Tunnel Fire Research Articles

Study on road performance and flame retardant properties of direct-to-plant warm mixing-flame retardant SBS composite modified asphalt

In order to mitigate the current state of the asphalt tunnel fire crisis, this study intends to prepare a novel environmentally friendly direct-to-plant warm mixing-flame retardant SBS composite modified asphalt that will slow down the burning of asphalt itself and reduce the amount of smoke that is produced. This research introduced the preparation process for direct-to-plant SBS modified asphalt. Through conventional performance experiments, flash point and oxygen index tests, and based on DSR and BBR tests, a comparative analysis of ATH and HF-216 flame retardants was conducted. Additionally, the road performance and flame retardant properties of various warm mix types were analyzed by compounding them with flame retardants. The findings indicate that ATH and HF-216 flame retardants can, respectively, raise the softening point by 13 % and 16 %, lower the ductivity by 6 % and 7 %, and decrease the needle penetration of D-SBS by 10 % and 18 %.Both can enhance asphalt's high-temperature characteristics while negatively affecting its low-temperature characteristics. Warm mixing agent and flame retardant can greatly increase the consistency and deformation resistance of direct-to-plant SBS-modified asphalt; however, they also reduce the ductility of the material by 26 %, 16 %, and 12 %, respectively, which will negatively impact its performance at low temperatures. The composite modified asphalt's high temperature stability can be enhanced by compound mixing the three types of warm mixture before and after aging; nevertheless, the fatigue performance declines to varying degrees and the fatigue factor rises by 3535, 3811, and 3889 kPa, respectively. The warm mixture and flame retardant mixture's S value is 82.5 MPa, 33.7 MPa, 13.8 MPa (-12°C), and 187.4 MPa, 90.7 MPa, and 40.6 MPa (-18°C) higher than the D-SBS mixture's, respectively. The low temperature brittleness of D-SBS can be increased by combining a heated mixture with a flame retardant. The burning times of the Marshall and rut plate specimens are shortened by 31, 46, 55, and 86 s, respectively, when compared to the D-SBS combination. The residual stability is raised by 19.2 %, 21.2 %, and 6 %, 10.7 %, respectively, while the mass loss before and after combustion is decreased by 3.9 g, 5.8 g, and 26 g, 32 g, respectively. AH type exhibits superior flame retardant performance than WH type.

Characteristics of thermal smoke temperature and CO hazardous substance in tunnel fires: A review

Characteristics of thermal smoke temperature and CO hazardous substance in tunnel fires: A review

Experimental investigation on maximum ceiling temperature and longitudinal attenuation in a closed tunnel with an inclined shaft

For tunnel fires with open and closed tunnel ends, the smoke flow pattern and air supply conditions vary considerably, resulting in different maximum excess ceiling temperature (ΔTmax) and its longitudinal distribution (ΔTx). However, few studies have focused on the tunnel closed at both ends with an inclined shaft (typical tunnel structure during construction). Hence, tunnel model 1 (tunnel closed at both ends with an inclined shaft) and tunnel model 2 (tunnel open at both ends) are built for comparison and analysis. The results show that tunnel model 1 has higher ceiling temperatures and slower attenuation than tunnel model 2. Therefore, the ΔTx in tunnel model 1 needs to be re-analyzed in detail. Different inclined shaft slopes, fire heat release rates, longitudinal and vertical fire positions are considered. In tunnel model 1, for h (lifting height of burner surface) = 0, the ΔTmax value tends to be constant for the same heat release rate, irrespective of the longitudinal fire position. For h = 5 cm, the ΔTmax value takes on a rising trend with the fire moving downstream. Moreover, the inclined shaft slope within this study has little influence on ΔTx. As the fire moves downstream, the downstream ΔTx/ΔTmax value decreases more rapidly. From h = 0 to h = 5 cm, the value of ΔTx/ΔTmax drops slightly faster, but the gap is small and can be ignored. Finally, the experimental correlations are proposed to estimate the longitudinal ceiling temperature distribution in a closed tunnel with an inclined shaft.

