Open Access

Impact of Fiber Orientation on the Mechanical Characteristics of Hybrid Banana Palm Amino Composites and AI-based Performance Prediction

Dipti N. Kashyap, diptikashyap222@gmail.com
Department of Mechanical Engineering, Yeshwantrao Chavan College of Engineering, Wanadongri, Nagpur, MH, India
Shrikant R. Jachak, shrikant88@gmail.com
Department of Mechanical Engineering, Yeshwantrao Chavan College of Engineering, Wanadongri, Nagpur, MH, India
Sandip S. Khedkar, ssskhedkar@ycce.edu
Department of Mechanical Engineering, Yeshwantrao Chavan College of Engineering, Wanadongri, Nagpur, MH, India
Maheskumar Ponnuswamy, ponmaheskumar@gmail.com
Department of Mechanical Engineering, Nandha College of Technology, Perundurai, Erode, TN, India
G. Suresh, gs210081976@gmail.com
Department of Mathematics, Vel Tech High Tech Dr.Rangarajan Dr.Sakunthala Engineering College, Avadi, Chennai, TN, India
R. Revathi, revathi21688@gmail.com
Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education foundation, Vaddeswaram, Guntur, AP, India
S. Mayakannan kannanarchieves@gmail.com
Department of Mechanical Engineering, Rathinam Technical Campus, Coimbatore, TN, India
Department of Mechanical Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, TN, India



J. Environ. Nanotechnol., Volume 14, No 3 (September 2025) pp. 223-233

https://doi.org/10.13074/jent.2025.09.2531645

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Abstract

This research utilized the compression technique to produce hybrid composite layers of equal amounts of Palm fiber and Banana fiber with varying fiber alignments [0/0/0/0/0/0(S1), 0/45/0/0/45/0(S2), 0/90/0/0/90/0 (S3), and +45/−45/+45/+45/−45/+45 (S4)], incorporated in amino resin matrix with TiO2 as a nanofiller. The effect of fiber direction on natural fiber composites was assessed by tensile strength (TS), flexural strength (FS), impact strength (IS), and interlaminar shear strength tests (ILSS), performed. Furthermore, a comprehensive statistical analysis was conducted using Machine Learning methods such as artificial neural networks (ANN) for predictive purposes. Composite density is greatly affected by voids and imperfections, as shown by the experimental results, in the intervals (0/45/0/0/45/0). The experimental density and void content of composite S2 were higher than those of the other composites. In comparison to other composites, composite S1 (0/0/0/0/0/0) had a 5% to 29% higher flexural load-bearing capacity, impact strength, and tensile strength. Composite S1, a fiber-oriented composite, demonstrated the highest interlaminar shear strength value of 3.35 MPa compared to other composites. Scanning electron microscope (SEM) analysis revealed a beneficial interaction between amino resin and Banana-Palm eco fibers within the composite. It accurately estimates strengths with high R2 ratings of 1, 0.98, and 0.99 for TS, FS, and IS. The interaction coefficients of the model are approximately 1, indicating strong correlative and predictive significance.

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Reference


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