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Multi-scale analysis of drying thermally thick biomass for bioenergy applications

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  • Kung, Kevin S.
  • Ghoniem, Ahmed F.

Abstract

Drying is a crucial process in many thermochemical processes for bioenergy. However, most existing drying models often have the following shortcomings: they are feedstock-dependent, or they are unable to describe the spatial inhomogeneity that often develops within thermally thick biomass particles under higher temperature gradients. In this paper, a multi-scale analysis was undertaken on the dynamics of drying thermally thick biomass under high temperatures, based on a new physical drying kinetics approach that is independent on feedstock-specific empirical parameters. A single-particle approach was then layered onto this kinetics model to understand how the spatially inhomogeneous moisture and temperature profiles inside a biomass particle evolve over time during drying. This process generates predicted temperature and drying time profiles that were successfully validated against experimental data. Subsequently, the impact on drying by various factors—particle size, geometry, initial moisture content, and reactor temperature—was studied. These observations were used to consider the design choices of a commercial-scale dryer, highlighting the key trade-offs, as well as optimized combinations of temperature and particle size that minimizes the operating cost. The approach described in this paper can be readily integrated into other mathematical descriptions of bioenergy conversion processes such as gasification and combustion.

Suggested Citation

  • Kung, Kevin S. & Ghoniem, Ahmed F., 2019. "Multi-scale analysis of drying thermally thick biomass for bioenergy applications," Energy, Elsevier, vol. 187(C).
  • Handle: RePEc:eee:energy:v:187:y:2019:i:c:s0360544219316834
    DOI: 10.1016/j.energy.2019.115989
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    References listed on IDEAS

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    1. Anderson, Jan-Olof & Westerlund, Lars, 2014. "Improved energy efficiency in sawmill drying system," Applied Energy, Elsevier, vol. 113(C), pages 891-901.
    2. Gebreegziabher, Tesfaldet & Oyedun, Adetoyese Olajire & Hui, Chi Wai, 2013. "Optimum biomass drying for combustion – A modeling approach," Energy, Elsevier, vol. 53(C), pages 67-73.
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    5. Kung, Kevin S. & Thengane, Sonal K. & Shanbhogue, Santosh & Ghoniem, Ahmed F., 2019. "Parametric analysis of torrefaction reactor operating under oxygen-lean conditions," Energy, Elsevier, vol. 181(C), pages 603-614.
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    Cited by:

    1. Claudio, Caio C. & Perazzini, MaisaT.B. & Perazzini, Hugo, 2022. "Modeling and estimation of moisture transport properties of drying of potential Amazon biomass for renewable energy: Application of the two-compartment approach and diffusive models with constant or m," Renewable Energy, Elsevier, vol. 181(C), pages 304-316.
    2. Kuznetsov, G.V. & Nigay, N.A. & Syrodoy, S.V. & Gutareva, N. Yu & Malyshev, D. Yu, 2022. "A comparative analysis of the characteristics of the water removal processes in preparation for incineration of typical wood waste and forest combustible materials," Energy, Elsevier, vol. 239(PE).
    3. Kung, Kevin S. & Thengane, Sonal K. & Ghoniem, Ahmed F. & Lim, C. Jim & Cao, Yankai & Sokhansanj, Shahabaddine, 2022. "Start-up, shutdown, and transition timescale analysis in biomass reactor operations," Energy, Elsevier, vol. 248(C).

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