A new approach for fatigue damage detection in adhesive joints modified with nanoparticles under different temperatures

• Published in: Fatigue & fracture of engineering materials & structures Vol. 45; no. 6; pp. 1763 - 1783
• Main Authors: Khashaba, Usama A., Najjar, Ismail M. R.
• Format: Journal Article
• Language: English
• Published: Oxford Wiley Subscription Services, Inc 01.06.2022
• Subjects: Adhesive joints; Carbon fibers; cyclic stress–strain curve; Damage detection; Damping; Dissipation factor; Energy dissipation; Fatigue failure; Fatigue limit; Fatigue strength; Fiber composites; Hysteresis loops; Nanoparticles; nano‐silicon carbide; Potential energy; Room temperature; scarf adhesive joints; stiffness degradation; Thickness
• ISSN: 8756-758X; 1460-2695
• DOI: 10.1111/ffe.13698

Scarf adhesive joints (SAJs) in carbon fiber composites were fabricated with 5° taper angle and bondline thickness of 0.17 mm. The joints are modified with SiC‐nanoparticles and characterized through tensile and fatigue loading at room temperature (RT) and 50°C. The analysis of the hysteresis loop in terms of loss and storage moduli, potential and dissipated energies, and damping factor is a quite new topic and one of the important goals of this study. At RT, the fatigue limit of the SAJs was improved by 55% when the bondline thickness decreased from 0.25 to 0.17 mm and further enhanced by 22% with SiC incorporation. For the first time, the evolution of the potential energy versus fatigue cycles of the SAJs can be modeled for early predicting joint life and hence helps in preventing their sudden failure. At 50°C, the fatigue strength of the SiC‐SAJ is approximately equal to the unmodified joint at RT. Highlights Incorporation of SiC‐nanoparticles in the adhesive layer improves the fatigue lifetime. Potential energy is a powerful tool for monitoring the damage in the adhesive joints. Bondline thickness is a determining factor for the mechanical properties of the joint. Storage modulus and potential energy can be modeled for early prediction of joint life.