Thermal Behavior Prediction of Sludge Co-Combustion with Coal: Curve Extraction and Artificial Neural Networks

Abstract

Previous studies on the co-combustion of sludge and coal have not effectively utilized the characteristics of the combustion process to predict thermal behavior. Therefore, focusing on these combustion process characteristics is essential to understanding and predicting thermal behavior during the co-combustion of sludge and coal. In this paper, we use thermogravimetric analysis to study the co-combustion of coal and sludge at different temperatures (300–460 °C, 460–530 °C, and 530–600 °C). Our findings reveal that the ignition improves, but the combustion worsens with more sludge. Then, we further employ curve extraction based on temperature and image segmentation to extract the DTG (weight loss rate) curves. We successfully predicted the DTG curves for different blends using nonlinear regression and curve extraction, achieving an excellent R2 of 99.7%. Moreover, the curve extraction method predicts DTG better than artificial neural networks for two samples in terms of R2 (99.7% vs. 99.1% and 99.7% vs. 94.9%), which guides the application of co-combusting coal and sludge.