Fiber-reinforced plastics (FRPs) with adaptive properties make lightweight structures feasible that not only possess a high mechanical force absorption but are also able to adapt their mechanical characteristics, such as geometry and rigidity, to external influences. Within the framework of the basic research presented here, new adaptive FRPs are developed on a basis of textile reinforcement semi-finished products integrated with actuators made from shape-memory alloys (SMAs). The realization of adaptive FRPs requires not only knowledge of the material-specific actuatory properties of the functional materials. It also necessitates the development of textile-technical solutions fully exploiting the actuatory potential of the SMAs within the composite. Promising approaches are hybrid yarn structures based on friction spinning technology. In order to reduce the great experimental effort, modeling and simulation of the SMA's material behavior and of the adaptive FRPs' complex composite behavior are carried out by means of finite element methods. It is shown that the developed actuators generate sufficiently high tensions of about 700-800 N/mm 2 , to bend the FRP specimen up to 45 .In comparison to conventional isotropic materials such as metals, lightweight constructions from fiber-reinforced plastics (FRPs) have many advantages with regards to the design of material properties. A purposeful alignment and array of the reinforcement thread layers permits the local and global suitable adjustment of strength and rigidity in the FRPs. The applicationoriented material characteristics of FRP composites enable the material and energy-efficient realization of components used in vehicle and aerospace engineering, in the field of regenerative energies, for example, as highly resilient rotor blades in wind power plants.Apart from the possibility to purposefully realize mechanical gradient properties in the reinforcement textile and the composite component by integrating functional threads, the principle of laminated layer construction of FRPs promises great potential in the functionalization of lightweight structures and components. 1-3 By integrating functional elements in the form of sensors and actuators in or between the individual reinforcement layers and the thereby realizable active functional constructions, the high performance already achieved by FRPs can be considerably increased. The integration of actuatorily operating materials allows for the execution of FRPs whose properties can be set selectively, for instance in order to
The industrial importance of fiber reinforced plastics (FRPs) is growing steadily in recent years, which are mostly used in different niche products, has been growing steadily in recent years. The integration of sensors and actuators in FRP is potentially valuable for creating innovative applications and therefore the market acceptance of adaptive FRP is increasing. In particular, in the field of highly stressed FRP, structural integrated systems for continuous component parts monitoring play an important role. This presented work focuses on the electro-mechanical characterization of adaptive three-dimensional (3D)FRP with integrated textile-based actuators.Here, the friction spun hybrid yarn, consisting of shape memory alloy (SMA) in wire form as core, serves as an actuator. Because of the shape memory effect, the SMA-hybrid yarn returns to its original shape upon heating that also causes the deformation of adaptive 3D FRP. In order to investigate the influences of the deformation behavior of the adaptive 3D FRP, investigations in this research are varied according to the structural parameters such as radius of curvature of the adaptive 3D FRP, fabric types and number of layers of the fabric in the composite. Results show that reproducible deformations can be realized with adaptive 3D FRP and that structural parameters have a significant impact on the deformation capability.
For fiber-reinforced plastic composites, fiber-matrix adhesion is a significant aspect of composite properties. While conventional lightweight structures are always aiming for high fiber-matrix adhesion, innovative and unconventional functional constructions require different concepts. The research work treating adaptive fiber-reinforced plastic composites with shape memory alloy wires presented here uses the approach of actuators freely movable within the composite. This is supposed to prevent mechanical tensions in the interfaces of actuator and composite structure, which would otherwise cause damages of the composite. This work examines hybrid yarns based on friction spinning technology, with shape memory alloy wires as their core component as well as glass fibers, and partly polypropylene, as their sheath component. Additionally, the surface properties of the shape memory alloy wires being used are modified by sanding and coating. The results of a characterization by pull-out testing clearly show that a coating of the shape memory alloy wires with an abherent causes considerable decrease in adhesion and friction in the interface and leads to the mobility of the shape memory alloy wires in the later composite. An even greater effect is attained by sheathing the hybrid yarns in an additional layer of polypropylene, compacting the yarn cross-section. Thus, the pull-out force could be reduced to 35-40% of the reference structure.
The scope of the present paper is the modeling of the mechanical behavior of textile-reinforced composites with an integrated system of wires made of shape memory alloys. A phenomenological model for the description of the material behavior of shape memory alloys is implemented in a commercial FE code. As the textile reinforcement shows periodically repeating patterns, the inner architecture of the composite can described by a representative volume element. Effective viscoelastic material parameters of the textile-reinforced composite are determined with the help of homogenization techniques. For the application of the developed composite structure as a simple actuator, numerical results are compared with experimental data.
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