Work

Study on the temperature variation characteristics of subway vehicles interior fire based on realistic scenarios

Year: 2025
Type: article
Abstract: Subway vehicle fire incidents pose significant safety challenges, making it crucial to understand temperature variation characteristics. Realistic fire scenarios in subway vehicles involve dynamic door opening and air conditioning ventilation, both of which greatly impact temperature variations. However, existing research has not addressed the impact of these factors. This paper addresses this gap by proposing three predictive models for temperature variation. First, a 150 kW fire source experiment is analyzed across 6 scenarios, revealing that the maximum temperature rise may occur either before or after door opening, indicating that models for before and after door opening should be studied independently. Second, CFD simulations are conducted across 70 scenarios to analyze temperature variations, identifying fire source location, fire source power, and air conditioning ventilation speed as key factors influencing temperature variation in realistic fire scenarios. Third, based on the simulation data and key factors, a maximum temperature rise model, a maximum temperature difference model, and a temperature attenuation model are proposed to predict interior temperature variations in realistic fire scenarios. Finally, comparisons between these models and experimental results showed root mean square errors of 10.5 °C and 9.07 °C for the maximum temperature rise and attenuation models, respectively, with the experimental data for the maximum temperature difference also complying with the model's range. This paper provides a theoretical basis for accurately predicting temperature variation in realistic subway vehicle fire scenarios, offering meaningful insights for improving fire safety measures and emergency response strategies.
Authors: Yan Huo, Xin Tian, Yong Sun, Ruonan Li, Gaowan Zou, Xueyan Xu
Language: English
Open Access status: gold
Estimated APC paid: $1,620
OpenAlex ID: W4417026912
FWCI: 0.583
Cites: 25
Cited by: 1
Related to: