Métodos de elementos finitos mixtos para problemas no ... PDFs/Duran...Title Métodos de elementos...
Transcript of Métodos de elementos finitos mixtos para problemas no ... PDFs/Duran...Title Métodos de elementos...
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Métodos de elementos finitos mixtos paraproblemas no uniformemente elípticos
Ricardo G. Durán
Departamento de MatemáticaFacultad de Ciencias Exactas y Naturales
Universidad de Buenos AiresIMAS, UBA-CONICET
IMAL, Santa FeSeptember 2, 2016
R. G. Durán Métodos mixtos para problemas degenerados
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SUMMARY
Anisotropic error estimates for mixed methods: review ofseveral arguments.
Degenerate elliptic problems.
Weighted Poincaré type inequalities.
Weighted error estimates for the Raviart-Thomasinterpolation.
Application to the Fractional Laplacian.
R. G. Durán Métodos mixtos para problemas degenerados
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SUMMARY
Anisotropic error estimates for mixed methods: review ofseveral arguments.
Degenerate elliptic problems.
Weighted Poincaré type inequalities.
Weighted error estimates for the Raviart-Thomasinterpolation.
Application to the Fractional Laplacian.
R. G. Durán Métodos mixtos para problemas degenerados
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SUMMARY
Anisotropic error estimates for mixed methods: review ofseveral arguments.
Degenerate elliptic problems.
Weighted Poincaré type inequalities.
Weighted error estimates for the Raviart-Thomasinterpolation.
Application to the Fractional Laplacian.
R. G. Durán Métodos mixtos para problemas degenerados
![Page 5: Métodos de elementos finitos mixtos para problemas no ... PDFs/Duran...Title Métodos de elementos finitos mixtos para problemas no uniformemente elípticos Author Ricardo G. Durán](https://reader036.fdocumentos.tips/reader036/viewer/2022081400/607a011d28dc4a58853c74e6/html5/thumbnails/5.jpg)
SUMMARY
Anisotropic error estimates for mixed methods: review ofseveral arguments.
Degenerate elliptic problems.
Weighted Poincaré type inequalities.
Weighted error estimates for the Raviart-Thomasinterpolation.
Application to the Fractional Laplacian.
R. G. Durán Métodos mixtos para problemas degenerados
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SUMMARY
Anisotropic error estimates for mixed methods: review ofseveral arguments.
Degenerate elliptic problems.
Weighted Poincaré type inequalities.
Weighted error estimates for the Raviart-Thomasinterpolation.
Application to the Fractional Laplacian.
R. G. Durán Métodos mixtos para problemas degenerados
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RAVIART-THOMAS SPACES ON TRIANGLES
For k = 0,1,2, · · ·
RT k (T ) = P2k (T )⊕ (x , y)Pk (T )
and its extension to tetrahedra (Nedelec),
RT k (T ) = P3k (T )⊕ (x , y , z)Pk (T )
R. G. Durán Métodos mixtos para problemas degenerados
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RAVIART-THOMAS INTERPOLATION
RTk : H1(T )n → RT k (T )
Face (or edge if n = 2 ) degrees of freedom:∫Fi
RTkσ · ni pk ds =
∫Fi
σ · ni pk ds ∀pk ∈ Pk (Fi)
Internal degrees of freedom (for k ≥ 1)∫T
RTkσ · pk−1 dx =
∫Tσ · pk−1 dx ∀pk−1 ∈ Pn
k−1(T )
R. G. Durán Métodos mixtos para problemas degenerados
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FUNDAMENTAL PROPERTY
∫T
div (σ − RTkσ) q = 0 ∀q ∈ Pk (T )
i.e.,div RTkσ = Pkdiv σ
wherePk : L2(T )→ Pk
is the L2-orthogonal projection.
R. G. Durán Métodos mixtos para problemas degenerados
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REGULARITY ASSUMPTION
Raviart-Thomas (1975), Nedelec (1980)
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REGULARITY ASSUMPTION
hT exterior diameter, ρT interior diameter
hT
ρT≤ γ
The constant in the error estimates depends on the regularityparameter γ
R. G. Durán Métodos mixtos para problemas degenerados
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CLASSIC ERROR ANALYSIS
STANDARD ARGUMENTS
FhT hTˆ
ρT ρ
Tˆ
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CLASSIC ERROR ANALYSIS
T reference element F : T → T affine transformation
The Piola transform preserves the degrees of freedom!
σ(x) =1
|det DF (x)|DF (x)σ(x)
where x = F (x).
RTkσ = RTk σ
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ERROR ESTIMATES
Polynomial approximation + Piola transform⇒
‖σ − RTkσ‖L2(T ) ≤ C(γ) hmT ‖Dmσ‖L2(T )
1 ≤ m ≤ k + 1
R. G. Durán Métodos mixtos para problemas degenerados
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ESTIMATES UNDER WEAKER CONDITIONS
In the case of standard Lagrange interpolation it is known thatthe regularity condition can be relaxedBabuska-Aziz, Jamet, Krizek, Al Shenk, Dobrowolski, Apel,Nicaise, Formaggia, Perotto, Acosta, Lombardi, D., etc..
Is it possible to relax the regularity condition for RTinterpolation?
YES!
We developed several arguments to obtain estimates in 2 and 3dimensions.
R. G. Durán Métodos mixtos para problemas degenerados
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CASE k = 0 , n = 2
We work in a family of reference elements and use the Piolatransform associated with
F : T → T
F (x) = Mx + b
with
‖M‖, ‖M−1‖ ≤ C
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CASE k = 0 , n = 2
R. G. Durán Métodos mixtos para problemas degenerados
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CASE k = 0 , n = 2
REMARK:
In this way we obtain from the reference family the family of allelements with maximum angle α satisfying α < ψ(C) < π
MAXIMUM ANGLE CONDITION
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CASE k = 0 , n = 2
From the definition of RT0 on the reference element
∫`i
(σ − RT0σ) · νi = 0 ∀`i edge of T
Then, if `i is the edge with normal ei,∫`1
(σ − RT0σ)2 = 0
and ∫`2
(σ − RT0σ)1 = 0
R. G. Durán Métodos mixtos para problemas degenerados
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CASE k = 0 , n = 2
We use the Poincaré type inequality on
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CASE k = 0 , n = 2
∫`v = 0 =⇒
‖v‖L2(T )≤ C
h1
∥∥∥∥∂v∂x
∥∥∥∥L2(T )
+ h2
∥∥∥∥∂v∂y
∥∥∥∥L2(T )
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CASE k = 0 , n = 2
Taking
v = (σ − RT0σ)i
we obtain
‖(σ − RT0σ)i‖L2(T )≤C
h1
∥∥∥∥∂(σ − RT0σ)i
∂x
∥∥∥∥L2(T )
+h2
∥∥∥∥∂(σ − RT0σ)i
∂y
∥∥∥∥L2(T )
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CASE k = 0 , n = 2
We have to eliminate the dependence on RT0σ from the righthand side
But,∂(RT0σ)1
∂x=∂(RT0σ)2
∂y=
div RT0σ
2
and∂(RT0σ)1
∂y=∂(RT0σ)2
∂x= 0
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CASE k = 0 , n = 2
but, from the commutative diagram property:
div RT0σ = P0divσ
and therefore,
‖div RT0σ‖L2(T )≤ ‖divσ‖L2(T )
Then,
‖σ − RT0σ‖L2(T )
≤ C
h1
∥∥∥∂σ∂x
∥∥∥L2(T )
+ h2
∥∥∥∂σ∂y
∥∥∥L2(T )
+ (h1 + h2)‖divσ‖L2(T )
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CASE k = 0 , n = 2
Therefore, using the Piola transform we obtain,
‖σ − RT0σ‖L2(T ) ≤C
sinαhT‖Dσ‖L2(T )
for a general triangle T with maximum angle α.
