Data-driven characterization of porous materials by using frequency-dependent measurements

The identification of the acoustical properties of materials plays a key role in the numerical prediction of the acoustic performance and the structural behavior of any mechanical system. Therefore, to obtain an accurate frequency-dependent response, it is essential a suitable choice of the parametric models for each material. However, such models could be inadequate by the material nature or not valid for a given frequency range. In this work, a novel numerical optimization strategy for the characterization of material acoustic properties is introduced, which only uses a reduced number of experimental measurements with the advantage of avoiding parametric model choices.