A hybridizable discontinuous Galerkin method for simulation of electrostatic problems with floating potential conductors
Type
ArticleKAUST Department
Computational Electromagnetics LaboratoryComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering
Electrical Engineering Program
KAUST Grant Number
2016-CRG5-2953Date
2020-09-22Preprint Posting Date
2020-05-29Submitted Date
2020-04-29Permanent link to this record
http://hdl.handle.net/10754/663704
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Show full item recordAbstract
In an electrostatic simulation, an equipotential condition with an undefined/floating potential value has to be enforced on the surface of an isolated conductor. If this conductor is charged, a nonzero charge condition is also required. While implementation of these conditions using a traditional finite element method (FEM) is not straightforward, they can be easily discretized and incorporated within a discontinuous Galerkin (DG) method. However, DG discretization results in a larger number of unknowns as compared to FEM. In this work, a hybridizable DG (HDG) method is proposed to alleviate this problem. Floating potential boundary conditions, possibly with different charge values, are introduced on surfaces of each isolated conductor and are weakly enforced in the global problem of HDG. The unknowns of the global HDG problem are those only associated with the nodes on the mesh skeleton and their number is much smaller than the total number of unknowns required by DG. Numerical examples show that the proposed method is as accurate as DG while it improves the computational efficiency significantly.Citation
Chen, L., Dong, M., Li, P., & Bagci, H. (2020). A hybridizable discontinuous Galerkin method for simulation of electrostatic problems with floating potential conductors. International Journal of Numerical Modelling: Electronic Networks, Devices and Fields. doi:10.1002/jnm.2804Sponsors
This work is supported in part by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No 2016-CRG5-2953 and in part by the National Natural Science Foundation of China under Grant 61701424. The authors would like to thank the King Abdullah University of Science and Technology Supercomputing Laboratory (KSL) for providing the required computational resources.Publisher
WileyDOI
10.1002/jnm.2804arXiv
2006.02549Additional Links
https://onlinelibrary.wiley.com/doi/10.1002/jnm.2804ae974a485f413a2113503eed53cd6c53
10.1002/jnm.2804
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