Journal Article10.1016/j.biombioe.2022.106370
Process modelling and thermodynamic performance optimization of biomass air gasification fuelled with waste poultry litter pellet by integrating Aspen plus with RSM
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TL;DR: In this article , the processing of waste poultry litter pellet biomass for the generation of enriched hydrogen syngas using biomass gasifier was investigated and the sensitivity analysis was performed in which the influence of equivalence ratio (ER), gasification temperature, and moisture content on the producer gas (PG) composition, gas yield, H2/CO ratio, cold gas efficiency (CGE), and the higher heating value (HHV) were investigated.
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Abstract: This present study investigates the processing of waste poultry litter pellet biomass for the generation of enriched hydrogen syngas using biomass gasifier. Modelling of biomass gasifier was performed in Aspen Plus and Model validation was done using four different agricultural waste biomass with the experimental result and, a good agreement was attained. Sensitivity analysis was performed in which the influence of equivalence ratio (ER), gasification temperature, and moisture content on the producer gas (PG) composition, gas yield, H2/CO ratio, cold gas efficiency (CGE), and the higher heating value (HHV) were investigated. Furthermore, RSM has been employed for the multi-objectives optimization of the variable gasification parameters. R2 value obtained from ANOVA for H2, CGE, and HHV are 92.26%, 93.2%, and 92.4% respectively. The optimized values of H2, CGE, and HHV are 0.21, 57.67%, and 5.71 MJ/Nm3 respectively corresponding to temperature at 830.30 °C, equivalence ratio 0.2, and moisture content 16.36%. The desirability value obtained was around 0.87.
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Citations
A novel system integrating water electrolysis and supercritical CO2 cycle for biomass to methanol
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Hydrogen production from municipal solid waste via chemical looping gasification using CuFe2O4 spinel as oxygen carrier: An Aspen Plus modeling
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Poultry litter valorization: Development and optimization of an electro-chemical and thermal tri-generation process using an extreme gradient boosting algorithm
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