Multi-objective optimization of a municipal solid waste gasifier

Municipal solid waste (MSW) is the largest waste stream around the world and has a great potential for syngas generation through gasification process. Many researchers have worked on biomass and coal gasification; however, a few of them have considered MSW as feedstock. The present study employs a combination of computational fluid dynamics (CFD) approach, response surface method (RSM), and genetic algorithm (GA) to optimize a MSW-driven gasifier with the simultaneous consideration of efficiency and environmental effects. This study is conducted for Rasht city which is located in the north of Iran and highly suffers from waste disposal problems. This work is to investigate the influence of major parameters on the performance of the gasifier and to find out the optimal set of design variables. The results illustrate that the efficiency of the gasifier is more influenced by the geometric parameters rather than equivalence ratio; however, the effects of equivalence ratio and geometrical parameters on total emission of pollutants are comparable. The efficiency and total emission of pollutants of the best trade-off design (or optimal design) are observed to be 32.2% and 4.8 ppm, respectively.