Details

Autor(en) / Beteiligte

• Xiong, Qingang
• Zhang, Jingchao
• Xu, Fei
• Wiggins, Gavin
• Stuart Daw, C.

Titel

Coupling DAEM and CFD for simulating biomass fast pyrolysis in fluidized beds

Ist Teil von

• Journal of analytical and applied pyrolysis, 2016-01, Vol.117 (C), p.176-181

Ort / Verlag

United States: Elsevier B.V

Erscheinungsjahr

2016

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• •The algorithm to couple DAEM and CFD was proposed.•Reaction rates were numerical integrated with high accuracy.•A lab-scale fluidized bed for biomass fast pyrolysis was simulated.•Effects of distribution function and standard deviation were investigated. We report results from computational simulations of an experimental, lab-scale bubbling bed biomass pyrolysis reactor that include a distributed activation energy model (DAEM) for the kinetics. In this study, we utilized multiphase computational fluid dynamics (CFD) to account for the turbulent hydrodynamics, and this was combined with the DAEM kinetics in a multi-component, multi-step reaction network. Our results indicate that it is possible to numerically integrate the coupled CFD–DAEM system without significantly increasing computational overhead. It is also clear, however, that reactor operating conditions, reaction kinetics, and multiphase flow dynamics all have major impacts on the pyrolysis products exiting the reactor. We find that, with the same pre-exponential factors and mean activation energies, inclusion of distributed activation energies in the kinetics can shift the predicted average value of the exit vapor-phase tar flux and its statistical distribution, compared to single-valued activation-energy kinetics. Perhaps the most interesting observed trend is that increasing the diversity of the DAEM activation energies appears to increase the mean tar yield, all else being equal. These findings imply that accurate resolution of the reaction activation energy distributions will be important for optimizing biomass pyrolysis processes.