Tunnel shaft impact on smoke transport in fire-induced high-speed train stopping

When a moving high-speed train experiences a sudden fire and is forced to stop in a tunnel with a shaft, the smoke transport characteristics become complex due to the coupled effects of the train's piston effect and natural smoke extraction through the shaft, posing significant risks to personnel safety and tunnel infrastructure. This study numerically reproduces the above fire scenario to analyze the impact of the tunnel shaft on smoke transport characteristics following a fire-induced train stoppage. The research utilizes the renormalization group (RNG) k-ε turbulence model with buoyancy correction and the volume heat source model, utilizing a sliding mesh technique to simulate the movement of a fire-affected high-speed train in a tunnel with a shaft. The reliability of the numerical approach is validated through moving model test results. The study examines the evolution of smoke flow velocity and temperature during the uniform speed–deceleration–stopping phase and for 360 s after the train halts. Additionally, the effects of the distance between the fire source and the shaft (Df-s), the shaft height (H), and the shaft area (S) on smoke flow velocity and temperature are analyzed. Finally, orthogonal range analysis identifies Df-s as the most significant factors influencing peak temperature and the high-temperature smoke zone in the tunnel, with a markedly stronger effect than the other two parameters. The results can provide guidance for the escape and evacuation of personnel in the event of a fire on a high-speed train inside a tunnel.

Authors

Institutions

Publication Details

Journal
Physics of Fluids
Published
2025-02-01
DOI
https://doi.org/10.1063/5.0250033
Citations
5
Primary Topic
Fire dynamics and safety research
Type
article
Field-Weighted Citation Impact
6.52

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Tunnel shaft impact on smoke transport in fire-induced high-speed train stopping

Z. Tang, Shuang Meng, Dan Zhou, Hao Du
5 citations
Physics of Fluids
Fire dynamics and safety research
6.52
article

Tunnel shaft impact on smoke transport in fire-induced high-speed train stopping

Z. Tang, Shuang Meng, Dan Zhou, Hao Du
article en
5 citations

Abstract

When a moving high-speed train experiences a sudden fire and is forced to stop in a tunnel with a shaft, the smoke transport characteristics become complex due to the coupled effects of the train's piston effect and natural smoke extraction through the shaft, posing significant risks to personnel safety and tunnel infrastructure. This study numerically reproduces the above fire scenario to analyze the impact of the tunnel shaft on smoke transport characteristics following a fire-induced train stoppage. The research utilizes the renormalization group (RNG) k-ε turbulence model with buoyancy correction and the volume heat source model, utilizing a sliding mesh technique to simulate the movement of a fire-affected high-speed train in a tunnel with a shaft. The reliability of the numerical approach is validated through moving model test results. The study examines the evolution of smoke flow velocity and temperature during the uniform speed–deceleration–stopping phase and for 360 s after the train halts. Additionally, the effects of the distance between the fire source and the shaft (Df-s), the shaft height (H), and the shaft area (S) on smoke flow velocity and temperature are analyzed. Finally, orthogonal range analysis identifies Df-s as the most significant factors influencing peak temperature and the high-temperature smoke zone in the tunnel, with a markedly stronger effect than the other two parameters. The results can provide guidance for the escape and evacuation of personnel in the event of a fire on a high-speed train inside a tunnel.

Physics of FluidsVol. 37(2)
Central South University (CN), State Key Laboratory of Vehicle NVH and Safety Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 4%
Fire dynamics and safety research
6.52
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.