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Article . 2021 . Peer-reviewed
License: Elsevier TDM
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Kinetic model study on biomass pyrolysis and CFD application by using pseudo-Bio-CPD model

Authors: Jiaye Zhang; Houzhang Tan; Chongming Chen; Shijie Zheng; Xuebin Wang; Zia ur Rahman;

Kinetic model study on biomass pyrolysis and CFD application by using pseudo-Bio-CPD model

Abstract

Abstract Pyrolysis is the key step in biomass thermochemical conversion process. The network model can accurately predict the pyrolysis process but generally cannot incorporate the combustion and gasification sub-models due to its complexity. This paper used the Bio-CPD model to predict the pyrolysis products of softwood and hardwood respectively; based on the predicted results, two empirical-simple forms of pyrolysis models were further optimized. The ultimate kinetic parameters obtained are suitable for biomass pyrolysis at high heating rate. For softwood, after being optimized, the apparent frequency factor and E/R of single rate are 4.3106e + 07 s−1, 10042 K respectively. While for two-competing rates model, the parameters are, α1 = 0.75, α2 = 0.89, A1 = 7992 s−1, E1/R = 7000 K, A2 = 8.3e + 09 s−1, E2/R = 14520 K, respectively. The numerical simulation of biomass pyrolysis and combustion process were performed by using CFD code Ansys Fluent. The results reveal that the release of volatile predicted by the default parameters have a delay compared with the actual process and is not appropriate for biomass simulation, while the optimized parameters in two simple models are accurate enough to simulate the biomass pyrolysis at high heating rate (103–105 K/s).

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
32
Top 10%
Top 10%
Top 10%