Design of a Kelvin cell acoustic metamaterial. (28th April 2020)

• Record Type: Journal Article
• Authors: Rice, H.J.; Kennedy, J.; Göransson, P.; Dowling, L.; Trimble, D.
• Is Part Of: Journal of sound and vibration. Volume 472(2020)
• Publication Date: 2020-04-28
• Subjects: Acoustic metamaterial -- Noise control -- Additive manufacture -- 3D printing; Sound -- Periodicals; Vibration -- Periodicals; Son -- Périodiques; Vibration -- Périodiques; Sound; Vibration; Periodicals; Electronic journals; 620.205
• DOI: 10.1016/j.jsv.2019.115167
• Languages: English
• ISSNs: 0022-460X

Abstract

Abstract: Advancements in 3D print technology now allow the printing of structured acoustic absorptive materials at appropriate microscopic scales and sample sizes. Optimisation of parameter sets associated with a Kelvin Cell structure have the potential to develop various metabehaviours in the associated acoustic responses. The repeatability of the fundamental cell unit also provide a route for the development of viable macro models to simulate built up structures based on detailed models of the individual cell units. This paper describes a process to model, print and test such a sample. Manufacturing restraints will initially guide the optimised design and introduce response uncertainties associated with surface finishes and critical geometric dimensions. A "micro to macro" model is developed using a full visco thermal acoustic model of a single cell to develop a frequency dependent cell transfer matrix. The transfer matrices for the repeated cells may then be combined until sufficient material depth is achieved and efficiently generate an absorptivity for the material layer. Two prints using different processes (digital light processing (DLP) and selective laser melting (SLM)) of nominally the same kelvin cell structure. For the metal print the model predicts the absorptivity well once an allowance is made for the surface roughness. The DLP has a smoother finish with a lower geometric fidelity; however the DLP sample is still well modelled by the process.