The ignition and flame-spread processes in the forest and urban fires involve the pyrolysis reactions of biomass materials. One of the most common methods for estimating the fire performance of a material is the evaluation of kinetic parameters, i.e., activation energy (𝐸), pre-exponential factor (𝐴), and reaction model (𝑓(𝛼)), from thermogravimetric analysis (TG) data. Typically, 𝐸 is estimated based on an Arrhenius-type equation such as Kissinger, Kissinger-Akahira-Sunose (KAS), and Friedman equations. Then, its value is adjusted along with other parameters by assuming a reaction model, e.g., the 𝑛-order model. This study proposes a Gaussian process regression (GPR) method to determine more reliable kinetic parameters without any assumptions of reaction mechanisms. This paper studies both constant and variable kinetic parameters and compares the GPR method with the conventional methods that assume the 𝑛-order model. The results of numerically calculated conversion (𝛼) indicated that the GPR model achieves the best fit with the experimental data.

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This work is licensed under a Creative Commons Attribution 4.0 License.



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