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Application of a neural fuzzy model combined with simulated annealing algorithm to predict optimal conditions for polyethylene waste non-isothermal pyrolysis.

Authors :
Pan R
Duque JVF
Martins MF
Debenest G
Source :
Heliyon [Heliyon] 2020 Nov 25; Vol. 6 (11), pp. e05598. Date of Electronic Publication: 2020 Nov 25 (Print Publication: 2020).
Publication Year :
2020

Abstract

In the present study, the waste polyethylene (PE) pyrolysis under different non-isothermal conditions was investigated to estimate the optimal conversions and pyrolysis rates. The pyrolysis study was carried out using Thermogravimetry (TG) of the virgin and the waste PE under different heating rates of 5, 10, 15 and 20 °C/min. The TG experiments indicated that the virgin and the waste PE pyrolysis processes mainly underwent in the temperature range of 390-510 °C. Subsequently, the adaptive neural fuzzy model was adopted to predict the conversions and the pyrolysis rates of the virgin and the waste PE. The optimal operating conditions in different temperature ranges were optimized by the simulated annealing algorithm (SA). Moreover, the R-squared values of the virgin PE conversions (~ 1) and pyrolysis rates (> 0.999), and the waste PE conversions (~ 1) and pyrolysis rates (> 0.999) revealed the high accuracy of the adaptive neural fuzzy model predicted results.<br />Competing Interests: The authors declare no conflict of interest.<br /> (© 2020 Published by Elsevier Ltd.)

Details

Language :
English
ISSN :
2405-8440
Volume :
6
Issue :
11
Database :
MEDLINE
Journal :
Heliyon
Publication Type :
Academic Journal
Accession number :
33294718
Full Text :
https://doi.org/10.1016/j.heliyon.2020.e05598