Debonding quantification in adhesive bonded joints by the inverse finite element method

In the past two decades, the aerospace industry has massively shifted from aluminum-made components to composite materials such as carbon fiber reinforced polymers (CFRP), striving for more fuel efficient and lighter aircrafts. Consequently, traditional joints have been replaced by adhesive bonded interfaces, which are also the most common choice to repair damaged components. Although adhesive bonding is the most efficient choice for permanent connections, it is not free of disadvantages: one of the most common failure modes, the debonding of the two laps, is very problematic to detect and predict in practice. Therefore, frequent inspections must be performed to ensure structural safety, increasing maintenance costs, and lessening the availability of the platforms. The development of innovative sensing technologies has allowed for a close monitoring of structural interfaces, and several structural health monitoring techniques have been proposed to monitor adhesive bonded connections. Sensitivity and correlation between measurements and debonding entity has been demonstrated in the literature: nevertheless, hardly any technique has been proposed and quantitively evaluated to estimate the debonding entity independently of the applied loads, such as misalignment-induced torsion, which is a major confounding influence in the traditional backface strain gauge technique. This paper proposes the inverse finite element method (iFEM) as a load and material independent approach to infer the debonding entity from strain measurements in adhesive-bonded joints. Two approaches to estimate the debonding entity with the iFEM are compared on cracked leap shear specimens representative of CFRP repair patches: one is based on anomaly indexes, the other on performing a model selection with multiple iFEM models including different damages. The latter demonstrates satisfactory performances; thus, it is considered a significant scientific advancement in this field.