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)0C 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 H2, 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 °C and equivalence ratio 0.32 using response optimizer. The composite desirability observed was 0.59. •A robust model of biomass gasification based on minimization of Gibbs free energy was developed using ASPEN Plus simulator.•Gasification modelling has been validated to perform sensitivity analysis of Syzygium cumini biomass fuel.•Response surface methodology (RSM) has been applied for the multi-objective optimizations.•ANOVA tool was used for estimation of hydrogen concentration, cold gas efficiency, and higher heating value.•.Gasification temperature and equivalence ratio and has been optimized using response optimizer plot.