| Abstract [eng] |
Lightweight high strength and durability, corrosion resistance material properties of Carbon and Glass Fiber Reinforced Polymer Composites (CFRP and GFRP) make them attractive to use and even replace metallic parts in many industries, such as aviation, wind energy, civil engineering. Fatigue life prediction of CFRP and GFRP structures is complex due to material structure (different material properties at different directions), difficulties to detect already existing damage or defect and lack of effective numerical modelling approaches. The dissertation combines Digital Image Correlation (DIC) technique as experimental method to identify defect or damage in composite structures and peridynamics with kinetic theory of fracture as numerical methods to predict defect/damage growth and fatigue life of composite structures. Due to DIC non-contact features material defects/damages are detected from unevenness in strain field measured directly on operating structure surface. Peridynamics is capable of simulating any defect/damage growth without additional techniques, unlike conventional finite element methods. The kinetic theory of fracture model, once calibrated for symmetric cyclic loading, can be applied to any different cyclic loading conditions without additional experimental tests to find the model coefficients. All of the above mentioned methods significantly improve existing fatigue life prediction approaches, resulting in a novel fatigue life prediction methodology for composites, which due to minimal experimental testing and effective modelling capabilities becomes attractive to use in various industries related to composites. |
