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Publishing Language: Chinese | Open Access

Large-scale experiments on surface fire spread rate

Chang LIUKunpeng JISihang ZHANGPeng LIJingshan HANZhi YANG( )
State Grid Electric Power Engineering Research Institute, Beijing 100069, China
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Abstract

Objective

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.

Methods

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.

Results

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.

Conclusions

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.

CLC number: X932; TM75 Document code: A Article ID: 1002-4956(2026)02-0026-09

References

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Experimental Technology and Management
Pages 26-34

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Cite this article:
LIU C, JI K, ZHANG S, et al. Large-scale experiments on surface fire spread rate. Experimental Technology and Management, 2026, 43(2): 26-34. https://doi.org/10.16791/j.cnki.sjg.2026.02.004

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Received: 19 November 2025
Published: 20 February 2026
© 2026 Experimental Technology and Management. All rights reserved.

This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/).