摘要：Oily sludge is a hazardous waste stream of oil refineries that requires an effective process and an environment-friendly route to convert and recover valuable products. In this study, the pyrolytic conversion of the wet waste oil sludge was implemented in an autoclave pyrolyzer and a thermogravimetric analyzer (TGA) at 5°C/min, 20°C/min, and 40°C/min, respectively. The kinetic analysis was performed using model-free methods, such as Friedman, Kissenger–Akahira–Sunose (KAS), and Ozawa–Flynn–Wall (OFW) to examine the complex reaction mechanism. The average activation energy of wet waste oil sludge (WWOS) estimated from Friedman, KAS, and OFW methods was 198.68 ± 66.27 kJ/mol, 194.60 ± 56.99 kJ/mol, and 193.28 ± 54.88 kJ/mol, respectively. The activation energy increased with the conversion, indicating that complex multi-step processes are involved in the thermal degradation of WWOS. An artificial neural network (ANN) was employed to predict the conversion during heating at various heating rates. ANN allows complex non-linear relationships between the response variable and its predictors. nH, ΔG, and ΔS were found to be 191.26 ± 2.82 kJ/mol, 240.79 ± 2.82 kJ/mol, and −9.67 J/mol K, respectively. The positive values of ΔH and ΔG and the slightly negative value of ΔS indicate the endothermic nature of the conversion process, which is non-spontaneous without the supply of energy.
