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Decision analysis for plastic waste gasification considering energy, exergy, and environmental criteria using TOPSIS and grey relational analysis

Rezgar HasanzadehDepartment of Mechanical Engineering, Faculty of Engineering, Urmia University, Urmia 5756151818, the Islamic Republic of IranParisa MojaverDepartment of Mechanical Engineering, Faculty of Engineering, Urmia University, Urmia 5756151818, the Islamic Republic of IranTaher AzdastDepartment of Mechanical Engineering, Faculty of Engineering, Urmia University, Urmia 5756151818, the Islamic Republic of IranShahram KhalilaryaDepartment of Mechanical Engineering, Faculty of Engineering, Urmia University, Urmia 5756151818, the Islamic Republic of IranAta ChitsazDepartment of Mechanical Engineering, Faculty of Engineering, Urmia University, Urmia 5756151818, the Islamic Republic of IranMarc A. RosenFaculty of Engineering and Applied Science, University of Ontario Institute of Technology, Oshawa, Ontario, L1G 0C5 Canada
2023en
ABI

Аннотация

Plastic waste is becoming of increasing interest in gasification research because the gasification of plastic waste not only produces a valuable hydrogen-rich syngas but also can help reduce environmental problems caused by these materials. Most studies in the field of plastic waste gasification have only focused on evaluating effects of process parameters and optimizing the process by considering input variables. The present study explores the comparative performance analysis of a wide range of prevalent plastic waste types utilizing multi-criteria decision-making techniques. This study uses the “technique for order preference by similarity to ideal solution” (TOPSIS) and grey relational analysis (GRA) and presents a thorough sensitivity analysis. Low-density polyethylene results in maximum lower heating value of syngas and has a desirable performance from cold gas and exergy efficiencies viewpoints in air gasification. The findings of TOPSIS and GRA techniques show that low-density polyethylene as plastic waste exhibits the best performance in an air gasification process and the results of the sensitivity analysis confirm this. However, the decision making in steam gasification was challenging where TOPSIS and GRA techniques introduced high-density polyethylene and low-density polyethylene as the best candidates, respectively. Again, the findings of the sensitivity analysis confirmed the result. High-density polyethylene exhibits the best performance in steam gasification according to sensitivity analysis via the TOPSIS technique while low-density polyethylene ranked first according to sensitivity analysis of GRA. The findings can contribute to a better understanding of the selection of plastic waste feedstock for air and steam gasification by considering energy, exergy, and environmental factors.

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