Numerical Study on the Influence of the Slope Composition of the Asymmetric V-Shaped Tunnel on Smoke Spread in Tunnel Fire

Asymmetrical V-shaped tunnels often appear in tunnels crossing the river or urban underground road tunnels. The smoke flow inside is affected by a lot of factors. A full understanding of the smoke flow in this kind of tunnel is the basis of the smoke control. In this study, the effects of slope composition and fire heat release rate (HRR) on the longitudinal induced airflow velocity, the smoke back-layering length at the small slope side, and the maximum ceiling temperature were studied by the numerical method. The results show that when the fire occurs at the slope change point of the V-shaped tunnel, the maximum ceiling temperature decreases with the increase in the slope of the large-slope side tunnel. The longitudinally induced velocity is primarily related to the slope of the large-slope side tunnel and the fire HRR. When the slope difference between the side tunnels or the slope of the large-slope side tunnel is large, the smoke in the small-slope side tunnel flows back toward the fire source after reaching its maximum dispersion distance and then reaches a quasi-steady state. The smoke back-layering length is mainly affected by the slope and length of the large-slope side tunnel. When the slope of the large-slope side tunnel is 9%, the induced airflow velocity from the small-slope side can prevent the spread of smoke. The empirical models of the smoke back-layering length and the longitudinal induced airflow velocity in the small-slope side tunnel are drawn, respectively, by the theoretical analysis and the numerical results. This study can provide technical support for the design and operation of smoke control systems in V-shaped tunnels.

Optimised prediction of tunnel fire heat release rate using the ResNet18_2CLSTM model with bagging for multimodal data

Accurate predictions of HRR will improve preparedness and response strategies, enhance safety, and minimise damage in tunnel fires. In this study, a deep learning prediction model for HRR under multimodal data fusion is proposed. A multimodal dataset is first established to obtain flame images and flue gas time series data through model-scale tunnel fire experiments. During the model training process, ResNet18 was used to extract features from the flame image, and 2CLSTM was employed to understand the time series of the flame image features and flue gas features to establish the correlation with the HRR. It was evaluated that the error analyses of the measured and predicted values of the validation set yielded R2 greater than 0.85, with errors and standard deviations less than 4 kW. And the model predicted better in the flame growth and decay phases. However, there is some deviation in the predictions near the peak HRR. To address this issue, the Bagging algorithm was introduced to optimise the model. The results show that the ResNet18_2CLSTM model with Bagging reduces the RMSE by 20.47 % and increases the R2 by 4.64 % compared to the original model, and the accuracy is greatly improved.

Fire and smoke transport dynamics in a dead-end tunnel under heavy rainfall

Fire is one of the most common major accidents during tunnel construction and operation. This work conducted scale-model experiments to investigate the pool burning progress and flame characteristics in a dead-end tunnel with one end closed and the other open under heavy rainfall. The results show that, compared to opening both ends, the global burning time of fires is significantly decreased, and the quasi-stable burning phase is advanced under the combined effects of the closed end and heavy rainfall. The reason is that the increase in ceiling temperature, resulting from the accumulation of hot smoke, leads to an increase in radiative feedback of the fuel from the environment and an acceleration in the pool's burning rate. A coefficient (denoted by γ) is defined to evaluate the increase in the burning rate resulting from the dead-end. The enhancement ratio is found to be related to rainfall intensity, raindrop size, and pool size, and a correlation has been established based on the experimental results. The fire has an increased flame height and a reduced tilt angle under the impact of the dead-end. The changes in flame geometry parameters are mainly influenced by thermal buoyancy and the restriction of the dead-end. Prediction formulas for flame height and tilt angle under the combined effects of the dead-end and heavy rainfall have been proposed based on theoretical analysis. Under these combined effects, the tunnel space becomes eroded by dirty air.

A Tunnel Fire Detection Method Based on an Improved Dempster-Shafer Evidence Theory

