Abstract

Pyrolysis and autoignition of beech wood covered with an acrylic-based waterborne coating layer are experimentally and numerically examined. Thermogravimetric Analysis (TGA) tests were conducted first for wood and coating to derive the kinetic parameters combining a numerical model, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Subsequently, bench scale autoignition tests of thermally thick wood and coating-wood composite with varying coating thickness were performed under four radiative heat fluxes. Thermal conductivities and heat capacities of wood, coating and yielded residue were determined by inversely modelling the measured surface and 3 mm in-depth temperatures at a moderate heat flux. Reliability of the fully parameterized model was validated by simulating the collected surface temperatures and mass loss rates at the remaining heating conditions. Meanwhile, the recorded autoignition times were predicted by the model using the measured critical temperature and critical mass flux. The results show that both GA and PSO yield identical accuracy in fitting the TGA measurements, and their average results are adopted. The parameterized model successfully captures the measured surface temperatures and mass loss rates before ignition despite some minor deviations. Application of the coating considerably improves the fire resistance of wood by increasing the critical heat flux, critical temperature, critical mass flux and ignition time. The measured autoignition times are relatively well estimated, and an approximate linear correlation exists between ignition time and coating thickness.

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