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HIGHER ORDER RT ELEMENTS
Applying similar arguments than for RT0, i. e.,
A generalized Poincaré inequality
For example, for k = 1
∫`v p1 = 0 ∀p1 ∈ P1(`) ,
∫T
v = 0 =⇒
‖v‖L2(T )≤ C
2∑i,j=1
hihj
∥∥∥∥ ∂2v∂xi∂xj
∥∥∥∥L2(T )
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HIGHER ORDER RT ELEMENTS
We obtain
‖σ − RTkσ‖L2(T ) ≤ Chk+1T ‖Dk+1(σ − RTkσ)‖L2(T )
under the MAXIMUM ANGLE CONDITION
How do we bound ‖Dk+1RTkσ‖L2(T ) ?
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HIGHER ORDER RT ELEMENTS
We obtain
‖σ − RTkσ‖L2(T ) ≤ Chk+1T ‖Dk+1(σ − RTkσ)‖L2(T )
under the MAXIMUM ANGLE CONDITION
How do we bound ‖Dk+1RTkσ‖L2(T ) ?
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HIGHER ORDER RT ELEMENTS
We use
Dk+1RTkσ = Dkdiv RTkσ
But,div RTkσ = Pkdiv σ
and then,
‖Dk+1RTkσ‖L2(T ) ≤ C‖DkPkdivσ‖L2(T )
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HIGHER ORDER RT ELEMENTS
But, we can prove
‖DkPk f‖L2(T ) ≤ C(α)‖Dk f‖L2(T )
where α is the maximum angle of T
REMARK: An analogous estimate can be obtained by usinginverse inequalities, but in this way the constant would dependon the minimum angle!
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HIGHER ORDER RT ELEMENTS
Summing up we obtain
‖σ − RTkσ‖L2(T ) ≤ Chk+1T ‖Dk+1σ‖L2(T )
under the MAXIMUM ANGLE CONDITION
This analysis is simple but has some important drawbacks!
It does not apply to obtain
‖σ − RTkσ‖L2(T ) ≤ ChmT ‖Dmσ‖L2(T ), 1 ≤ m ≤ k + 1
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HIGHER ORDER RT ELEMENTS
Summing up we obtain
‖σ − RTkσ‖L2(T ) ≤ Chk+1T ‖Dk+1σ‖L2(T )
under the MAXIMUM ANGLE CONDITION
This analysis is simple but has some important drawbacks!
It does not apply to obtain
‖σ − RTkσ‖L2(T ) ≤ ChmT ‖Dmσ‖L2(T ), 1 ≤ m ≤ k + 1
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HIGHER ORDER RT ELEMENTS
In particular m = 1
‖σ − RTkσ‖L2(T ) ≤ ChT‖Dσ‖L2(T )
=⇒ INF − SUP
IMPORTANT IN ERROR ANALYSIS!
Moreover,
The extension of the arguments to the 3d case does not give acomplete result: It only applies to a restricted class of elements
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HIGHER ORDER RT ELEMENTS
In particular m = 1
‖σ − RTkσ‖L2(T ) ≤ ChT‖Dσ‖L2(T )
=⇒ INF − SUP
IMPORTANT IN ERROR ANALYSIS!
Moreover,
The extension of the arguments to the 3d case does not give acomplete result: It only applies to a restricted class of elements
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THE 3D CASE
Two generalizations of the MAXIMUM ANGLE CONDITION:
REGULAR VERTEX PROPERTYA family of tetrahedra satisfies the RVP if for some vertex,the three edges containing that vertex remain “Uniformlylinearly independent”.
MAXIMUM ANGLE CONDITIONA family of tetrahedra satisfies the MAC if the anglesbetween edges and between faces remain uniformlybounded away from π.
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THE 3D CASE
In 2D RVP ⇐⇒ MAC
In 3D RVP =⇒ MAC
BUT NOT CONVERSELY!
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THE 3D CASE
Now we have to work with two families of reference elements
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THE 3D CASE
Using the Piola transform associated with
F : T → T
F (x) = Mx + b
with‖M‖, ‖M−1‖ ≤ C
we obtain RVP from the left family and MAC from the union of
both families.
A straightforward generalization of the argument given in 2Dproves the error estimate under the RVP property!
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THE 3D CASE
Using the Piola transform associated with
F : T → T
F (x) = Mx + b
with‖M‖, ‖M−1‖ ≤ C
we obtain RVP from the left family and MAC from the union of
both families.
A straightforward generalization of the argument given in 2Dproves the error estimate under the RVP property!
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THE 3D CASE
Using the Piola transform associated with
F : T → T
F (x) = Mx + b
with‖M‖, ‖M−1‖ ≤ C
we obtain RVP from the left family and MAC from the union of
both families.
A straightforward generalization of the argument given in 2Dproves the error estimate under the RVP property!
R. G. Durán Métodos mixtos para problemas degenerados
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QUESTIONS
1 It is possible to obtain error estimates under MAC in 3D ?
2 It is possible to obtain error estimates for less regularfunctions?
Yes!
But we need a different argument.
Idea: Reduction to a finite dimensional problem
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QUESTIONS
1 It is possible to obtain error estimates under MAC in 3D ?
2 It is possible to obtain error estimates for less regularfunctions?
Yes!
But we need a different argument.
Idea: Reduction to a finite dimensional problem
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Case k = 0 in 3D
We use the face average interpolant
Π : H1(T )3 → P1(T )3
∫S
Πσ =
∫Sσ
Properties of Π:
‖DΠσ‖L2(T ) ≤ ‖Dσ‖L2(T )
‖σ − Πσ‖L2(T ) ≤ ChT‖Dσ‖L2(T ) C independent of the
shape!
