Modeling and optimizing an acoustic metamaterial to minimize low-frequency structure-borne sound

Daniel John Jagodzinski, Matthias Miksch, Quirin Aumann, Gerhard Müller

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Conventional noise control solutions used in the transportation industry have proven to be effective in minimizing structure-borne sound at mid to high frequencies; however, a lightweight means to control low-frequency structure-borne sound remains elusive. Recent advancements in additive manufacturing technologies have enabled researchers to develop novel acoustic metamaterial concepts capable of reducing low-frequency structure-borne sound. This work presents a methodology to numerically model and optimize an acoustic metamaterial to facilitate the development of more advanced acoustic metamaterial concepts. The investigated acoustic metamaterial consists of a periodic structure embedded with resonant inclusions that are tuned to resonate out of phase with the host structure causing an attenuation in surface vibrations. First, a numerical model of the metamaterial is created using the finite element method to generate mass and stiffness matrices for a honeycomb sandwich structure. Second, the system matrices are reduced using the Craig-Bampton Method, which are then modified to include the contribution of tuned vibration absorbers as resonant inclusions. Subsequently, the particle swarm optimization strategy is employed to optimize the mass, stiffness and damping properties of the tuned vibration absorbers to minimize the RMS surface velocity over a specified frequency range. Overall, the acoustic metamaterial exhibits a strong ability to reduce the RMS surface velocity within an optimized frequency range indicating reduced structure-borne sound emission compared to conventional honeycomb structures.

Original languageEnglish
Pages (from-to)2877-2891
Number of pages15
JournalMechanics Based Design of Structures and Machines
Volume50
Issue number8
DOIs
StatePublished - 2022

Keywords

  • Acoustic metamaterial
  • low-frequency structure-borne sound
  • model order reduction
  • particle swarm optimization
  • radiated sound power
  • tuned vibration absorber

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