Investigating Low-Rank Approximations for the Finite Element-Boundary Integral Method
(2023) 17th European Conference on Antennas and Propagation, EuCAP 2023- Abstract
This paper explores acceleration of the finite element-boundary integral hybrid method using the adaptive cross approximation. Our code implementing the hybrid method in Python based on open source packages is briefly presented. A simple one-level version of the adaptive cross approximation is described and it is used to accelerate the boundary integral matrices. We present results for scattering against a dielectric sphere with a comparison to analytical results for verification. We also present results for scattering against cylinders with varying length, where cylinders were selected as a simplification of wind turbine blades. Comparisons between a full matrix assembly and the acceleration method show that significant compression can... (More)
This paper explores acceleration of the finite element-boundary integral hybrid method using the adaptive cross approximation. Our code implementing the hybrid method in Python based on open source packages is briefly presented. A simple one-level version of the adaptive cross approximation is described and it is used to accelerate the boundary integral matrices. We present results for scattering against a dielectric sphere with a comparison to analytical results for verification. We also present results for scattering against cylinders with varying length, where cylinders were selected as a simplification of wind turbine blades. Comparisons between a full matrix assembly and the acceleration method show that significant compression can be achieved, even with a simple acceleration scheme. We also present the monostatic radar cross-section for the largest cylinder computed for multiple angles of incidence.
(Less)
- author
- Wingren, Niklas LU and Sjöberg, Daniel LU
- organization
- publishing date
- 2023
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- acceleration methods, adaptive cross approximation, computational electromagnetics, hybrid methods, open source software
- host publication
- 17th European Conference on Antennas and Propagation, EuCAP 2023
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 17th European Conference on Antennas and Propagation, EuCAP 2023
- conference location
- Florence, Italy
- conference dates
- 2023-03-26 - 2023-03-31
- external identifiers
-
- scopus:85162241513
- ISBN
- 9788831299077
- DOI
- 10.23919/EuCAP57121.2023.10133141
- language
- English
- LU publication?
- yes
- id
- 8fddcccd-5278-409a-bc84-3601228a9fe2
- date added to LUP
- 2023-10-30 10:42:32
- date last changed
- 2023-11-21 23:49:14
@inproceedings{8fddcccd-5278-409a-bc84-3601228a9fe2, abstract = {{<p>This paper explores acceleration of the finite element-boundary integral hybrid method using the adaptive cross approximation. Our code implementing the hybrid method in Python based on open source packages is briefly presented. A simple one-level version of the adaptive cross approximation is described and it is used to accelerate the boundary integral matrices. We present results for scattering against a dielectric sphere with a comparison to analytical results for verification. We also present results for scattering against cylinders with varying length, where cylinders were selected as a simplification of wind turbine blades. Comparisons between a full matrix assembly and the acceleration method show that significant compression can be achieved, even with a simple acceleration scheme. We also present the monostatic radar cross-section for the largest cylinder computed for multiple angles of incidence.</p>}}, author = {{Wingren, Niklas and Sjöberg, Daniel}}, booktitle = {{17th European Conference on Antennas and Propagation, EuCAP 2023}}, isbn = {{9788831299077}}, keywords = {{acceleration methods; adaptive cross approximation; computational electromagnetics; hybrid methods; open source software}}, language = {{eng}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Investigating Low-Rank Approximations for the Finite Element-Boundary Integral Method}}, url = {{http://dx.doi.org/10.23919/EuCAP57121.2023.10133141}}, doi = {{10.23919/EuCAP57121.2023.10133141}}, year = {{2023}}, }