RT0σ = RT0Πσ
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Case n = 3, k = 0
If
‖τ − RT0τ‖L2(T ) ≤ C1hT‖Dτ‖L2(T ) ∀τ ∈ P1(T )3
Then,
‖σ − RT0σ‖L2(T ) ≤ (C + C1)hT‖Dσ‖L2(T ) ∀σ ∈ H1(T )3
with a constant C independent of T !
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Case n = 3, k = 0
Proof:
‖σ − RT0σ‖L2(T ) ≤ ‖σ − Πσ‖L2(T ) + ‖Πσ − RT0Πσ‖L2(T )
≤ ChT‖Dσ‖L2(T ) + C1hT‖DΠσ‖L2(T )
≤ (C + C1)hT‖Dσ‖L2(T )
In this way we obtain
‖σ − RT0σ‖L2(T ) ≤ C(α) hT‖Dσ‖L2(T )
where α is the maximum angle of T .
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ANOTHER ARGUMENT
Recall the original proof (Raviart-Thomas):
‖RTkσ‖L2(T )≤ C‖σ‖H1(T )
.
Complete H1-norm appears on the right hand side.
=⇒ C = C(γ)
where γ is the mesh regularity constant.
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ERROR ESTIMATES
Idea (in 2D for simplicity):
To obtain sharper estimates on T !
Consider the first components
σ1 and RTk ,1σ
Ideally, we would like
‖RTk ,1σ‖L2(T )≤ C‖σ1‖H1(T )
.
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ERROR ESTIMATES
But it is false:
For example, on the reference triangle:
σ = (0, y2) =⇒ RT0σ =13
(x , y)
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ERROR ESTIMATES
Which are the essential degrees of freedom defining RTk ,1σ?
To answer this question one can try to “kill” degrees of freedomby modifying σ without changing RTk ,1σ.
Key observation:
τ = (0,g(x)) =⇒ RTk ,1τ = 0
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ERROR ESTIMATES
Which are the essential degrees of freedom defining RTk ,1σ?
To answer this question one can try to “kill” degrees of freedomby modifying σ without changing RTk ,1σ.
Key observation:
τ = (0,g(x)) =⇒ RTk ,1τ = 0
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ERROR ESTIMATES
Then,
τ = (σ1(x , y), σ2(x,y)− u2(x ,0)) =⇒ RTk ,1τ = RTk ,1σ
But,
τ · n = 0 on the edge `2 contained in y = 0
Then, the degrees of freedom defining RT0 associated with that
edge vanish!
For k = 0 this gives
‖RTk ,1σ‖L2(T )≤ C‖σ1‖H1(T )
+ ‖divσ‖L2(T )
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ERROR ESTIMATES
For k > 0 we can “kill" internal degrees of freedom:
τ = (σ1(x , y), σ2(x , y)− σ2(x ,0)− yqk−1(x , y))
with
qk−1 ∈ Pk−1
τ · n = 0 on `2
RTk ,1τ = RTk ,1σ
qk−1 can be chosen such that internal degrees of freedomcorresponding to w2 vanish!
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THE 3D CASE
We apply this argument to the two reference families (we omitdetails which are rather technical!)
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THE 3D CASE
In this way we obtain the first reference family
‖RTkσ‖L2(T ) ≤ C‖σ‖L2(T )+
∑i,j
hj
∥∥∥∥∂σi
∂xj
∥∥∥∥L2(T )
+hT‖divσ‖L2(T )
and analogous estimates under the regular vertex property.
Remark: These error estimates are of anisotropic type!For maximum angle condition we obtain
‖RTkσ‖L2(T ) ≤ C‖σ‖L2(T ) + hT‖Dσ‖L2(T )
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THE 3D CASE
In this way we obtain the first reference family
‖RTkσ‖L2(T ) ≤ C‖σ‖L2(T )+
∑i,j
hj
∥∥∥∥∂σi
∂xj
∥∥∥∥L2(T )
+hT‖divσ‖L2(T )
and analogous estimates under the regular vertex property.
Remark: These error estimates are of anisotropic type!
For maximum angle condition we obtain
‖RTkσ‖L2(T ) ≤ C‖σ‖L2(T ) + hT‖Dσ‖L2(T )
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THE 3D CASE
In this way we obtain the first reference family
‖RTkσ‖L2(T ) ≤ C‖σ‖L2(T )+
∑i,j
hj
∥∥∥∥∂σi
∂xj
∥∥∥∥L2(T )
+hT‖divσ‖L2(T )
and analogous estimates under the regular vertex property.
Remark: These error estimates are of anisotropic type!For maximum angle condition we obtain
‖RTkσ‖L2(T ) ≤ C‖σ‖L2(T ) + hT‖Dσ‖L2(T )
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DEGENERATE ELLIPTIC PROBLEMS
We consider problems of the form−div (A(x)∇u) = g in Ω
u = 0 on ΓD−A∇u · n = f on ΓN
(1)
λω(x)|ξ|2 ≤ ξT · A(x)ξ ≤ Λω(x)|ξ|2
where ω is a non-negative function that can vanish or becomeinfinity in subsets of Ω with vanishing n-dimensional measure.
Typical examples: Examples: ω(x) = |x |α or ω(x) = dist(x , Γ)α
with Γ ⊂ ∂Ω.
For simplicity we will consider
−div (ω∇u) = g
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DEGENERATE ELLIPTIC PROBLEMS
We consider problems of the form−div (A(x)∇u) = g in Ω
u = 0 on ΓD−A∇u · n = f on ΓN
(1)
λω(x)|ξ|2 ≤ ξT · A(x)ξ ≤ Λω(x)|ξ|2
where ω is a non-negative function that can vanish or becomeinfinity in subsets of Ω with vanishing n-dimensional measure.
Typical examples: Examples: ω(x) = |x |α or ω(x) = dist(x , Γ)α
with Γ ⊂ ∂Ω.
For simplicity we will consider
−div (ω∇u) = g
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DEGENERATE ELLIPTIC PROBLEMS
We consider problems of the form−div (A(x)∇u) = g in Ω
u = 0 on ΓD−A∇u · n = f on ΓN
(1)
λω(x)|ξ|2 ≤ ξT · A(x)ξ ≤ Λω(x)|ξ|2
where ω is a non-negative function that can vanish or becomeinfinity in subsets of Ω with vanishing n-dimensional measure.
Typical examples: Examples: ω(x) = |x |α or ω(x) = dist(x , Γ)α
with Γ ⊂ ∂Ω.
For simplicity we will consider
−div (ω∇u) = g
R. G. Durán Métodos mixtos para problemas degenerados
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WEIGHTED POINCARÉ INEQUALITIES
This kind of problems were first studied by Fabes, Kenig andSerapioni (1982).
