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Improving and predicting the strengths of fiber-reinforced composites using a graphene-based self-healing system and finite element analysis
Patlolla, Vamsidhar Reddy
Patlolla, Vamsidhar Reddy
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dissertation
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2018-05
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Abstract
A new method for self-healing is developed by incorporating graphene nanoparticles into
the microcapsules to improve the healing efficiency after initial failure and to extend the service
life of a composite. Graphene is used for this study because of its single atomic layer structure and
excellent physical properties. The microcapsules were characterized using scanning electron
microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), Fourier transform infrared
spectroscopy (FTIR), Raman spectroscopy, differential scanning calorimetry (DSC), and dynamic
mechanical analysis (DMA) to confirm the encapsulation of nanoparticles along with the healing
agent. Finite element analysis (FEA) models for the microcapsules were developed to determine
the optimum physical characteristics of the capsules. FEA models using cohesive element
technology were also developed for the mode 1 critical energy release rate (G1C) test of the
composites. The models were validated by experimental testing results. After the first failure, the
elastic properties of self-healing microcapsules were incorporated into the model. Analysis results
suggest that 20% of the load-carrying capability can be recovered for dicyclopentadiene (DCPD)
capsules and by 42% when graphene microcapsules were used. Furthermore, four-point bend test
coupons were fabricated and tested for their interlaminar tensile (ILT) strength, the objective here
to suppress failure due to free-edge effects. This was achieved by using metal clamps, wrapping,
and self-healing methods. FEA models developed for ILT strength measurements correlated to the
mechanical test results. These models were used to simulate the performance of self-healing
capsules under four-point bending. Results suggested that 43% ILT strength could be recovered
for self-healing capsules without nanoparticles, and 79% ILT strength could be recovered for selfhealing capsules with graphene.
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Thesis (Ph.D.)-- Wichita State University, College of Engineering, Dept. of Mechanical Engineering
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Wichita State University
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Copyright 2018 by Vamisidhar Patlolla
All Rights Reserved