Application of Neural Network for the Prediction of Tensile Properties of Friction Stir Welded Composites

Shettigar, Arun Kumar and Prabhu, Subramanya R B and Malghan, Rashmi L and Rao, Srikantha and Herbert, Mervin A (2017) Application of Neural Network for the Prediction of Tensile Properties of Friction Stir Welded Composites. Materials Science Forum, 880 (1). pp. 128-131. ISSN 1662-9752

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Abstract

In this paper, an attempt has been made to apply the neural network (NN) techniques topredict the mechanical properties of friction stir welded composite materials. Nowadays, friction stri welding of composites are predominatally used in aerospace, automobile and shipbuilding applications. The welding process parameters like rotational speed, welding speed, tool pin profile and type of material play a foremost role in determining the weld strength of the base material. An error back propagation algorithm based model is developed to map the input and output relation of friction stir welded composite material. The proposed model is able to predict the joint strength with minimum error

Item Type: Article
Uncontrolled Keywords: Neural Network, Friction Stir Welding, Composite, Error Back Propagation
Subjects: Engineering > MIT Manipal > Mechanical and Manufacturing
Depositing User: MIT Library
Date Deposited: 20 Feb 2017 13:25
Last Modified: 20 Feb 2017 13:25
URI: http://eprints.manipal.edu/id/eprint/148332

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