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2 DGM for elliptic problems

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38 2 Elliptic <strong>problems</strong><br />

∑<br />

∫<br />

Γ ∈F ID<br />

h<br />

Γ<br />

σ −1 (n · 〈∇e h 〉) 2 dS (2.174) AB.9<br />

≤ C HC M<br />

C W<br />

˜C(1 + CI )(1 + C A )h 2µ−2 |u| 2 H µ (Ω) .<br />

This and ( 2.168) AB.4 yield the estimate<br />

{<br />

‖e h ‖ 2 1,σ ≤ ˜C 1 + C }<br />

HC M<br />

(1 + C I )(1 + C A ) h 2µ−2 |u| 2 H<br />

C (Ω). W<br />

(2.175) AB.11<br />

It follows from ( AB.3 2.167), ( AB.4a 2.169), ( AB.6 2.171) and ( AB.11 2.175) that<br />

B h (e h ,ψ − Π h1 ψ) ≤ c 4 h µ |ψ| H 2 (Ω) |u| H µ (Ω), (2.176) AB.12<br />

{<br />

1/2<br />

where c 4 = c ˜C1/2 2 1 + C hC M<br />

C W<br />

(1 + C I )(1 + C A )}<br />

+<br />

2 ˜C(C A + CJ 2)1/2 .<br />

Finally, by ( 2.176), AB.12 ( 2.166) AB.2 and ( 2.162),<br />

A8.4<br />

exerAB1<br />

‖e h ‖ 2 L 2 (Ω) ≤ cc 4h µ |u| H µ (Ω)‖e h ‖ L 2 (Ω), (2.177) AB.13<br />

which already implies estimate ( 2.164). A8.20<br />

⊓⊔<br />

Exercise 2.34. Verify identity ( AB.1 2.165).<br />

Remark 2.35. In RWG01 [RWG01] the Neumann problem (i.e., ∂Ω = ∂Ω N ) was considered.<br />

The penalty coefficient σ was chosen according<br />

σ| Γ = C W<br />

h β , Γ ∈ F h , (2.178) A3.3a<br />

Γ<br />

insteand of ( 2.72), A3.3 where β ≥ 1/2 is a real number. If triangular grids do<br />

not contain any hanging node (i.e., T h are con<strong>for</strong>ming) then the optimal error<br />

estimation in the L 2 -norm of the NIPG method was proved provided that<br />

β ≥ 3 <strong>for</strong> d = 2 and β ≥ 3/2 <strong>for</strong> d = 3. In this case the interior penalty<br />

is so strong that DGFE methods behave likes the standard con<strong>for</strong>ming (i.e.,<br />

continuous) finite element schemes. For more details see [RWG01].<br />

RWG01<br />

sec:num_sc<br />

2.7 Numerical examples<br />

In this section, we shall justify the a priori error estimates ( 2.131), A4.1 ( 2.141) A4.32 and<br />

( 2.164). A8.20 In the first example, we assume that the exact solution is sufficiently<br />

regular. We show that the use of a higher degree of polynomial approximation<br />

increases the rate of convergence of the method. In the second example, the exact<br />

solution has a singularity. Then the order of convergence does not increase<br />

with the increasing degree of the used polynomial approximation. The computational<br />

results are in agreement with theory and show that the accuracy<br />

of the method is determined by the degree of the polynomial approximation<br />

as well the regularity of the solution.

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