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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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Main Authors: Tien,Thinh Le, Minh, Vuong Le
Format: Bài trích
Language:English
Published: Springer 2022
Subjects:
Neural Network
Carbon nanotubes
Online Access: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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spelling 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
_version_ 1751856278999662592
score 8.891053

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