In this paper, full-scale fire experiments and numerical simulations in a underground powerhouse of a hydropower station during construction stage were carried out to study the temperature distribution and smoke propagation. Characteristic of inverse ambient temperature in the vertical direction was found, resulting in the vertical movement of smoke being different from that in a uniform temperature environment. The maximum temperature rise appeared at non highest points. Smoke characteristic parameters like smoke settling heights and temperature rise were discussed under different HRR of fire source to determine the fire risk distribution of the powerhouse. Two ventilation modes are proposed, and the comparison of smoke control effects between each ventilation modes was made. The optimal ventilation mode and ventilation volume in different fire scenarios are proposed. The research findings can offer scenario and data support to fire smoke control and emergency plan design in the powerhouse of hydropower stations.

Fire accident seriously threatens the stable operation and personnel security in the subway station, and thermal stratification is an important factor used to determine smoke settlement. Therefore, this paper carried out a series of model experiments by altering the heat release rate (HRR), fire locations, and ventilation conditions. The vertical temperature of the central longitudinal axis was measured, and the S value representing that thermal stratification characteristic was calculated and compared under various fire scenarios. The results showed that the temperature changing curve in the vertical direction was significantly affected by ventilation volume, but it had little to do with the HRR and fire location. The increase of HRR could influence the value of S by enhancing the upper temperature for the whole space and heating the lower temperature near the fire. In addition, the S value decreased with the distance under different longitudinal fire source locations, whereas the variety of S was not monotonical with the deviating transverse distance. And the larger ventilation volume was conducive to restricting smoke diffusion and improving the value of S. This work could provide data support and theoretical reference for controlling smoke stratification under subway station fire.

With the development of urban transportation, metros have become an important means of travel for residents. However, casualty and economic loss might occur in metro systems due to various emergencies. Social media has gradually become the main way to express people’s needs, which provides a new analysis perspective for risk management in metros. This study takes the Zhengzhou Metro flood as an example and collects relevant social media data. Then, the analysis method of social media data evolution characteristics in metro emergencies is proposed. Finally, the evolution characteristics of social media data are analyzed from three aspects: spatiotemporal distribution, emotional distribution, and hot topics classification. The results show that: The temporal distribution of social media data is affected by the emergency process and official media; the spatial distribution of social media data reflects the distribution of stations affected by emergency and temporary shelters; timely and appropriate official media reports are conducive to guiding public emotions toward positive; and the key hot topics can be divided into disaster environment (DE), disaster impact (DI), disaster carrier (DC), emergency management (EM), positive comment (PC), and negative comment (NC). The proposed method can provide support for public opinion analysis and risk management in metro emergencies.

Real-time social media data can be used to improve data timeliness and accuracy during disaster emergency responses. The key disaster area needs are prioritized here using a disaster relief index system for emergency rescue and command support needs, post-disaster emergency rescue needs, basic living support needs and public infrastructure support needs. The emergency relief evaluation model uses entropy weights and the grey improvement technique for order preference by similarity to an ideal solution (TOPSIS). The method is applied to the typhoon Lekima response as an example to assess the specific emergency rescue needs in the cities of affected provinces to verify the effectiveness of this disaster evaluation model by comparison with disaster loss data.

Full-scale fire experiments in real highway tunnels were conducted to evaluate the temperature measurement errors in such experiments. The longitudinal temperature distributions in the tunnel were measured in repeated trials with the same conditions. Statistical analyses were then use to quantify the temperature measurement errors in different areas and at different times. The maximum error was more than ±20℃ with the maximum relative error reaching 40%. Fluctuations in the flow rate and fire power were two important factors affecting the uncertainties with then increased the standard deviation of the temperature in the smoke front arrival stage and the fire power attenuation stage. There were significant differences in the standard deviations of the temperature upstream and downstream of the fire source. The upwind smoke diffusion is more easily disturbed by flow rate fluctuations with a maximum relative temperature error of more than 20%. The results support accuracy evaluations and error analyses of full-scale experimental tunnel fire data.

Full-scale experiments in a bifurcated tunnel in a hydropower station with a fire source at the junction area were conducted to investigate fire-induced smoke spread characteristics in connected regions. The spread and descent of smoke in each tunnel were studied by analyzing the temperature profiles and smoke layer heights coupled with on-site observations. The results show that the slope and ventilation strongly affect the smoke risks in each tunnel with the smoke temperature steadily decreasing with distinct stratification upwind of the fire source. The smoke and fresh air mixture flow disrupted the smoke stratification and caused the smoke level to lower in the tunnel with the vertical temperature distribution becoming more uniform. Moreover, the aggravation of smoke deposition in the uphill direction in tunnel 2# increased the smoke temperature in the longitudinal direction below 3 m. The different fire risks in different tunnel sections should be carefully considered in smoke control designs. For the present fire heat release rate, the smoke layer height remained at 4.2 m in the upstream tunnel, while the downstream tunnels faced higher risks that the smoke layer descending below 1.5 m. The uphill slope in tunnel 2# increased the smoke descent with the smoke height decreasing to 0.8 m after 2 min, which should be considered in smoke control designs and fire emergency.

Large metro transfer stations have been widely constructed in China, among which the double-island station faces the serious fire safety issues owing to its large passenger flow. In this paper, simulation cases were carried out to investigate the effectiveness of different ventilation modes by jointly operating tunnel ventilation fan (TVF) and platform screen doors (PSD) under two typical fire scenarios in the platform. The numerical model was established by Fire Dynamics Simulator software and verified via reduced-scale model experiments. The results indicate that the TVF mode of supplying at the end near fire and exhausting at the other end is superior to that of exhausting at both ends. Besides, activating more PSD and TVF on the both sides of platform will restrict smoke in one end to the greater extent. During a fire in the middle of the platform, opening all PSD near tunnel-2 and TVF in tunnel-2 and tunnel-3 is the most appropriate mode. While during a fire at the left end of the platform, activating all PSD and TVF on both sides is the optimal operation mode. The conclusions can provide guidance for smoke control design and on-site emergency ventilation operation in double-island platform fire.