Rapid and accurate assessment of dynamic threats to surrounding assets, such as transmission lines, chemical storage tanks and nuclear facilities, during the propagation of forest-grassland wildfires is critical for emergency response and disaster mitigation. Traditional fire risk assessment methods typically rely on static hazard maps or single-time fire-front predictions and therefore fail to adequately account for the continuous spatiotemporal evolution of fire behavior influenced by changing environmental factors (e.g., wind and fuel), leading to cumulative error propagation in dynamic risk prediction. Furthermore, the complex and heterogeneous failure mechanisms of different infrastructure types are seldom incorporated into a unified, dynamically updating risk framework. Therefore, this study aims to develop a novel, integrated risk assessment method capable of continuously updating infrastructure failure probabilities as wildfire intensity and extent evolve.

The proposed framework synergistically integrates a data-driven wildfire spread prediction model with a dynamic Bayesian network (DBN). The fire-affected landscape and key protected assets were first discretized into interconnected spatial nodes. A DBN structure was then constructed to capture two fundamental dependencies: the temporal autocorrelation of fire conditions at each node (how the state evolves) and the spatial dependencies between adjacent nodes (how fire spreads from one location to another). The core parameters of this DBN were informed by a data-driven fire spread model. Specifically, predictions of key fire behavior metrics, namely, spread rate and fireline intensity, were generated for each node. Then, DBN conditional probabilities were updated over time using the predicted spread rate and the fireline intensity, which were further mapped to asset-specific fragility models to infer evolving failure probabilities.

Using the proposed framework, we built a kilometer-scale synthetic fire scenario using every single protected asset and showed that the 24-h failure probabilities of transmission lines, chemical tanks, and nuclear facilities increased by up to 22%, 68% and 20% across wind-fuel scenarios. In addition, a case study based on observations from the 2022 Oak Fire (California, USA) was conducted using multiple protected assets. The 24-h failure probabilities reached 0.24 for transmission lines, 0.14 for hazardous-chemical tanks, and 0.53 for the nuclear facility. Furthermore, we evaluated a firebreak construction strategy: as the suppression effect on the rate of spread increased, the failure probability could be reduced to as low as 0 for transmission-line nodes and to 0.12 for the nuclear facility, whereas the probability reduction for hazardous-chemical tanks was not significant due to their spatial distribution and structural differences.

This study proposes a novel dynamic wildfire risk assessment framework that integrates data-driven spread prediction with probabilistic graphical modeling. By continuously updating a DBN using fire behavior model outputs, the proposed approach effectively mitigates cumulative prediction errors in a spatiotemporally evolving environment and provides quantitative support for rapid response, emergency resource allocation, and intervention strategy assessment.

Understanding the pyrolysis characteristics of tobacco powder is crucial to controlling the formation of harmful substances and enhancing the safety and quality of heated cigarettes, thus providing a scientific basis for optimizing the design of heated cigarettes. Although the extant studies mainly explored the pyrolysis characteristics and product distributions of some tobacco powders, they barely considered the development of a reliable, component-specific kinetic model for the pyrolysis of tobacco powder in heated cigarettes. To address this research gap, we explored the pyrolysis process and the kinetic parameters of tobacco powder in heated cigarettes, followed by the development of a reliable model.

First, employing thermogravimetric (TG) analysis, the thermal weight loss of the sample (tobacco powder, 10±0.02 mg) was studied under a purge gas (nitrogen) at a flow rate (50.0 mL/min). Following a pre-dehydration step (heating to 100 ℃, holding for 30 min, and cooling to room temperature), the sample was heated from 50 ℃ to 500 ℃ at four heating rates: 5, 10, 15, and 20 ℃/min. Next, the resulting TG and derivative TG (DTG) curves were recorded. Second, we calculated the apparent activation energy for the pyrolysis of tobacco powder using three model-free fitting methods: the Kissinger-Akahira-Sunose (KAS), Friedman (FR), and Flynn-Wall-Ozawa (FWO) methods. Finally, we proposed a four-step pseudo-component kinetic model covering the four-stage pyrolysis of tobacco powder: water evaporation, hemicellulose pyrolysis, cellulose pyrolysis, and lignin pyrolysis. Additionally, a genetic algorithm was employed to optimize 19 kinetic parameters (e.g., activation energy, pre-exponential factor, reaction order, and stoichiometric coefficient) in the model to considerably minimize the error between calculated and experimental DTG values.

