| Issue |
Acta Acust.
Volume 9, 2025
|
|
|---|---|---|
| Article Number | 84 | |
| Number of page(s) | 13 | |
| Section | Building Acoustics | |
| DOI | https://doi.org/10.1051/aacus/2025070 | |
| Published online | 21 January 2026 | |
Scientific Article
Prediction of rainfall noise radiated by sandwich panels using the Finite Transfer Matrix Method
Acoustics Research Unit, University of Liverpool, Liverpool, L69 7ZN, UK
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Received:
2
September
2025
Accepted:
5
December
2025
Abstract
Multilayer elements, such as sandwich panels, are often used to form the roof of a building or car; hence validated prediction models are needed to determine the sound radiated by them during rainfall. To calculate the radiation efficiency of a sandwich panel formed from two plates and a porous material, the Finite Transfer Matrix Method (FTMM) has been used with an order-reduced integral equation and an additional term to account for nearfield radiation because, in comparison with homogeneous plates, sandwich panels tend to have high damping. Transfer mobility measurements on the sandwich panel showed that vibrational energy was concentrated near the point of excitation due to the panel being highly damped, and confirmed the validity of the limp porous material model for the foam that was used as the porous material. Experimental validation of the prediction models used artificial rain with drops impacting at approximately terminal velocity. This demonstrated that it was necessary to include the effect of nearfield radiation in the overall radiation efficiency. An assessment of existing empirical and semi-empirical models for the time-dependent force applied by liquid water drops showed that for this application of artificial rain in the laboratory it was reasonable to assume a dry surface when predicting the structure-borne sound power input.
Key words: Rain noise / Sandwich panel / Transfer matrix method
© The Author(s), Published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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