Data-driven analysis and prediction of tensile behavior of coir-based composites

被引:3
|
作者
Mahajan, Aditi [1 ]
Singh, Inderdeep [1 ]
Arora, Navneet [1 ]
机构
[1] Indian Inst Technol Roorkee, Mech & Ind Engn Dept, Roorkee 247667, Uttarakhand, India
关键词
Coir composite; Polymeric composites; Mechanical properties; Machine learning; Neural network;
D O I
10.1016/j.matlet.2023.134719
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Coconut husk-derived coir fiber composites, an eco-friendly alternative to conventional polymer composites, are being considered as a viable substitute for non-structural applications. The current research endeavor aims to develop a framework for analyzing and predicting the tensile properties of short coir-based composites (SCBCs) using neural networks. The effect of parameters such as fiber treatment, fiber content, fiber aspect ratio, manufacturing process, and matrix type on the tensile properties of SCBCs has been considered. The standard performance metrics assessed the feasibility of the developed model. The coefficient of determination (R2) of 0.9661 and 0.9816 was obtained for the tensile strength and tensile modulus prediction model, respectively.
引用
收藏
页数:5
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