In recent years, global climate change and intensified human activities have significantly increased surface fire risk in power transmission corridors spanning mountainous and forested areas, posing a serious threat to the safe and stable operation of modern power grids. Surface vegetation serves as the primary fuel for ground fires and wildfires, directly influencing the flame spread velocity, fire development stages, and combustion intensity. Therefore, investigating the combustion characteristics of surface vegetation is crucial for improving wildfire prevention systems, enhancing the accuracy of fire behavior predictions, and ensuring the operational reliability of transmission infrastructures. However, current research on the combustibility and fire behavior of various surface fuels in transmission corridors remains insufficient, particularly in terms of comparative analyses across different vegetation types and accumulation thicknesses. There is a pressing need for systematic experimental studies to reveal the heat release mechanisms, fire growth, and gas emission characteristics of these vegetation types.

This study aimed to experimentally explore the combustion characteristics of typical surface vegetation in transmission corridors under varying accumulation thicknesses, compare differences in fire behavior among vegetation types, and identify key parameters, including flame spread patterns, mass loss rate evolution, temperature distributions, and gas volume fraction dynamics. The combustion characteristics of different types of surface vegetation in transmission corridors were investigated through small-scale experiments. A self-designed 1m² small-scale combustion platform was constructed and equipped with cameras, a thermocouple array, a high-precision electronic balance, and gas sensors to collect key combustion data, including flame behavior, temperature distribution, mass loss, and gas volume fractions, during the tests. Three typical vegetation types—shrubs, coniferous litter (pine needles), and broadleaf litter (maple leaves)—were selected as the research objects. For each vegetation type, three accumulation thicknesses (10, 15, and 20cm) were specified. Under an ambient wind speed of 1 m/s, key parameters, including flame morphology, flame height, mass loss rate, temperature distributions, and smoke gas volume fraction, were recorded and analyzed to reveal the spatiotemporal evolution of their combustion characteristics.

The results showed that the combustion process of typical surface vegetation in transmission corridors could be divided into four stages: initial, development, peak, and extinguishment. Flame propagation exhibited an arc-shaped outward expansion pattern. As the accumulation thickness increased, the flame height, mass loss rate, and peak temperature also increased. The CO₂ volume fraction followed a "sharp rise-gradual decline" trend, whereas the volume fraction of CO exhibited a phased characteristic of concentrated release in the initial and extinguishing stages. The volume fractions of both CO and CO₂ increased with increasing accumulation thickness. At the same accumulation thickness, flame heights ranked from highest to lowest as coniferous litter, shrubs, and broadleaf litter. Among them, coniferous litter exhibited the highest combustion intensity, greatest flame height, maximum mass loss rate, and most pronounced multipeak fluctuation behavior.

This study reveals the combustion characteristics of typical surface vegetation in transmission corridors under varying accumulation thicknesses. This study also systematically analyzes the differences in flame spread characteristics, thermal behavior, and gas emissions across vegetation types. The findings provide a robust experimental basis for assessing surface fire risk, modeling fire behavior, and developing wildfire warning strategies for power transmission corridors.

The morphology of large-scale wildfire fronts is a crucial factor in assessing wildfire spread and determining safe distances for transmission corridors. Understanding the dynamic evolution of these fronts is essential for effective real-time wildfire monitoring and prevention. Most existing research focuses on small-scale experimental scenarios that struggle to replicate the complex interactions among multiple factors, such as fuel types and meteorological parameters, during actual wildfires. Few studies have examined fire front morphology in large-scale scenarios that incorporate meteorological conditions, and current research often falls short of the accuracy needed for effective wildfire prevention and control. This study aims to investigate the effects of different fuel types and meteorological conditions on wildfire front morphology through large-scale experiments, providing experimental data and theoretical support for the development of fire front spread models applicable to actual wildfire situations.

A 50 m×40 m full-scale wildfire combustion experimental platform was constructed for this study, integrating UAV thermal infrared imaging, tower-based visual monitoring, and multi-source meteorological sensing systems. We conducted large-scale, systematic experiments on wildfire spread using two common surface fuels (wheat straw and pine needle litter) under varying meteorological conditions. The analysis focused on the effects of fuel type, wind direction, and wind speed on key parameters, including fire front morphology, temporal variation in stable fire front length, and fire front propagation angle. We systematically compared surface fire-front spread under various working conditions.

