Coupling of a time domain boundary element method to compliant surface models

Hargreaves, JA ORCID: https://orcid.org/0000-0003-4736-7507 and Cox, TJ ORCID: https://orcid.org/0000-0002-4075-7564 2010, Coupling of a time domain boundary element method to compliant surface models , in: EAA Euroregio Conference, 15 - 18 September 2010, Ljubljana.

[img]
Preview
PDF - Accepted Version
Download (476kB) | Preview

Abstract

The Boundary Element Method (BEM) can be used to predict the scattering of sound in rooms. It reduces the problem of modelling the volume of air to one involving only the surfaces; hence the number of unknowns scales more favourably with problem size and frequency than it does for volumetric methods such as FEM and FDTD. The time domain BEM predicts the transient scattering of sound, and is usually solved in an iterative manner by marching on in time from known initial conditions. Accurate representation of surface properties is crucial to obtain realistic simulations and the use of surface impedance is an established solution to this for frequency-domain problems. Recent research has successfully coupled digital filter representations of surface impedance to FDTD models, but the best way of achieving this for time domain BEM is currently unresolved. These authors have previously published work which coupled a time domain BEM to a surface-reflectance well model. This paper builds upon that work to couple state of the art material representations from FDTD with time domain BEM. Accuracy, efficiency and effect on algorithm stability are compared.

Item Type: Conference or Workshop Item (Lecture)
Themes: Built and Human Environment
Schools: Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre
Refereed: No
Depositing User: Dr Jonathan Hargreaves
Date Deposited: 16 Jan 2012 14:00
Last Modified: 15 Feb 2022 18:09
URI: https://usir.salford.ac.uk/id/eprint/19381

Actions (login required)

Edit record (repository staff only) Edit record (repository staff only)

Downloads

Downloads per month over past year