Article
  • Artificial Neural Network for Prediction of Mechanical Properties of HDPE Based Nanodiamond Nanocomposite
  • Santosh Kumar Sahu and P. S. Rama Sreekanth

  • School of Mechanical Engineering, VIT-AP University, Inavolu, Amaravati Andhra Pradesh, India 522237

  • HDPE 기반의 나노다이아몬드 복합소재의 물성 예측을 위한 인공신경망 연구
  • Reproduction, stored in a retrieval system, or transmitted in any form of any part of this publication is permitted only by written permission from the Polymer Society of Korea.

Abstract

The mechanical performance of the nanocomposite depends on the processing conditions of the samples. Therefore a predictive model is essential to proceed the combination of processing conditions into account, for accurately predicting the mechanical properties is a critical requirement in manufacturing industries. The current investigation explores the prediction of mechanical properties of high-density polyethylene (HDPE)-based nano-diamond nanocomposite (i.e., HDPE/0.1 ND) using an artificial neural network (ANN) model under various processing conditions of temperature and pressure. A 2-10-2 (2 input, 10 hidden and 2 output layer) neural network model with Levenberg–Marquardt algorithm is developed to predict Young's modulus and Hardness of HDPE/0.1 ND nanocomposite. The model accurately predicted Young's modulus and hardness with a correlation coefficient of more than 0.99. The root means square error (r.m.s) of experimental vs. predicted value is minimal, confirming the proposed ANN model's high reliability and accuracy.


Keywords: artificial neural network, mechanical properties, nanodiamond, polymer matrix nanocomposite.

  • Polymer(Korea) 폴리머
  • Frequency : Bimonthly(odd)
    ISSN 0379-153X(Print)
    ISSN 2234-8077(Online)
    Abbr. Polym. Korea
  • 2023 Impact Factor : 0.4
  • Indexed in SCIE

This Article

  • 2022; 46(5): 614-620

    Published online Sep 25, 2022

  • 10.7317/pk.2022.46.5.614
  • Received on May 2, 2022
  • Revised on Jul 1, 2022
  • Accepted on Jul 8, 2022

Correspondence to

  • Santosh Kumar Sahu and P. S. Rama Sreekanth
  • School of Mechanical Engineering, VIT-AP University, Inavolu, Amaravati Andhra Pradesh, India 522237

  • E-mail: sksahumech@gmail.com, happyshrikanth@gmail.com