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

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.

The Optimization and Parameters Effect on Distilled Product from Pyrolysis of LDPE based on RSM for Liquid Fuel Production

“…It was explained by the fact that, the rise in heating rate increased the pyrolysis rate. This phenomenon stimulated to increase the thermally decomposed of LDPE [20]. At the constant values of heating rate, extending the residence time from 30 to 180 min improved the % distilled product.…”

Toward a cleaner and more sustainable world: A framework to develop and improve waste management through organizations, governments and academia

“…The preservation of water and soil by strategically planning landfill areas that do not impact water table or produce methane gas by imposing explosion risks in the surroundings, contribute to the environmental pillar ( Tseng, 2011 ). Among the articles that involve solid waste in the context of sustainability, the main issues mentioned are finite natural resources and riches that can be exploited from the waste ( Pan et al., 2020 ; Tan et al., 2014 ).…”

Comparison of Sb2O3 and Sb2O3/SiO2 Double Stacked pH Sensing Membrane Applied in Electrolyte-Insulator-Semiconductor Structure

“…Post-RTA in different temperatures (400 °C, 500 °C, 600 °C) was applied in EIS structure [ 21 ]. The sensor performance including sensitivity [ 22 ], hysteresis [ 23 ], and drift, rate [ 24 ], were measured to find the optimal annealing condition [ 25 ]. To examine the improvements of material properties, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and atomic force microscope (AFM) [ 26 , 27 ] were used to examine the crystalline structure, chemical bindings, and surface roughness.…”