Tobacco powder pyrolysis proceeded in four stages, illustrated using the 20℃/min heating rate: 1) dehydration (50—208 ℃), where the mass loss (8.73%) was mainly due to the evaporation of bound water in the tobacco powder; 2) hemicellulose pyrolysis (208—291 ℃), where the mass loss reached 19.20% owing to hemicellulose decomposition; 3) cellulose pyrolysis (291—372 ℃), where the mass loss was 22.50%, accounting for the maximum weight-loss rate (0.381 wt%/℃) at 325 ℃; 4) lignin pyrolysis (372—500 ℃), where the mass loss was 14.40%, marking a gradual decrease in the weight-loss rate owing to the complex structure and high thermal stability of lignin. Notably, the 10 ℃/min heating rate yielded the highest weight-loss rate (0.390 wt%/℃) and lowest residual mass (35.0%). Furthermore, the apparent activation energy calculations were highly reliable, with the correlation coefficients (R²) of all three model-free fitting methods exceeding 0.97. Particularly, the KAS, FWO, and FR methods yielded activation energy ranges of 200.89—519.66, 198.11—505.40, and 198.17—505.53 kJ/mol, respectively, exhibiting high correlation throughout the process. As the conversion rate increased, the activation energy exhibited a "first up, then down, then up again" trend. In detail, the activation energy stabilized at approximately 200 kJ/mol when the conversion rate was less than 0.1 (the dehydration stage), then increased rapidly to 249 kJ/mol as the conversion rate increased from 0.1 to 0.3 (hemicellulose pyrolysis). It stabilized again at approximately 250 kJ/mol at a conversion rate of 0.3—0.5 (cellulose pyrolysis) before decreasing to 219 kJ/mol as the conversion rate reached 0.6 (initial lignin pyrolysis). Afterward, it increased rapidly as the conversion rate exceeded 0.6 (lignin decomposition into phenols and aromatic compounds). The kinetic model, optimized using the genetic algorithm, converged after 120 iterations (with a deviation of 5.00%). Notably, the optimized activation energies for the four pseudo-components were 62.00 kJ/mol (water), 118.83 kJ/mol (hemicellulose), 217.31 kJ/mol (cellulose), and 192.13 kJ/mol (lignin). Further, the model accurately simulated the experimental data, with the TG and DTG curves achieving high R² values (>0.94) for all four heating rates.

We clarified the four-stage pyrolysis characteristics of tobacco powder in heated cigarettes. We established that the three model-free fitting methods can be used to reliably calculate the conversion-rate-dependent apparent activation energies for the pyrolysis of tobacco powder, reflecting the differences in energy requirements across the pyrolysis stages. Furthermore, our kinetic model can accurately simulate the pyrolysis of tobacco powder, providing key theoretical support for improving the quality of heated cigarettes.

Pumped storage power stations pump water to upper reservoirs when the electricity load is low; they release water to lower reservoirs to generate electricity when the electricity load is high. In these stations, cable tunnels, which connect underground transformers and ground switch stations, usually have high-fall, long-distance, and large-slope attributes. These affect the cable flame spread characteristics.

This paper studies the effect of slope (0°-45°) on cable flame morphology, flame front distance, average flame spread rate, cable surface temperature, and ceiling temperature by conducting cable flame spreading experiments in a 1/10 small-scale cable tunnel. Thermocouples are used to measure the cable surface temperature and tunnel ceiling temperature. A camera is used to record the cable flame morphology, while a computer is used to record data from the camera and thermocouples.

The flame front distance and the average flame spread rate increase with the tunnel slope. When the tunnel slopes are 0°, 15°, 30°, and 45°, the cable flame front distances are 539, 783, 1076, and 1300 mm, respectively, with average cable flame spread rates of 0.43, 0.92, 1.28, and 1.53 mm/s. With increasing slope, the first peak of the cable surface temperature moves upward, and so does the first peak of the tunnel ceiling temperature. When the slope is 0°, the first peak temperature and position of the cable surface and the ceiling are 650 ℃ and -0.25 m, respectively. When the slope is 15°, the first peak temperature and position of the cable surface and the ceiling are 400 ℃ and -0.50 m, respectively. When the slope is 30°, the cable surface's first peak temperature and position are 200℃ and -0.25 m, respectively, whereas those of the ceiling are 250 ℃ and -0.50 m, respectively. When the slope is 45°, the cable surface's first peak temperature and position are 200 ℃ and -1.00 m, respectively, whereas those of the ceiling are 250 ℃ and -1.50 m, respectively. The peak position of the tunnel ceiling temperature is farther than the peak position of the cable surface temperature.

