International Journal of Applied Science and Engineering
Published by Chaoyang University of Technology

B. Sidda Reddya*, J. Suresh Kumarb, and K. Vijaya Kumar Reddyb

aSchool of Mechanical Engineering, R. G. M. College of Engineering and Technology, Nandyal, Kurnool (Dt), Andhra Pradesh, India
bDepartment of Mechanical Engineering, J. N. T. U. H. College of Engineering, J. N. T. University, Kukatpally, Hyderabad, India


 

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ABSTRACT


This paper discusses the use of D-optimal designs in the design of experiments (DOE) and artificial neural networks (ANN) in predicting the deflection and stresses of carbon fibre reinforced plastic (CFRP) square laminated composite plate subjected to uniformly distributed load. For training and testing of the ANN model, a number of finite element analyses have been carried out using D-optimal designs by varying the fibre orientations and thickness of each lamina. The composite plate is modeled using shell 99 elements. The ANN model has been developed using multilayer perceptron (MLP) backpropagation algorithm. The adequacy of the developed model is verified by root mean square error and regression coefficient. The results showed that the training algorithm of backpropagation was sufficient enough in predicting the deflection and stresses.


Keywords: D-optimal designs; finite element method; artificial neural networks; multilayer perceptron.


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ARTICLE INFORMATION


Received: 2013-01-18
Revised: 2013-03-12
Accepted: 2013-05-21
Available Online: 2013-12-01


Cite this article:

Reddy, B.S., Kumar, J.S., Reddy, K.V.K. 2013. Prediction of deflection and stresses of laminated composite plate with an artificial neural network aid. International Journal of Applied Science and Engineering, 11, 393–413. https://doi.org/10.6703/IJASE.2013.11(4).393