Please use this identifier to cite or link to this item: https://idr.l4.nitk.ac.in/jspui/handle/123456789/7376
Title: Application of neural network for the prediction of tensile properties of friction stir welded composites
Authors: Shettigar, A.K.
Prabhu, S.
Malghan, R.
Rao, S.
Herbert, M.
Issue Date: 2017
Citation: Materials Science Forum, 2017, Vol.880, , pp.128-131
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. � 2017 Trans Tech Publications, Switzerland.
URI: http://idr.nitk.ac.in/jspui/handle/123456789/7376
Appears in Collections:2. Conference Papers

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