Imperial College London
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ProfessorSpencerSherwin

Faculty of Engineering, Department of Aeronautics

Head of the Department of Aeronautics
 
 
 
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Contact

 

+44 (0)20 7594 5052s.sherwin Website

 
 
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Location

 

318City and Guilds BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Yakovlev:2015:10.1007/s10915-015-0076-6,
author = {Yakovlev, S and Moxey, D and Kirby, RM and Sherwin, SJ},
doi = {10.1007/s10915-015-0076-6},
journal = {Journal of Scientific Computing},
pages = {192--220},
title = {To CG or to HDG: A Comparative Study in 3D},
url = {http://dx.doi.org/10.1007/s10915-015-0076-6},
volume = {67},
year = {2015}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Since the inception of discontinuous Galerkin (DG) methods for elliptic problems, there has existed a question of whether DG methods can be made more computationally efficient than continuous Galerkin (CG) methods. Fewer degrees of freedom, approximation properties for elliptic problems together with the number of optimization techniques, such as static condensation, available within CG framework made it challenging for DG methods to be competitive until recently. However, with the introduction of a static-condensation-amenable DG method—the hybridizable discontinuous Galerkin (HDG) method—it has become possible to perform a realistic comparison of CG and HDG methods when applied to elliptic problems. In this work, we extend upon an earlier 2D comparative study, providing numerical results and discussion of the CG and HDG method performance in three dimensions. The comparison categories covered include steady-state elliptic and time-dependent parabolic problems, various element types and serial and parallel performance. The postprocessing technique, which allows for superconvergence in the HDG case, is also discussed. Depending on the direct linear system solver used and the type of the problem (steady-state vs. time-dependent) in question the HDG method either outperforms or demonstrates a comparable performance when compared with the CG method. The HDG method however falls behind performance-wise when the iterative solver is used, which indicates the need for an effective preconditioning strategy for the method.
AU  - Yakovlev,S
AU  - Moxey,D
AU  - Kirby,RM
AU  - Sherwin,SJ
DO  - 10.1007/s10915-015-0076-6
EP  - 220
PY  - 2015///
SN  - 0885-7474
SP  - 192
TI  - To CG or to HDG: A Comparative Study in 3D
T2  - Journal of Scientific Computing
UR  - http://dx.doi.org/10.1007/s10915-015-0076-6
UR  - http://hdl.handle.net/10044/1/28889
VL  - 67
ER  -
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