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  4. Mixing evolution behavior of raw and gasified biomass pellets in a fluidized bed reactor
 
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Mixing evolution behavior of raw and gasified biomass pellets in a fluidized bed reactor

Publikationstyp
Journal Article
Date Issued
2022-12-31
Sprache
English
Author(s)
Wang, Shen  
Song, Tao  
Jarolin, Kolja 
Dymala, Timo 
Dosta, Maksym  
Heinrich, Stefan  
Shen, Laihong  
Institut
Feststoffverfahrenstechnik und Partikeltechnologie V-3  
Mehrskalensimulation von Feststoffsystemen V-EXK1 (H)  
TORE-URI
http://hdl.handle.net/11420/13874
Journal
Chemical engineering science  
Volume
264
Article Number
118161
Citation
Chemical Engineering Science 264: 118161 (2022-12-31)
Publisher DOI
10.1016/j.ces.2022.118161
Scopus ID
2-s2.0-85139408168
Due to a large particle size and a small specific surface, a homogeneous mixing of biomass pellets with bed materials during gasification plays a critical role in the devolatilization and carbon conversion. In this work, the mixing evolution behavior of biomass pellets at different gasification stages is investigated for the first time. Two bubbling fluidized beds are established to perform the preparation of biomass samples undergoing different gasification times and visualized mixing experiments, respectively. An image processing technique is introduced for the determination of the real-time distribution of biomass pellets. The vertical and lateral migration paths of biomass pellets at different gasification stages are revealed. The improvement of binary mixing by adjusting the operating conditions as well as the adaptability to different biomass loadings are discussed. A convolutional neural network is developed to validate the influence of fluidization velocity on the resulting flow and classify the fluidization behavior.
Subjects
Binary mixing evolution
Biomass pellet
Convolutional neural networks
Fluidized bed
Gasification
MLE@TUHH
Funding(s)
Mulitiskalen Simulation zur Analyse und Optimierung der Chemical-Looping Vergasung  
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