Examining the bending test properties of bio-composites strengthened with fibers through a combination of experimental and modeling approaches

IF 2.3 3区材料科学 Q3 MATERIALS SCIENCE, COMPOSITES

Journal of Composite Materials Pub Date : 2024-03-16 DOI:10.1177/00219983241240819

Khalissa Saada, Chouki Farsi, Salah Amroune, Mohamed Fnides, Moussa Zaoui, Hocine Heraiz

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引用次数: 0

Abstract

This study explores the relationship between natural fiber filling density (10%, 15%, 25%) and its impact on the bending properties of polymer compounds reinforced with Diss, Sisal and Luffa fibers. Using advanced techniques like fiber analysis and Fourier transform infrared spectrometry (FTIR), the research reveals that a 25% filling density results in the highest stress values (25.61 MPa, 22.21 MPa and 20.88 MPa) for Diss, Sisal and Luffa compounds, respectively, fostering robust bonds in Diss-reinforced polymers. The Artificial Neural Network (ANN) model demonstrates superior predictive capability with correlation coefficients exceeding 0.99 for stress and displacement, outperforming Response Surface Methodology (RSM). Analysis of Variance (ANOVA) underscores the impact of sample section parameters and fiber rate on stress, establishing the significance of type parameters and fiber rate on displacement. This integration of ANN and RSM represents a paradigm shift in predicting bending mechanical properties, advancing our understanding of composite materials for innovative applications.

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通过实验和建模相结合的方法考察纤维增强生物复合材料的弯曲测试特性

本研究探讨了天然纤维填充密度（10%、15%、25%）之间的关系及其对使用屾纤维、剑麻纤维和丝瓜纤维增强的聚合物化合物弯曲性能的影响。通过使用纤维分析和傅立叶变换红外光谱仪（FTIR）等先进技术，研究发现填充密度为 25% 的屾纤维、剑麻纤维和丝瓜纤维化合物的应力值最高（分别为 25.61 兆帕、22.21 兆帕和 20.88 兆帕），从而促进了屾纤维增强聚合物的牢固结合。人工神经网络（ANN）模型显示出卓越的预测能力，应力和位移的相关系数超过 0.99，优于响应面方法（RSM）。方差分析 (ANOVA) 强调了样品截面参数和纤维率对应力的影响，并确定了类型参数和纤维率对位移的重要性。这种将 ANN 和 RSM 相结合的方法代表了预测弯曲机械性能的范式转变，推动了我们对复合材料创新应用的理解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Composite Materials 工程技术-材料科学：复合

CiteScore

5.40

自引率

6.90%

发文量

274

审稿时长

6.8 months

期刊介绍： Consistently ranked in the top 10 of the Thomson Scientific JCR, the Journal of Composite Materials publishes peer reviewed, original research papers from internationally renowned composite materials specialists from industry, universities and research organizations, featuring new advances in materials, processing, design, analysis, testing, performance and applications. This journal is a member of the Committee on Publication Ethics (COPE).