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Pyrolysis of different rank fuels: characteristics and kinetic parameter study using nonlinear optimization and artificial neural network

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Abstract

During the pyrolysis process, solid fuels decompose at different degradation rates and temperature ranges owing to their complex structure and composition. Therefore, predicting the thermal degradation of a wide range of solid fuels is paramount for understanding the thermal stability of fuels to effectively utilize them. In this study, the proposed artificial neural network (ANN) (NN-5-22-22-2), with three layers and tansig–logsig transfer functions, predicts the thermogravimetry (TG) and the derivative thermogravimetry (DTG) curves based on 24,750 experimental data points as input parameters (six different heating rates, 825 temperature points, and moisture, volatile, and fixed carbon content of five types of samples). In this exploratory study, we applied a nonlinear optimization method, namely the generalized reduced gradient (GRG) algorithm, to determine the activation energy (E) and frequency factor (A) in a nonlinear equation instead of using the conventional slope and intercept method. Five types of rank fuels were calculated using a distributed activation energy model (DAEM) at six heating rates (5, 10, 20, 30, 40, and 50 °C min−1). The results of the highest average correlation factor, low mean square error values, and low normalized mean square error values of the prediction and experimental data were in agreement. Thus, we demonstrated that the GRG algorithm is an appropriate method for analyzing kinetic data.

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Acknowledgements

This research was supported by a grant from the National Research Foundation of Korea and funded by the Ministry of Science, ICT, and Future Planning (Grant No. 2022K1A4A8A01080312).

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Authors and Affiliations

  1. School of Mechanical Engineering, Pusan National University, 2, Busandaehak-ro 63 beon-gil, Geumjeong-gu, Busan, 46241, Republic of Korea

    Viet Thieu Trinh & Chung-Hwan Jeon

  2. School of Mechanical Engineering, Hanoi University of Science and Technology, No 1, Dai Co Viet, Hai Ba Trung, Hanoi, Vietnam

    Viet Thieu Trinh

  3. Pusan Clean Energy Research Institute, Pusan National University, 2, Busandaehak-ro 63 beon-gil, Geumjeong-gu, Busan, 46241, Republic of Korea

    Byoung-Hwa Lee, Tae-Yong Jeong & Chung-Hwan Jeon

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  1. Viet Thieu Trinh
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Contributions

TVT, TYJ, BHL, and CHJ conceived and planned the research. TVT conducted the experiments. TVT, BHL, and CHJ contributed to the results analysis. TVT and CHJ contributed to the review of the original and revised versions of the manuscript. TVT took the lead in writing the manuscript. All authors helped shape the research, discussed the results, and contributed to the final manuscript.

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Correspondence to Byoung-Hwa Lee or Chung-Hwan Jeon.

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Trinh, V.T., Lee, BH., Jeong, TY. et al. Pyrolysis of different rank fuels: characteristics and kinetic parameter study using nonlinear optimization and artificial neural network. J Therm Anal Calorim 148, 5493–5507 (2023). https://doi.org/10.1007/s10973-023-12084-6

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  • DOI: https://doi.org/10.1007/s10973-023-12084-6

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