Description of the fatigue behaviour of fabric-reinforced fibre-plastic composites under combined interlaminar shear and out-of-plane compressive stress

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The goal of the project is the experimental investigation of the fatigue behaviour of fabric-reinforced polymer (FRP) composites with thermoset matrix under combined interlaminar shear and out-of-plane compressive loading. On this basis, models are to be developed which will from the founda-tion for the damage-tolerant design of FRP-components in future, taking into account the specific layer architecture and arrangement in highly stresses primary structures such as fan blades in the low-pressure section of a jet engine, profiled shafts or aircraft fuselages. In order to improve understanding, scientific research will focus on the interlaminar crack growth in dependence of a superimposed constant out-of-plane compression loading and the specific fabric architecture in the appli-cation period. Therefore, a bi-axial test method will be enhanced which was developed and tested in cooperation of the applicants. Methods for the experimental determination of fracture mechanical parameters such as delamination length and stress intensity factors are developed. Algorithms of image recognition (machine learning - computer vision) and the method of linking experiment and simulation (virtual twin) are suitable for this purpose. Assuming linear-elastic fracture mechanics, cyclic energy release rates, fracture resistance curves, crack closure functions etc. will be derived from the experimental data of the cyclic tests depending on the fabric reinforcement and the stress combination. Along with the newly developed bi-axial cyclic test method, which is performed on an Instron 8800 servo-hydraulic testing machine, standardised test methods such as DCB and ENF are used for fundamental characterization of cyclic delamination growth without the influence of out-of-plane compressive loading. In addition, improved methods of CT-analysis generate detailed knowledge about the fabric architecture/arrangement of the three pre-selected plain weave fabrics. In the developed methods of multi-scale simulation this data is used to describe the fabric-specific influence on the delamination behaviour under out-of-plane compressive stress. The results of the multi-scale approach are compared with the experimentally determined data so that factors influencing delamination growth and phenomenological phenomena such as cracks jumps in a fabric-reinforced composites can be determined and separated by correlation analysis. New analysis methods from the field of machine learning are used to combine all results. Methods from the subsections of supervised and unsupervised learning such as mathematical classification, regression or grouping models are used. The goal is to generate and provide predictive crack growth laws (e.g. Paris-Erdogan) and Wöhler curves for the damage-tolerant engineering design of fabric-reinforced composites.