A fundamental tool in their analysis is the Poincaré inequality inweighted norms, namely,
‖f − fΩ‖Lpω(Ω) ≤ C‖∇f‖Lp
ω(Ω)
For our error analysis we need the stronger “Improved Poincaréinequality”:
‖f − fΩ‖Lpω(Ω) ≤ C‖d∇f‖Lp
ω(Ω)
where d is the distance to the boundary.
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WEIGHTED POINCARÉ INEQUALITIES
This kind of problems were first studied by Fabes, Kenig andSerapioni (1982).
A fundamental tool in their analysis is the Poincaré inequality inweighted norms, namely,
‖f − fΩ‖Lpω(Ω) ≤ C‖∇f‖Lp
ω(Ω)
For our error analysis we need the stronger “Improved Poincaréinequality”:
‖f − fΩ‖Lpω(Ω) ≤ C‖d∇f‖Lp
ω(Ω)
where d is the distance to the boundary.
R. G. Durán Métodos mixtos para problemas degenerados
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WEIGHTED POINCARÉ INEQUALITIES
FKS proved, for Q a cube,
‖f − fQ‖Lpω(Q) ≤ C`(Q)‖∇f‖Lp
ω(Q)
for two classes of weights ω
ω ∈ Ap
ω = (JF )1−p/n, (1 < p < n)
where F : Rn → Rn is a quasi-conformal mapping.
An interesting example that they give is ω = |x |α, α > 0.
Actually they proved the result for n ≥ 3 and p = 2, buttheir argument can be extended straightforward.
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WEIGHTED POINCARÉ INEQUALITIES
FKS proved, for Q a cube,
‖f − fQ‖Lpω(Q) ≤ C`(Q)‖∇f‖Lp
ω(Q)
for two classes of weights ω
ω ∈ Ap
ω = (JF )1−p/n, (1 < p < n)
where F : Rn → Rn is a quasi-conformal mapping.
An interesting example that they give is ω = |x |α, α > 0.
Actually they proved the result for n ≥ 3 and p = 2, buttheir argument can be extended straightforward.
R. G. Durán Métodos mixtos para problemas degenerados
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WEIGHTED POINCARÉ INEQUALITIES
FKS proved, for Q a cube,
‖f − fQ‖Lpω(Q) ≤ C`(Q)‖∇f‖Lp
ω(Q)
for two classes of weights ω
ω ∈ Ap
ω = (JF )1−p/n, (1 < p < n)
where F : Rn → Rn is a quasi-conformal mapping.
An interesting example that they give is ω = |x |α, α > 0.
Actually they proved the result for n ≥ 3 and p = 2, buttheir argument can be extended straightforward.
R. G. Durán Métodos mixtos para problemas degenerados
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IDEA OF THE PROOF FOR ω = JF 1−p/n
Using a change of variables, Hölder and that f isquasi-conformal:
∫Q|ϕ(x)−cQ|pω(x) dx ≤ C`(Q)p
(∫F (Q)|(ϕ F−1)(y)− cQ|p∗ dy
) pp∗
∫F (Q)|∇(ϕ F−1)(y)|p dy ≤ C
∫Q|∇ϕ(x)|pω(x) dx
and therefore, it is enough to prove(∫F (Q)|(ϕ F−1)(y)− cQ|p∗ dy
) 1p∗
≤ C
(∫F (Q)|∇(ϕ F−1)(y)|p
) 1p
But this is the un-weighted Sobolev-Poincaré in F (Q) which is aJohn domain.
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IDEA OF THE PROOF FOR ω = JF 1−p/n
Using a change of variables, Hölder and that f isquasi-conformal:
∫Q|ϕ(x)−cQ|pω(x) dx ≤ C`(Q)p
(∫F (Q)|(ϕ F−1)(y)− cQ|p∗ dy
) pp∗
∫F (Q)|∇(ϕ F−1)(y)|p dy ≤ C
∫Q|∇ϕ(x)|pω(x) dx
and therefore, it is enough to prove(∫F (Q)|(ϕ F−1)(y)− cQ|p∗ dy
) 1p∗
≤ C
(∫F (Q)|∇(ϕ F−1)(y)|p
) 1p
But this is the un-weighted Sobolev-Poincaré in F (Q) which is aJohn domain.
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IDEA OF THE PROOF FOR ω = JF 1−p/n
Using a change of variables, Hölder and that f isquasi-conformal:
∫Q|ϕ(x)−cQ|pω(x) dx ≤ C`(Q)p
(∫F (Q)|(ϕ F−1)(y)− cQ|p∗ dy
) pp∗
∫F (Q)|∇(ϕ F−1)(y)|p dy ≤ C
∫Q|∇ϕ(x)|pω(x) dx
and therefore, it is enough to prove(∫F (Q)|(ϕ F−1)(y)− cQ|p∗ dy
) 1p∗
≤ C
(∫F (Q)|∇(ϕ F−1)(y)|p
) 1p
But this is the un-weighted Sobolev-Poincaré in F (Q) which is aJohn domain.
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A REPRESENTATION FORMULA
Suppose that Ω is star-shaped with respect to a ball.
Given a function f we denote with f an appropriate weightedaverage.
f (y)− f = −∫
ΩG(x , y) · ∇f (x) dx
G(x , y) =
∫ 1
0
(x − y)
tϕ
(y +
x − yt
)dttn
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A REPRESENTATION FORMULA
Suppose that Ω is star-shaped with respect to a ball.
Given a function f we denote with f an appropriate weightedaverage.
f (y)− f = −∫
ΩG(x , y) · ∇f (x) dx
G(x , y) =
∫ 1
0
(x − y)
tϕ
(y +
x − yt
)dttn
R. G. Durán Métodos mixtos para problemas degenerados
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A REPRESENTATION FORMULA
Suppose that Ω is star-shaped with respect to a ball.
Given a function f we denote with f an appropriate weightedaverage.
f (y)− f = −∫
ΩG(x , y) · ∇f (x) dx
G(x , y) =
∫ 1
0
(x − y)
tϕ
(y +
x − yt
)dttn
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POINCARÉ INEQUALITY
It is easy to see that
|G(x , y)| ≤ C|x − y |n−1
and therefore,
|f (y)− f | ≤ C∫
Ω
|∇f (x)||x − y |n−1 dx
and the Poincaré inequality
‖f − fΩ‖Lp(Ω) ≤ C‖∇f‖Lp(Ω)
follows easily.
The weighted case can be proved using results for fractionalintegrals (this is what FKS did for Ap weights).
