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Computational fluid dynamics modelling of biomass fast pyrolysis in fluidised bed reactors, focusing different kinetic schemes
•CFD model is developed for fast pyrolysis in 300g/h fluidised bed reactor.•Various kinetics schemes (simple, global and advanced) for fast pyrolysis process are tested.•Model predictions are in good agreements with experiments.•Biomass particle type and size and reactor temperature are also investi...
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Published in: | Bioresource technology 2016-08, Vol.213, p.333-341 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | •CFD model is developed for fast pyrolysis in 300g/h fluidised bed reactor.•Various kinetics schemes (simple, global and advanced) for fast pyrolysis process are tested.•Model predictions are in good agreements with experiments.•Biomass particle type and size and reactor temperature are also investigated.•Developed models can be useful for the design of large-scale pyrolysis reactor.
The present work concerns with CFD modelling of biomass fast pyrolysis in a fluidised bed reactor. Initially, a study was conducted to understand the hydrodynamics of the fluidised bed reactor by investigating the particle density and size, and gas velocity effect. With the basic understanding of hydrodynamics, the study was further extended to investigate the different kinetic schemes for biomass fast pyrolysis process. The Eulerian–Eulerian approach was used to model the complex multiphase flows in the reactor. The yield of the products from the simulation was compared with the experimental data. A good comparison was obtained between the literature results and CFD simulation. It is also found that CFD prediction with the advanced kinetic scheme is better when compared to other schemes. With the confidence obtained from the CFD models, a parametric study was carried out to study the effect of biomass particle type and size and temperature on the yield of the products. |
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ISSN: | 0960-8524 1873-2976 |
DOI: | 10.1016/j.biortech.2016.02.042 |