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Lightweight structures and designs have been widely used in a number of engineered structures due to ecological and environmental aspects. Nonetheless, lightweight structures typically experience a reduced noise and vibration reduction performance as a consequence of their increased stiffness-to-mass-ratio. To enhance it, novel low mass and compact countermeasures are often sought to address the challenges of achieving not only a good Noise, Vibrations and Harshness (NVH) reduction performance but also maintaining a lightweight design. Recently, locally resonant metamaterials have emerged and shown potential as a lightweight noise and vibration solution with a superior performance in tunable frequency ranges, known as stop bands i.e. frequency regions where free wave propagation is not allowed. These can be achieved by assembling resonant elements that are tuned to the targeted frequency range onto a host structure.

The NVH optimization of new vehicle models can in principle only be carried out in a relatively late stage of the development process, when the geometrical data (CAD) are available and can be used to generate detailed Finite Element (FE) models of the car body. Unfortunately, in this stage of the development process most of the geometrical data are already fixed and countermeasures are limited and expensive. In order to be able to evaluate design concepts in an earlier conceptual stage of the development process existing models of similar predecessor vehicles must be used leading to techniques such as “mesh-morphing” or “concept modelling” (see for instance [1, 2]). Here, a different approach is investigated based on a substructuring technique.

A large number of testing procedures have been developed to ensure vehicle safety in common and extreme driving situations. However, these conventional testing procedures are insufficient for testing autonomous vehicles. They have to handle unexpected scenarios with the same or less risk a human driver would take. Currently, safety related systems are not adequately tested, e.g. in collision avoidance scenarios with pedestrians. Examples are the change of pedestrian behaviour caused by interaction, environmental influences and personal aspects, which cannot be tested in real environments. It is proposed to use augmented reality techniques. This method can be seen as a new (Augmented) Pedestrian in the Loop testing procedure.

Maximizing the acoustic attenuation is one of the important design criteria of automotive exhaust systems. Although both analytical and numerical approaches exist to evaluate the acoustic transmission properties of exhaust systems, they are, at present, insufficient to model the full geometrical complexity and to accurately assess the influence of thermal and aerodynamic phenomena onto the acoustic attenuation characteristics. For this reason, an experimental test campaign is often still indispensable to evaluate the aeroacoustic performance of exhaust systems. One of the most commonly used experimental characterization techniques for flow duct systems is the two-port characterization.