An experimental and metamodeling approach to tensile properties of natural fibers composites

Mohamad Alhijazi, Babak Safaei*, Qasim Zeeshan, Mohammed Asmael, Mohammad Harb, Zhaoye Qin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

The present work presents an analysis of the tensile properties of Palm as well as Luffa natural fiber composites (NFC) in high density polyethylene (HDPE), polypropylene (PP), Epoxy, and Ecopoxy (BioPoxy 36) matrixes, taking into consideration the effect of fibers volume fraction variation. Finite element analysis i.e. representative volume element (RVE) model with chopped random fiber orientation was utilized for predicting the elastic properties. Tensile test following ASTM D3039 standard was conducted. Artificial neural network, multiple linear regression, adaptive neuro-fuzzy inference system, and support vector machine were implemented for defining the design space upon the considered parameters and evaluating the reliability of these machine learning approaches in predicting the tensile strength of natural fibers composites. Furthermore, BioPoxy 36 with 0.3 luffa fibers exhibited the highest tensile strength. Finite element analysis (FEA) findings profusely agreed with the experimental results. ANFIS Machine Learning (ML) tool showed least prediction error in predicting tensile strength of natural fibers composites.

Original languageEnglish
Pages (from-to)4377-4393
Number of pages17
JournalJournal of Polymers and the Environment
Volume30
Issue number10
Early online date11 Jul 2022
DOIs
Publication statusPublished - 01 Oct 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Keywords

  • Finite element analysis
  • Luffa fibers
  • Machine learning
  • Palm fibers
  • Tensile properties

ASJC Scopus subject areas

  • Environmental Engineering
  • Polymers and Plastics
  • Materials Chemistry

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