Tunnel fires are generally detected using various sensors, including measuring temperature, CO concentration, and smoke concentration. To address the ambiguity and inconsistency in multi-sensor data, this paper proposes a tunnel fire detection method based on an improved Dempster-Shafer (DS) evidence theory for multi-sensor data fusion. To solve the problem of evidence conflict in the DS theory, a two-level multi-sensor data fusion framework is adopted. The first level of fusion involves feature fusion of the same type of sensor data, removing ambiguous data to obtain characteristic data, and calculating the basic probability assignment (BPA) function through the feature interval. The second-level fusion derives basic probability numbers from the BPA, calculates the degree of evidence conflict, normalizes the BPA to obtain the relative conflict degree, and optimizes the BPA using the trust coefficient. The classical DS evidence theory is then used to integrate and obtain the probability of tunnel fire occurrence. Different heat release rates, tunnel wind speeds, and fire locations are set, forming six fire scenarios. Sensor monitoring data under each simulation condition are extracted and fused using the improved DS evidence theory. The results show that there is a 67.5%, 83.5%, 76.8%, 83%, 79.6%, and 84.1% probability of detecting fire when it occurs, respectively, and identifies fire occurrence in approximately 2.4 s, an improvement from 64.7% to 70% over traditional methods. This demonstrates the feasibility and superiority of the proposed method, highlighting its significant importance in ensuring personnel safety.

Arc Ignition Methods and Combustion Characteristics of Small-Current Arc Faults in High-Voltage Cables

High-voltage cables will continue to operate for a period of time in the event of a small current arc fault, which poses a risk of fire. Two simulated ignition methods, moving electrode and melting fuses, are proposed to analyze the ignition characteristics of low-current arcs. The ignition test was carried out, and the combustion effect was compared. The results indicate that the moving electrode ignition method can achieve long-distance arc ignition test when the current is small and is suitable for simulating the arc ignition situation of cable outer protective layer damage. By controlling the movement speed, it can be ensured that the arc will not be interrupted during the electrode movement process. However, the arc is difficult to sustain using the fuse melting method when the current is small and the distance is long. The fuse melting method is suitable for simulating insulation breakdown situations. The results show that the critical arc duration for cable ignition under five different current conditions of 2–10 A is 28 s, 21 s, 14 s, 9 s, and 4 s, respectively. The maximum height of the cable flame under 2–10 A arc current is 9–52 cm and 16–63 cm, respectively, when the arc duration is 50 s and 100 s. The self-ignition time of the cable after the arc extinguishing is 8–95 s and 14–261 s, respectively. The maximum temperature of the cable flame is positively correlated with arc current, and the maximum flame temperature of the cable under 2–10 A arc current is 540–980 °C. Based on the actual current monitoring data in cable tunnels, the research results can provide reference for the risk assessment and protection of cable tunnel fires.

Smoke control and temperature distribution of tunnel fires under longitudinal ventilation combined with shaft exhaust

Longitudinal segmental smoke exhaust is often used for fire tunnels longer than 5 km. With the combined effect of longitudinal ventilation in the main tunnel and fan suction in the exhaust shaft, the smoke exhaust path is different from that of a traditional single-tube tunnel. Findings reported in the literature is insufficient to support the rapid development of extra-long road tunnels. In this paper, a numerical model was established by FDS (Fire Dynamics Simulator), and a 1:15 model test platform was built for verification. The effects of different longitudinal velocities, exhaust velocities, bifurcation angles, and exhaust shaft slopes on tunnel fires were analyzed for the longitudinal ventilation combined with shaft exhaust smoke evacuation mode (LVSE). The results show that when the exhaust velocity is greater than 4.5m/s, increasing the exhaust velocity has a limited effect on reducing the smoke length downstream of the exhaust shaft. The bifurcation angle has a significant effect on the velocity distribution in the ventilation shaft and the main tunnel. When the bifurcation angle is less than 45°, the airflow in the main tunnel is more likely to enter the exhaust shaft, and the velocity in the exhaust shaft is more than 5m/s. It is more favorable to reduce the smoke length when the slope of the exhaust shaft is not less than 7%. The high-temperature flue gas collects and forms a vortex near the vent under the LVSE mode, which makes the temperature decay rate slower than that when only longitudinal ventilation is used. The temperature decay model for the LVSE mode is obtained. This study is intended to provide a reference basis for the fire safety design of extra-long road tunnels under the LVSE mode.

