An inverse wavenumber identification tool is used to characterize the vibration behavior of three structures and meta-structures with different complexity levels: a plane steel panel, a curved thick composite sandwich shell and a stiffened aluminum aircraft sidewall panel. Bare structures are first studied and then equipped with spatially distributed small-scale resonators, leading to meta-structures. For the two curved panels, tests are conducted under diffuse acoustic field and point mechanical excitations. For each studied case, the effect of the industrially-oriented small-scale resonators is highlighted using frequency and wavenumber analysis, showing general attenuation of the vibration level and even band gaps occurrence. The complex wavenumber identification allows also estimating the structural loss factor in the composite sandwich panel, while the multi-modal behavior is captured in the aluminum aircraft sidewall panel.
The sound transmission loss of complex curved aircraft panels under diffuse acoustic field excitation is experimentally and numerically studied. Two different aircraft sidewall panels are considered: a thick composite sandwich panel and a thin aluminium panel with stiffening elements (stringers and frames). Both bare configuration and with attached soundproofing material are tested in laboratory conditions in coupled rooms. The numerical approach relies on a wave finite element method including modal order reduction at cell scale and an extension based on the transfer matrix method, for the inclusion of poroelastic treatments. The results obtained show that the proposed numerical scheme is efficient for predicting the sound transmission loss of such complex structures.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.