Experimental study on static and dynamic behavior of woven carbon fabric laminates using in-house piezoelectric sensors, acoustic emission, digital image correlation and scanning electron microscopy
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Ali, Hafiz Qasim (2019) Experimental study on static and dynamic behavior of woven carbon fabric laminates using in-house piezoelectric sensors, acoustic emission, digital image correlation and scanning electron microscopy. [Thesis]
Official URL: http://risc01.sabanciuniv.edu/record=b2297080 (Table of contents)
This study focuses on dynamic and static failure analysis of carbon fabric reinforced polymeric composite materials. The first part signifies the production of Piezoelectric Polyvinylidene fluoride (PVDF) nanofibers-based sensor for structural health monitoring of composites. Results obtained from the characterization of electrospun PVDF nanofibers confirm that electrospinning promotes the formation of β-phase. Dynamic flexural tests are performed on woven carbon fabric composites with embedded and surface mounted PVDF sensors to study the capability of these sensors to record strain history and damage progression in composite materials. Moreover, these PVDF sensors are able to capture three distinct stages of fatigue life of composite specimen. This result is validated by the strain measurement with the video extensometer during tests. It is important to emphasize that surface mounted PVDF sensors do not show any sign of malfunctioning during the test. SEM analysis of fractured surfaces of composite specimens shows vivid delamination and fiber pullouts through the thickness, thus indicating gradual growth of damage in laminates. The second part of this study is related to static failure analysis of woven fabric carbon reinforced polymeric composites under tensile and flexural loading. To conduct a detailed investigation Acoustic Emission (AE) is used to attain damage evolution under flexural loading conditions. For the first time GAP function has been suggested to find out the optimal number of clusters for AE data, the advantage of this function is its suitability for classifying elongated data points in vectoral space of acoustic data. Three clusters of data are determined with this new approach indicating various failure types in composite laminates and it is shown that simultaneous occurrence of all failures results in a major change of material stiffness. These failures are also substantiated by Scanning Electron Microscope (SEM) studies of fracture surfaces. Further studies on tensile behavior of the same laminates are conducted with the help of SEM micrographs and 3D-digital image correlation (DIC) technique. Remarkably, it is seen that presence of the shear and transverse strain fields at the surface of the tensile specimen obtained through DIC technique can be correlated to shear dominant and high energy failure (interlaminar delamination and fiber pull outs) respectively, which are also confirmed by SEM images of same fracture regions.
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