JOURNAL ARTICLE
A computational micromechanical approach to predicting Young's modulus of continuous banana and palmyra fiber-reinforced epoxy composites.
Published In: International Journal of Computational Materials Science & Engineering, 2023, v. 12, n. 2. P. 1 1 of 3
Database: Applied Science & Technology Source Ultimate 2 of 3
Authored By: Bhaskar, Vennapusa Vijaya; Srinivas, Kolla; Devireddy, S. B. R. 3 of 3
Abstract
The prediction of Young's modulus properties of a hybrid composite using micromechanical models based on the geometrical characteristics and individual constituent properties of materials is a challenging task for the researchers. In this work, the micromechanical and experimental approaches are used to evaluate the hybrid effect on the Young's modulus properties of continuous banana and palmyra fiber-reinforced epoxy composites. In computational modeling, a square unit cell is employed by using ANSYS to study the effect of the fiber weight percentage and weight ratio over Young's modulus properties along the longitudinal and transverse direction. The effectiveness of the numerical predictions is evaluated by comparing with the experimental results and analytical micromechanical models (Rule of hybrid Mixture, Halpin–Tsai (HT), and Lewis and Nielsen). In the experimental approach, the hybrid composites were fabricated with the continuous banana and palmyra fibers reinforced with epoxy by varying the fiber percentages (10%, 20%, 30% and 40%) and weight ratios (1:1, 1:3, and 3:1). The micromechanical approaches show that Young's modulus of the hybrid composites is consistently increased with the fiber percentages. The longitudinal Young's modulus obtained by the Lewis and Nielsen equation gave good agreement with numerical and experimental results. On the other hand, the experimental transverse Young's modulus gave a better fit with the inverse rule of hybrid mixture as compared with other analytical model predictions. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Computational Materials Science & Engineering. 2023/06, Vol. 12, Issue 2, p1
- Document Type:Article
- Subject Area:History
- Publication Date:2023
- ISSN:20476841
- DOI:10.1142/S2047684122500233
- Accession Number:160454484
- Copyright Statement:Copyright of International Journal of Computational Materials Science & Engineering is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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