Adhesively bonded joints in composite materials: An overview

TLDR

A review of investigations on adhesively bonded joints in fibre‑reinforced plastic composite structures is presented. An accurate strength prediction of the adhesively bonded joints is essential to reduce expensive testing at the design stage. The study examines how surface preparation, joint configuration, adhesive properties, environmental factors, and analytical and numerical stress‑analysis methods—including linear and nonlinear models—affect bonded FRP joint behavior and failure prediction. No consensus exists on a single failure prediction method, though progressive damage models show promise, yet the absence of reliable failure criteria hampers broader use of adhesively bonded joints in load‑bearing structures.

Abstract

A review of the investigations that have been made on adhesively bonded joints of fibre-reinforced plastic (FRP) composite structures (single skin and sandwich construction) is presented. The effects of surface preparation, joint configuration, adhesive properties, and environmental factors on the joint behaviour are described briefly for adhesively bonded FRP composite structures. The analytical and numerical methods of stress analysis required before failure prediction are discussed. The numerical approaches cover both linear and non-linear models. Several methods that have been used to predict failure in bonded joints are described. There is no general agreement about the method that should be used to predict failure since the failure strength and modes are different according to the various bonding methods and parameters, but progressive damage models are quite promising since important aspects of the joint behaviour can be modelled by using this approach. However, a lack of reliable failure criteria still exists, limiting in this way a more widespread application of adhesively bonded joints in principal load-bearing structural applications. An accurate strength prediction of the adhesively bonded joints is essential to decrease the amount of expensive testing at the design stage.