Investigation of hot deformation behavior of Mg reinforced with BN nanocomposite using ANN

Authors

  • R Vara Prasad Kaviti Mechanical Engineering, Brindavan College of Engineering, Bengaluru-560063, Karnataka, India.
  • Rajashekar Patil Mechanical Engineering, Brindavan College of Engineering, Bengaluru-560063, Karnataka, India.
  • D. Jeyasimman Mechanical Engineering, Periyar Maniammai Institute of Science and Technology, Thanjavur-613403, Tamilnadu
  • Bharath V G Mechanical Engineering, Brindavan College of Engineering, Bengaluru-560063, Karnataka, India.

Keywords:

Nanocomposite, Hot deformation, (ANN) Artificial Neural Network

Abstract

The present study aims to study the hot deformation behavior of Mg reinforced with BN Nanocomposite. The hot deformation behavior of Mg reinforced with BN (1.5 wt.%) is reviewed by following ASTM standards E209, i.e., hot deformation on MTS-810 universal test apparatus. Three parameters, namely Tempertature, Strain rate and True strain, were considered in this study. The experiments for flow stress have been conducted as per ASTM standards E209. The flow stress obtained for Mg reinforced with BN (1.5 wt.%) is predicted by the ANN Toolbox of MATLAB R2021a using the Levenberg-Marquardt (trainlm) algorithm, which trains the feed-forward neural network having 3-5-1 (three input neurons, five hidden neurons in the single hidden layer and one output neuron). Experimental data sets obtained from the hot deformation test have been utilized to develop ANN. The results concluded that the error for flowstress of Mg reinforced with BN (1.5 wt.%) lies within 16%, with an average percentage error of 2.39%  between experimental values and ANN  predicted values.

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Published

18-10-2022

How to Cite

Kaviti, R. V. P., Patil, R., Jeyasimman, D., & Bharath, V. G. (2022). Investigation of hot deformation behavior of Mg reinforced with BN nanocomposite using ANN. International Journal of Health Sciences, 6(S9), 3735–3744. Retrieved from https://sciencescholar.us/journal/index.php/ijhs/article/view/13451

Issue

Vol. 6 No. S9 (2022)

Section

Peer Review Articles
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