A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Prediction of back-layering length in subway tunnel with on-fire train running
Graphical abstract Display Omitted
Highlights The dynamic variations of smoke back-layering in motion train fire are studied. The maximum back-layering length varies logarithmically with the wind pressure. The effect of HRR, speed and deceleration on back-layering length are analyzed. An empirical model is proposed to predict the maximum back-layering length.
Abstract The exploitation and utilization of urban underground space effectively contribute to the sustainable development of society. Tunnel fire safety is necessary to ensure normal operation. Motion train fire is more serious and complex than stationary fire in tunnels due to the influence of unsteady piston wind. This study investigates the smoke back-layering characteristics of a burning subway train during emergency braking. A three-dimensional unsteady numerical model adopting the dynamic mesh technique is built to investigate the smoke diffusion characteristics of motion train fire. Experimental tests are conducted based on a 60 m-long scaled-down experimental setup to verify the accuracy of the numerical model. On this basis, the dynamic characteristics of smoke back-layering length as the longitudinal wind pressure is less than the critical value are studied, considering the influence of heat release rate (HRR), train speed, and train deceleration. The results indicate that the maximum back-layering length follows the logarithmic law with the variation of longitudinal wind pressure. An empirical model is proposed to predict the maximum back-layering length at various longitudinal wind pressure, and it is helpful to the optimization design of ventilation systems for tunnel motion fire.
Prediction of back-layering length in subway tunnel with on-fire train running
Graphical abstract Display Omitted
Highlights The dynamic variations of smoke back-layering in motion train fire are studied. The maximum back-layering length varies logarithmically with the wind pressure. The effect of HRR, speed and deceleration on back-layering length are analyzed. An empirical model is proposed to predict the maximum back-layering length.
Abstract The exploitation and utilization of urban underground space effectively contribute to the sustainable development of society. Tunnel fire safety is necessary to ensure normal operation. Motion train fire is more serious and complex than stationary fire in tunnels due to the influence of unsteady piston wind. This study investigates the smoke back-layering characteristics of a burning subway train during emergency braking. A three-dimensional unsteady numerical model adopting the dynamic mesh technique is built to investigate the smoke diffusion characteristics of motion train fire. Experimental tests are conducted based on a 60 m-long scaled-down experimental setup to verify the accuracy of the numerical model. On this basis, the dynamic characteristics of smoke back-layering length as the longitudinal wind pressure is less than the critical value are studied, considering the influence of heat release rate (HRR), train speed, and train deceleration. The results indicate that the maximum back-layering length follows the logarithmic law with the variation of longitudinal wind pressure. An empirical model is proposed to predict the maximum back-layering length at various longitudinal wind pressure, and it is helpful to the optimization design of ventilation systems for tunnel motion fire.
Prediction of back-layering length in subway tunnel with on-fire train running
Fan, Xianwang (author) / Yang, Junbin (author) / Zhang, Huan (author) / Wan, Zhihao (author) / Liu, Jiali (author) / Liu, Zhikai (author) / Zhu, Chunguang (author) / Zheng, Wandong (author)
2023-08-22
Article (Journal)
Electronic Resource
English
| British Library Online Contents | 2016
Effects of ambient pressure on smoke back-layering in subway tunnel fires
| British Library Online Contents | 2018