First, in the inclined cable tunnel, the Coandǎ and stacking effects increase the flame inclined angle and the preheating area of the unburned cable, with the unburned cable's heating rate and the average cable flame rate increasing. Second, the cable ceiling heating has little effect on cable flame spreading. However, the copper core inside the cable acts as a "heater" and a "radiator, " affecting the cable's burning behavior. The high-temperature core heats the unburned cable zone, increasing the preheating area and cable flame spread rate. Third, in the inclined tunnel, the stacking effect enhances the heat dissipation of cable burning. In the horizontal tunnel, the high-temperature ceiling heats the cable and increases the cable's burning time. Fourth, under the combined effects of longitudinal airflow inertia and thermal buoyancy forces, the peak position of the tunnel ceiling temperature is farther than the peak position of the cable surface temperature.

Given the confined and elongated configuration of ultrawide subsea immersed tube tunnels, fires can lead to a rapid spread of flames and smoke, posing a substantial threat to the structural integrity of the tunnel and the safety of personnel. Traditional fire protection designs are often not ideal for cooling and controlling fires in such environments. Therefore, developing effective fire prevention and control technologies specifically suited to subsea tube tunnels is of great practical importance for ensuring tunnel safety and facilitating personnel evacuation. The main objective of this study is to evaluate the fire suppression and cooling effects of high-pressure mist in subsea immersed tube tunnels. To simulate real-life conditions, a full-scale 1:1 experimental model of a subsea tunnel was constructed, with the width, height, and length being 18.0, 6.6, and 25.0 m, respectively. This study aims to evaluate the combustion behavior, temperature distribution, and cooling efficiency of high-pressure water mist under different heat release rates.

Gasoline was used as the fuel source in experiments conducted at three heat release rates: 2.5, 5.0, and 10.0 MW. Key parameters, including the flame height, temperature variation curves, and the cooling effects of high-pressure water mist, were measured throughout the experiments. The experimental setup was designed to closely replicate real fire scenarios in subsea tunnels, ensuring accurate and reproducible results. During the experiments, high-precision temperature sensors and imaging devices were used to continuously record and analyze the temperature distribution and flame characteristics.

The experimental results showed significant differences in the flame characteristics and temperature distribution across different heat release rates. For example, the maximum flame heights under 2.5, 5.0, and 10.0 MW heat release rates were 4.5, 6.0, and 6.6 m, respectively. Without high-pressure water mist for fire suppression, the highest ceiling temperatures reached 180℃, 310℃, and 528℃, respectively, posing a certain threat to the structural integrity of the tunnel. Upon activation of the high-pressure water mist, ceiling temperatures in all fire scenarios dropped significantly, falling below 300℃, thereby effectively reducing the risk of structural damage. Furthermore, for the 2.5 MW heat release rate, the activation of the high-pressure water mist rapidly reduced the temperature in the burning area to below 150℃. While complete suppression of flames was more challenging in higher-power fire scenarios, the water mist significantly lowered the ceiling temperature and the temperature in the burning area. This slowed the fire progression, providing valuable time for personnel evacuation and firefighting efforts.

The experimental results confirm the effectiveness of high-pressure water mist in controlling fires within subsea immersed tube tunnels, particularly in reducing ceiling temperatures and minimizing structural damage risks. The use of high-pressure water mist in such tunnels can effectively reduce temperatures and mitigate the impact of fires on tunnel structures, providing technical support for improving fire safety. Overall, this research provides valuable insights for enhancing fire safety strategies in subsea immersed tube tunnels and provides practical recommendations for designing fire prevention and control systems.

With the establishment of high-voltage transmission lines across forested areas, their inspection becomes crucial to reduce the fire risk of transmission lines and forest areas. At present, few studies have studied the path planning for unmanned aircraft inspection of transmission lines based on the fire risk in forest areas, but they do not address the security of the operation and maintenance of the power grid system or consider the interactions between different influencing factors. Therefore, an unmanned aerial vehicle path planning framework for forest power grid inspection is proposed based on the analytic network process method and genetic algorithm. Moreover, a path optimization method based on the maximum deflection angle constraint is developed.

