The acoustic characterization of porous materials with rigid solid frame plays a key role in the prediction of the acoustic behavior of any dynamic system that incorporates them. In order to obtain an accurate prediction of its frequency-dependent response, a suitable choice of the parametric models for each material is essential. However, such models could be inadequate for a given material or only valid in a specific frequency range. In this work, a novel non-parametric methodology is proposed for the characterization of the acoustic properties of rigid porous materials. Unlike most widespread methodologies, this technique is based on the solution of a sequence of frequency-by-frequency well-posed inverse problems, thus increasing the characterization accuracy. Once a reduced number of experimental measurements is available, the proposed method avoids the a priori choice of a parametric model.
A non-parametric fluid-equivalent approach for the acoustic characterization of rigid porous materials / Carbajo, J.; Prieto, A.; Ramis, J.; Del Rio Martin, L.. - In: APPLIED MATHEMATICAL MODELLING. - ISSN 0307-904X. - 76:(2019), pp. 330-347. [10.1016/j.apm.2019.05.046]
A non-parametric fluid-equivalent approach for the acoustic characterization of rigid porous materials
L. Del Rio Martin
2019-01-01
Abstract
The acoustic characterization of porous materials with rigid solid frame plays a key role in the prediction of the acoustic behavior of any dynamic system that incorporates them. In order to obtain an accurate prediction of its frequency-dependent response, a suitable choice of the parametric models for each material is essential. However, such models could be inadequate for a given material or only valid in a specific frequency range. In this work, a novel non-parametric methodology is proposed for the characterization of the acoustic properties of rigid porous materials. Unlike most widespread methodologies, this technique is based on the solution of a sequence of frequency-by-frequency well-posed inverse problems, thus increasing the characterization accuracy. Once a reduced number of experimental measurements is available, the proposed method avoids the a priori choice of a parametric model.File | Dimensione | Formato | |
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