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Mathematics of Computation

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Optimally accurate higher-order finite element methods for polytopial approximations of domains with smooth boundaries

Authors: James Cheung, Mauro Perego, Pavel Bochev and Max Gunzburger
Journal: Math. Comp. 88 (2019), 2187-2219
MSC (2010): Primary 65N30
Published electronically: February 21, 2019
MathSciNet review: 3957891
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Abstract: Meshing of geometric domains having curved boundaries by affine simplices produces a polytopial approximation of those domains. The resulting error in the representation of the domain limits the accuracy of finite element methods based on such meshes. On the other hand, the simplicity of affine meshes makes them a desirable modeling tool in many applications. In this paper, we develop and analyze higher-order accurate finite element methods that remain stable and optimally accurate on polytopial approximations of domains with smooth boundaries. This is achieved by constraining a judiciously chosen extension of the finite element solution on the polytopial domain to weakly match the prescribed boundary condition on the true geometric boundary. We provide numerical examples that highlight key properties of the new method and that illustrate the optimal $H^1$- and $L^2$-norm convergence rates.

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Additional Information

James Cheung
Affiliation: Interdisciplinary Center for Applied Mathematics, Virginia Tech, Blacksburg, Virginia 24061
MR Author ID: 1230885

Mauro Perego
Affiliation: Center for Computing Research, Sandia National Laboratories, Albuquerque, New Mexico 87123
MR Author ID: 869976

Pavel Bochev
Affiliation: Center for Computing Research, Sandia National Laboratories, Albuquerque, New Mexico 87123
MR Author ID: 38390

Max Gunzburger
Affiliation: Department of Scientific Computing, Florida State University, Tallahassee, Florida 32309
MR Author ID: 78360

Received by editor(s): February 8, 2018
Received by editor(s) in revised form: October 28, 2018
Published electronically: February 21, 2019
Additional Notes: Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA-0003525.
This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research. Additionally, the first and fourth authors were supported by US Department of Energy grant DE-SC0009324 and US Air Force Office of Scientific Research grant FA9550-15-1-0001.