Prediction of Elastic modulus using Finite Element Modeling and Artificial Neural Network model in LLDPE Nanocomposite

1. Prediction of Elastic modulus using Finite Element Modeling
and Artificial Neural Network model in LLDPE
Nanocomposite
Composite Development
ASWIN S KUMAR
KTE20ME020
Roll no: 20
Department of Mechanical Engineering
KRISHNAPRASAD T S
KTE20ME040
Roll no: 40
Department of Mechanical Engineering
Rajiv Gandhi Institute of Technology, Kottayam
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Guided by Prof. Antony J K
Associate Professor

2. Table of Contents
1 REVIEW
WORK DONE SO FAR
WORKS NEED TO BE COMPLETED
2
3
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3. REVIEW
(a) our result. (b) from research paper
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Figure: Overall comparison

4. WORK DONE SO FAR
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UD COMPOSITE
• Matrix:HDPE
• Fiber:SWCNT
• Geometry Type:Square

5. WORK DONE SO FAR
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From Research Paper Analytical Results

6. WORKS NEED TO BE COMPLETED
Reference paper validation
Development of analytical database for further study
Planning to complete Artificial Neural Network Modelling by April 15 and to start
the project documentation
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7. References
I. Charitos, A. Drougkas, and E. Kontou, “Prediction of the elastic modulus of lldpe/cnt nanocomposites by
analytical modeling and finite element analysis,” Materials Today Communications, vol. 24, p. 101070, 2020.
G. Arora, H. Pathak Modeling of transversely isotropic properties of CNT-polymer composites using
meso-scale FEM approach
Compos. B Eng., 166 (2019), pp. 588-597
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