R. G. Durán Métodos mixtos para problemas degenerados
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POINCARÉ INEQUALITY
It is easy to see that
|G(x , y)| ≤ C|x − y |n−1
and therefore,
|f (y)− f | ≤ C∫
Ω
|∇f (x)||x − y |n−1 dx
and the Poincaré inequality
‖f − fΩ‖Lp(Ω) ≤ C‖∇f‖Lp(Ω)
follows easily.
The weighted case can be proved using results for fractionalintegrals (this is what FKS did for Ap weights).
R. G. Durán Métodos mixtos para problemas degenerados
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POINCARÉ INEQUALITY
It is easy to see that
|G(x , y)| ≤ C|x − y |n−1
and therefore,
|f (y)− f | ≤ C∫
Ω
|∇f (x)||x − y |n−1 dx
and the Poincaré inequality
‖f − fΩ‖Lp(Ω) ≤ C‖∇f‖Lp(Ω)
follows easily.
The weighted case can be proved using results for fractionalintegrals (this is what FKS did for Ap weights).
R. G. Durán Métodos mixtos para problemas degenerados
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IMPROVED POINCARÉ INEQUALITY
But we can do better with a little more effort:
Using the same representation formula we can prove theImproved Poincaré inequality.
Moreover, the argument can be applied to the weighted casefor Muckenhoupt weights.
We have to use the well known estimate:∫|x−y |≤ε
|f (y)||x − y |n−1 dy . εMf (x)
R. G. Durán Métodos mixtos para problemas degenerados
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IMPROVED POINCARÉ INEQUALITY
But we can do better with a little more effort:
Using the same representation formula we can prove theImproved Poincaré inequality.
Moreover, the argument can be applied to the weighted casefor Muckenhoupt weights.
We have to use the well known estimate:∫|x−y |≤ε
|f (y)||x − y |n−1 dy . εMf (x)
R. G. Durán Métodos mixtos para problemas degenerados
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IMPROVED POINCARÉ INEQUALITY
But we can do better with a little more effort:
Using the same representation formula we can prove theImproved Poincaré inequality.
Moreover, the argument can be applied to the weighted casefor Muckenhoupt weights.
We have to use the well known estimate:∫|x−y |≤ε
|f (y)||x − y |n−1 dy . εMf (x)
R. G. Durán Métodos mixtos para problemas degenerados
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IMPROVED POINCARÉ INEQUALITY
Going back to
|f (y)− f | .∫
Ω
|∇f (x)||x − y |n−1 dx
The key observation is that G(x , y) vanishes for |x − y | > cd(x)(This argument was introduced in Drelichman-D.).
Then|f (y)− f | .
∫|x−y |.d(x)
|∇f (x)||x − y |n−1 dx
R. G. Durán Métodos mixtos para problemas degenerados
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IMPROVED POINCARÉ INEQUALITY
Going back to
|f (y)− f | .∫
Ω
|∇f (x)||x − y |n−1 dx
The key observation is that G(x , y) vanishes for |x − y | > cd(x)(This argument was introduced in Drelichman-D.).
Then|f (y)− f | .
∫|x−y |.d(x)
|∇f (x)||x − y |n−1 dx
R. G. Durán Métodos mixtos para problemas degenerados
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IMPROVED POINCARÉ INEQUALITY
Going back to
|f (y)− f | .∫
Ω
|∇f (x)||x − y |n−1 dx
The key observation is that G(x , y) vanishes for |x − y | > cd(x)(This argument was introduced in Drelichman-D.).
Then|f (y)− f | .
∫|x−y |.d(x)
|∇f (x)||x − y |n−1 dx
R. G. Durán Métodos mixtos para problemas degenerados
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IMPROVED POINCARÉ INEQUALITY
We use duality,
∫Ω|f (y)− f |g(y) dy .
∫Ω
∫|x−y |.d(x)
g(y)
|x − y |n−1 dy |∇f (x)|dx
.∫
Ωd(x) Mg(x) |∇f (x)|dx ≤ ‖g‖Lp′ (Ω) ‖d∇f‖Lp(Ω)
and then‖f − fΩ‖Lp(Ω) ≤ C‖d∇f‖Lp(Ω)
R. G. Durán Métodos mixtos para problemas degenerados
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GENERALIZATION TO JOHN DOMAINS
The representation formula can be generalized replacingsegments by appropriate curves.
John domains are those satisfying a “Twisted cone condition”.
For all y ∈ Ω there exists a rectifiable curve joining y with afixed x0 ∈ Ω (we take it = 0 to simplify notation), given by aparametrization γ(t , y) such that
γ(0, y) = y , γ(1, y) = 0
and there exist K , δ > 0 such that
|γ(t , y)| ≤ K , d(γ(t , y)) ≥ δt
R. G. Durán Métodos mixtos para problemas degenerados
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GENERALIZATION TO JOHN DOMAINS
With similar arguments we obtain
f (y)− f = −∫
ΩG(x , y) · ∇f (x) dx
where now
G(x , y) =
∫ 1
0
γ(t , y) +
x − γ(t , y)
t
ϕ
(x − γ(t , y)
t
)dttn
which satisfies the same properties as in the case ofstar-shaped domains.
R. G. Durán Métodos mixtos para problemas degenerados
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GENERALIZATION TO JOHN DOMAINS
With similar arguments we obtain
f (y)− f = −∫
ΩG(x , y) · ∇f (x) dx
where now
G(x , y) =
∫ 1
0
γ(t , y) +
x − γ(t , y)
t
ϕ
(x − γ(t , y)
t
)dttn
which satisfies the same properties as in the case ofstar-shaped domains.
R. G. Durán Métodos mixtos para problemas degenerados
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ESTIMATES IN FRACTIONAL SOBOLEV SPACES
In many applications it is useful to have estimates for lessregular functions.
We can generalize the argument to prove improved Poincaréinequalities in fractional Sobolev spaces (Drelichman-D.):
‖f − fΩ‖Lp(Ω) ≤ C|dsDsf |pwhere we are using the notation
|dsDsf |pp =
∫Ω
∫Ω
|f (x)− f (y)|p
|x − y |n+ps ds(x)ds(y) dxdy
How can we generalize the representation formula?
R. G. Durán Métodos mixtos para problemas degenerados
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ESTIMATES IN FRACTIONAL SOBOLEV SPACES
In many applications it is useful to have estimates for lessregular functions.
We can generalize the argument to prove improved Poincaréinequalities in fractional Sobolev spaces (Drelichman-D.):
‖f − fΩ‖Lp(Ω) ≤ C|dsDsf |pwhere we are using the notation
|dsDsf |pp =
∫Ω
∫Ω
|f (x)− f (y)|p
|x − y |n+ps ds(x)ds(y) dxdy
How can we generalize the representation formula?
R. G. Durán Métodos mixtos para problemas degenerados
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ESTIMATES IN FRACTIONAL SOBOLEV SPACES
In many applications it is useful to have estimates for lessregular functions.
