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

Arun Kumar Shettigar; Subramanya Prabhu; Rashmi Malghan; Shrikantha Rao; Mervin Herbert

doi:10.4028/www.scientific.net/MSF.880.128

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HomeMaterials Science ForumMaterials Science Forum Vol. 880Application of Neural Network for the Prediction...

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

Abstract:

In this paper, an attempt has been made to apply the neural network (NN) techniques to predict 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.

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4th Asia Conference on Mechanical and Materials Engineering

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Periodical:

Materials Science Forum (Volume 880)

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128-131

DOI:

https://doi.org/10.4028/www.scientific.net/MSF.880.128

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Online since:

November 2016

Authors:

Arun Kumar Shettigar*, Subramanya Prabhu, Rashmi Malghan, Shrikantha Rao, Mervin Herbert

Keywords:

Composite, Error Back Propagation, Friction Stir Welding, Neural Network

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