Numerical Characterization of Complex Materials and Vibro-Acoustic Systems

[Abstract] The acoustic characterization of materials plays an important role in a wide range of industrial applications. To get a proper acoustic characterization of a material, the knowledge of its intrinsic parameters is fundamental. However, this task is becoming increasingly difficult due to the continuous development of new materials. A classical parametric approach can be used to perform the acoustic characterization of a material. Once a model and its constitutive law are chosen, their unknown parameters are estimated by fitting the experimental data with the mechanical response of the model. The main drawback of this methodology is that the wrong choice of the parametric model can lead to get a response far from the experimental data. The main pnrpose of this dissertation is to present a non-parametric methodology to characterize acoustically different materials. This data-driven methodology allows to avoid the epistemic uncertainty of an unsuitable model selection since the mathematical modeling of the materials is based only on the available experimental measnrements. The proposed methodology requires the numerical solution of an inverse problem at each frequency of interest. To illustrate the efficiency of the methodology, numerical simulations are performed by using real-world measnrements of porous, viscoelastic, and poroelastic materials. ; [Resumen] La caracterización acústica de materiales desempeña un papel importante en un gran número de aplicaciones industriales. Para lograr una caracterización adecuada del material es fundamental conocer sus parámetros intrínsecos. Sin embargo, la aparición y desarrollo de nuevos materiales hace esa tarea cada vez más difíciL Para caracterizar un material, es posible utilizar un enfoque paramétrico clásico: una vez elegido un modelo y su ley constitutiva, se estiman sus parámetros desconocidos ajustando los datos experimentales a la respuesta mecánica del modelo considerado. El inconveniente más relevante de esta metodología es que una elección errónea del ...