{"title":"Flexural and Free Vibration Analysis of Glass and Natural Fiber-Based Hybrid Laminated Composites: Experimental and Numerical Insights","authors":"Dhaneshwar Prasad Sahu, Shivam Kumar, Mahesh Kumar Gupta","doi":"10.1007/s12221-025-00902-7","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":557,"journal":{"name":"Fibers and Polymers","volume":"26 4","pages":"1765 - 1782"},"PeriodicalIF":2.2000,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fibers and Polymers","FirstCategoryId":"88","ListUrlMain":"https://link.springer.com/article/10.1007/s12221-025-00902-7","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, TEXTILES","Score":null,"Total":0}
引用次数: 0
Abstract
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.
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