On the sensitivity of the design of composite sound absorbing structures. (15th November 2021)

• Record Type: Journal Article
• Authors: Trinh, V.H.; Guilleminot, J.; Perrot, C.
• Is Part Of: Materials & design. Volume 210(2021)
• Publication Date: 2021-11-15
• Subjects: Multi-layer absorber -- Membrane -- Foam -- Sound absorption -- Perforated panel -- Optimization -- Global sensitivity -- Polynomial chaos expansions; Materials -- Periodicals; Engineering design -- Periodicals; Matériaux -- Périodiques; Conception technique -- Périodiques; Electronic journals; 620.11
• DOI: 10.1016/j.matdes.2021.110058
• Languages: English
• ISSNs: 0264-1275

Abstract

Graphical abstract: Highlights: Sound absorption can be tailored by using optimized composite panels. Global sensitivity indices are computed through Monte-Carlo and spectral approaches. Sensitivity functions are related to sound absorption resonance behaviors. Foam microstructural parameters are generally found to be the most influential ones. Abstract: The acoustic properties of composite structures made of a perforated panel, an air gap, and a porous layer, can be studied numerically by a combined use of ad hoc optimization and sensitivity analysis methods. The methodology is briefly described and is systematically applied to a series of multi-layer configurations under manufacturing constraints. We specifically consider a foam layer of constant thickness presenting three different degrees of reticulations (pore opening). For each foam layer, the optimal geometrical parameters of the perforated panel and the cavity depth maximizing sound absorption under normal incidence are determined, together with the corresponding sensitivity indices. The simulation results are found in good agreement with interpretations and experimental data provided elsewhere. From a general perspective, the framework can be used to identify the most influential parameters within multiscale settings for acoustics studies, hence enabling robust design under material and microstructural uncertainties for instance.