Pyrolysis characteristics and kinetic reaction parameters estimation of sassafras wood via thermogravimetric modeling calculation coupled with hybrid optimization methodology

Li Xu, Zhongzhe Zhu, Shengcai Li, Youchao Zhang, Lei Wang and Wanghu Sun

Energy, 2023, vol. 263, issue PD

Abstract: The thermokinetics of sassafras wood pyrolysis were studied via thermogravimetric inverse modeling. Model-free combined with model-fitting methods were used to explore the optimal kinetics. Results indicate the obtained averaged activation energy and pre-exponential factor are 215.12 kJ/mol and 8.65 × 1017s−1, while the reaction model in charge is g(α) = [-ln(1-α)]1/3. In the following, Kissinger-based K–K method was adopted to separate the single reaction kinetics for each pseudo components. The analysis of K–K method provided the basis of the search range for each kinetic parameters. Finally, a new optimization algorithm was put forward, and the multi parallel reactions scheme incorporated into the Grey Wolf Optimization coupled with the Least Squared Fitting procedure was adopted to perform the optimization. The predicted MLR curves based on the simultaneously optimized kinetic parameters fit well with the experimental data not only at heating rates of 10, 20 and 30 K/min, but also at 5 and 40 K/min which were not used in the optimization. Such results indicated the excellent applicability of the optimized parameters and efficiency of the hybrid optimization procedure. Results from the present work could be a guidance for further biomass pyrolysis evaluation under more complex practical scenarios.

Keywords: Sassafras wood; Kinetic modeling; Grey wolf optimization; Pyrolysis kinetics (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:263:y:2023:i:pd:s0360544222028225

DOI: 10.1016/j.energy.2022.125936

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