Energy conservation – A novel approach of co-combustion of paint sludge and Australian lignite by principal component analysis, response surface methodology and artificial neural network modeling

Paint sludge is a waste with potential carcinogens, and its disposal via landfilling, incineration and conversion to other materials is limited. For proper disposal, paint sludge was investigated by thermogravimetric study and was blended with lignite in 70:30, 60:40, 50:50 percentage ratios respect...

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Veröffentlicht in:Environmental technology & innovation 2020-11, Vol.20, p.101061, Article 101061
Hauptverfasser: S.P., Sathiya Prabhakaran, G., Swaminathan, Joshi, Viraj V.
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Sprache:eng
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Zusammenfassung:Paint sludge is a waste with potential carcinogens, and its disposal via landfilling, incineration and conversion to other materials is limited. For proper disposal, paint sludge was investigated by thermogravimetric study and was blended with lignite in 70:30, 60:40, 50:50 percentage ratios respectively. Kinetics was computed by Freeman–Carroll and Sharp–Wentworth methods and the activation energy was found in the range of 126–175 kJ/kg and 18–75 kJ/kg respectively. The solid-state reaction mechanism was investigated by Kennedy–Clark and Coats–Redfern methods and was validated by master plot method. Second-order reaction mechanism (F2) was followed by paint sludge up to 0.5 conversion and after that it followed two-dimensional diffusion–reaction mechanism (D2) in the degradation process. Blending of paint sludge with lignite coal shifted the reaction mechanism of contracting volume (R3) up to 0.5 conversions and after that, it followed the same mechanism (D2) in the co-combustion process. The percentage contribution of paint sludge in the thermal degradation of blends was 70.71% and was confirmed by principal component analysis. Response Surface Methodology (RSM) revealed the optimum degradation zones and its empirical relations with temperature and blend ratios respectively. Artificial Neural Network (ANN) modeling suggested four models with multi-layer perception carrying 22 neurons fit for the study. [Display omitted] •Evaluation of 16 kinetic models by 3 model based methods.•Study at higher blending ratios of Paint Sludge.•Multi-disciplinary tools like PCA, ANN and RSM were used.•Synergistic effect and combustion indices study was done.
ISSN:2352-1864
2352-1864
DOI:10.1016/j.eti.2020.101061