Ray, Subhrajit (2009) Processing and Characterization of Titania Filled Epoxy - Glass Fiber Composites. MTech thesis.
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Abstract
The present work describes the development and characterization of a new set of hybrid polymer composites consisting of glass fibre reinforcement, epoxy resin and 
particulate fillers. The newly developed composites are characterized with respect to their mechanical and erosion wear characteristics. Experiments are carried out to study the effect of fiber content, impact velocity, impingement angle, stand-off distance and erodent size on the solid particle erosion behaviour of these glass fiber epoxy based hybrid composites. Then the significant control factors and their interactions predominantly influencing the wear rate are identified by using Taguchi method. The study reveals that the fiber content in the composites, impact velocity, impingement angle and erodent size have substantial influence in determining the rate of material loss from the composite surface due to erosion. Also, artificial neural network (ANN) technique has been use to predict the erosion rate based on the experimentally measured database of composites. The morphology of eroded surfaces is examined by using scanning electron microscopy (SEM) and possible erosion mechanisms are discussed.
particulate fillers. The newly developed composites are characterized with respect to their mechanical and erosion wear characteristics. Experiments are carried out to study the effect of fiber content, impact velocity, impingement angle, stand-off distance and erodent size on the solid particle erosion behaviour of these glass fiber epoxy based hybrid composites. Then the significant control factors and their interactions predominantly influencing the wear rate are identified by using Taguchi method. The study reveals that the fiber content in the composites, impact velocity, impingement angle and erodent size have substantial influence in determining the rate of material loss from the composite surface due to erosion. Also, artificial neural network (ANN) technique has been use to predict the erosion rate based on the experimentally measured database of composites. The morphology of eroded surfaces is examined by using scanning electron microscopy (SEM) and possible erosion mechanisms are discussed.| Item Type: | Thesis (MTech) |
|---|---|
| Uncontrolled Keywords: | epoxy, glass fiber, titania |
| Subjects: | Engineering and Technology > Metallurgical and Materials Science > Composites |
| Divisions: | Engineering and Technology > Department of Mechanical Engineering |
| ID Code: | 1349 |
| Deposited By: | Subhrajit Ray |
| Deposited On: | 22 May 2009 20:13 |
| Last Modified: | 13 Jun 2012 17:11 |
| Supervisor(s): | Biswas, S |
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