Abstract
The scope of this work is to consolidate research dealing with the vibroacoustics of periodic media. This investigation aims at developing and validating tools for the design and characterization of global vibroacoustic treatments based on foam cores with embedded periodic patterns, which allow passive control of acoustic paths in layered concepts. Firstly, a numerical test campaign is carried out by considering some perfectly rigid inclusions in a 3D-modeled porous structure; this causes the excitation of additional acoustic modes due to the periodic nature of the meta-core itself. Then, through the use of the Delany–Bazley–Miki equivalent fluid model, some design guidelines are provided in order to predict several possible sets of characteristic parameters (that is unit cell dimension and foam airflow resistivity) that, constrained by the imposition of the total thickness of the acoustic package, may satisfy the target functions (namely, the frequency at which the first Transmission Loss (TL) peak appears, together with its amplitude). Furthermore, when the Johnson–Champoux–Allard model is considered, a characterization task is performed, since the meta-material description is used in order to determine its response in terms of resonance frequency and the TL increase at such a frequency. Results are obtained through the implementation of machine learning algorithms, which may constitute a good basis in order to perform preliminary design considerations that could be interesting for further generalizations.
Highlights
Present-day urbanization and traffic growth could seriously threaten human health, inducing annoyance, sleep disturbance, or even ischemic heart diseases [1], the interest on environment noise reduction is quickly growing
In order to overcome such a constraint, low frequency performance of acoustic packages can be significantly enhanced by resorting to the use of porous media with embedded periodic inclusions acting as local resonators [8,9,10]
The scope of this work is to develop and validate tools for boosting up the characterization of vibroacoustic packages based on foam cores with embedded periodic patterns through the implementation of machine learning algorithms
Summary
Present-day urbanization and traffic growth could seriously threaten human health, inducing annoyance, sleep disturbance, or even ischemic heart diseases [1], the interest on environment noise reduction is quickly growing In this context, porous media for acoustic purposes are materials made of channels, cracks, or cavities, in which sound waves pass through the foam and lose energy due to viscous and thermal effects [2,3]. In order to overcome such a constraint, low frequency performance of acoustic packages can be significantly enhanced by resorting to the use of porous media with embedded periodic inclusions acting as local resonators [8,9,10] Such a configuration represents a meta-material and provides proper dynamic filtering effects to the material, which could be beneficial for both the system dynamics and manufacturing. The periodic geometry induces wave interference with constructive and destructive effects [13], which may lead to an enhancement of sound-absorbing properties with respect to traditional materials, such as porous ones [10]
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