The adaptation of a wing contour is important for most aircraft, because of the different flight states. That’s why an enormous number of mechanisms exists and reaches from conventional slats and flaps to morphing mechanisms, which are integrated in the wing. Especially integrated mechanisms reduce the number of gaps at the wing skin and produce less turbulent flow. However these concepts are located at a certain section of the wing. This leads to morphing and fixed wing sections, which are located next to each other. Commonly, the transition between these sections is not designed or a wing fence is used. If the transition is not designed, the wing has a step with an activated morphing mechanism and that produces additional vortices. A new skin design will be presented in order to smooth the contour between a fixed wing and a morphing wing. Here the transition between a droop nose and a fixed wing is considered. The skin material is a mix of ethylene propylene diene monomer rubber and glass-fiber reinforced plastic. The rubber is the baseline material, while the glass-fiber is added as stripes in chord-wise direction. In span-wise direction the glass fiber is connected with the rubber. The rubber carries the loads in span-wise direction and reduces the required actuation force. The glass fiber stiffens the skin locally in chord wise direction and keeps the basic contour of the skin. Some geometrical parameters within the skin layup can be varied to change the transition along the span or to reduce the maximum strain within the skin. The local strain maximum is a result of the material transition with different modules. One design of a leading edge was manufactured with an existing mold and it has a span of 200 mm. There are two essential aspects from a structural point of view. One is a nearly continuous deformation along the span and the second is the maximum strain in the rubber. Both aspects are investigated in an experiment and the results are compared with a simulation model. The results show a reliable concept and its numerical model, which will be assigned to a full scale demonstrator. This demonstrator will have a span of 1000 mm and will show the smooth skin transition between a droop nose and a fixed wing.

The technology of swarm intelligence has been applied to a mechanical vibration monitoring system composed of a network of units equipped with sensors and actuators. The expression of “swarm intelligence” was first used in 1988 in the context of cellular robotic systems, where lots of simple agents may generate self-organized patterns through mutual interactions. There are various examples of the swarm intelligence in the natural environment, a swarm of ants, birds or fish. In this sense, the network of agents in a swarm may have some kind of intelligence or higher function than those appeared in a simple agent, which is defined as the swarm intelligence. The concept of swarm intelligence may be applied in diverse engineering fields such as flexible pattern recognition, adaptive control system, or intelligent monitoring system, because some kind of intelligence may emerge on the network without any special control system. In this study, a simulation model of a five degree-of-freedom lumped mass-spring system was prepared as an example of a mechanical dynamic system. Five units composed of a displacement sensor and a variable damper as actuator were assumed to be placed on each mass of the system. Each unit was connected to each other to exchange the information of state variables measured by sensors on each unit. Because the network of units configured as a mutual connected neural network, a kind of artificial intelligence, the network of units may memorize the several expected vibration-controlled patterns and may produce the signal to the actuators on the unit to reduce the vibration of target system. The simulation results showed that the excited vibration was reduced autonomously by selecting the position where the damping should be applied.

Mechanoluminescence (ML) is a property of inorganic and organic materials that describes the emission of light due from the application of force. Inorganic crystals (mostly phosphors) and certain organic macromolecules exhibit elastico-ML and are a natural fit for structural health monitoring (SHM) of composite structures. Composites with particulate ML crystals enable the visualization of stress distribution over a plane and over contoured surfaces in a spatially continuous manner. Imaging ML composites with affordable high-resolution imaging methods further enables the creation of high-resolution validation method for computational methods. Also, with the embedding of suitable photo-detectors for signal detection, the need for additional wiring, sensor electronics and high-level electronics is eliminated. In this conference proceedings technical publication, the application of commercially available ZnS:Cu, Mn phosphors for SHM of polymer composites will be presented via experimental and structural simulation. Results demonstrate the dependence of intensity of elastico-ML (in cd/cm 2 ) on strain rate, strain and composition (w/w of ML particulates). The experiments show methods to fabricate elastic coupons of phosphors in polydimethylsiloxane (PDMS) and subsequent methods for application in SHM. The structures are excited at 5Hz to 17.5Hz to develop empirical relationships between strain rate and EML intensity and it is shown that the intensity increases nonlinearly with the magnitude of stress/strain rate. A range of stresses transferred to the EML particles by the PDMS matrix is also numerically predicted. The numerical simulations show the importance of interfacial binding in the transfer of stress and subsequent EML emission. These results also provided a basis for validation and improvement of structural simulation models.

