Cover Image

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...

Full description

Saved in:
Bibliographic Details
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/5853
https://doi.org/10.1007/978-3-030-92574-1_80
Tags: Add Tag
No Tags, Be the first to tag this record!
id oai:localhost:PNK-5853
record_format dspace
spelling 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
_version_ 1751856283932164096
score 8.891053

Similar Items