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.

Due to their advantageous characteristics, shape memory alloys (SMAs) are prominent representatives in smart materials. They can be used in application fields such as soft robotics, biomimetics, and medicine. Within this work, a fiber–elastomer composite with integrated SMA wire is developed and investigated. Bending and torsion occur when the SMA is activated because of the anisotropic structure of the textile. The metrological challenge in characterizing actuators that perform both bending and torsion lies in the large active deformation of the composite and the associated difficulties in fully imaging and analyzing this with optical measurement methods. In this work, a multi-sensor camera system with up to four pairs of cameras connected in parallel is used. The structure to be characterized is recorded from all sides to evaluate the movement in three-dimensional space. The energy input and the time required for an even deflection of the actuator are investigated experimentally. Here, the activation parameters for the practical energy input required for long life with good deflection, i.e., good efficiency, were analyzed. Different parameters and times are considered to minimize the energy input and, thus, to prevent possible overheating and damage to the wire. Thermography is used to evaluate the heating of the SMA wire at different actuation times over a defined time.

The growing demand for intelligent systems with improved human-machine interactions has created an opportunity to develop adaptive bending structures. Interactive fibre rubber composites (IFRCs) are created using smart materials as actuators to obtain any desired application using fibre-reinforced elastomer. Shape memory alloys (SMAs) play a prominent role in the smart material family and are being used for various applications. Their diverse applications are intended for commercial and research purposes, and the need to model and analyse these application-based structures to achieve their maximum potential is of utmost importance. Many material models have been developed to characterise the behaviour of SMAs. However, there are very few commercially developed finite element models that can predict their behaviour. One such model is the Souza and Auricchio (SA) SMA material model incorporated in ANSYS, with the ability to solve for both shape memory effect (SME) and superelasticity (SE) but with a limitation of considering pre-stretch for irregularly shaped geometries. In order to address this gap, Woodworth and Kaliske (WK) developed a phenomenological constitutive SMA material model, offering the flexibility to apply pre-stretches for SMA wires with irregular profiles. This study investigates the WK SMA material model, utilizing deformations observed in IFRC structures as a reference and validating them against simulated models using the SA SMA material model. This validation process is crucial in ensuring the reliability and accuracy of the WK model, thus enhancing confidence in its application for predictive analysis in SMA-based systems.

Materials that can change shape in response to external parameters are becoming essential in developing future technologies in robotics, aerospace, and smart systems. This study focuses on the development of fiber-reinforced composites embedded with shape memory alloys (SMA) to enable localized bending and twisting deformations. By carefully designing the internal fiber structure and incorporating SMA wires, the composites were fabricated to deform in specific ways when activated. Multiple design variants were created to study how changes in fiber orientation, number of SMA wires and localized stiffness influence the deformation behavior. A depth-sensing camera setup with synchronized Azure Kinect devices was used to capture and analyze the resulting 3D shape changes. The obtained data facilitated the identification and tracking of specific points on the composite, enabling precise deformation measurement. The results highlight the significant impact of fiber angles and stiff sections on guiding bending and twisting behavior, contributing valuable insights toward the design of adaptive smart materials with controlled, complex deformation capabilities.

This paper investigates the deformation behavior of shape memory alloy (SMA)-integrated fiber-reinforced composites, with an emphasis on how different fiber orientations influence bend-twist coupling. The study combines experimental analysis, finite element simulations using Ansys, and analytical modeling via Classical Laminate Theory (CLT) to assess the mechanical response of these composites. The experiments revealed that composites with higher fiber angles (60°) exhibited dominant twisting behavior, while those with lower angles (30° and 45°) showed more pronounced bending deformation. The simulations corroborated these trends, offering detailed insights into the displacement behavior. The CLT model further predicted a decrease in deflection with increasing fiber angles, which was consistent with experimental results, although some deviations in Z-deformation were attributed to material and manufacturing factors. This research highlights the critical role of fiber orientation in achieving desired deformations in SMA-integrated composites, offering valuable insights for the design of adaptive structures. The findings demonstrate the potential for optimizing fiber configurations to tailor bend-twist coupling in advanced composite applications.