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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| Định dạng: | Bài trích |
| 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/5853 https://doi.org/10.1007/978-3-030-92574-1_80 |
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oai:localhost:PNK-58532022-08-17T05:54:52Z 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. 2022-07-13T01:59:42Z 2022-07-13T01:59:42Z 2022 Bài trích https://link.springer.com/chapter/10.1007/978-3-030-92574-1_80 https://dlib.phenikaa-uni.edu.vn/handle/PNK/5853 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/5853 https://doi.org/10.1007/978-3-030-92574-1_80 |
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1751856283932164096 |
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8.891145 |