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Article Dans Une Revue SIAM Journal on Numerical Analysis Année : 2022

Hybrid high-order and weak Galerkin methods for the biharmonic problem

Résumé

We devise and analyze two-hybrid high-order (HHO) methods for the numerical approximation of the biharmonic problem. The methods support polyhedral meshes, rely on the primal formulation of the problem, and deliver $O(h^{k+1})$ $H^2$-error estimates when using polynomials of order $k\ge0$ to approximate the normal derivative on the mesh (inter)faces. Both HHO methods hinge on a stabilization in the spirit of Lehrenfeld--Sch\"oberl for second-order PDEs. The cell unknowns are polynomials of order $(k+2)$ that can be eliminated locally by means of static condensation. The face unknowns approximating the trace of the solution on the mesh (inter)faces are polynomials of order $(k+1)$ in the first HHO method which is valid in dimension two and uses an original stabilization involving the canonical hybrid finite element, and they are of order $(k+2)$ for the second HHO method which is valid in arbitrary dimension and uses only $L^2$-orthogonal projections in the stabilization. A comparative discussion with the weak Galerkin methods from the literature is provided, highlighting the close connections and the improvements proposed herein. Additionally, we show how the two HHO methods can be combined with a Nitsche-like boundary-penalty technique to weakly enforce the boundary conditions. An originality in the devised Nitsche's technique is to avoid any penalty parameter that must be large enough. Finally, numerical results showcase the efficiency of the proposed methods and indicate that the HHO methods can generally outperform discontinuous Galerkin methods and even be competitive with $C^0$-interior penalty methods on triangular meshes.
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Dates et versions

hal-03185683 , version 1 (30-03-2021)
hal-03185683 , version 2 (08-04-2022)

Identifiants

Citer

Zhaonan Dong, Alexandre Ern. Hybrid high-order and weak Galerkin methods for the biharmonic problem. SIAM Journal on Numerical Analysis, 2022, 60 (5), pp.2626-2656. ⟨10.1137/21M1408555⟩. ⟨hal-03185683v2⟩
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