We can generalize the argument to prove improved Poincaréinequalities in fractional Sobolev spaces (Drelichman-D.):
‖f − fΩ‖Lp(Ω) ≤ C|dsDsf |pwhere we are using the notation
|dsDsf |pp =
∫Ω
∫Ω
|f (x)− f (y)|p
|x − y |n+ps ds(x)ds(y) dxdy
How can we generalize the representation formula?
R. G. Durán Métodos mixtos para problemas degenerados
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ESTIMATES IN FRACTIONAL SOBOLEV SPACES
Idea: regularize f and take "part" of the derivatives to thefunction used to average:
Define,
u(y , t) = (f ∗ ϕt )(y)
andg(t) = u(γ(t , y) + tz, t)
Then,
f (y)−(f ∗ϕ)(z) = u(y ,0)−u(z,1) = g(0)−g(1) = −∫ 1
0g′(t) dt
= −∫ 1
0∇u(γ(t , y) + tz, t) · (γ(t , z) + z) + ut (γ(t , y) + tz, t) dt
R. G. Durán Métodos mixtos para problemas degenerados
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ESTIMATES IN FRACTIONAL SOBOLEV SPACES
Idea: regularize f and take "part" of the derivatives to thefunction used to average:
Define,
u(y , t) = (f ∗ ϕt )(y)
andg(t) = u(γ(t , y) + tz, t)
Then,
f (y)−(f ∗ϕ)(z) = u(y ,0)−u(z,1) = g(0)−g(1) = −∫ 1
0g′(t) dt
= −∫ 1
0∇u(γ(t , y) + tz, t) · (γ(t , z) + z) + ut (γ(t , y) + tz, t) dt
R. G. Durán Métodos mixtos para problemas degenerados
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ESTIMATES IN FRACTIONAL SOBOLEV SPACES
Multiplying by ϕ(z) and integrating in z we have
f (y)− c =
∫Rn
(f (y)− (f ∗ ϕ)(z))ϕ(z) dz
= −∫Rn
∫ 1
0∇u(γ(t , y) + tz, t) · (γ(t , z) + z)ϕ(z) dtdz
−∫Rn
∫ 1
0ut (γ(t , y) + tz, t)ϕ(z) dtdz
= I + II
Let us bound for example I (II can be handled analogously).
R. G. Durán Métodos mixtos para problemas degenerados
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ESTIMATES IN FRACTIONAL SOBOLEV SPACES
Changing variables γ(t , y) + tz = x and using
∂u∂xj
(x , t) = f ∗ (ϕt )xj (x)
and(ϕt )xj (x) =
1tn+1
∂ϕ
∂xj
(xt
)we have
I =
∫ 1
0
∫Rn
∑j
∫Rn
f (w)1
tn+1∂ϕ
∂xj
(x − wt
)dw
· ψ(x , y , t) dxdttn
with ψ(x , y , t) bounded
But, using that suppϕ ⊂ B(0, δ/4), we can see that theintegration in t reduces to t > c|x − y |.
R. G. Durán Métodos mixtos para problemas degenerados
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ESTIMATES IN FRACTIONAL SOBOLEV SPACES
Changing variables γ(t , y) + tz = x and using
∂u∂xj
(x , t) = f ∗ (ϕt )xj (x)
and(ϕt )xj (x) =
1tn+1
∂ϕ
∂xj
(xt
)we have
I =
∫ 1
0
∫Rn
∑j
∫Rn
f (w)1
tn+1∂ϕ
∂xj
(x − wt
)dw
· ψ(x , y , t) dxdttn
with ψ(x , y , t) bounded
But, using that suppϕ ⊂ B(0, δ/4), we can see that theintegration in t reduces to t > c|x − y |.
R. G. Durán Métodos mixtos para problemas degenerados
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ESTIMATES IN FRACTIONAL SOBOLEV SPACES
Using that ∫1
tn+1∂ϕ
∂xj
(x − wt
)dw = 0
we can subtract f (x) to obtain,
I .∫Rn
∫ 1
c|x−y |
(∫|x−w |<δt/2
|f (w)− f (x)|tn+1
∣∣∣∣∇ϕ(x − wt
)∣∣∣∣dw
)dttn dx
But |x − w | ≤ d(x) and so,
R. G. Durán Métodos mixtos para problemas degenerados
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ESTIMATES IN FRACTIONAL SOBOLEV SPACES
Using that ∫1
tn+1∂ϕ
∂xj
(x − wt
)dw = 0
we can subtract f (x) to obtain,
I .∫Rn
∫ 1
c|x−y |
(∫|x−w |<δt/2
|f (w)− f (x)|tn+1
∣∣∣∣∇ϕ(x − wt
)∣∣∣∣dw
)dttn dx
But |x − w | ≤ d(x) and so,
R. G. Durán Métodos mixtos para problemas degenerados
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ESTIMATES IN FRACTIONAL SOBOLEV SPACES
Using that ∫1
tn+1∂ϕ
∂xj
(x − wt
)dw = 0
we can subtract f (x) to obtain,
I .∫Rn
∫ 1
c|x−y |
(∫|x−w |<δt/2
|f (w)− f (x)|tn+1
∣∣∣∣∇ϕ(x − wt
)∣∣∣∣dw
)dttn dx
But |x − w | ≤ d(x) and so,
R. G. Durán Métodos mixtos para problemas degenerados
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ESTIMATES IN FRACTIONAL SOBOLEV SPACES
I
.∫Rn
∫ 1
c|x−y |
∫|x−w |<d(x)
|f (w)− f (x)||w − x |
np +s
1
tn+ np′+1−s
∣∣∣∣∇ϕ(x − wt
)∣∣∣∣dwdtdx
.∫
g(x)
|x−y|n−s
dx
where
g(x) :=
(∫|x−w |<d(x)
|f (w)− f (x)|p
|w − x |n+ps dw
) 1p
Using this “representation formula” we can extend theargument given above to the fractional case.
R. G. Durán Métodos mixtos para problemas degenerados
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ESTIMATES IN FRACTIONAL SOBOLEV SPACES
I
.∫Rn
∫ 1
c|x−y |
∫|x−w |<d(x)
|f (w)− f (x)||w − x |
np +s
1
tn+ np′+1−s
∣∣∣∣∇ϕ(x − wt
)∣∣∣∣dwdtdx
.∫
g(x)
|x−y|n−s
dx
where
g(x) :=
(∫|x−w |<d(x)
|f (w)− f (x)|p
|w − x |n+ps dw
) 1p
Using this “representation formula” we can extend theargument given above to the fractional case.
