Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/2236
Title: Estimation of the Dynamic Properties of Epoxy Glass Fabric Composites with Natural Rubber Particle Inclusions
Authors: Sankar, H.R.
Srikant, R.R
Krishna, P.V
Rao, V.B
Babu, P.B.
Keywords: Composites;
Damping enhancement
Aartificial neural networks
Issue Date: 2013
Publisher: International Journal of Automotive and Mechanical Engineering
Citation: 10.15282/ijame.7.2012.13.0078
Abstract: Conventional materials are being replaced in the field of engineering by composite materials, due to their tailorable properties and high specific properties. These materials are extensively used in structural applications. Damping is one of the important properties of the materials used in structures, and needs to be enhanced in order to reduce structural vibrations. In the present work, the improvement of the material damping of glass fabric epoxy composites with particle rubber inclusions is studied. The effect of particle size on the damping and stiffness parameters at different frequencies and temperatures is studied experimentally. Considerable enhancement in damping without significant reduction in stiffness is observed at lower particle sizes. The damping property in both bending and shear modes is more with 0.254 mm rubber particle inclusions among the selected sizes. A lower reduction in stiffness is observed with the inclusion of lower particle sizes (0.254 mm and 0.09 mm) when compared with higher particle sizes. An ANN-based prediction model is developed to predict these properties for a given frequency/temperature and particle size. The predicted values are very close to the experimental values with an maximum error of 5%.
Description: NITW
URI: http://localhost:8080/xmlui/handle/123456789/2236
Appears in Collections:Mechanical Engineering

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