Pyrolysis Study of Mixed Polymers for Non-Isothermal TGA: Artificial Neural Networks Application
Pure polymers of polystyrene (PS), low-density polyethylene (LDPE) and polypropylene (PP), are the main representative of plastic wastes. Thermal cracking of mixed polymers, consisting of PS, LDPE, and PP, was implemented by thermal analysis technique “thermogravimetric analyzer (TGA)” with heating...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Polymers |
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| Online Access: | https://www.mdpi.com/2073-4360/14/13/2638 |
| _version_ | 1797408318166138880 |
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| author | Ibrahim Dubdub |
| author_facet | Ibrahim Dubdub |
| author_sort | Ibrahim Dubdub |
| collection | DOAJ |
| description | Pure polymers of polystyrene (PS), low-density polyethylene (LDPE) and polypropylene (PP), are the main representative of plastic wastes. Thermal cracking of mixed polymers, consisting of PS, LDPE, and PP, was implemented by thermal analysis technique “thermogravimetric analyzer (TGA)” with heating rate range (5–40 K/min), with two groups of sets: (ratio 1:1) mixture of PS and PP, and (ratio 1:1:1) mixture of PS, LDPE, and PP. TGA data were utilized to implement one of the machine learning methods, “artificial neural network (ANN)”. A feed-forward ANN with Levenberg-Marquardt (LM) as learning algorithm in the backpropagation model was performed in both sets in order to predict the weight fraction of the mixed polymers. Temperature and the heating rate are the two input variables applied in the current ANN model. For both sets, 10-10 neurons in logsig-tansig transfer functions two hidden layers was concluded as the best architecture, with almost (R > 0.99999). Results approved a good coincidence between the actual with the predicted values. The model foresees very efficiently when it is simulated with new data. |
| first_indexed | 2024-03-09T03:57:43Z |
| format | Article |
| id | doaj.art-9d05b6f278bf4caa90aef80197e4f417 |
| institution | Directory Open Access Journal |
| issn | 2073-4360 |
| language | English |
| last_indexed | 2024-03-09T03:57:43Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Polymers |
| spelling | doaj.art-9d05b6f278bf4caa90aef80197e4f4172023-12-03T14:18:46ZengMDPI AGPolymers2073-43602022-06-011413263810.3390/polym14132638Pyrolysis Study of Mixed Polymers for Non-Isothermal TGA: Artificial Neural Networks ApplicationIbrahim Dubdub0Department of Chemical Engineering, King Faisal University, Al-Hassa 31982, Saudi ArabiaPure polymers of polystyrene (PS), low-density polyethylene (LDPE) and polypropylene (PP), are the main representative of plastic wastes. Thermal cracking of mixed polymers, consisting of PS, LDPE, and PP, was implemented by thermal analysis technique “thermogravimetric analyzer (TGA)” with heating rate range (5–40 K/min), with two groups of sets: (ratio 1:1) mixture of PS and PP, and (ratio 1:1:1) mixture of PS, LDPE, and PP. TGA data were utilized to implement one of the machine learning methods, “artificial neural network (ANN)”. A feed-forward ANN with Levenberg-Marquardt (LM) as learning algorithm in the backpropagation model was performed in both sets in order to predict the weight fraction of the mixed polymers. Temperature and the heating rate are the two input variables applied in the current ANN model. For both sets, 10-10 neurons in logsig-tansig transfer functions two hidden layers was concluded as the best architecture, with almost (R > 0.99999). Results approved a good coincidence between the actual with the predicted values. The model foresees very efficiently when it is simulated with new data.https://www.mdpi.com/2073-4360/14/13/2638pyrolysismixed polymersthermogravimetric analyzer (TGA)artificial neural networks (ANN) |
| spellingShingle | Ibrahim Dubdub Pyrolysis Study of Mixed Polymers for Non-Isothermal TGA: Artificial Neural Networks Application Polymers pyrolysis mixed polymers thermogravimetric analyzer (TGA) artificial neural networks (ANN) |
| title | Pyrolysis Study of Mixed Polymers for Non-Isothermal TGA: Artificial Neural Networks Application |
| title_full | Pyrolysis Study of Mixed Polymers for Non-Isothermal TGA: Artificial Neural Networks Application |
| title_fullStr | Pyrolysis Study of Mixed Polymers for Non-Isothermal TGA: Artificial Neural Networks Application |
| title_full_unstemmed | Pyrolysis Study of Mixed Polymers for Non-Isothermal TGA: Artificial Neural Networks Application |
| title_short | Pyrolysis Study of Mixed Polymers for Non-Isothermal TGA: Artificial Neural Networks Application |
| title_sort | pyrolysis study of mixed polymers for non isothermal tga artificial neural networks application |
| topic | pyrolysis mixed polymers thermogravimetric analyzer (TGA) artificial neural networks (ANN) |
| url | https://www.mdpi.com/2073-4360/14/13/2638 |
| work_keys_str_mv | AT ibrahimdubdub pyrolysisstudyofmixedpolymersfornonisothermaltgaartificialneuralnetworksapplication |