The results revealed the following: 1) Fire front morphology is significantly affected by fuel type, where wheat straw produces a smooth arc-shaped front, and pine needles result in a sharp, multi-branched, and irregular morphology. The fire front angle increases continuously during combustion, with the temperature decay rate in the burned area of pine needles being significantly faster than that of wheat straw. Wind direction dictates the overall spread direction of the front, whereas wind speed primarily affects the size of the front angle. 2) The variation trend and fluctuation amplitude of stable fire front length are jointly influenced by fuel and meteorological conditions. The fire front length of wheat straw decreases steadily over time, whereas that of pine needles exhibits significant short-term oscillations. Greater differences in maximum and minimum wind directions lead to more intense fluctuations in fire front length. Under identical wind directions, higher average wind speeds correspond to greater extreme values of fire front length. 3) The fire front propagation angle gradually decreases during the spread process. The wheat straw fire front is generally smooth with minor fluctuations, whereas the pine needle fire front displays significant local curvature and irregular trajectories. Greater stability in wind direction and higher average wind speeds result in a smaller average fire front propagation angle, causing the front to approach a straighter line.

Through large-scale surface fire spread experiments, this study elucidates the influence of fuel type and meteorological conditions on key parameters such as fire front morphology, temporal variation of stable fire front length, and fire front propagation angle. It reveals the comprehensive influence mechanism between meteorological conditions and fuel properties regarding fire front morphology, offering a large-scale experimental basis and critical parameter support for developing wildfire spread prediction models and improving wildfire prevention and control strategies in transmission corridors. Future research will expand these large-scale wildfire experiments to include more complex scenarios, thereby enhancing our understanding of real wildfire behavior.

Surface fire spread rate is a key parameter for characterizing surface fire behavior, and understanding its variation patterns is of great significance for wildfire prevention and control. Existing research predominantly relies on small-scale experiments, which limits the applicability of fire spread models built on these data to real wildfire scenarios. This study aims to investigate the effects of fuel type and fuel bed density on surface fire spread rate through large-scale experiments, thereby providing an experimental basis and theoretical support for the development of fire spread models applicable to actual wildfires.

Utilizing a large-scale power grid wildfire experimental platform, this study conducted surface fire spread experiments under different fuel types (shrubland surface litter and coniferous forest surface litter) and fuel bed densities (1.0, 1.5, and 2.0 kg/m²) within a 2000 m² combustion area. The experimental setup included an array of 99-K-type thermocouples to collect surface temperature data, unmanned aerial vehicles to record visible and infrared imagery of the fire spread process for extracting fireline morphology, and a small weather station to monitor real-time meteorological conditions such as wind speed and direction. By analyzing the flame front spread rate, fireline expansion rate, and temperature response characteristics, surface fire spread behavior under various working conditions was systematically compared.

The experimental results demonstrate the following points. 1) The flame front spread rate is comprehensively regulated by fuel type, fuel bed density, and meteorological conditions. The acceleration phase of the flame front occurs earlier in shrubland surface litter than in coniferous forest surface litter. Increasing the fuel bed density reduces the peak flame front spread rate while enhancing combustion stability. Meteorological factors are the primary cause of the observed multipeak fluctuations in the spread rate. 2) The fireline expansion rate exhibits fluctuating characteristics, with peak values determined by fuel type. The peak fireline expansion rate of shrubland surface litter is greater than that of coniferous forest surface litter. An increase in fuel bed density promotes fireline expansion in shrubland surface litter but inhibits it in coniferous forest surface litter. 3) The temperature response characteristics reflect flame front spread and fireline expansion behaviors. Fuel type governs the continuity of fire head spread; the loose structure of shrubland surface litter facilitates uniform heat transfer, whereas the compact structure of coniferous forest surface litter leads to heat accumulation. Fuel bed density influences the speed and spatial direction of the temperature response by modifying internal oxygen supply and combustion completeness.

Through large-scale surface fire spread experiments, this study clarifies the influence of fuel type and fuel bed density on flame front spread rate, fireline expansion rate, and temperature response characteristics. The resulting dataset provides large-scale experimental support for developing predictive fire spread models for actual wildfires and offers valuable insights for wildfire prevention and control along power transmission lines. Future work will involve conducting large-scale wildfire experiments under different slope terrains to deepen the understanding of real wildfire spread behavior.

Oil-filled electrical equipment is widely used in substations/converter stations and hydropower projects as key facilities for securing power supply. However, transformer oil leaks from the rupture, accumulates at the base of oil-filled equipment, and encounters an ignition source, forming an external heat source that leads to a fire in the oil-filled equipment. Notably, heat from this external source is transferred back to the equipment via conduction, convection, radiation, and other pathways. This accumulated internal heat causes oil from ruptured oil-filled equipment to be sprayed and ignited by an external heat source, forming a jet fire. The transition to a jet fire triggers nonlinear shifts in the system's original state, leading to further deterioration in the degree of fire hazard. As fire incidents involving oil-filled equipment pose a major safety hazard in the electric power industry, effective and reliable prevention and control strategies must rely on a precise understanding of their dynamics. Therefore, a comprehensive and profound understanding of the characteristics of oil-filled equipment jet fire dynamics under the influence of external heat sources is of practical importance for improving the fire prevention and control capabilities of the electric power industry and for developing major fire monitoring and early warning technologies. In essence, once internal transformer oil leaks and burns, fire development mainly experiences two typical stages: first, the instability of oil-filled equipment combustion under the influence of an external heat source to form a jet fire, and second, the formation of a jet fire, which considerably changes the typical characteristics of the fire parameters. An oil-filled-equipment fire is a combination of combustion phenomena of multiple fire modes, such as bottom pool fire, sidewall flow fire, and top jet fire.

