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CFD modeling of the effects of particle shrinkage and intra-particle heat conduction on biomass fast pyrolysis

Author

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  • Zhong, Hanbin
  • Xiong, Qingang
  • Zhu, Yuqin
  • Liang, Shengrong
  • Zhang, Juntao
  • Niu, Ben
  • Zhang, Xinyu

Abstract

This study numerically characterizes the combined effects of particle shrinkage and intra-particle heat conduction on biomass fast pyrolysis using computational fluid dynamics (CFD). The so-called multi-fluid model (MFM) was employed to simulate hydrodynamics and biomass fast pyrolysis was modeled by a lumped kinetics. The particle shrinkage and intra-particle heat conduction were modeled through modification of the diameter of biomass phases and reaction rate constant. Four cases with different combinations of particle shrinkage and intra-particle heat conduction were designed and their performances regarding product yields were compared. The hydrodynamics and reaction behaviors in the reactor were predicted. The distributions of particle diameter and density, product yields, and char properties were analyzed and compared with the experiments. The mechanisms for the effects of these two models were revealed. Both the particle shrinkage and intra-particle heat conduction effects lead to lower tar yield and higher char yield. The predicted product yields considering both models are in the best agreement with the experiment results.

Suggested Citation

  • Zhong, Hanbin & Xiong, Qingang & Zhu, Yuqin & Liang, Shengrong & Zhang, Juntao & Niu, Ben & Zhang, Xinyu, 2019. "CFD modeling of the effects of particle shrinkage and intra-particle heat conduction on biomass fast pyrolysis," Renewable Energy, Elsevier, vol. 141(C), pages 236-245.
    • Handle: RePEc:eee:renene:v:141:y:2019:i:c:p:236-245
    DOI: 10.1016/j.renene.2019.04.006
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    1. Kan, Tao & Strezov, Vladimir & Evans, Tim J., 2016. "Lignocellulosic biomass pyrolysis: A review of product properties and effects of pyrolysis parameters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1126-1140.
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    Cited by:

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    2. Thoharudin, & Hsiau, Shu-San & Chen, Yi-Shun & Yang, Shouyin, 2022. "Numerical modeling of biomass fast pyrolysis by using an improved comprehensive reaction scheme for energy analysis," Renewable Energy, Elsevier, vol. 181(C), pages 355-364.
    3. Brillard, A. & Brilhac, J.F., 2020. "Improvements of global models for the determination of the kinetic parameters associated to the thermal degradation of lignocellulosic materials under low heating rates," Renewable Energy, Elsevier, vol. 146(C), pages 1498-1509.
    4. Hosseinzadeh, Saman & Fattahi, Abolfazl & Sadeghi, Sadegh & Rahmani, Ebrahim & Bidabadi, Mehdi & Zarei, Fatemeh & Xu, Fei, 2020. "Mathematical analysis of steady-state non-premixed multi-zone combustion of porous biomass particles under counter-flow configuration," Renewable Energy, Elsevier, vol. 159(C), pages 705-725.
    5. Kardaś, Dariusz & Hercel, Paulina & Polesek-Karczewska, Sylwia & Wardach-Świȩcicka, Izabela, 2019. "A novel insight into biomass pyrolysis – The process analysis by identifying timescales of heat diffusion, heating rate and reaction rate," Energy, Elsevier, vol. 189(C).
    6. Farahani, Moein Farmahini & Akbari, Shahin & Sadeghi, Sadegh & Bidabadi, Mehdi & Moghadam, Mohammadamir Ghasemian & Xu, Fei, 2020. "Analytical study of transient counter-flow non-premixed combustion of biomass in presence of thermal radiation," Renewable Energy, Elsevier, vol. 159(C), pages 312-325.
    7. Zhou, Tao & Yang, Shiliang & Wei, Yonggang & Hu, Jianhang & Wang, Hua, 2020. "Impact of wide particle size distribution on the gasification performance of biomass in a bubbling fluidized bed gasifier," Renewable Energy, Elsevier, vol. 148(C), pages 534-547.
    8. Kaczor, Zuzanna & Buliński, Zbigniew & Werle, Sebastian, 2020. "Modelling approaches to waste biomass pyrolysis: a review," Renewable Energy, Elsevier, vol. 159(C), pages 427-443.
    9. Yang, Shiliang & Fan, Feihu & Hu, Jianhang & Wang, Hua, 2020. "Particle-scale evaluation of the biomass steam-gasification process in a conical spouted bed gasifier," Renewable Energy, Elsevier, vol. 162(C), pages 844-860.
    10. Kabir, Faryal & Gulfraz, Muhammad & Raja, Ghazala Kaukab & Inam-ul-Haq, Muhammad & Awais, Muhammad & Mustafa, Muhammad Salman & Khan, Sami Ullah & Tlili, Iskander & Shadloo, Mostafa Safdari, 2020. "Screening of native hyper-lipid producing microalgae strains for biomass and lipid production," Renewable Energy, Elsevier, vol. 160(C), pages 1295-1307.
    11. Wang, Cui & Zhu, Chao & Huang, Jianbing & Li, Linfeng & Jin, Hui, 2021. "Enhancement of depolymerization slag gasification in supercritical water and its gasification performance in fluidized bed reactor," Renewable Energy, Elsevier, vol. 168(C), pages 829-837.
    12. Du, Shaohua & Yuan, Shouzheng & Zhou, Qiang, 2021. "Numerical investigation of co-gasification of coal and PET in a fluidized bed reactor," Renewable Energy, Elsevier, vol. 172(C), pages 424-439.
    13. Ding, Yanming & Chen, Wenlu & Zhang, Wenlong & Zhang, Xueting & Li, Changhai & Zhou, Ru & Miao, Fasheng, 2022. "Experimental and numerical simulation study of typical semi-transparent material pyrolysis with in-depth radiation based on micro and bench scales," Energy, Elsevier, vol. 258(C).
    14. Zhong, Hanbin & Xiong, Qingang & Yin, Lina & Zhang, Juntao & Zhu, Yuqin & Liang, Shengrong & Niu, Ben & Zhang, Xinyu, 2020. "CFD-based reduced-order modeling of fluidized-bed biomass fast pyrolysis using artificial neural network," Renewable Energy, Elsevier, vol. 152(C), pages 613-626.

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