Fiber-reinforced rubber composites with integrated shape memory alloy (SMA) actuator wires present a promising approach for the creation of soft and highly elastic structures with adaptive functionalities for usage in aerospace, robotic, or biomedical applications. In this work, the flat-knitting technology is used to develop glass-fiber-reinforced fabrics with tailored properties designed for active bending deformations. During the knitting process, the SMA wires are integrated into the textile and positioned with respect to their actuation task. Then, the fabrics are infiltrated with liquid silicone, thus creating actively deformable composites. For dimensioning such structures, a comprehensive understanding of the interactions of all components is required. Therefore, a simulation model is developed that captures the properties of the rubber matrix, fiber reinforcement, and the SMA actuators and that is capable of simulating the active bending deformations of the specimens. After model calibration with experimental four-point-bending data, the SMA-driven bending deformation is simulated. The model is validated with activation experiments of the actively deformable specimens. The simulation results show good agreement with the experimental tests, thus enabling further investigations into the deformation mechanisms of actively deformable fiber-reinforced rubbers.

Recently, there has been remarkable progress in the development of smart textiles, especially knitted strain sensors, to achieve reliable sensor signals. Stable and reliable electro-mechanical properties of sensors are essential for using textile-based sensors in medical applications. However, the challenges associated with significant hysteresis and low gauge factor (GF) values remain for using strain sensors for motion capture. To evaluate these issues, a comprehensive investigation of the cyclic electro-mechanical properties of weft-knitted strain sensors was conducted in the present study to develop a drift-free elastic strain sensor with a robust sensor signal for motion capture for medical devices. Several variables are considered in the study, including the variation of the basic knit pattern, the incorporation of the electrically conductive yarn, and the size of the strain sensor. The effectiveness and feasibility of the developed knitted strain sensors are demonstrated through an experimental evaluation, by determining the gauge factor, its nonlinearity, hysteresis, and drift. The developed knitted piezoresistive strain sensors have a GF of 2.4, a calculated drift of 50%, 12.5% hysteresis, and 0.3% nonlinearity in parts.

Shape memory alloys (SMA) are a promising material class for active lightweight structure applications with movement functionality. Due to their high activation energy potential and good processability in wire shape, they are well suited for application in actively deformable, fibre-reinforced composite structures. In order to generate large deflections from the limited deformation potential of SMA, detailed analysis of the deformation mechanisms is required. In this work, a bionic approach is pursued, investigating the characteristics of locomotion systems of insects. A simplified joint concept is derived from the cockroach knee and implemented using flat knitting technology. A composite joint is manufactured with a resin infusion process and experimentally verified in regards to its motion behaviour. The presented results show good deformation behaviour with large deformation angles up to 60°, suggesting large potential for further development of the presented approach.

Carbon fibres (CF) are used in CF reinforced plastic (CFRP) components. However, waste from CF yarn trim, CFRP and the end of life (EOL) CFRP structures will cause a recycling challenge in the next decades because of strict environmental regulations. Currently, recycling is carried out almost entirely by the use of pyrolysis to regain CF as a valuable resource. This high temperature process is energy consuming, and the resulting fibres are brittle. Hence, they are not suitable for processing of textiles into yarns or new reinforcement structures. To enable grave to cradle processing, a new approach based on a solvolysis recovery of CF and subsequent yarn spinning to obtain hybrid yarns suitable for textile processing, especially by weft knitting, was the focus of the international research project IGF/CORNET 256EBR. For the first time, it was possible to process hybrid yarns made of rCF on a weft knitting machine to produce biaxial reinforced structures to form CFRP from recycled carbon fibres. Therefore, various modifications were done on the textile machinery. In this way, it was possible to process the rCF and to get out a reproducible textile structure for the production of 3D recycled CFRP (rCFRP) parts.

Adaptive structures based on fiber-rubber composites with integrated Shape Memory Alloys are promising candidates for active deformation tasks in the fields of soft robotics and human-machine interactions. Solid-body hinges improve the deformation behavior of such composite structures. Textile technology enables the user to develop reinforcement fabrics with tailored properties suited for hinged actuation mechanisms. In this work, flat knitting technology is used to create biaxially reinforced, multilayer knitted fabrics with hinge areas and integrated Shape Memory Alloy wires. The hinge areas are achieved by dividing the structures into sections and varying the configuration and number of reinforcement fibers from section to section. The fabrics are then infused with silicone, producing a fiber-rubber composite specimen. An existing simulation model is enhanced to account for the hinges present within the specimen. The active deformation behavior of the resulting structures is then tested experimentally, showing large deformations of the hinged specimens. Finally, the simulation results are compared to the experimental results, showing deformations deviating from the experiments due to the developmental stage of the specimens. Future work will benefit from the findings by improving the deformation behavior of the specimens and enabling further development for first applications.