R. G. Durán Métodos mixtos para problemas degenerados
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MORE GENERAL WEIGHTS
The above arguments are based on continuity properties of theHardy-Littlewood maximal function.
With different arguments we proved (Acosta-Cejas-D.):
‖f − fΩ‖Lpω(Ω) ≤ C‖d∇f‖Lp
ω(Ω)
for doubling weights ω which satisfies the local Poincaré
‖f − fQ‖Lpω(Q) ≤ C‖∇f‖Lp
ω(Q)
for whitney type cubes.
In particular the improved Poincaré is valid for the weightsconsidered by FKS.
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MORE GENERAL WEIGHTS
The above arguments are based on continuity properties of theHardy-Littlewood maximal function.
With different arguments we proved (Acosta-Cejas-D.):
‖f − fΩ‖Lpω(Ω) ≤ C‖d∇f‖Lp
ω(Ω)
for doubling weights ω which satisfies the local Poincaré
‖f − fQ‖Lpω(Q) ≤ C‖∇f‖Lp
ω(Q)
for whitney type cubes.
In particular the improved Poincaré is valid for the weightsconsidered by FKS.
R. G. Durán Métodos mixtos para problemas degenerados
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MORE GENERAL WEIGHTS
The above arguments are based on continuity properties of theHardy-Littlewood maximal function.
With different arguments we proved (Acosta-Cejas-D.):
‖f − fΩ‖Lpω(Ω) ≤ C‖d∇f‖Lp
ω(Ω)
for doubling weights ω which satisfies the local Poincaré
‖f − fQ‖Lpω(Q) ≤ C‖∇f‖Lp
ω(Q)
for whitney type cubes.
In particular the improved Poincaré is valid for the weightsconsidered by FKS.
R. G. Durán Métodos mixtos para problemas degenerados
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MIXED METHODS FOR DEGENERATE PROBLEMS
−div (ω∇u) = g in Ω
u = 0 on ΓD−ω∇u · n = f on ΓN
The mixed formulation is given byσ + ω∇u = 0 in Ω
divσ = g in Ωu = 0 on ΓD
σ · n = f on ΓN
Notation:
H(div ,Ω) = τ ∈ L2(Ω)n : div τ ∈ L2(Ω)
and,
HΓN (div ,Ω) = τ ∈ H(div ,Ω) : τ · n = 0 on ΓN
R. G. Durán Métodos mixtos para problemas degenerados
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MIXED METHODS FOR DEGENERATE PROBLEMS
−div (ω∇u) = g in Ω
u = 0 on ΓD−ω∇u · n = f on ΓN
The mixed formulation is given byσ + ω∇u = 0 in Ω
divσ = g in Ωu = 0 on ΓD
σ · n = f on ΓN
Notation:
H(div ,Ω) = τ ∈ L2(Ω)n : div τ ∈ L2(Ω)
and,
HΓN (div ,Ω) = τ ∈ H(div ,Ω) : τ · n = 0 on ΓN
R. G. Durán Métodos mixtos para problemas degenerados
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MIXED METHODS FOR DEGENERATE PROBLEMS
−div (ω∇u) = g in Ω
u = 0 on ΓD−ω∇u · n = f on ΓN
The mixed formulation is given byσ + ω∇u = 0 in Ω
divσ = g in Ωu = 0 on ΓD
σ · n = f on ΓN
Notation:
H(div ,Ω) = τ ∈ L2(Ω)n : div τ ∈ L2(Ω)
and,
HΓN (div ,Ω) = τ ∈ H(div ,Ω) : τ · n = 0 on ΓN
R. G. Durán Métodos mixtos para problemas degenerados
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MIXED FEM APPROXIMATION
Dividing by ω the first equation we obtain the mixed weakformulation:
Find σ ∈ H(div ,Ω) and u ∈ L2(Ω) such that
σ · n = f on ΓN
and∫
Ω ω−1 σ · τ dx −
∫Ω u div τ dx = 0 ∀τ ∈ HΓN (div ,Ω)∫
Ω v div σ dx =∫
Ω gv dx ∀v ∈ L2(Ω)
Recall that the Dirichlet boundary condition is implicit in theweak formulation (i. e., it is imposed in a natural way)
R. G. Durán Métodos mixtos para problemas degenerados
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MIXED FEM APPROXIMATION
Dividing by ω the first equation we obtain the mixed weakformulation:
Find σ ∈ H(div ,Ω) and u ∈ L2(Ω) such that
σ · n = f on ΓN
and∫
Ω ω−1 σ · τ dx −
∫Ω u div τ dx = 0 ∀τ ∈ HΓN (div ,Ω)∫
Ω v div σ dx =∫
Ω gv dx ∀v ∈ L2(Ω)
Recall that the Dirichlet boundary condition is implicit in theweak formulation (i. e., it is imposed in a natural way)
R. G. Durán Métodos mixtos para problemas degenerados
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THE FRACTIONAL LAPLACIAN
One of our motivations to analyze mixed approximations fordegenerate problems was the fractional laplacian.
(−∆)sv = f in Ω
v = 0 on ∂Ω
This is a non local problem.Caffarelli and Silvestre have shown that this problem isequivalent to a degenerate elliptic problem in n + 1 variables:v(x) = u(x ,0) where If u(x , y) is the solution of with α = 1− 2s
div (yα∇u(x , y)) = 0 in D := Ω× (0,Y )− limy→0 yαuy = f on Γ := Ω× 0
u = 0 ∂D \ Γ
R. G. Durán Métodos mixtos para problemas degenerados
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THE FRACTIONAL LAPLACIAN
One of our motivations to analyze mixed approximations fordegenerate problems was the fractional laplacian.
(−∆)sv = f in Ω
v = 0 on ∂Ω
This is a non local problem.Caffarelli and Silvestre have shown that this problem isequivalent to a degenerate elliptic problem in n + 1 variables:v(x) = u(x ,0) where If u(x , y) is the solution of with α = 1− 2s
div (yα∇u(x , y)) = 0 in D := Ω× (0,Y )− limy→0 yαuy = f on Γ := Ω× 0
u = 0 ∂D \ Γ
R. G. Durán Métodos mixtos para problemas degenerados
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THE FRACTIONAL LAPLACIAN
In other words, the fractional laplacian is a Dirichlet toNeumann map.
Nochetto-Otárola-Salgado analyzed standard FEMapproximation for these problems.
Acosta-Borthagaray analyzed numerical approximations of thenon-local problem.
Our motivation to use mixed methods is that the variableσ = yα∇u(x , y) seems to behave better than ∇u.
R. G. Durán Métodos mixtos para problemas degenerados
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THE FRACTIONAL LAPLACIAN
In other words, the fractional laplacian is a Dirichlet toNeumann map.
Nochetto-Otárola-Salgado analyzed standard FEMapproximation for these problems.
