In the framework of the Cost Action CERTBOND (Reliable roadmap for certification of bonded primary structures), a wide group of researchers from 27 European Countries have had the opportunity to work on the topic of certification of bonded joints for primary structural applications from different engineering sectors such as the aerospace, automotive, civil engineering, wind energy and marine sectors. Since virtual testing and optimization are basic tools in the certification process, one of the key objectives of CERTBOND is to critically review some of the available models and failure theories for adhesive joints. The present paper summarizes the outcome of this task. Nine different models/theories are described in detail. Specifically, reviewed are the Classical Analytical Methods, the Process Zone Methods, Linear Elastic Fracture Mechanics (LEFM), the Virtual Crack Closure Technique (VCCT), the Stress Singularity Approach, Finite Fracture Mechanics (FFM), the Cohesive Zone Method (CZM), the Progressive Damage Modeling method and the Probabilistic methods. Also, at the end of the paper, the modeling of temperature effects on adhesive joints have been addressed. For each model/theory, information on the methodology, the required input, the main results, the advantages and disadvantages and the applications are given.

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Blending of biodegradable polymers in combination with low-price organic fillers has proven to be a suitable approach to produce cost-effective composites in order to address pollution issues and develop products with superior mechanical properties. In the present research work PBAT/PHB/Babassu composites with 25, 50, and 75% of each polymer and 20% of Babassu were produced by melting extrusion. Their thermal, mechanical, and morphological behavior was investigated by differential scanning calorimetry (DSC), tensile testing, and scanning electron microscopy (SEM). Blending PBAT with PHB inhibited the crystallization of both polymers whereas adding Babassu did not significantly change their melting behaviour. Incorporation of Babassu reduced the tensile strength of its respective blends between 4.8 and 32.3%, and elongation at break between 26.0 and 66.3%. PBAT as highly ductile and low crystalline polymer may be seen as a crystallization tool control for PHB as well as a plasticizer to PBAT/PHB blends and PBAT/PHB/Babassu composites. As PBAT content increases: (i) elongation at break increases and (ii) surface fracture becomes more refined indicating the presence of more energy dissipation mechanisms. As PBAT/PHB/Babassu composites are biodegradable, environmental friendly, and cost effective, products based on these compounds have a great potential since their mechanical properties such as ductility, stiffness, and tensile strength are still suitable for several applications even at lower temperatures (−40 °C).

Bisphenol F and aniline-based benzoxazine monomers were selected to fabricate basalt, glass and carbon fiber reinforced polybenzoxazine via vacuum infusion, respectively. The impacts of the type of fiber reinforcement on the resulting material properties of the fiber reinforced polymers (FRPs) were studied. FRPs exhibited a homogenous morphology with completely impregnated fibers and near-zero porosity. Carbon fiber reinforced polybenzoxazine showed the highest specific mechanical properties because of its low density and high modulus and strength. However, regarding the flammability, fire, smoke and toxicity properties, glass and basalt reinforced polybenzoxazine outperformed carbon fiber reinforced polybenzoxazine. This work offers a deeper understanding of how different types of fiber reinforcement affect polybenzoxazine-based FRPs and provides access to FRPs with inherently good fire, smoke and toxicity performance without the need for further flame retardant additives.

Since fatigue investigations are expensive and time consuming, models capable of predicting lifetime by leveraging existing experimental data are desirable.Here, this task is accomplished by combining machine learning (ML) and finite element analysis (FEA). The dataset contains 365 points comprising four adhesives with four different joint types. The model is fed with four input parameters: stress ratio and stress amplitude (functions of the applied load), and stress concentration factor and multiaxiality, which are obtained from FEA. An extremely randomized trees (ERT) algorithm, capable of dealing with small and noisy datasets, is used to design the model. After calibration, the model's performance was assessed on unseen data and compared with a linear regression model. The ERT predictions yield a significantly smaller error factor (ER) of 2.13 than that of the linear model (ER = 5.89). A relevance analysis shows that at least one FEA-based parameter must be fed into the model.

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Fatigue failure criteria for structural film adhesive joints considering multiaxiality, mean stress and temperature effects were investigated. Multiaxiality was addressed by testing butt, scarf and thick adherend shear test joints. Mean stress effect was evaluated under stress ratios of −1.0 and 0.1, and the temperature assessed at −55°C, RT and +100°C. Fatigue results were assessed using three fatigue criteria: (1) maximum principal stress, (2) linear Drucker‐Prager stress or (3) Findley's critical plane. All criteria worked well on fitting the multiaxial fatigue behaviour of joints with criteria (2) and (3) performing slightly better. However, criterion (1) is parameter‐free, which avoids data fitting. Mean stress effect was successfully described based on a Haigh transformation. Temperature effect was characterised using the criterion (1), which was capable of combining fatigue data at different temperatures. An increase of temperature led to fatigue strength reduction, meaning that a knock‐down factor approach could be used.