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Fiber-metal-laminates (FML) provide excellent fatigue behavior, damage tolerant properties, and inherent corrosion resistance.To speed up manufacturing and simultaneously increase the geometrical complexity of the produced FML parts, Mennecart et al. proposed a new single-step process combining deep-drawing with infiltration (HY-LCM). Although the first experimental results are promising, the process involves several challenges, mainly originating from the Fluid-Structure-Interaction (FSI) between deep-drawing and infiltration. This work aims to investigate those challenges to comprehend the underlying mechanisms. A new close-to-process test setup is proposed on the experimental side, combining deep-drawing of a hybrid stack with a linear infiltration. A process simulation model for FMLs is presented on the numerical side, enabling a prediction of the dry molding forces, local Fiber Volume Content (FVC) within the three glass fiber (GF) interlayers, and simultaneous fluid progression. The numerical results show that the local deformation of the hybrid stack and required forces are predictable. Furthermore, lateral sealing of the hybrid stacks leads to deviations from the intended initially one-dimensional fluid progression. Eventually, the numerical results demonstrate that most flow resistance originates from geometrically critical locations. Future experimental and numerical work will combine these insights to focus on the flow evaluation during deformation and a successful part-level application.

AbstractTo increase the use of fiber reinforced lightweight structural components in the automotive industry, their manufacturing processes have to obtain demanding economic requirements. One possibility is to use Compression Resin Transfer Molding (CRTM), which is fast and can be highly automated. One disadvantage can be the very high cavity pressure during injection. To avoid this disadvantage, a pressure-controlled RTM (PC-RTM) process was developed. PC-RTM uses a variable mold gap height and an embedded pressure sensor to control the cavity pressure actively during mold filling. In this work, we investigate this process by experiments and simulations with varying initial mold gap and controlled cavity pressure. We show that PC-RTM is a viable manufacturing process with short cycle times and high robustness. Furthermore, the simulations are validated by comparison to the experiments and show the same process characteristics.

The wet compression molding (WCM) process enables short cycle times for production of fiber-reinforced plastics due to simultaneous infiltration, viscous draping and consolidation in one process step. This requires a comprehensive knowledge of occurring mutual dependencies in particular for the development of process simulation methods and for process optimization. In this context, it is necessary to develop suitable test benches to enable an evaluation of the outlined viscous draping behavior. In order to evaluate and suitably design the draping process, grippers are mounted on a surrounding frame, which enables targeted restraining of the local material draw-in during forming. In supporting the development of the new test bench, first experimental and simulation results are compared, which thereby enables a first validation of the simulation approaches. Results show a good agreement between experimental and numerical results in terms of shear deformation and final gripper displacement under dry and viscous conditions. Results recommend that future development for investigations of viscous draping effects should focus an enabling measurement of gripper displacement during the forming process. Beyond that, the modular test bench design enables experimental and virtual draping optimization and deduction of blank holder concepts for WCM tools.

•Experiment to identify influence factors of nozzle clogging.•Identification of reasons causing clogging of sphere-filled polycarbonate.•Dimensionless number to describe intermittent clogging.•Model for the occurrence of nozzle clogging.•Mathematical viscosity model to approximate printability of materials.

Optimisation of manufacturing process parameters requires resource-intensive search in a high-dimensional parameter space. In some cases, physics-based simulations can replace actual experiments. But they are computationally expensive to evaluate. Surrogate-based optimisation uses a simplified model to guide the search for optimised parameter combinations, where the surrogate model is iteratively improved with new observations. This work applies surrogate-based optimisation to a composite textile draping process. Numerical experiments are conducted with a Finite Element (FE) simulation model. The surrogate model, a deep artificial neural network, is trained to predict the shear angle of more than 24,000 textile elements. Predicting detailed process results instead of a single performance scalar improves the model quality, as more relevant data from every experiment can be used for training. For the textile draping case, the approach is shown to reduce the number of resource-intensive FE simulations required to find optimised parameter configurations. It also improves on the best-known overall solution.

