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 c...

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Bibliographic Details
Published in:Biomass conversion and biorefinery 2021-10, Vol.11 (5), p.1703-1718
Main Authors: Bahari, Ali, Atashkari, Kazem, Mahmoudimehr, Javad
Format: Article
Language:English
Subjects:
Biotechnology
Coal gasification
Computational fluid dynamics
Efficiency
Emission
Energy
Environmental effects
Equivalence ratio
Genetic algorithms
Multiple objective analysis
Municipal solid waste
Municipal waste management
Optimization
Original Article
Parameters
Pollutants
Renewable and Green Energy
Response surface methodology
Solid waste management
Synthesis gas
Waste disposal
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Summary: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.
ISSN:2190-6815
2190-6823
DOI:10.1007/s13399-019-00592-1