Cart (Loading....) | Create Account
Close category search window
 

Multilevel Characteristic Basis Finite-Element Method (ML-CBFEM)—An Efficient Version of a Domain Decomposition Algorithm for Large-Scale Electromagnetic Problems

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)

We introduce a memory-efficient version of the Characteristic Basis Finite-Element Method (CBFEM), which combines the domain decomposition with the use of characteristic basis functions (CBFs) that are tailored for each individual subdomain. Although the conventional CBFEM is inherently an efficient approach, the final number of unknowns is primarily determined by the size (or the number) of the subdomains. The larger the size of the subdomains, or fewer the number, the less is the final number of unknowns. However, if we employ “large” subdomains, it is more difficult to generate CBFs for each subdomain due to the memory bottleneck in utilizing direct solution techniques employed to generate the CBFs. In the proposed multilevel approach, referred to herein as the Multilevel CBFEM (ML-CBFEM), we first decompose the computational domain into several “smaller” subdomains, and generate the CBFs for each subdomain in a conventional manner. Then, these bases are combined in a multilevel fashion to derive the CBFs for larger subdomains. In each level, the CBFs are created by using the bases in the lower level. This approach, also called “nested” CBFEM, leads to a considerable reduction in the matrix size and memory, and thus, makes use of direct solvers efficiently.

Published in:

Antennas and Propagation, IEEE Transactions on  (Volume:57 ,  Issue: 10 )

Date of Publication:

Oct. 2009

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.