Analyzing and Modeling the Municipal Sewage Sludge Drying Process Using Python

• Published in: Processes 2023-12, Vol.11 (12), p.3263
• Main Authors: Mihelič, Erik, Klinar, Dušan, Rižnar, Klavdija, Oprčkal, Primož
• Format: Article
• Language: English
• Subjects: Analysis; Chemical engineering; Chemical reactions; Control algorithms; Cost control; Critical point; Data analysis; Design optimization; Diffusion coefficient; Drying; Efficiency; Energy consumption; Flat plates; Heat; Heat transfer; Heat transfer coefficients; Humidity; Libraries; Machine learning; Mass transfer; Mathematical models; Modelling; Moisture content; Optimization; Parameters; Process controls; Programming languages; Relative humidity; Sewage sludge; Sludge; Sludge drying; Visualization; Water treatment
• ISSN: 2227-9717; 2227-9717
• DOI: 10.3390/pr11123263

The programming language Python offers the opportunity to analyze and model the municipal sewage sludge (MSS) drying process in an illustrative chemical engineering practice. The drying process is performed on a flat plate while maintaining a uniform, parallel drying air speed. The Python program helps to analyze the digitalized weight measurements from each sample. The program enables the sorting of input data, determination of the drying critical point, and evaluation of the first and second drying periods. Moreover, the model calculates the fundamental drying parameter and forms a drying master curve to support the transfer to different drying conditions. The basic parameters calculated are mass transfer coefficient, heat transfer coefficient, and diffusion coefficient. The results are consistent with published data for those coefficients over the drying temperature range of 19.4–52.4 °C and relative humidity range of 8.2–33.6%. The findings of this study demonstrate the potential of Python as a powerful tool for analyzing experimental data and modeling chemical processes, which can lead to improved process design, optimization, and control.