Research on Domain Decomposition Method Based on the FETI-DP Algorithm in EOS and MFS
The electron optics simulator (EOS) and the magnetic focusing simulator (MFS), part of the microwave tube simulator suite (MTSS), use the finite element method (FEM) to calculate electrostatic fields, electron trajectories, and magnetic fields in both 2-D and 3-D models. With the growing demand for high-precision and multiscale computations, EOS and MFS are required to handle problems with numerous meshes, leading to a sharp increase in the number of unknowns in the matrix equation. To tackle this challenge, EOS and MFS have implemented the domain decomposition method (DDM) based on the dual-primal finite element tearing and interconnecting (FETI-DP) algorithm, which is well-suited for parallel computation and is expected to enhance solving efficiency for large-scale analysis. This article presents the implementation and the computational performance of the FETI-DP algorithm in EOS and MFS. Test results show that the FETI-DP algorithm offers significant advantages in computational time in most cases. Additionally, tests demonstrate that EOS and MFS can perform parallel computing, enabling the analysis of large-scale 2-D axisymmetric electron optics systems and significantly accelerating computation speed.
Authors
- Yulu Hu (ORCID: https://orcid.org/0000-0002-9800-3300)
- Quan Hu (ORCID: https://orcid.org/0009-0000-0419-7283)
- Bin Li (ORCID: https://orcid.org/0000-0003-4397-1651)
- Xiaobing Wang (ORCID: https://orcid.org/0000-0002-0907-364X)
- Xiaofang Zhu
Institutions
- University of Electronic Science and Technology of China (CN)
- National Engineering Research Center of Electromagnetic Radiation Control Materials (CN)
Publication Details
- Journal
- IEEE Transactions on Electron Devices
- Published
- 2025-03-18
- DOI
- https://doi.org/10.1109/ted.2025.3549397
- Primary Topic
- Advanced Sensor and Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- National Science and Technology Major Project