RESUMEN
A virtual test setup for investigating single fibres in a transverse shear flow based on a parallel-plate rheometer is presented. The investigations are carried out to verify a numerical representation of the fluid-structure interaction (FSI), where Arbitrary Lagrangian-Eulerian (ALE) and computational fluid dynamics (CFD) methods are used and evaluated. Both are suitable to simulate flexible solid structures in a transverse shear flow. Comparative investigations with different model setups and increasing complexity are presented. It is shown, that the CFD method with an interface-based coupling approach is not capable of handling small fibre diameters in comparison to large fluid domains due to mesh dependencies at the interface definitions. The ALE method is more suited for this task since fibres are embedded without any mesh restrictions. Element types beam, solid, and discrete are considered for fibre modelling. It is shown that the beam formulation for ALE and 3D solid elements for the CFD method are the preferred options.
RESUMEN
Fiber reinforced composites combine low density with high specific mechanical properties and thus became indispensable for today's lightweight applications. In particular, carbon fibre reinforced plastic (CFRP) is broadly used for aerospace components. However, damage and failure behaviour, especially for complex fibre reinforcement set-ups and under impact loading conditions, are still not fully understood yet. Therefore, relatively large margins of safety are currently used for designing high-performance materials and structures. Technologies to functionalise the materials enabling the monitoring of the structures and thus avoiding critical conditions are considered to be key to overcoming these drawbacks. For this, sensors and actuators are bonded to the surface of the composite structures or are integrated into the composite lay-up. In case of integration, the impact on the mechanical properties of the composite materials needs to be understood in detail. Additional elements may disturb the composite structure, impeding the direct connection of the composite layers and implying the risk of reducing the interlaminar integrity by means of a lower delamination resistance. In the presented study, the possibility of adjusting the interface between the integrated actuator and sensor layers to the composite layers is investigated. Different polymer layer combinations integrated into carbon fibre reinforced composite layups are compared with respect to their interlaminar critical energy release rates GIc and GIIc. A standard aerospace unidirectionally reinforced (UD) CFRP prepreg material was used as reference material configuration. The investigations show that it is possible to enhance the mechanical properties, especially the interlaminar energy release rate by using multilayered sensor-actuator layers with Polyimide (PI) outer layers and layers with low shear stiffness in between.
RESUMEN
Damage identification of composite structures is a major ongoing challenge for a secure operational life-cycle due to the complex, gradual damage behaviour of composite materials. Especially for composite rotors in aero-engines and wind-turbines, a cost-intensive maintenance service has to be performed in order to avoid critical failure. A major advantage of composite structures is that they are able to safely operate after damage initiation and under ongoing damage propagation. Therefore, a robust, efficient diagnostic damage identification method would allow monitoring the damage process with intervention occurring only when necessary. This study investigates the structural vibration response of composite rotors by applying machine learning methods and the ability to identify, localise and quantify the present damage. To this end, multiple fully connected neural networks and convolutional neural networks were trained on vibration response spectra from damaged composite rotors with barely visible damage, mostly matrix cracks and local delaminations using dimensionality reduction and data augmentation. A databank containing 720 simulated test cases with different damage states is used as a basis for the generation of multiple data sets. The trained models are tested using k-fold cross validation and they are evaluated based on the sensitivity, specificity and accuracy. Convolutional neural networks perform slightly better providing a performance accuracy of up to 99.3% for the damage localisation and quantification.
RESUMEN
The impact behavior of carbon fiber epoxy bumper brackets reinforced with 2D biaxial and 2D triaxial braids was experimentally and numerically analyzed. For this purpose, a phenomenological damage model was modified and implemented as a user material in ABAQUS. It was hypothesized that all input parameters could be determined from a suitable high-speed test program. Therefore, novel impact test device was designed, developed and integrated into a drop tower. Drop tower tests with different impactor masses and impact velocities at different bumper bracket configurations were conducted to compare the numerically predicted deformation and damage behavior with experimental evidence. Good correlations between simulations and tests were found, both for the global structural deformation, including fracture, and local damage entities in the impact zone. It was proven that the developed phenomenological damage models can be fully applied for present-day industrial problems.