Resin Transfer Molding (RTM) enables an intrinsic manufacturing of fiber reinforced composite parts containing integrated metallic inserts. The inserts are embedded into the fiber layers in the preforming stage of the process and therefore influence the following mold filling. The fiber structure around the embedded insert is strongly influenced by the insert resulting in high local variations of fiber volume fraction which changes the local permeability. This leads to an inhomogenic flow front and can even result in dry spots of the cured part. To predict the formation of air bubbles, a two-phase mold filling simulation is used under consideration of local fiber volume fraction. Local fiber structure is determined using CT-scans of manufactured parts with different orientations of the insert in relation to the preform and to the filling direction. The mold filling simulations allow the evaluation of different filling strategies and show a strong influence of the insert on the local flow front propagation.

The resin transfer molding (RTM) offers great conditions for mass production of fiber reinforced plastics. In this process, preformed fiber textiles are infiltrated with matrix material (for example: epoxy resin). During the infiltration, the matrix material starts a curing process until the complete consolidation. After the de-molding and a short post-processing step, the final part is ready to use. To reduce the cycle time for the RTM manufacturing, it is necessary to model and predict the flow behavior of the matrix material in a realistic way. An important parameter is the preform permeability, which characterizes the flow resistance of fibers against the flowing matrix material.In this study a new measurement setup is presented, which is able to determine the permeability directly during the manufacturing process, with integrated pressure and temperature sensors. This approach has many advantages against conventional measurement setups, that try to recreate the RTM process with a simple replication. With these replicas, it is only possible to simulate low flow velocities and pressures. Dynamic effects that occur at higher velocities cannot be regarded. Furthermore, the new setup has the advantage that measurement artifacts, like capillarity, have a lower impact. In addition to that, the infiltration can be done with a constant viscosity test fluid as well as with reactive matrix material. Thus, it allows further determination of the time depending viscosity.

The entire simulation process for long fiber reinforced thermoplastics is examined to determine the effective mechanical properties which are influenced by the microstructural fiber orientation state. Therefore, flow and fiber orientation simulations are conducted and the obtained fiber orientation tensors are used in two-scale structural simulations. The fiber orientation distributions as well as the mechanical properties are compared with micro-computed tomography data and results from threepoint bending tests performed by dynamical mechanical analysis (DMA), respectively. The validated results show that prediction of the essential mechanical properties is possible with the applied combinated methods and that the knowledge of the fiber orientation and its gradients is of crucial importance for the entire simulation process.

Hybrid material systems are designed by the specific combination of different materials. As a result, expanded property profiles can be achieved, which would not be possible with monolithic material solutions. For lightweight, high strength and high rigidity, complex shaped structural components, which are used in the automotive industry and in aerospace, hybrid material systems offer an outstanding potential. A comprehensive understanding regarding the interaction of the individual components of the hybrid material is of great importance for a more efficient design of future structures. In this work, existing hybrid solutions for industrial applications and those, which are subject of current research, are analyzed and categorized first. Intrinsic and extrinsic material combinations are considered at different levels, ranging from hybrid laminates on shell level to complex hybrid structures on component level. Based on the situation analysis, different hybrid solutions are evaluated and compared considering the requirements of the automotive industry. Furthermore, the associated physical mechanisms which are responsible for the respective property profile are considered and explained systematically. The long-term objective of the work is to establish a methodology to derive the necessary physical mechanisms and, based on that, to derive optimal hybrid solutions for desired property profiles.

Traditional additive manufacturing (also known as 3D printing) of continuous carbon fiber reinforced plastic (CCFRP) lacks the ability to manufacture parts with high speed and energy efficiency. This is mainly because of the contact needed and the slow heat transfer from the conventional hotend to the composite filaments. A microwave heating assisted additive manufacturing method is here presented which allows manufacturing CCFRP with a higher speed as compared to conventional methods. The permittivity of printed specimens with different fiber volume fraction was investigated. By using the measured dielectric properties, a micro-scale microwave radiation and heat transfer model between the fiber and resin matrix has been established. The skin-core temperature difference of the moving CCFRP filaments during conventional thermal and microwave heating has been simulated to reveal the relationship between the temperature difference, filament diameter and printing speed. Non-isothermal crystallization behavior and mechanical strengths of thermal and microwave printed specimens have been studied, and the reasons for the different results have been analyzed.