Metamaterials are attracting increasing interest in the field of acoustics due to their sound insulation effects. By periodically arranged structures, acoustic metamaterials can influence the way sound propagates in acoustic media. To date, the design of acoustic metamaterials relies primarily on the expertise of specialists since most effects are based on localized solutions and interference. This paper outlines a deep learning-based approach to extend current knowledge of metamaterial design in acoustics. We develop a design method by using conditional generative adversarial networks. The generative network proposes a cell candidate regarding a desired transmission behavior of the metamaterial. To validate our method, numerical simulations with the finite element method are performed. Our study reveals considerable insight into design strategies for sound insulation tasks. By providing design directives for acoustic metamaterials, cell candidates can be inspected and tailored to achieve desirable transmission characteristics.

Model order reduction techniques can be used during the operation phase of a product to generate virtual sensor outputs and enable diagnosis and monitoring systems. This contribution shows an approach with the example of an active magnetic bearing. The reduced model is used to calculate a non-measurable physical quantity (here force) and uses a measurable quantity (temperature) to check for plausibility. As a test case, the dynamic force response under the influence of varying eddy currents due to temperature changes is investigated. Using a special test rig with a 6-dof force measurement platform, the effects are shown and the simulation results are validated.

In order to perform an accurate flow-induced vibration analysis of heat exchanger tubing, natural frequencies, mode shapes, and damping values must be known. This study concerns experimental determination of the above parameters for titanium tubing in an underwater environment. Being a lightweight material with high stiffness, it was anticipated that high natural frequencies with small damping values would be encountered which could be erroneously altered by the mounting and cabling of traditional instrumentation such as accelerometers. A 1-g microaccelerometer was used to perform a preliminary modal survey to determine system natural frequencies, mode shapes, and separation of tube and fixture modes. It was found that mounted instrumentation did indeed cause mass loading problems resulting in erroneous natural frequencies and damping values. Noncontacting pressure transducers were used to confirm the identical tube mode shapes and to then determine true tube natural frequencies and damping values using a variety of excitation techniques. The study concludes by evaluating the most applicable techniques to be used in order to obtain valid data.