Novel reduction techniques for exterior vibro-acoustic models and their use in model-based sensing and identification

van Ophem, S (2019) Novel reduction techniques for exterior vibro-acoustic models and their use in model-based sensing and identification. Doctoral Thesis, 272pp.

Record type: Thesis (Doctoral)

Abstract

The physical interaction between vibrating structures and acoustics is of paramount importance in modern society. It is encountered in many products of daily use, such as vehicles, home appliances, and musical instruments but also in industrial environments, such as an assembly line in a factory. On the one hand, sound can be considered pleasant or useful in the context of music or communication. On the other hand, undesired sound, or noise, can cause health issues and is hence regarded as a problem. The physical principles behind sound waves and their mathematical description are known since a long time, but the analytical solution for problems with a moderate to high geometrical complexity is too difficult to obtain. Therefore, engineers make use of numerical computer models that approximately solve the underlying physics to predict and prevent the resulting noise from a vibrating structure. Besides the assessment of acoustic comfort, additional fields of application arise for vibro-acoustic models that are combined with physical measurements. For example, material properties and boundary conditions, or the health of a structure can be derived by doing an inverse identification. Another possibility is to combine them in a state-estimator to get an accurate prediction of the unmeasured field variables, thus to create a virtual vibro-acoustic sensor. For low-frequency noise and vibration modeling deterministic element based numerical approximation schemes, such as the finite element method, are most often used. The expectations and desires from academia and industry on what should be calculated with these models have increased throughout the years. Thus, although the available computing power is larger than before, solving such models remains a demanding task. Especially when a series of solutions is desired, for example when an optimization is performed, or when simulation results are desired in near-real time, the required time and calculation resources might be unacceptable. Therefore, this dissertation's main focus is on model order reduction techniques. Its main contributions are split into two parts. The first part is focused on the advancement of model order reduction techniques for vibro-acoustic systems to reduce the calculation complexity of these models. Specifically, the focus is on exterior vibro-acoustic problems in the time domain. Since they require the inclusion of the Sommerfeld radiation condition to correctly model the wave propagation to infinity, which is not included in the weak form of the finite element method, an additional stable boundary condition has to be introduced. Therefore, a conjugated infinite element description is chosen and it is shown how the resulting model can be reduced in size effectively with several examples. Furthermore, a parametric model order reduction scheme is derived that allows for low-rank parametric changes in the reduced order model of the second order system without sampling of the parameter space. A potential disadvantage of the shown algorithm is that it can lead to large reduced order models when an extensive set of parameters is considered. Hence, the first part concludes with the derivation of an automatic reduction algorithm for second order systems with many inputs, where the aim is to arrive at a model of acceptable size. The second part of this dissertation investigates the possibilities to use the aforementioned model order reduction techniques for efficient vibro-acoustic sensing and modeling. The effectiveness of the derived reduced order models is shown by constructing a virtual sensor that accurately estimates both the pressure and acoustic intensity of a complex radiating structure with the inclusion of only a small amount of measurements. Additionally, it is shown with an experimental setup how the derived parametric model order reduction scheme can be used for fast inverse identification of structural boundary conditions. The required reduced order model is obtained with the proposed automatic reduction algorithm. The potential of this algorithm is also assessed in a substructuring context, which could be beneficial for the modeling of unit cells, for example to evaluate the performance of metamaterials. The second part concludes by presenting a time reversed version of the conjugated infinite element description that works as an acoustic sink, which can be used in a time reversal simulation for scatterer and source identification.

This record has no associated files available for download.