Previous studies have focused on single-mode fire dynamics experiments. Little attention has been paid to key scientific issues, such as the evolution of typical fire characteristics and the prediction of fire behavior under combined combustion of multiple fire modes, which have posed considerable challenges for the prevention and control of fires in electric-power charging equipment and fire rescue missions. In view of oil-filled equipment jet fire accidents and their complex fire characteristics, issues in electric power fire prevention and control remain serious challenges. Fundamental scientific questions regarding these dynamics remain unresolved, necessitating further theoretical studies to address the safety challenges they pose.

In this study, we designed and constructed an experimental platform to simulate the fire dynamics of oil-filled electrical equipment. By integrating the measurement systems for the mass-loss rate, temperature, radiation heat flux, and image acquisition, we clarified the basic combustion phenomena of these fires. Furthermore, we established the typical phases and morphological characteristics and revealed the evolution laws of the characteristic parameters, such as the flame height, flame temperature, and flame radiation.

We identified the catastrophic mechanism of oil-filled equipment jet fire at its essence, further enriching the theory of fire dynamics and providing strong scientific and technological support for enhancing fire prevention and control strategies within the power industry.

Wildfires are one of the most critical disasters faced by power grid facilities. They can easily cause damage to the transmission equipment body, loss of power supply load, and power outages. However, the current power grid’s wildfire sensing methods have certain limitations, especially the ability to accurately reproduce real combustion scenarios, which considerably hampers the precision of mountain fire warnings and the forward-looking level of situational analysis. To address these limitations, large-scale real wildfire experiments in power grid facilities are urgently needed. These experiments will provide comprehensive data on fire ignition, development, and spread under real-world conditions, helping to improve wildfire emergency response by enhancing identification algorithms, situational analysis, and decision-making capabilities. This study aims to enhance the accuracy and scientific rigor of predisaster risk identification, disaster monitoring and early warning, in-disaster situational analysis, and postdisaster loss assessment. This study designs and develops a large-scale experimental platform for joint “sky–ground” sensing of power grid wildfires, capable of simulating wildfire ignition, development, and spread within power grid disaster scenarios.

During the design process of the experimental platform, accurate control is applied to factors such as combustible type, humidity, and density. By measuring multidimensional characteristic parameters from satellites, drones, overhead power lines, and the earth’s surface, this study gathers comprehensive experimental data, including remote sensing images, drone imagery, surface flame temperature, near-surface thermal radiation, airborne smoke temperature, meteorological parameters, and multiangle video recordings. Adhering to the principles of repeatability, controllable boundaries, scene authenticity, data validity, and full-process recording, the experimental combustion scale can reach tens of thousands of square meters, enabling comprehensive, multidimensional joint sensing.

Preliminary experiments conducted on a scale of several thousand square meters demonstrate the following: 1) The experimental platform could effectively capture the multidimensional characteristics of aerial and ground wildfire dynamics, including early ignition, development, and postdisaster burn sites. At an experimental scale of 2 000 m², a satellite visible light channel with a resolution of 0.75 m can distinguish flame and smoke patterns. Moreover, the ground visualization system, positioned at heights of 15, 10, and 3 m, can capture fire and smoke images from multiple angles. 2) During the development stage of a fire, the experimental platform can enable comprehensive recording of fire line movement and temperature evolution, with a spatial resolution of 5 m on the ground and 10 m in the air. Furthermore, the platform facilitates the collaborative analysis of multidimensional data by integrating satellite remote sensing, aerial visualization, thermal infrared imaging, and ground-based contact measurements. 3) Through experiments, a method is proposed for recognizing initial fire point features, conducting multidimensional data collaborative fire assessments, and sensing fire intensity parameters.

This study establishes a large-scale experimental platform for joint “sky–ground” sensing of power grid wildfires. Through large-scale wildfire experiments in power grid facilities, this study clarifies the flame morphology characteristics of wildfires and proposes a multidimensional data collaborative fire dynamic analysis method. This study reveals the evolution patterns of key fire parameters, such as surface flame temperature and smoke temperature, enabling a comprehensive and detailed reconstruction of wildfire dynamics in power grids. These findings hold substantial theoretical value and practical applications for improving the scientific accuracy of wildfire prevention and control, enhancing fire monitoring and early warning systems, and strengthening situational analysis capabilities.