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Journal of Material Cycles and Waste Management

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11.10.2022 | ORIGINAL ARTICLE

Interactions of operating parameters on the production of waste polypropylene pyrolysis oil: neural fuzzy model and genetic algorithm optimization

verfasst von: Ruming Pan, Marcio Ferreira Martins, Gérald Debenest

Erschienen in: Journal of Material Cycles and Waste Management | Ausgabe 1/2023

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Abstract

This study aims to maximize the waste polypropylene (WPP) pyrolysis oil yield by regulating the operating parameters. The interactions of operating parameters on the distributions of WPP pyrolysis products were studied comprehensively by the neural fuzzy model. The genetic algorithm was utilized to determine the optimal operating parameters for WPP pyrolysis oil yield. Consequently, the highest oil yield of 68.4 wt% was achieved under 456 °C, 20 min, and 50 mL/min. WPP pyrolysis oil components were characterized by Fourier transform infrared spectroscopy (FTIR) and gas chromatography/mass spectrometry (GC/MS) analyses. The oil was composed of alkenes, alkanes, and naphthenes, with the carbon number ranging from C8 to C34. Lower carrier gas flow rate, shorter residence time, and lower temperature were conducive to forming oil's light fraction. In comparison, higher carrier gas flow rate, longer residence time, and higher temperature resulted in a high oil's heavy fraction production.

Vorheriger Artikel Contribution of waste segregation to GHG emissions, land usage, and health risk of NMVOC exposure: a study in Malaysia

Nächster Artikel Optimization of copper recovery from electronic waste using response surface methodology and Monte Carlo simulation under uncertainty

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Titel: Interactions of operating parameters on the production of waste polypropylene pyrolysis oil: neural fuzzy model and genetic algorithm optimization
verfasst von: Ruming Pan
Marcio Ferreira Martins
Gérald Debenest
Publikationsdatum: 11.10.2022
Verlag: Springer Japan
Erschienen in: Journal of Material Cycles and Waste Management / Ausgabe 1/2023
Print ISSN: 1438-4957
Elektronische ISSN: 1611-8227
DOI: https://doi.org/10.1007/s10163-022-01521-7

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