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Modified Quasi-Physical Grassland Fire Spread Model: Sensitivity Analysis

Author

Listed:
  • Esmaeil Mohammadian Bishe

    (School of Mechanical Engineering, Sharif University of Technology, Azadi Ave., Tehran 1458889694, Iran)

  • Hossein Afshin

    (School of Mechanical Engineering, Sharif University of Technology, Azadi Ave., Tehran 1458889694, Iran)

  • Bijan Farhanieh

    (School of Mechanical Engineering, Sharif University of Technology, Azadi Ave., Tehran 1458889694, Iran)

Abstract

Developing models for predicting the rate of fire spread (ROS) in nature and analyzing the sensitivity of these models to environmental parameters are of great importance for fire study and management activities. A comprehensive sensitivity analysis of a general and modified quasi-physical model is provided in the current study to predict parameters that affect grassland fire propagation patterns. The model considers radiative heat transfer from the flame and fuel body and convective heat transfer to predict the fire’s rate of spread and the grassland fire patterns. The model’s sensitivity to ten main parameters that affect fire propagation, including temperature, humidity, wind speed, specifications of vegetable fuel, etc., is studied, and the results are discussed and analyzed. The model’s capability is validated with experimental studies and a comprehensive physical model WFDS. The model’s capability, as quasi-physical, faster than the real-time model, shows high consistency in fire propagation parameters compared with experimental real data from the Australian grassland fire Cases C064 and F19. The comprehensive sensitivity analysis provided in this study resulted in a modified equation for the corrected rate of fire spread which shows quite an improvement in ROS prediction from 5% to 65% compared with the experimental results. The study could be a base model for future studies, especially for those researchers who aim to design experiments and numerical studies for grassland fire spread behavior.

Suggested Citation

  • Esmaeil Mohammadian Bishe & Hossein Afshin & Bijan Farhanieh, 2023. "Modified Quasi-Physical Grassland Fire Spread Model: Sensitivity Analysis," Sustainability, MDPI, vol. 15(18), pages 1-23, September.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13639-:d:1238440
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    References listed on IDEAS

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    1. Keith L. Kline & Virginia H. Dale & Erin Rose & Bruce Tonn, 2021. "Effects of Production of Woody Pellets in the Southeastern United States on the Sustainable Development Goals," Sustainability, MDPI, vol. 13(2), pages 1-19, January.
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    4. Jorge Pereira & Jérôme Mendes & Jorge S. S. Júnior & Carlos Viegas & João Ruivo Paulo, 2022. "A Review of Genetic Algorithm Approaches for Wildfire Spread Prediction Calibration," Mathematics, MDPI, vol. 10(3), pages 1-19, January.
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