After determining the assessment routes, the framework integrates field research and historical data to determine the objective data of these routes and identifies six classes of factors affecting the risk of forest fires: combustible factors, terrain factors, meteorological factors, human factors, surface wet conditions, and rescue conditions. These factors are subdivided into 18 typical factors by researching the historical accident cases and related literature. The forest fire risk indicator system is developed using typical factors, and to guarantee that this indicator system can effectively reflect the actual risk level, herein, the typical factors selected are those that are commonly used and recognized by previous researchers. Subsequently, weights for these typical factors are computed based on the analytic network process. Compared with the hierarchical analysis method, which is traditionally applied in earlier works, the network analysis method has the advantage of considering the interactions between the factors. The weights with objective data are combined to calculate the fire risk value for each grid. The high fire risk grids are employed as inspection nodes, and the shortest inspection path is acquired using path planning via the unmanned aerial vehicle inspection based on the genetic algorithm to reach the objective of obtaining real-time data in a short time, at low cost, and with high coverage. For the nodes in the path that do not meet the maximum deflection angle constraint, path optimization is conducted by adding new optimization nodes and the shortest path is ensured under the condition that the roadbed meets the maximum deflection angle constraint.

Sections #3542—#3547 of the line of an important transmission channel in Anhui are taken as an application object. Ten high fire risk areas around the line are determined, and path planning is performed on them. The proposed framework yields an optimal path length of 5 391.72 m, and the path length optimized based on the maximum deflection angle is 5 401.36 m. Here, the path length is only increased by 0.179% compared with the original one. This indicates that the path optimization method not only makes the original path satisfy the constraint of maximum deflection angle, but also increases the path length to be shorter, which has good optimization effect.

This work presents a path planning framework for the unmanned aerial vehicle inspection based on the results of fire risk assessment considering the interactions between various forest fire risk factors. In addition, the proposed path optimization method can make the path satisfy all constraints with a small increase in the path length. The proposed framework and optimization method offer reference and future ideas for realizing the unmanned aerial vehicle inspection of transmission lines in forest areas.

External wind almost always exists around high-rise buildings. Due to the superimposed or competitive effect of wind pressure, buoyancy, and thermal expansion, the fire behaviors in high-rise building enclosures with two openings exhibit more complex dynamic evolution characteristics than those without external wind effects. In situations with such effects, new models are required to systematically analyze the fire behavior evolution mechanism.

In this study, we established a more practical compartment fire scenario and performed numerical analyses using the computational fluid dynamics (CFD) code, fire dynamics simulator (FDS), to study the evolution of the fire behavior of a compartment with two opposite openings. A total of 48 simulations were performed, wherein different wind speeds and heat release rates were considered. The fire source was a propane burner in the center of the compartment. The simulation duration was set at 350 s. The use of numerical simulations opened up the potential for a direct evaluation of a wide range of variables (e.g., the mass rate of inflow and outflow through openings and temperature) and even more complex quantities (e.g., the heat release rate within predefined volumes such as windward side space, leeward side space, and space inside the compartment). To obtain accurate simulations, sensitivity analysis was performed. The impact of crosswind speed on the behavior of fire spill plume on the windward and leeward sides, the temperature inside the compartment, and the flow pattern across the two openings were analyzed. Combined with the energy conservation equation, the average temperature rise model inside the compartment at over-ventilated conditions under the crosswind was established based on dimensional analysis. A critical wind speed (v_c) was determined for the conversion of gas from bidirectional to unidirectional flow according to the pressure differences among the windward side, the compartment, and the leeward side.

This study finds that a uniform mesh size of 2 cm is sufficient to achieve convergence. The results indicate that (1) the fire spill plume on the windward side at under-ventilated conditions gradually disappears as the wind speed (v) increases. Afterward, the fire spill plume on the leeward side also disappears gradually. At the same time, the heat release rate inside the compartment gradually increases. The critical criterion for the occurrence of the fire spill plume is that the global equivalence ratio Φ equals 0.645. When Φ≤0.645, combustion occurs only within the compartment. When Φ>0.645, the fire spill plume appears outside the compartment. (2) As the wind speed increases, the average temperature within the compartment constantly decreases at under-ventilated conditions and constantly increases at over-ventilated conditions. When v < v_c, there is a bidirectional flow through the openings on the windward or leeward side; when v≥v_c, the flow through the openings on both sides is unidirectional. The accuracy of the critical wind speed model is further verified based on an analysis of the mass flow rate through the openings on both sides.

The outcomes and findings of this study will help improve the existing theories of enclosure fire dynamics and provide theoretical and technical support for the fire protection of high-rise buildings.