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Coupled heat and mass transfer modelling in convective drying of biomass at particle-level: Model validation with experimental data

Author

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  • Nagata, Gabriele A.
  • Costa, Thiago V.
  • Perazzini, Maisa T.B.
  • Perazzini, Hugo

Abstract

Acai berry waste (13.40 mm diameter, 1250 kg m−3 specific mass, 1850 J kg−1 °C−1 specific heat and 0.91 sphericity) is a large-scale agroindustrial by-product that can be used as source of biomass for thermochemical conversion. As this material has high initial moisture content, prior thermal treatment using drying is necessary. In this work, mathematical modelling of the single particle drying kinetics of acai berry waste was performed. The experimental conditions were: temperature of 42 °C and 57 °C and gas velocity of 1.8 m·s−1. Non-isothermal model consisted of differential equations based on macroscopic energy balance and on the differential form of the analytical solution of the diffusive model. The estimated values of h were 47.78 W·m−2·°C−1 at 42 °C and 42.55 W·m−2·°C−1 at 57 °C and for D0 and Ea were 1.39 × 10−4 m2·min−1 and 26.88 kJ·mol−1 at 42 °C, respectively, and 2.94 × 10−4 m2·min−1 and 25.05 kJ·mol−1 at 57 °C, respectively. The optimum value of Bim was equal to 2.5. The results showed that the non-isothermal model gave good predictions for both temperature and moisture content of the solid during drying. It was verified that there was not a significative dependence of the moisture diffusion with the heating rate of the solid.

Suggested Citation

  • Nagata, Gabriele A. & Costa, Thiago V. & Perazzini, Maisa T.B. & Perazzini, Hugo, 2020. "Coupled heat and mass transfer modelling in convective drying of biomass at particle-level: Model validation with experimental data," Renewable Energy, Elsevier, vol. 149(C), pages 1290-1299.
  • Handle: RePEc:eee:renene:v:149:y:2020:i:c:p:1290-1299
    DOI: 10.1016/j.renene.2019.10.123
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    3. 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.

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