scholarly journals Evaluating the Effect of Blending Ratio on the Co-Gasification of High Ash Coal and Biomass in a Fluidized Bed Gasifier Using Machine Learning

2019 ◽  
Vol 5 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Ali Yener Mutlu ◽  
Özgün Yücel ◽  
Furkan Elmaz
2014 ◽  
Vol 53 (49) ◽  
pp. 18678-18689 ◽  
Author(s):  
Veena Patil-Shinde ◽  
Tejas Kulkarni ◽  
Rahul Kulkarni ◽  
Prakash D. Chavan ◽  
Tripurari Sharma ◽  
...  

2018 ◽  
Vol 11 (1) ◽  
pp. 323-341 ◽  
Author(s):  
Shishir Tiwary ◽  
Suhas B. Ghugare ◽  
Prakash D. Chavan ◽  
Sujan Saha ◽  
Sudipta Datta ◽  
...  

J ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 266-287
Author(s):  
Zheng Lian ◽  
Yixiao Wang ◽  
Xiyue Zhang ◽  
Abubakar Yusuf ◽  
Lord Famiyeh ◽  
...  

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.


2021 ◽  
Vol 784 (1) ◽  
pp. 012033
Author(s):  
Xuefeng Li ◽  
Zhenhua Yan ◽  
Qingping Zhang ◽  
Bo Gao ◽  
Hao Chen ◽  
...  

2020 ◽  
Vol 6 ◽  
pp. 275-285
Author(s):  
Jurarat Nisamaneenate ◽  
Duangduen Atong ◽  
Anun Seemen ◽  
Viboon Sricharoenchaikul

Fuel ◽  
2022 ◽  
Vol 307 ◽  
pp. 121816
Author(s):  
Chao Wang ◽  
Mengjuan Zhang ◽  
Zhennan Han ◽  
Dingrong Bai ◽  
Wenli Duo ◽  
...  

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 2006
Author(s):  
Diamantis Almpantis ◽  
Anastasia Zabaniotou

This study explored the suitability of simulation tools for accurately predicting fluidized bed gasification in various scenarios without disturbing the operational system, and dedicating time to experimentation, in the aim of benefiting the decision makers and investors of the low-carbon waste-based bioenergy sector, in accelerating circular bioeconomy solutions. More specifically, this study aimed to offer a customized circular bioeconomy solution for a rice processing residue. The objectives were the simulation and economic assessment of an air atmospheric fluidized bed gasification system fueled with rice husk, for combined heat and power generation, by using the tools of Aspen Plus V9, and the Aspen Process Economic Analyzer. The simulation model was based on the Gibbs energy minimization concept. The technological configurations of the SMARt-CHP technology were used. A parametric study was conducted to understand the influence of process variables on product yield, while three different scenarios were compared: (1) air gasification; (2) steam gasification; and (3) oxygen-steam gasification-based scenario. Simulated results show good accuracy for the prediction of H2 in syngas from air gasification, but not for the other gas components, especially regarding CO and CH4 content. It seems that the RGIBBS and Gibbs free minimization concept is far from simulating the operation of a fluidized bed gasifier. The air gasification scenario for a capacity of 25.000 t/y rice husk was assessed for its economic viability. The economic assessment resulted in net annual earnings of EUR 5.1 million and a positive annual revenue of EUR 168/(t/y), an excellent pay out time (POT = 0.21) and return of investment (ROI = 2.8). The results are dependent on the choices and assumptions made.


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