Prediction and optimization of syngas production from napier grass air gasification via kinetic modelling and response surface methodology
In this research, a kinetic model was developed for Napier grass air gasification using Aspen Plus software and thereafter collated and validated with experimental results obtained from a lab-scale fluidized bed reactor. Herein, the model was further employed to investigate the effect of gasificatio...
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Main Authors: | , , |
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Format: | Article |
Published: |
Elsevier
2023
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Online Access: | http://psasir.upm.edu.my/id/eprint/110189/ https://linkinghub.elsevier.com/retrieve/pii/S0360544223002773 |
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Summary: | In this research, a kinetic model was developed for Napier grass air gasification using Aspen Plus software and thereafter collated and validated with experimental results obtained from a lab-scale fluidized bed reactor. Herein, the model was further employed to investigate the effect of gasification operating parameters, including temperature (650–850) °C, equivalence ratio (0.2–0.4), and moisture content (0–18) wt. on products’ yields and syngas quality. The model was segregated into four sections: the drying, devolatilization, combustion, and reduction sections. The outputs of tar, gas, and char from the devolatilization section were defined by external Microsoft Excel subroutine. Kinetic parameters were incorporated in the combustion and reduction sections to simulate tar cracking, oxidation, and reduction reactions. A good agreement was observed between the predicted and experimental results. Furthermore, response surface methodology (RSM) was employed to analyze the mutual effects of process variables and perform multi-objective optimization to maximize producer gas yield, higher heating value, carbon conversion efficiency, and cold gas efficiency by incorporating the predicted results from the developed kinetic model. The optimized syngas yield and HHV were 69.42 wt and 8.14 MJ/Nm3 at 850 °C, 0.3021, and 15.69 wt for temperature, ER, and moisture content, respectively. |
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