基于玻璃和天然纤维的混合层压复合材料的弯曲和自由振动分析:实验和数值见解

IF 2.2 4区 工程技术 Q1 MATERIALS SCIENCE, TEXTILES
Dhaneshwar Prasad Sahu, Shivam Kumar, Mahesh Kumar Gupta
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引用次数: 0

摘要

本文研究了由玻璃纤维和不同天然纤维组成的四种不同层压复合材料的弯曲和自由振动性能。所提出的层压复合材料由四层组成,顶层和底层为玻璃纤维,中间两层为不同的天然纤维,如亚麻、红麻、abaca-剑麻和杂交菠萝。混合层压复合材料结构的制造是通过手工铺设技术完成的。层压复合材料的弹性常数是根据ISO 527-5标准在INSTRON, 5967中进行单轴拉伸试验来确定的。采用单轴拉伸试验的弹性特性,利用有限元软件ABAQUS进行了数值模拟。随后,通过三点弯曲试验研究了不同混杂层合复合材料的弯曲性能。随后,利用有限元软件ABAQUS分析了不同边界条件下纤维角度取向、纵横比、边厚比等几何参数对复合材料固有频率的影响。随后,介绍了基于人工神经网络(ANN)的预测模型的发展。所构建的模型与测试结果具有很强的一致性。使用Levenberg-Marquardt训练算法的相关系数为0.9994,表明人工神经网络模型的预测结果与实验结果之间存在显著关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Flexural and Free Vibration Analysis of Glass and Natural Fiber-Based Hybrid Laminated Composites: Experimental and Numerical Insights

The present work investigated the flexural and free vibration behavior of four different kinds of laminate composites consisting of glass fiber and different natural fiber-based. The proposed laminated composites are composed of four layers top and bottom layers are glass fibers and the middle two layers are different natural fibers, such as flax, kenaf, abaca-sisal and hybrid pineapple. The fabrication of the hybrid laminated composite structures is done via hand-layup techniques. The elastic constants of the laminated composites are determined by conducting the uniaxial tensile test in the INSTRON, 5967 as per ISO 527–5 standard. The numerical simulation is also performed using finite element (FE) software ABAQUS by adopting elastic properties from the uniaxial tensile test. Subsequently, the flexural behavior of the different hybrid laminated composites is investigated through the three-point bending test. Later, the effect of various geometric parameters, such as fiber angle orientation, aspect ratio, and side-to-thickness ratio, on the natural frequencies of the proposed hybrid laminated composites is analyzed using the finite element software ABAQUS under different boundary conditions. Subsequently, the development of the prediction model using an artificial neural network (ANN) is presented. The constructed model shows a strong alignment with the test results. A correlation of 0.9994 using the Levenberg–Marquardt training algorithm highlights a significant relationship between the predicted and the experimental outcomes of the artificial neural network model.

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来源期刊
Fibers and Polymers
Fibers and Polymers 工程技术-材料科学:纺织
CiteScore
3.90
自引率
8.00%
发文量
267
审稿时长
3.9 months
期刊介绍: -Chemistry of Fiber Materials, Polymer Reactions and Synthesis- Physical Properties of Fibers, Polymer Blends and Composites- Fiber Spinning and Textile Processing, Polymer Physics, Morphology- Colorants and Dyeing, Polymer Analysis and Characterization- Chemical Aftertreatment of Textiles, Polymer Processing and Rheology- Textile and Apparel Science, Functional Polymers
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