SIMULATION OF TRANSVERSAL FIBER BRIDGING IN FIBER REINFORCED COMPOSITE MATERIALS
This study examines the phenomenon of transverse fiber bridging in fiber-reinforced composite materials through double cantilever beam (DCB) testing. Fiber-reinforced composites have a primary weakness in crack toughness in the thickness direction, which affects the strength and stiffness of the mat...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/73670 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | This study examines the phenomenon of transverse fiber bridging in fiber-reinforced composite materials through double cantilever beam (DCB) testing. Fiber-reinforced composites have a primary weakness in crack toughness in the thickness direction, which affects the strength and stiffness of the material structure. Fiber bridging occurs when fibers form a bridge over the crack surface, enhancing the crack toughness of the composite. In this study, the cohesive zone model (CZM) is utilized to model delamination and investigate the influence of parameters such as interface properties, DCB width, fiber bridging dimensions, ply 90o thickness, and interface arrangement on transverse fiber bridging phenomena. Validation is performed by comparing simulation results with experimental data [1]. The study aims to gain a better understanding of the parameter effects on the effectiveness of fiber bridging formation in fiber-reinforced composites. In conclusion, it was found that the interface arrangement parameter exhibits the highest effectiveness in transverse fiber bridging formation. The parameters of interface property difference and fiber bridging dimensions also display significant effectiveness in bridging formation. However, the DCB width parameter shows low effectiveness due to its dependence on the interface arrangement. The ply 90o thickness parameter has the lowest level of effectiveness. Nevertheless, these findings need to be validated through direct experiments to obtain a more accurate understanding of the influence of each parameter in a realistic situation.
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