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A comprehensive two dimensional Computational Fluid Dynamics model for an updraft biomass gasifier

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  • Fernando, Niranjan
  • Narayana, Mahinsasa

Abstract

This study focuses on developing a dynamic two dimensional Computational Fluid Dynamics (CFD) model of a moving bed updraft biomass gasifier. The model uses inlet air at room temperature as the gasifying medium and a fixed batch of biomass. The biomass batch is initially ignited by a heat source which is removed after a certain amount of time. This model operates by the heat emitted by combustion reactions, until the fuel is finished. Since the operation is batch wise, model is transient and takes into consideration the effect of bed movement as a result of shrinkage. The CFD model is capable of simulating the movement of interface between solid packed bed and gas free board and this motion is also presented. The model is validated by comparing the simulation results with experimental data obtained from a laboratory scale updraft gasifier operated in batch mode with Gliricidia. The developed model is used to find the optimum air flow rate that maximizes the cumulative CO production. It is found that from the simulation study for the particular experimental gasifier, a flow rate of 7 m3/h maximizes the CO production. The maximum cumulative CO production was 6.4 m3 for a 28 kg batch of Gliricidia.

Suggested Citation

  • Fernando, Niranjan & Narayana, Mahinsasa, 2016. "A comprehensive two dimensional Computational Fluid Dynamics model for an updraft biomass gasifier," Renewable Energy, Elsevier, vol. 99(C), pages 698-710.
  • Handle: RePEc:eee:renene:v:99:y:2016:i:c:p:698-710
    DOI: 10.1016/j.renene.2016.07.057
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    References listed on IDEAS

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    2. Ismail, Tamer M. & Ramos, Ana & Monteiro, Eliseu & El-Salam, M. Abd & Rouboa, Abel, 2020. "Parametric studies in the gasification agent and fluidization velocity during oxygen-enriched gasification of biomass in a pilot-scale fluidized bed: Experimental and numerical assessment," Renewable Energy, Elsevier, vol. 147(P1), pages 2429-2439.
    3. Zepeng Sun & Yazhuo Wang & Jing Gu & Haoran Yuan & Zejian Liu & Leilei Cheng & Xiang Li & Xian Li, 2023. "CFD Simulation and Experimental Study on a Thermal Energy Storage–Updraft Solid Waste Gasification Device," Energies, MDPI, vol. 16(12), pages 1-33, June.
    4. Wang, Linzheng & Zhang, Ruizhi & Deng, Ruiqu & Liu, Zeqing & Luo, Yonghao, 2023. "Comprehensive parametric study of fixed-bed co-gasification process through Multiple Thermally Thick Particle (MTTP) model," Applied Energy, Elsevier, vol. 348(C).
    5. Setyawan, M. Ismail Bagus & Dafiqurrohman, Hafif & Akbar, Maha Hidayatullah & Surjosatyo, Adi, 2021. "Characterizing a two-stage downdraft biomass gasifier using a representative particle model," Renewable Energy, Elsevier, vol. 173(C), pages 750-767.
    6. Ullah, Atta & Hong, Kun & Gao, Yanan & Gungor, Afsin & Zaman, Muhammad, 2019. "An overview of Eulerian CFD modeling and simulation of non-spherical biomass particles," Renewable Energy, Elsevier, vol. 141(C), pages 1054-1066.
    7. Gupta, Saurabh & Choudhary, Shikhar & Kumar, Suraj & De, Santanu, 2021. "Large eddy simulation of biomass gasification in a bubbling fluidized bed based on the multiphase particle-in-cell method," Renewable Energy, Elsevier, vol. 163(C), pages 1455-1466.
    8. Wickramaarachchi, W.A.M.K.P. & Narayana, Mahinsasa, 2020. "Pyrolysis of single biomass particle using three-dimensional Computational Fluid Dynamics modelling," Renewable Energy, Elsevier, vol. 146(C), pages 1153-1165.
    9. Yepes Maya, Diego Mauricio & Silva Lora, Electo Eduardo & Andrade, Rubenildo Vieira & Ratner, Albert & Martínez Angel, Juan Daniel, 2021. "Biomass gasification using mixtures of air, saturated steam, and oxygen in a two-stage downdraft gasifier. Assessment using a CFD modeling approach," Renewable Energy, Elsevier, vol. 177(C), pages 1014-1030.
    10. Gu, Tianbao & Yin, Chungen & Ma, Wenchao & Chen, Guanyi, 2019. "Municipal solid waste incineration in a packed bed: A comprehensive modeling study with experimental validation," Applied Energy, Elsevier, vol. 247(C), pages 127-139.
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