Modeling and multi-objective optimization of variable air gasification performance parameters using Syzygium cumini biomass by integrating ASPEN Plus with Response surface methodology (RSM)

The present study developed a robust method for the modeling and optimization of variable air gasification parameters using the ASPEN Plus simulator and Response surface methodology (RSM). A comprehensive thermochemical equilibrium based model of downdraft gasifier was developed by minimizing Gibbs free energy. Model validation was done by comparing the simulated result with the experimental result of four different feedstocks from the literature and, a good agreement was attained. The Complete modeling of the air gasification process was segregated into four phases viz. biomass drying, biomass decomposition, biomass gasification, and producer gas filtration. Drying operation and yield distribution during pyrolysis were computed by incorporating FORTRAN sub-routine statement. Sensitivity analysis was performed to obtain syngas composition using Syzygium cumini biomass fuel and different gasification performances like gas yield (GY), cold gas efficiency (CGE), and higher heating value (HHV) using gasification temperature (600-900)degrees C and equivalence ratio (ER) (0.2-0.6). Furthermore, RSM has been employed for the multi-objective optimizations of the variable gasification parameter. Central composite design (CCD) is adopted. Two independent parameters viz. temperature and equivalence ratio have opted as decision parameters for estimating the optimum performance parameters i.e., hydrogen concentrations, CGE, and HHV. Regression models created from the ANOVA results are found to be highly accurate in predicting output response variables. The optimal values of H-2, CGE, and HHV are found to be 0.1 (mole frac), 25.23%, and 3.96 MJ/kg respectively corresponding to optimized temperature at 887.879 degrees C and equivalence ratio 0.32 using response optimizer. The composite desirability observed was 0.59. (c) 2021 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

Automated summary

This study developed a robust method for modeling and optimizing variable air gasification parameters using ASPEN Plus simulator and Response Surface Methodology (RSM). A comprehensive thermochemical equilibrium-based model of downdraft gasifier was developed by minimizing Gibbs free energy, and good agreement was attained between simulated and experimental results. The air gasification process was modeled in four phases, including biomass drying, decomposition, gasification, and gas filtration, with sensitivity analysis performed to obtain syngas composition and optimize gasification performance.