunnel system, including a 6.7-km undersea tunnel that adopts the sidewall smoke extraction system. To evaluate the potential tunnel fire hazards, a 1:1 full-scale HZMB tunnel section model (16 m × 7.2 m × 150 m) was constructed, and eight full-scale tunnel fire tests were conducted with the sidewall smoke extraction. The temperature distribution and smoke movement under different vent arrangements and fire sizes (1.2–6.6 MW) were quantified. Results indicated that the fire HRR was mainly affected by the size of the liquid-fuel pool but insensitive to the arrangement of ventilation. The correlation between HRR and diesel pool-fire area can be fitted by a linear function of MW. The sidewall smoke extraction generated a tilted fire plume and non-uniform temperature distribution at the transverse direction, whereas the temperature decay still followed the exponential decay for the far fire field region. The decay factor increases with the increase of the HRR and increases when distributing the ventilation capability into two vent groups. A relatively slow smoke motion (0.8–1.2 m/s) and good smoke stratification were demonstrated in the tests, indicating a robust condition for safe evacuation. This research deepens the understanding of fire and smoke characteristics in tunnels with the sidewall extraction and highlights the importance of full-scale test data in the development of the smart tunnel-fire protection system.
Full-scale fire tests in the underwater tunnel section model with sidewall smoke extraction
Highlights Eight groups of fire tests up to 6.6 MW in a 150-m long full-scale underwater tunnel model. Fire and smoke dynamics are revealed in tunnel with a unique sidewall extraction. Sidewall extraction slows down the smoke spread and keeps a good stratification. Propose a framework of establishing full-scale tunnel fire database for smart fire system.
Abstract The Hong Kong–Zhuhai–Macau Bridge (HZMB) is a 55-km bridge-tunnel system, including a 6.7-km undersea tunnel that adopts the sidewall smoke extraction system. To evaluate the potential tunnel fire hazards, a 1:1 full-scale HZMB tunnel section model (16 m × 7.2 m × 150 m) was constructed, and eight full-scale tunnel fire tests were conducted with the sidewall smoke extraction. The temperature distribution and smoke movement under different vent arrangements and fire sizes (1.2–6.6 MW) were quantified. Results indicated that the fire HRR was mainly affected by the size of the liquid-fuel pool but insensitive to the arrangement of ventilation. The correlation between HRR and diesel pool-fire area can be fitted by a linear function of MW. The sidewall smoke extraction generated a tilted fire plume and non-uniform temperature distribution at the transverse direction, whereas the temperature decay still followed the exponential decay for the far fire field region. The decay factor increases with the increase of the HRR and increases when distributing the ventilation capability into two vent groups. A relatively slow smoke motion (0.8–1.2 m/s) and good smoke stratification were demonstrated in the tests, indicating a robust condition for safe evacuation. This research deepens the understanding of fire and smoke characteristics in tunnels with the sidewall extraction and highlights the importance of full-scale test data in the development of the smart tunnel-fire protection system.
Full-scale fire tests in the underwater tunnel section model with sidewall smoke extraction
Jiang, Yaqiang (author) / Zhang, Tianhang (author) / Liu, Shuai (author) / He, Qinli (author) / Li, Le (author) / Huang, Xinyan (author)
2022-01-07
Article (Journal)
Electronic Resource
English
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