Prediction Model for Tensile Modulus of Carbon Nanotube–Polymer Composites
This work develops a Neural Network (NN) model for the prediction of the tensile modulus of carbon nanotube (CN)/polymer nanocomposites, based on experimental database. A data set composed of 282 configurations is collected from available resources. Considered input variables of the dataset are such...
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| Ngôn ngữ: | English |
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Springer
2022
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| Truy cập trực tuyến: | https://link.springer.com/chapter/10.1007/978-3-030-92574-1_80 https://dlib.phenikaa-uni.edu.vn/handle/PNK/5715 https://doi.org/10.1007/978-3-030-92574-1_80 |
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oai:localhost:PNK-57152022-08-17T05:54:50Z Prediction Model for Tensile Modulus of Carbon Nanotube–Polymer Composites Tien,Thinh Le Minh, Vuong Le Neural Network Carbon nanotubes This work develops a Neural Network (NN) model for the prediction of the tensile modulus of carbon nanotube (CN)/polymer nanocomposites, based on experimental database. A data set composed of 282 configurations is collected from available resources. Considered input variables of the dataset are such as mechanical properties of separated phases, density of polymer matrix, processing method, geometry of CN, modification method at the CN surface, etc. while the problem output is the tensile modulus of nanocomposite. Parametric studies have been performed in finding optimum architecture of the proposed NN model. 2022-05-05T07:26:11Z 2022-05-05T07:26:11Z 2022 Bài trích https://link.springer.com/chapter/10.1007/978-3-030-92574-1_80 https://dlib.phenikaa-uni.edu.vn/handle/PNK/5715 https://doi.org/10.1007/978-3-030-92574-1_80 en Springer |
| institution |
Digital Phenikaa |
| collection |
Digital Phenikaa |
| language |
English |
| topic |
Neural Network Carbon nanotubes |
| spellingShingle |
Neural Network Carbon nanotubes Tien,Thinh Le Minh, Vuong Le Prediction Model for Tensile Modulus of Carbon Nanotube–Polymer Composites |
| description |
This work develops a Neural Network (NN) model for the prediction of the tensile modulus of carbon nanotube (CN)/polymer nanocomposites, based on experimental database. A data set composed of 282 configurations is collected from available resources. Considered input variables of the dataset are such as mechanical properties of separated phases, density of polymer matrix, processing method, geometry of CN, modification method at the CN surface, etc. while the problem output is the tensile modulus of nanocomposite. Parametric studies have been performed in finding optimum architecture of the proposed NN model. |
| format |
Bài trích |
| author |
Tien,Thinh Le Minh, Vuong Le |
| author_facet |
Tien,Thinh Le Minh, Vuong Le |
| author_sort |
Tien,Thinh Le |
| title |
Prediction Model for Tensile Modulus of Carbon Nanotube–Polymer Composites |
| title_short |
Prediction Model for Tensile Modulus of Carbon Nanotube–Polymer Composites |
| title_full |
Prediction Model for Tensile Modulus of Carbon Nanotube–Polymer Composites |
| title_fullStr |
Prediction Model for Tensile Modulus of Carbon Nanotube–Polymer Composites |
| title_full_unstemmed |
Prediction Model for Tensile Modulus of Carbon Nanotube–Polymer Composites |
| title_sort |
prediction model for tensile modulus of carbon nanotube–polymer composites |
| publisher |
Springer |
| publishDate |
2022 |
| url |
https://link.springer.com/chapter/10.1007/978-3-030-92574-1_80 https://dlib.phenikaa-uni.edu.vn/handle/PNK/5715 https://doi.org/10.1007/978-3-030-92574-1_80 |
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1751856278999662592 |
| score |
8.891145 |