Tensile Strength Prediction of Fiberglass Polymer Composites Using Artificial Neural Network Model

Spanu, Paulina; Abaza, Bogdan Felician

Paulina Spanu, Bogdan Felician Abaza

Tensile Strength Prediction of Fiberglass Polymer Composites Using Artificial Neural Network Model

Abstract:
Highlighting the properties of polymer composites is a complex process given their great diversity and the wide range in which their characteristics could vary. An Artificial Neural Network model for predicting tensile strength was designed using LabVIEW software. The proposed model was developed for randomly reinforced polymeric composite materials with 30%, 40% and 50% fiber-glass. Volume fraction of glass fibre has represented the independent variable for this study. The dependence of the tensile strength on the volume fraction was investigated and highlighted by modelling using neural networks. The designed Artificial Neural Network behaves as a computational system that process data input into a desired output using a network of functions composed of layers. The training process was developed with different Artificial Neural Network architectures with two hidden layers to produce the best prediction results. For each hidden layer the number of neurons was varied be-tween 3 to 50.

Keywords:
artificial neural network; composite; LabVIEW; tensile strength

Issue: 2022 Volume 59, Issue 2

Pages: 111-118

Publication date: 2022/7/1

https://doi.org/10.37358/MP.22.2.5590

Download Pdf Article

This article is published under the Creative Commons Attribution 4.0 International License

Citation Styles

Cite this article as:
SPANU, P., ABAZA, B.F., Tensile Strength Prediction of Fiberglass Polymer Composites Using Artificial Neural Network Model, Mater. Plast., 59(2), 2022, 111-118. https://doi.org/10.37358/MP.22.2.5590

Vancouver
Spanu P, Abaza BF. Tensile Strength Prediction of Fiberglass Polymer Composites Using Artificial Neural Network Model. Mater. Plast.[internet]. 2022 Apr;59(2):111-118. Available from: https://doi.org/10.37358/MP.22.2.5590

APA 6th edition
Spanu, P., Abaza, B.F. (2022). Tensile Strength Prediction of Fiberglass Polymer Composites Using Artificial Neural Network Model. Materiale Plastice, 59(2), 111-118. https://doi.org/10.37358/MP.22.2.5590

Harvard
Spanu, P., Abaza, B.F. (2022). 'Tensile Strength Prediction of Fiberglass Polymer Composites Using Artificial Neural Network Model', Materiale Plastice, 59(2), pp. 111-118. https://doi.org/10.37358/MP.22.2.5590

IEEE
P. Spanu, B.F. Abaza, "Tensile Strength Prediction of Fiberglass Polymer Composites Using Artificial Neural Network Model". Materiale Plastice, vol. 59, no. 2, pp. 111-118, 2022. [online]. https://doi.org/10.37358/MP.22.2.5590

Text
Paulina Spanu, Bogdan Felician Abaza,
Tensile Strength Prediction of Fiberglass Polymer Composites Using Artificial Neural Network Model,
Materiale Plastice,
Volume 59, Issue 2,
2022,
Pages 111-118,
ISSN 2668-8220,
https://doi.org/10.37358/MP.22.2.5590.
(https://revmaterialeplastice.ro/Articles.asp?ID=5590)
Keywords: artificial neural network; composite; LabVIEW; tensile strength

RIS
TY - JOUR
T1 - Tensile Strength Prediction of Fiberglass Polymer Composites Using Artificial Neural Network Model
A1 - Spanu, Paulina
A2 - Abaza, Bogdan Felician
JF - Materiale Plastice
JO - Mater. Plast.
PB - Materiale Plastice SRL
SN - 2668-8220
Y1 - 2022
VL - 59
IS - 2
SP - 111
EP - 118
UR - https://doi.org/10.37358/MP.22.2.5590
KW - artificial neural network
KW - composite
KW - LabVIEW
KW - tensile strength
ER -

BibTex
@article{MatPlast2022P111,
author = {Spanu Paulina and Abaza Bogdan Felician},
title = {Tensile Strength Prediction of Fiberglass Polymer Composites Using Artificial Neural Network Model},
journal = {Materiale Plastice},
volume = {59},
number = {2},
pages = {111-118},
year = {2022},
issn = {2668-8220},
doi = {https://doi.org/10.37358/MP.22.2.5590},
url = {https://revmaterialeplastice.ro/Articles.asp?ID=5590}
}

Download article Citations: