Localized MFS for three‐dimensional acoustic inverse problems on complicated domains

This paper proposes a semi‐analytical and local meshless collocation method, the localized method of fundamental solutions (LMFS), to address three‐dimensional (3D) acoustic inverse problems in complex domains. The proposed approach is a recently developed numerical scheme with the potential of bein...

Full description

Saved in:
Bibliographic Details
Published in:International journal of mechanical system dynamics 2022-03, Vol.2 (1), p.143-152
Main Authors: Chen, Zengtao, Wang, Fajie, Cheng, Suifu, Wu, Guozheng
Format: Article
Language:English
Subjects:
3D Helmholtz equation
acoustic inverse problems
Acoustics
Boundary conditions
Cauchy problems
Collocation methods
Computing time
Dimensional analysis
Helmholtz equations
inverse Cauchy problem
Inverse problems
Linear systems
localized method of fundamental solutions
meshless method
Nodes
Noise levels
Regularization
Singular value decomposition
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper proposes a semi‐analytical and local meshless collocation method, the localized method of fundamental solutions (LMFS), to address three‐dimensional (3D) acoustic inverse problems in complex domains. The proposed approach is a recently developed numerical scheme with the potential of being mathematically simple, numerically accurate, and requiring less computational time and storage. In  LMFS, an overdetermined sparse linear system is constructed by using the known data at the nodes on the accessible boundary and by making the remaining nodes satisfy the governing equation. In the numerical procedure, the pseudoinverse of a matrix is solved via the truncated singular value decomposition, and thus the regularization techniques are not needed in solving the resulting linear system with a well‐conditioned matrix. Numerical experiments, involving complicated geometry and the high noise level, confirm the effectiveness and performance of the LMFS for solving 3D acoustic inverse problems.
ISSN:2767-1402
2767-1399
2767-1402
DOI:10.1002/msd2.12031