University of Science and Technology-The University of Danang, Danang, Viet Nam
BibTex Citation Data :
@article{IJRED53994, author = {Thanh Xuan Nguyen-Thi and Thi Minh Tu Bui and Van Ga Bui}, title = {Simulation and experimental study of refuse-derived fuel gasification in an updraft gasifier}, journal = {International Journal of Renewable Energy Development}, volume = {12}, number = {3}, year = {2023}, keywords = {Refuse-derived fuel; Gasification; Updraft gasifier; Syngas; Waste to energy}, abstract = {Refuse-derived fuel (RDF) made from the mixture of wood and loose rice husk increases the porosity of the fuel in the furnace to facilitate the gasification process. Simulation results show that CO is concentrated in the incomplete combustion zone and CO 2 forms mainly in the fully burned area; CH 4 forms in the reduction region, while H 2 forms in the region of high temperature of the furnace. When the mixture composition was f=0.3, the CO concentration in the syngas reached about 21%, the H 2 concentration reached about 2% and the CH 4 concentration was too low to be ignored. When the mixture composition increased to f = 0.5, the CO concentration reached about 26%, the H 2 concentration remained almost unchanged and the CH 4 content increased to 6%. The calorific value of the syngas reached a maximum when f = 0.5 and the temperature of the reduction zone is in the range of 900K to 1200K. Air humidity affects CO concentration but not much on CH 4 and H 2 concentration as well as the syngas calorific value. The difference between simulation and experimental results is not more than 10% for CH 4 concentration and not more than 14% for CO 2 concentration. The power of the spark ignition engine is reduced by 30% when running on syngas compared to when running on gasoline.}, pages = {601--614} doi = {10.14710/ijred.2023.53994}, url = {https://ejournal.undip.ac.id/index.php/ijred/article/view/53994} }
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Co-gasification of waste biomass-low grade coal mix using downdraft gasifier coupled with dual-fuel engine system: Multi-objective optimization with hybrid approach using RSM and Grey Wolf Optimizer
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