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Enhancing the performance of <scp>CFRP</scp> composite joints through a hybrid approach: Geometric modification (stepped adherends) and adhesive modification

N. Karthikeyan, Jesuarockiam Naveen

2025Polymer Composites12 citationsDOIOpen Access PDF

Abstract

Abstract For aerospace applications, co‐curing bonding is more effective than co‐bonding and secondary bonding for joining fuselage frames to skins, wing ribs, and spars to skin joints. This study investigated the flexural and dynamic behaviors of co‐cured carbon fiber‐reinforced polymeric (CFRP) composite joints utilizing adherend and adhesive‐modified techniques. The adherend underwent modification to incorporate a stepped geometry and adhesive modified by multi‐walled carbon nanotubes (MWNCT). The flexural strength and modulus were enhanced by 13% and 12%, respectively, when using 0.75 wt% multi‐walled carbon nanotube (MWCNT) modified adhesive in co‐cured‐CFRP joints over epoxy adhesive‐stepped adherends. In addition to that, both stepped adherend and 0.75 wt% of MWCNT adhesive in co‐cured CFRP composite joints showed a 261% enhancement in flexural strength and a 45% increase in modulus contrast to plain epoxy adhesive neat co‐cured CFRP composite joints. Interestingly, MWCNTs with a 0.75 wt% demonstrated the highest natural frequencies among all three vibration mode shapes, outperforming the pure adhesive epoxy stepped adherend co‐cured CFRP composite joint by 5%, 2%, and 8%, respectively. The results were investigated using a statistical analysis known as ANOVA. Optimization and prediction were performed utilizing a MATLAB neural net fit tool in conjunction with the Levenberg–Marquardt algorithm. Highlights Adhesive prepared using six different wt% of multi‐walled carbon nanotubes (MWCNTs) using ultrasonication. Stepped adherend carbon fiber‐reinforced polymeric (CFRP) joints were fabricated by the co‐cure method. Maximum flexural and dynamic behaviors at 0.75 wt% MWCNT in adhesive. Statistical analysis was done using a one‐way ANOVA technique. An artificial neural network predicts the flexural and dynamic behavior of CFRP composite joints.

Topics & Concepts

Materials scienceComposite materialAdhesiveEpoxyFlexural strengthComposite numberCarbon nanotubeFlexural modulusCuring (chemistry)Layer (electronics)Mechanical Behavior of CompositesSmart Materials for ConstructionStructural Behavior of Reinforced Concrete
Enhancing the performance of <scp>CFRP</scp> composite joints through a hybrid approach: Geometric modification (stepped adherends) and adhesive modification | Litcius