Smart materials, such as thermal or magnetic shape memory alloys, provide interesting characteristics for new solid state actuators. However, their behavior is highly nonlinear and determined by strong hysteresis effects. This complex behavior must be adequately considered in simulation models which can be applied for efficient actuator design and optimization. We present a new phenomenological lumped element model for magnetic shape memory alloys (MSM). The model takes into account the two-dimensional hysteresis of the magnetic field induced strain as a function of both the compressive stress and the magnetic flux density. It is implemented in Modelica . The model bases on measured limiting hysteresis surfaces which are material specific. An extended Tellinen hysteresis modeling approach is used to calculate inner hysteresis trajectories in between the limiting surfaces. The developed model provides sufficient accuracy with low computational effort compared to finite element models. Thus, it is well suited for system design and optimization based on network models. This is demonstrated with exemplary models of MSM based actuators. System models and simulation results are shown and evaluated for different topologies.

This study presents a novel design of a miniature haptic actuator based on Magneto-Rheological (MR) fluids for mobile applications, and it evaluates the performance of a haptic actuator using a simulation model. The primary design goal for a haptic actuator for mobile applications is to miniaturize its size while generating realistic haptic sensations. To this end, this study proposes to design the MR actuator’s piston head (or plunger) in cone-shape and activate multiple modes of MR fluids (direct shear, flow and squeeze modes). Using a simulation model developed by integrating magnetic and force equations, the performance of a haptic actuator was evaluated in terms of the force (resistive force) produced by the actuator. The results show that a small actuator model, dimension of 10 mm (L) × 10 mm (W) × 6.5 mm (H), produced a maximum resistive force of about 5 N at 0.3 Watts, which is sufficient to provide force feedback to users.

Ground penetrating radar (GPR) is one of the most extensively used nondestructive evaluation methods with rapid development in civil engineering in the past few years for its efficiency and high resolution. The evaluation mechanism of concrete materials using GPR is generally based on the reflected signals from the rebar. According to rebar reflections, the corrosion level of the rebar and the material deteriorating condition above the rebar can be deduced. GPR has been successfully applied to shallow subsurface rebar detection in concrete structures. However, very few literatures have addressed the detectability of reflected signal from the deeper layer of rebar. As the result, only a small shallow section of the bridge deck can be evaluated by GPR data so far. In this paper, the detectability of the deeper rebar layer in concrete bridge decks using GPR is investigated with the help of data processing and image processing techniques. The GPR data collected from both a simulation model and a test slab are used to demonstrate the proposed methods and the preliminary results show the reflected signals from the second layer of rebar can be extracted using proposed methods.

In order to realize dielectric elastomer stack actuators suitable for dynamic applications a new actuator design with rigid, perforated electrodes is developed. The low surface resistance of the metal electrodes predestines this concept for dynamic applications where higher currents are present. Detailed numerical analyses are performed to show the potential of this approach, to study the complex material deformation and to optimize the aperture geometry. A multilayer stack actuator is then manufactured and characterized experimentally under various load conditions to gain suitable parameters for a parametrized model. It is subsequently used to attenuate vibrations of a truss structure. By careful adjusting the parameters it functions both as passive absober and as actuator. A comparison of experimental and simulation results proves the high quality of the simulation model. The work shows the great potential of the new design concept for future applications especially in the field of smart structures.

Smart materials have significantly varied properties and their various types are used broadly in many different engineering applications. It is important to develop tools which enable one to determine the best material for a particular application. In this research, system-level simulation models and collected material data are compiled in a GUI-based computer software called Polymers and Smart Materials Database (PSMD). This material selection tool encompasses material properties and material-level models as well as potential smart material applications. This type of compiled data can expedite the material selection process when designing smart material based systems by allowing one to choose the most effective material for the application. The software tool offers a wide variety of design and selection features. Material property and performance charts are provided to compare material properties and to choose the best material for optimal performance. The tool enables users to categorize material properties and create their own databases. This paper also highlights the modeling strategies being conducted in the area of elastomers and smart materials.