The Fire-ViT Model for Tunnel Fire Detection with Vision Transformer Improvement

Smoke detection in tunnels presents unique challenges, including low light conditions, visual obstructions like smoke and headlights, and the need to analyze ultrahigh-resolution images. To address these challenges, this study introduces an innovative model named Fire-ViT, leveraging the vision transformer (ViT) architecture. Unlike traditional convolutional neural networks that often struggle with false positives under these complex conditions, Fire-ViT incorporates an attention mechanism and multiperceptron layer, significantly enhancing its capability to discern details in high-resolution images specific to tunnel environments. The model’s performance is outstanding, achieving an accuracy rate of 99.87% on a high-resolution tunnel image dataset, markedly surpassing that of conventional models. Notably, Fire-ViT not only elevates detection accuracy and robustness but also cuts training time in half. This efficiency, coupled with its adaptability to the intricate tunnel environment, makes Fire-ViT an ideal solution for early warning systems against fires in tunnels, fulfilling the demand for high-standard, fine-grained fire detection.

Numerical study on smoke temperature distribution in naturally ventilated inclined tunnels: Effects of tunnel width and tunnel slope

Inclined tunnel fires exhibit unique characteristics compared to horizontal tunnel fires as a result of the stack effect. Nevertheless, there is still a lack of consensus among previous scholars regarding the smoke temperature distribution in inclined tunnel fires. This work conducts a numerical investigation on the smoke back-layering length upstream of the fire source and the temperature decay downstream of the fire source in naturally ventilated inclined tunnels with varying widths and slopes. Results indicate that as the tunnel slope increases from 0° to 8°, the smoke back-layering length first decreases and then continues at a constant value of 1.47H4/3/W1/3, while the effect of tunnel width is negligible. The decay factor in the one-dimensional flow stage (x/H≥4) exhibits two distinct patterns related to tunnel width: it initially remains constant and then drops when the tunnel is wide, whereas it monotonically drops when the tunnel is narrow. Two empirical models are developed to identify the segmented characteristics and verified through the relevant data from existing literature with similar fire scenarios. This work offers a method for estimating the smoke temperature distribution in inclined tunnels, providing crucial insights for fire prevention, smoke detection, and safety strategies in tunnel engineering.

Asymmetrical distribution of buoyancy flux and its effect on smoke propagation velocity and backlayering length in inclined tunnel fires

Inclined tunnels are commonly seen in modern society. Compared with horizontal tunnel fires, smoke movement in inclined tunnel fires exhibits noticeable asymmetry. In this study, a series of numerical simulations are conducted to investigate the asymmetrical distribution of source buoyancy flux and its impact on smoke movement in inclined tunnel fires. Because of buoyancy and the stack effect, the proportion of the buoyancy flux of the smoke advancing towards the upper portal, η, varies with time. When the fire plume impinges the tunnel ceiling, there is an initial distribution of buoyancy flux and the value of η is determined by tunnel inclination angle α. Subsequently, η gradually increases until the steady state is achieved. The growth trajectory of η with time is also controlled by α, but the steady-state value is dependent on both α and the fire location. Models are established to calculate η in different stages. The value of η influences smoke flow characteristics. Smoke propagation velocity scales with the cubic root of buoyancy flux per unit width, which can be derived based on η. Additionally, the backlayering length increases with the steady-state value of η. The findings contribute to a better understanding of the mechanisms governing the smoke flow in inclined tunnel fires.

Numerical simulation of the impact of rainfall on tunnel fire

An improved understanding of tunnel fire dynamics is crucial for fire and life safety. This work highlights the significance of Computational Fluid Dynamics (CFD) techniques in addressing the interaction between tunnel fires and rainfall. The discrete phase model based on the Lagrangian approach is applied to simulate raindrops, while the species transport model is used to simulate fuel combustion. A numerical model is established to investigate the impact of rainfall on tunnel fires, and the correctness of the model is verified by comparing the results to model-scale tunnel experiments. Results show that the raindrops increase the local pressure in the rainfall area, creating a pressure difference between the rainfall tunnel portal and the no-rain portal, which leads to longitudinal airflow inside the tunnel. This rain-induced airflow prevents smoke from moving toward the rainfall tunnel portal and decreases the smoke height near the no-rainfall portal. Correlations between the local increased pressure, induced-airflow velocity, and rainfall parameters are proposed. Besides, the model is scaled up to full-size, and real-scale tunnel fires under the influence of rainfall are evaluated. Findings draw attention to tunnel fire dynamics under extreme weather conditions for improved fire safety and evacuation strategies.

