Coupling heat transfer modelling and Monte Carlo simulations for integrated biomass combustion analysis

This study introduces a hybrid framework that couples deterministic heat transfer modelling with stochastic Monte Carlo simulations to analyze biomass combustion dynamics leading to forest fire. Trees are considered as lignocellulosic biomass of a cylindrical shape of 1 m diameter, and 30 m height. Energy balances performed around a tree species incorporates radiative losses via the Stefan–Boltzmann law and convective heat transfer based on Nusselt correlations. The combustion of a tree species is divided in three stages: ignition, growth, and termination. Temperature profiles reveal that during the combustion growth phase, flame lengths can reach up to 1.75 m and maintain a quasi‐steady state for approximately 6.94 h before declining. The stochastic module estimates ignition probabilities for nearby biomass elements based on temperature gradients and spatial proximity. Despite the simplifications made in our model, it exhibits decent performance in the modelling of a 2002 Colorado fire. The findings underscore the challenges of scaling simulation outputs and provide novel insights into the thermochemical conversion of biomass. This integrated approach bridges detailed heat transfer modelling and probabilistic combustion kinetics, offering a valuable tool for enhancing biomass conversion strategies and advancing chemical engineering applications in fire risk assessment.