The effect of different operational parameters on hydrogen rich syngas production from biomass gasification in a dual fluidized bed gasifier

2018 ◽  
Vol 126 ◽  
pp. 210-221 ◽  
Author(s):  
Ebrahim Yaghoubi ◽  
Qingang Xiong ◽  
Mohammad Hossein Doranehgard ◽  
Mehdi Mihandoust Yeganeh ◽  
Gholamreza Shahriari ◽  
...  
Keyword(s):  
Fluidized Bed ◽  
Biomass Gasification ◽  
Operational Parameters ◽  
Syngas Production ◽  
Dual Fluidized Bed ◽  
Fluidized Bed Gasifier

scholarly journals Tar abatement for clean syngas production during biomass gasification in a dual fluidized bed

2016 ◽  
Vol 152 ◽  
pp. 116-123 ◽  
Author(s):  
L.F. de Diego ◽  
F. García-Labiano ◽  
P. Gayán ◽  
A. Abad ◽  
T. Mendiara ◽  
...  
Keyword(s):  
Fluidized Bed ◽  
Biomass Gasification ◽  
Syngas Production ◽  
Dual Fluidized Bed

Biomass Gasification in Dual Fluidized Bed Gasifier

2007 ◽  
pp. 1213-1217 ◽  
Author(s):  
Toshiyuki Suda ◽  
Takahiro Murakami ◽  
Satoko Aoki ◽  
Yoshiaki Matsuzawa ◽  
Guangwen Xu ◽  
...  
Keyword(s):  
Fluidized Bed ◽  
Biomass Gasification ◽  
Dual Fluidized Bed ◽  
Fluidized Bed Gasifier

High H2/CO Ratio Syngas Production from Chemical Looping Gasification of Sawdust in a Dual Fluidized Bed Gasifier

2016 ◽  
Vol 30 (3) ◽  
pp. 1764-1770 ◽  
Author(s):  
Jimin Zeng ◽  
Rui Xiao ◽  
Dewang Zeng ◽  
Yang Zhao ◽  
Huiyan Zhang ◽  
...  
Keyword(s):  
Fluidized Bed ◽  
Chemical Looping ◽  
Syngas Production ◽  
Dual Fluidized Bed ◽  
Fluidized Bed Gasifier

scholarly journals Simulation of biomass gasification in a dual fluidized bed gasifier

2012 ◽  
Vol 2 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Jie He ◽  
Kristina Göransson ◽  
Ulf Söderlind ◽  
Wennan Zhang
Keyword(s):  
Fluidized Bed ◽  
Biomass Gasification ◽  
Dual Fluidized Bed ◽  
Fluidized Bed Gasifier

scholarly journals Hydrogen Production by Fluidized Bed Reactors: A Quantitative Perspective Using the Supervised Machine Learning Approach

J ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 266-287
Author(s):  
Zheng Lian ◽  
Yixiao Wang ◽  
Xiyue Zhang ◽  
Abubakar Yusuf ◽  
Lord Famiyeh ◽  
...  
Keyword(s):  
Machine Learning ◽  
Hydrogen Production ◽  
Fluidized Bed ◽  
Biomass Gasification ◽  
Supervised Machine Learning ◽  
Fluidized Bed Reactors ◽  
Hydrogen Yield ◽  
Carbon Conversion ◽  
Operational Parameters ◽  
Operational Conditions

The current hydrogen generation technologies, especially biomass gasification using fluidized bed reactors (FBRs), were rigorously reviewed. There are involute operational parameters in a fluidized bed gasifier that determine the anticipated outcomes for hydrogen production purposes. However, limited reviews are present that link these parametric conditions with the corresponding performances based on experimental data collection. Using the constructed artificial neural networks (ANNs) as the supervised machine learning algorithm for data training, the operational parameters from 52 literature reports were utilized to perform both the qualitative and quantitative assessments of the performance, such as the hydrogen yield (HY), hydrogen content (HC) and carbon conversion efficiency (CCE). Seven types of operational parameters, including the steam-to-biomass ratio (SBR), equivalent ratio (ER), temperature, particle size of the feedstock, residence time, lower heating value (LHV) and carbon content (CC), were closely investigated. Six binary parameters have been identified to be statistically significant to the performance parameters (hydrogen yield (HY)), hydrogen content (HC) and carbon conversion efficiency (CCE)) by analysis of variance (ANOVA). The optimal operational conditions derived from the machine leaning were recommended according to the needs of the outcomes. This review may provide helpful insights for researchers to comprehensively consider the operational conditions in order to achieve high hydrogen production using fluidized bed reactors during biomass gasification.

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