Variation of Geldart classification in MFM simulation of biomass fast pyrolysis considering the decrease of particle density and diameter

Hanbin Zhong, Fei Xu, Juntao Zhang, Yuqin Zhu, Shengrong Liang, Ben Niu and Xinyu Zhang

Renewable Energy, 2019, vol. 135, issue C, 208-217

Abstract: The multi-fluid model (MFM) has been widely used in computational fluid dynamics (CFD) simulation of biomass fast pyrolysis in the fluidized bed. After considering the variation of particle density and diameter, the Geldart classification of the formed char particles may be different with that of the virgin biomass particles due to the decrease of particle density and diameter. Thus, two or more Geldart group particles may be found in one solid phase. Normally, different gas-solid models are recommended for different Geldart particles. Therefore, in order to account the gas-solid drag of a specified solid phase with various Geldart particles, the present work applied the classification method proposed by Grace to determine the real-time particle classification in each computational cell during MFM simulation. A monotonic function which can avoid the potential discontinuous behavior was developed to combine different drag models from the inspiration of Lu-Gidaspow model. Based on the combined gas-solid drag model, the application of different drag models to the different Geldart particles in one solid phase was realized in the MFM. This method provides an option to precisely describe the gas-solid drag of the gas-solid fluidized bed reactor with the variation of Geldart classification in a specified solid phase.

Keywords: Multi-fluid model; Fluidized bed; Gas-solid drag; Geldart classification; Biomass; Pyrolysis (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148118314162
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:135:y:2019:i:c:p:208-217

DOI: 10.1016/j.renene.2018.11.097

Access Statistics for this article

Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides

More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().