Case Studies in Thermal Engineering (Dec 2022)

Investigation of combustion performance of tannery sewage sludge using thermokinetic analysis and prediction by artificial neural network

  • Arslan Khan,
  • Imtiaz Ali,
  • Wasif Farooq,
  • Salman Raza Naqvi,
  • Muhammad Taqi Mehran,
  • Ameen Shahid,
  • Rabia Liaquat,
  • Muhammad Waqas Anjum,
  • Muhammad Naqvi

Journal volume & issue
Vol. 40
p. 102586

Abstract

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The disposal and the management of sewage sludge from tanneries is a challenging issue for the leather industries because of their adverse effect on the environment. In this study the detailed characterization and assessment using kinetic and thermodynamic parameters of the tannery sewage sludge in combustion environment was employed. Isoconversional model-free methods like Ozawa-Flynn-Wall (OFW), Friedman and Kissinger-Akahira-Sunose (KAS) were employed to investigate the kinetics and the thermodynamic parameters in the air environment. Activation energies (Ea) for the Friedman, KAS and OFW were reported. The DTG curves at the heating rate of 5, 10, 20 and 40 °C/min show the diversified conversions in three major stages. The Ea values for the model ranges are Friedman (148.96 kJ/mol-395.23 kJ/mol), KAS (169.65 kJ/mol-383.75 kJ/mol) and OFW (176.44 kJ/mol-377.85 kJ/mol). The average Ea for the Friedman is 226.04 kJ/mol while for KAS and OFW the average Ea is 230.71 kJ/mol and 230.11 kJ/mol. Moreover, the values of ΔH, ΔG, and ΔS were analysed. Furthermore, the frequency distribution by applying the DAEM model is investigated, and there are six pseudo-components involved in the frequency distribution for combustion. For the thermal degradation prediction of the sewage sludge from the tannery, an artificial neural network (ANN) of the MLP-3-7-1 model was used. This model shows that there is good agreement between the experimental and the predicted values. Overall, this study highlights the importance of the ANN for the prediction of combustion behaviour of biomass with more accuracy.

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