Regression prediction of critical exhaust volumetric flow rate in tunnel fire with two-point extraction ventilation based on neural network method

In this study, a Genetic Algorithm-Backpropagation Neural Network (GA-BPNN) model was developed to predict critical exhaust volumetric flow rate in tunnel fires with two-point extraction ventilation system. Seven influencing factors served as inputs for the model, while the critical exhaust volumetric flow rate was the output. Experimental data from two reduced-scale tunnels were utilized to both train and validate the GA-BPNN model. The results demonstrate a satisfactory prediction performance, with key metrics such as Mean Absolute Percentage Error (MAPE), Relation Coefficient (R2), and Root Mean Square Error (RMSE) achieving values of 0.0384, 0.9989, and 3.5258, respectively. Importantly, the model maintains a maximum Absolute Percentage Error (APE) below 10 %. In contrast, the traditional BPNN model exhibited an APE of approximately 18.9 %. Moreover, the predictive results of the GA-BPNN model were compared with those of a previously semi-empirical formula. It was observed that the semi-empirical predictions exhibited APE exceeding 20 % for certain data points. This further underscores the superiority of the GA-BPNN model in predicting critical exhaust volumetric flow rates in tunnel fires with two-point ventilation system. These findings affirm the feasibility and effectiveness of GA-BPNN regression model as a reliable method for predicting critical exhaust volumetric flow rates under multiple factors.

Study on the maximum ceiling temperature and downstream temperature distribution in inclined tunnel fire

Constrained by various factors, including terrain, tunnels frequently exhibit slopes. While existing research on fires in inclined tunnels predominantly focuses on the characteristics of smoke flow in large slope tunnels, there is a notable lack of attention given to the study of micro-slope tunnels and important factors such as induced air inflow. Therefore, in this paper, the numerical simulation method is used to study the maximum ceiling temperature rise and downstream temperature distribution in inclined tunnel fire under the conditions of micro-slope and large slope. The results show that the main factors affecting the ceiling temperature rise are not only the tunnel slope, but also the HRR and the downstream length. These effects can be expressed by the stack effect intensity. When the inclined tunnel fire occurs, the maximum ceiling temperature and the downstream temperature distribution characteristics show two states. When the stack effect in the tunnel is diminished, there is no significant alteration in the maximum ceiling temperature and temperature distribution within the tunnel when compared to a horizontal tunnel. In a tunnel with a strong stack effect, the maximum temperature decreases as the stack effect increases, and the temperature distribution differs greatly from a horizontal tunnel. The theoretical analysis of this paper identifies the demarcation point of the two state changes as the dimensionless induced air inflow velocity of 0.1. On this basis, a piecewise prediction model for the maximum ceiling temperature of the inclined tunnel fire is established. Because the temperature distribution between the fire source and the maximum temperature position is not regular. Thus, using the maximum ceiling temperature as a reference point, an accurate segmented prediction model of temperature distribution is proposed for downstream Region 1. This study offers guidance for designing tunnel structures with high-temperature resistance and assessing safety conditions within the tunnel.

Modelling the maximum ceiling temperature with bifurcated plume in tunnel fires

Evaluation of the temperature profile induced by tunnel fire is of great significance for fire detection and structural damage assessment. In this work, a special plume model, namely, the “plume bifurcation” is introduced, and its impact on the temperature distribution is analysed theoretically. Full-scale tunnel fire experiments and numerical simulations are conducted to investigate the plume evolution under various heat release rates and ventilation conditions. Results show that the plume will sperate into two sub-streams under strong ventilation condition, resulting in the multi-dimensional plume movement pattern when rising. The sub-plume impingement point location, quantified by the longitudinal vertical deflection angle θv and horizontal bifurcation angle θh, is correlated with the fire heat release rate and ventilation condition. The plume bifurcation angle is 0 when the dimensionless ventilation velocity V′≤0.33, marking a single-stream plume; and rapidly increase and then slowly decrease with V′ when V′>0.33, representing the sudden occurrence and decay trend of plume bifurcation with the ventilation velocity. Finally, a novel bifurcated plume-based model to estimate the maximum ceiling temperature is proposed. This study reveals the role of multi-dimensional smoke movement in reshaping the temperature field, providing new perspectives for a deeper understanding of the smoke transport behaviour in longitudinally ventilated tunnel fires.

