A reduced order model including viscothermal losses

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

The Boundary Element Method (BEM) is a well-known numerical method for solving time harmonic acoustical problems. While the BEM has attractive features e.g. automatically satisfying the free field conditions, the frequency dependence of the Greens function makes is inconvenient for broadband simulations due to excessive computational costs. This problem becomes worse yet when viscous and thermal effects are included in the BE computations. Recently it has been suggested that a series expansion of the Greens function as well as its directional derivatives together with model order reduction techniques can relieve some of the computational demands. This paper applies similar ideas in the setting of the so-called boundary layer impedance boundary conditions used to approximate viscous and thermal effects. The final computational model can be used to efficiently perform broadband simulations including viscothermal losses of devices on the centimeter scale, thereby paving the path towards e.g. broadband shape optimization of small acoustical devices such as transducers, metamaterials and hearing aids.
Original languageEnglish
Title of host publicationProceedings of 24th International Congress on Acoustics
Number of pages8
Publication date2022
Publication statusPublished - 2022
Event24th International Congress on Acoustics - Hwabaek International Convention Center, Gyeongju, Korea, Republic of
Duration: 24 Oct 202228 Oct 2022
Conference number: 24
https://ica2022korea.org

Conference

Conference24th International Congress on Acoustics
Number24
LocationHwabaek International Convention Center
Country/TerritoryKorea, Republic of
CityGyeongju
Period24/10/202228/10/2022
Internet address

Keywords

  • Boundary element method
  • Viscothermal effects
  • Reduced order model

Fingerprint

Dive into the research topics of 'A reduced order model including viscothermal losses'. Together they form a unique fingerprint.

Cite this