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Hou, Fei; Zhong, Xiaoxing; Zanoni, Marco A.B.; Rashwan, Tarek L. and Torero, José L.
(2024).
DOI: https://doi.org/10.1016/j.energy.2024.131421
Abstract
Coal smouldering fires are global disasters and notoriously challenging to characterize. To better understand combustion and chemistry within these coal fires, TG-DSC experiments were carried out in two different coal samples in nitrogen and oxygen-limited (including ambient air) atmospheres. A mechanism with 8-step reactions simulating coal combustion was proposed, including one drying, two pyrolysis, two oxygen adsorption, and three high-temperature oxidations. The kinetic parameters were optimized via a Genetic Algorithm (GA). It was found that this 8-step mechanism created unnecessary overfitting to the TGA data. Therefore, two alternative schemes were developed with 5- and 4-step, which included and neglected oxygen adsorption, respectively. To compare the two schemes, GA and Gaussian multi-modal fitting were used to quantify the mass change rates in each step and their thermal effects as functions of oxygen concentrations. Moreover, the heat flow rates of coal samples were calculated and compared with measured DSC curves. The results indicated that oxygen adsorption could play a critical role in the transition from water evaporation to high-temperature combustion, and the 5-step scheme could reflect coal's intrinsic oxygen-limited combustion characteristics more accurately. Altogether, this study provides novel insight into coal smouldering under oxygen-limited conditions.
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