2015
DOI: 10.1007/s10915-015-0142-0
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Penalty Method for the Stationary Navier–Stokes Problems Under the Slip Boundary Condition

Abstract: We consider the penalty method for the stationary Navier-Stokes equations with the slip boundary condition. The well-posedness and the regularity theorem of the penalty problem are investigated, and we obtain the optimal error estimate O( ) in H k -norm, where is the penalty parameter. We are concerned with the finite element approximation with the P1b/P1 element to the penalty problem. The well-posedness of discrete problem is proved. We obtain the error estimate O(h + √ + h/ √ ) for the non-reduced-integrati… Show more

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Cited by 24 publications
(13 citation statements)
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“…, we obtain (with a similar argument to [23], Proof of Lemma 4.1], [24], Appendix] or [25], §2.2.2]):…”
Section: The Error and A Priori Estimates For The L 2 -Penalty Problemmentioning
confidence: 69%
“…, we obtain (with a similar argument to [23], Proof of Lemma 4.1], [24], Appendix] or [25], §2.2.2]):…”
Section: The Error and A Priori Estimates For The L 2 -Penalty Problemmentioning
confidence: 69%
“…In particular, the optimal rate of convergence O(h) was achieved by choosing ǫ = O(h 2 ) in the two-dimensional case. This strategy was then extended to the stationary Navier-Stokes equations in [20] and to the non-stationary Stokes equations in [21].…”
Section: Introductionmentioning
confidence: 99%
“…To prove the optimal error estimate, the inf-sup conditions of pressure and Lagrange multiplier have been used (cf. [4], [6], [28]). However, these arguments are not applicable to the non-stationary problem.…”
Section: Introductionmentioning
confidence: 99%
“…Now we turn our attention to the finite element approximation for the penalty problem. For the stationary Stokes/Navier-Stokes problem with the slip boundary condition, the FEM without penalty has been studied by Verfürth [25], [26], [27], Knobloch [14] and Bäncsh and Deckelnick [1], and the case of the penalty method has been investigated by Dione and Urquiza [6] and [12], [28]. The error estimates of all the above works become sub-optimal if the difference between n and n h is carefully taken into account (see Introduction of [12] for a comprehensive description of these works).…”
Section: Introductionmentioning
confidence: 99%
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