A mesh deformation method based on the affine transformation and skeleton transformation is proposed to reduce remesh in electromagnetic inverse problems. To balance the speed and quality of mesh generation, a novel mesh-generating procedure is proposed based on mesh quality control. A switching mechanism among affine transformation, skeleton transformation and remesh is proposed. Magnetic flux density is calculated in a superconducting magnetic energy storage system to test the proposed method. The numerical results demonstrate that the proposed method can obtain a qualified mesh in a fast manner compared with Distmesh2d and Mesh2d.
ZhaoYPXiaoXYXuW. Accelerating the optimal shape design of linear machines by transient simulation using mesh deformation and mesh connection techniques. IEEE Trans Ind Electron2018; 65: 9825–9833.
2.
ZhaoYPHoSLFuWN. A novel fast remesh-free mesh deformation method and its application to optimal design of electromagnetic devices. IEEE Trans Magn2014; 50: 1–4.
3.
HoSLZhaoYPFuWN,et al.A novel mesh morphing technique for large shape deformation and its application to optimal design problems. IEEE Trans Magn2013; 49: 2165–2168.
4.
HoSLZhaoYPFuWN. An efficient parameterized mesh method for large shape variation in optimal designs of electromagnetic devices. IEEE Trans Magn2012; 48: 4507–4510.
5.
ZhaoYPNiuSHoSL, et al.A parameterized mesh generation and refinement method for finite element parameter sweeping analysis of electromagnetic devices. IEEE Trans Magn2012; 48: 239–242.
6.
HoSLChenNNFuWN. A moving mesh embedded algorithm in finite element method for optimal design of electromagnetic devices. IEEE Trans Magn2011; 47: 2947–2950.
7.
YangLHoSLFuWN,et al.A mesh deformation algorithm and its application in optimal motor design. IEEE Trans Magn2016; 52: 1–4.
8.
YangMQKpalmaKRonsinJ. A survey of shape feature extraction techniques. Pattern Recognit2008; 15: 43–90.
9.
PerssonPOStrangG. A simple mesh generator in MATLAB. SIAM Rev2004; 46: 329–345.
10.
MaZGLiuBZhangHB. Skeleton based 3D mesh deformation. In: 2007 6th international conference on information, communications & signal processing, 2007, pp. 1–5. IEEE. http://doi.org/10.1109/ICICS.2007.4449684
11.
AlottoPBaumgartnerUFreschiF, et al.SMES Optimization benchmark extended: introducing Pareto optimal solutions into TEAM22. IEEE Trans Magn2008; 44: 1066–1069.
12.
EngwirdaD. Locally optimal Delaunay-refinement and optimisation-based mesh generation. Ph.D. thesis, the University of Sydney, http://hdl.handle.net/2123/13148 (2014).