Experimental study on transverse fire source and blockage locations influence on tunnel fire temperature distribution

Previous research has commonly assumed that tunnel fire blockage occurs at the central longitudinal axis of tunnels. However, fires may arise at different points within tunnels, each with various distances from the tunnel sidewall. The study aimed to investigate the distribution of ceiling temperature fields across various scenarios of blockage and transverse fire source locations by conducting a sequence of fire experiments within a reduced-scale 1:10 horseshoe-shaped tunnel model. The findings indicate that at sufficiently low ventilation velocities (v’≤0.19), the maximum ceiling temperature rise in the tunnel remains virtually unchanged regardless of the locations of blockage and transverse fire source. For higher ventilation velocities (v’>0.19), the maximum ceiling temperature rise diminishes with greater blockage-fire source distance. Additionally, the maximum ceiling temperature rise increases as the distance between the sidewall and the fire source diminishes. Furthermore, a new model has been formulated to forecast the dimensionless maximum ceiling temperature rise, incorporating both blockage and transverse fire locations.

Numerical studies on the synergistic effects of smoke extraction and control performance by mechanical ventilation shafts during tunnel fires

High smoke extraction efficiency and a relatively stable smoke layer stratification are both expected in tunnel ventilation systems. The purpose of this paper is to explore the overall performance of mechanical board-coupled shaft (MBCS) under different ventilation strategies. A total of 57 simulations were conducted, and the effects of the distance between the shaft and board (hD) and ventilation velocity on the overall performance were investigated. The results indicate that the performance of smoke extraction and control will be improved by the application of mechanical ventilation and board. Smoke movement patterns under different working conditions were different, for cases of hD≤0.40m the smoke could propagate through the whole tunnel without backflow, while for cases of hD>0.40m, the backflow exists and the smoke movement can be separated into three periods (propagation, stagnation, and retraction). The critical criterion of backflow was investigated and a simple model was deduced to estimate the maximum propagation length. Moreover, the dimensionless time for the smoke flow to reach its maximum propagation length was established. Finally, a comprehensive index φ was proposed to evaluate the synergistic effects of smoke extraction and control performance. These studies may provide positive significance for the ventilation design.

Particle swarm optimization inverse tracing method for mine tunnel fire based on quasi-steady-state heat transfer mechanism

Rapidly locating and assessing fires in coal mines is essential for effective response and minimizing damage. Traditional methods often struggle to swiftly and accurately pinpoint fire locations and statuses. Hence, this study introduces a particle swarm inverse tracing approach based on the quasi-steady-state heat transfer between high-temperature flue gases and mine tunnel walls. This method aims to remotely monitor smoke flow temperatures and gas concentrations to determine fire locations and combustion trends. Validation of the fire source tracing model was conducted through comprehensive tunnel fire experiments and numerical simulations. The particle swarm optimization inverse tracing method yielded a maximum 7.65 % error in fire location determination compared to actual measurements, while accurately matching the measured fire source heat release rate curve. These findings underscore the method’s high precision and reliability, particularly evident during the developmental and stable stages of fire burning.

Design of Adits for People Passing Spacing in High Altitude Highway Tunnels in Cold Regions

Existing research into this topic primarily focuses on low-altitude areas, neglecting the impact of extreme environmental conditions such as low temperature, low oxygen level, and low pressure in high-altitude regions. Based on the smoke diffusion theory, a series of CFD numerical simulations were conducted in order to investigate the characteristics of smoke diffusion in the highway tunnel at high altitude. The results indicated that the increase in altitude would enhance the longitudinal propagation velocity of smoke, leading to a more pronounced impact on temperature, CO concentration, and visibility at characteristic heights. Meanwhile, the altitude intensifies the inhibitory impact of longitudinal ventilation on smoke diffusion upwind of the fire source and augments the acceleration effect on smoke diffusion downwind, thereby impeding personnel evacuation on the downwind side. By taking the hazardous range at a characteristic height under the impact of wind velocity and the deceleration of evacuation velocity due to altitude into consideration, a new recommended reduction factor was deduced to design adits for people passing spacing in highway tunnels at high altitude. The findings can serve as a valuable reference for the personal evacuation in high-altitude highway tunnel fires and the design of spacing between adits for people passing within such tunnels.