LAPSE:2023.32454
Published Article
LAPSE:2023.32454
Towards Engineered Hydrochars: Application of Artificial Neural Networks in the Hydrothermal Carbonization of Sewage Sludge
April 20, 2023
Sewage sludge hydrochars (SSHs), which are produced by hydrothermal carbonization (HTC), offer a high calorific value to be applied as a biofuel. However, HTC is a complex processand the properties of the resulting product depend heavily on the process conditions and feedstock composition. In this work, we have applied artificial neural networks (ANNs) to contribute to the production of tailored SSHs for a specific application and with optimum properties. We collected data from the published literature covering the years 2014−2021, which was then fed into different ANN models where the input data (HTC temperature, process time, and the elemental content of hydrochars) were used to predict output parameters (higher heating value, (HHV) and solid yield (%)). The proposed ANN models were successful in accurately predicting both HHV and contents of C and H. While the model NN1 (based on C, H, O content) exhibited HHV predicting performance with R2 = 0.974, another model, NN2, was also able to predict HHV with R2 = 0.936 using only C and H as input. Moreover, the inverse model of NN3 (based on H, O content, and HHV) could predict C content with an R2 of 0.939.
Keywords
artificial neural networks, Biomass, hydrochar, hydrothermal carbonization, Machine Learning, sewage sludge, waste management
Suggested Citation
Kapetanakis TN, Vardiambasis IO, Nikolopoulos CD, Konstantaras AI, Trang TK, Khuong DA, Tsubota T, Keyikoglu R, Khataee A, Kalderis D. Towards Engineered Hydrochars: Application of Artificial Neural Networks in the Hydrothermal Carbonization of Sewage Sludge. (2023). LAPSE:2023.32454
Author Affiliations
Kapetanakis TN: Department of Electronic Engineering, Hellenic Mediterranean University, Chania, 73100 Crete, Greece [ORCID]
Vardiambasis IO: Department of Electronic Engineering, Hellenic Mediterranean University, Chania, 73100 Crete, Greece [ORCID]
Nikolopoulos CD: Department of Electronic Engineering, Hellenic Mediterranean University, Chania, 73100 Crete, Greece [ORCID]
Konstantaras AI: Department of Electronic Engineering, Hellenic Mediterranean University, Chania, 73100 Crete, Greece [ORCID]
Trang TK: Applied Chemistry Course, Department of Engineering, Kyushu Institute of Technology, Graduate School of Engineering, 1-1 Sensuicho, Tobata-ku, Kitakyushu 804-8550, Japan [ORCID]
Khuong DA: Applied Chemistry Course, Department of Engineering, Kyushu Institute of Technology, Graduate School of Engineering, 1-1 Sensuicho, Tobata-ku, Kitakyushu 804-8550, Japan [ORCID]
Tsubota T: Department of Applied Chemistry, Faculty of Engineering, Kyushu Institute of Technology, 1-1 Sensuicho, Tobata-ku, Kitakyushu 804-8550, Japan
Keyikoglu R: Department of Environmental Engineering, Gebze Technical University, 41400 Gebze, Turkey [ORCID]
Khataee A: Department of Environmental Engineering, Gebze Technical University, 41400 Gebze, Turkey; Research Laboratory of Advanced Water and Wastewater Treatment Processes, Department of Applied Chemistry, Faculty of Chemistry, University of Tabriz, Tabriz 51666-1 [ORCID]
Kalderis D: Department of Electronic Engineering, Hellenic Mediterranean University, Chania, 73100 Crete, Greece
Journal Name
Energies
Volume
14
Issue
11
First Page
3000
Year
2021
Publication Date
2021-05-21
Published Version
ISSN
1996-1073
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PII: en14113000, Publication Type: Journal Article
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LAPSE:2023.32454
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doi:10.3390/en14113000
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