Acosta-Borthagaray analyzed numerical approximations of thenon-local problem.
Our motivation to use mixed methods is that the variableσ = yα∇u(x , y) seems to behave better than ∇u.
R. G. Durán Métodos mixtos para problemas degenerados
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THE FRACTIONAL LAPLACIAN
In other words, the fractional laplacian is a Dirichlet toNeumann map.
Nochetto-Otárola-Salgado analyzed standard FEMapproximation for these problems.
Acosta-Borthagaray analyzed numerical approximations of thenon-local problem.
Our motivation to use mixed methods is that the variableσ = yα∇u(x , y) seems to behave better than ∇u.
R. G. Durán Métodos mixtos para problemas degenerados
![Page 110: Métodos de elementos finitos mixtos para problemas no ... PDFs/Duran...Title Métodos de elementos finitos mixtos para problemas no uniformemente elípticos Author Ricardo G. Durán](https://reader036.fdocumentos.tips/reader036/viewer/2022081400/607a011d28dc4a58853c74e6/html5/thumbnails/110.jpg)
THE FRACTIONAL LAPLACIAN
In other words, the fractional laplacian is a Dirichlet toNeumann map.
Nochetto-Otárola-Salgado analyzed standard FEMapproximation for these problems.
Acosta-Borthagaray analyzed numerical approximations of thenon-local problem.
Our motivation to use mixed methods is that the variableσ = yα∇u(x , y) seems to behave better than ∇u.
R. G. Durán Métodos mixtos para problemas degenerados
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AN ELEMENTARY EXAMPLE
To illustrate the idea consider the trivial example(yαu′(y))′ = y−1/2 in (0,1)
− limy→0 yαu′(y) = 1u(1) = 0
σ(y) = yαu′(y)
For example, taking α = 1/2, we can see that the expectedorder for∫ 1
0(σ − σh)2y−α dy ∼
∫ 1
0(u′(y)− u′h(y))2yα dy
is 3/4 the mixed method and 1/4 for the standard one.
R. G. Durán Métodos mixtos para problemas degenerados
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ERROR IN σ
4.2 4.4 4.6 4.8 5 5.2 5.4 5.6 5.8 6−12
−10
−8
−6
−4
−2
0
Number of elements
Err
or S
igm
a
alpha=0.50
Mixed unif, order=0.75Mixed grad, order=1.98Direct unif, order=0.25Direct grad, order=0.98
R. G. Durán Métodos mixtos para problemas degenerados
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ERROR IN u
4.2 4.4 4.6 4.8 5 5.2 5.4 5.6 5.8 6−12
−11
−10
−9
−8
−7
−6
−5
−4
−3
Number of elements
Err
or U
alpha=0.50
Mixed method unif, order=0.99Mixed method grad, order=0.98Direct method unif, order=1.25Direct method grad, order=1.91
R. G. Durán Métodos mixtos para problemas degenerados
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A NEGATIVE α
4.2 4.4 4.6 4.8 5 5.2 5.4 5.6 5.8 6−6
−5.8
−5.6
−5.4
−5.2
−5
−4.8
−4.6
−4.4
−4.2
−4
Number of elements
Err
or S
igm
a
alpha = − 0.1
Mixed method, order=1.04Direct method unif, order=0.78Direct method grad, order=0.97
R. G. Durán Métodos mixtos para problemas degenerados
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MIXED FEM APPROXIMATION
We will consider the approximation by the lowest orderRaviart-Thomas space in n-dimensions.
For a rectangular element R the local space is
RT0(R) = τ ∈ L2(R)n : τ (x) = (a1 + b1x1, · · · ,an + bnxn)
and for a simplex T ,
RT0(T ) = τ ∈ L2(T )n : τ (x) = (a1 + bx1, · · · ,an + bxn)
Associated with a partition Th of the domain Ω we introduce theglobal spaces
RT0(Th) = τ ∈ H(div ,Ω) : τ |R ∈ RT0(R) ∀R ∈ Th
and
P0(Th) = v ∈ L2(Ω) : v |R ∈ P0(R) : ∀R ∈ Th
R. G. Durán Métodos mixtos para problemas degenerados
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MIXED FEM APPROXIMATION
We will consider the approximation by the lowest orderRaviart-Thomas space in n-dimensions.
For a rectangular element R the local space is
RT0(R) = τ ∈ L2(R)n : τ (x) = (a1 + b1x1, · · · ,an + bnxn)
and for a simplex T ,
RT0(T ) = τ ∈ L2(T )n : τ (x) = (a1 + bx1, · · · ,an + bxn)
Associated with a partition Th of the domain Ω we introduce theglobal spaces
RT0(Th) = τ ∈ H(div ,Ω) : τ |R ∈ RT0(R) ∀R ∈ Th
and
P0(Th) = v ∈ L2(Ω) : v |R ∈ P0(R) : ∀R ∈ Th
R. G. Durán Métodos mixtos para problemas degenerados
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MIXED FEM APPROXIMATION
We will consider the approximation by the lowest orderRaviart-Thomas space in n-dimensions.
For a rectangular element R the local space is
RT0(R) = τ ∈ L2(R)n : τ (x) = (a1 + b1x1, · · · ,an + bnxn)
and for a simplex T ,
RT0(T ) = τ ∈ L2(T )n : τ (x) = (a1 + bx1, · · · ,an + bxn)
Associated with a partition Th of the domain Ω we introduce theglobal spaces
RT0(Th) = τ ∈ H(div ,Ω) : τ |R ∈ RT0(R) ∀R ∈ Th
and
P0(Th) = v ∈ L2(Ω) : v |R ∈ P0(R) : ∀R ∈ Th
R. G. Durán Métodos mixtos para problemas degenerados
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MIXED FEM APPROXIMATION
We will consider the approximation by the lowest orderRaviart-Thomas space in n-dimensions.
For a rectangular element R the local space is
RT0(R) = τ ∈ L2(R)n : τ (x) = (a1 + b1x1, · · · ,an + bnxn)
and for a simplex T ,
RT0(T ) = τ ∈ L2(T )n : τ (x) = (a1 + bx1, · · · ,an + bxn)
Associated with a partition Th of the domain Ω we introduce theglobal spaces
RT0(Th) = τ ∈ H(div ,Ω) : τ |R ∈ RT0(R) ∀R ∈ Th
and
P0(Th) = v ∈ L2(Ω) : v |R ∈ P0(R) : ∀R ∈ Th
R. G. Durán Métodos mixtos para problemas degenerados
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MIXED FEM APPROXIMATION
A fundamental tool for the error analysis is the well knownRaviart-Thomas operator defined by∫
FΠhτ · n dS =
∫Fτ · n dS
for all face F .
Πh satisfies
∫Ω
div (σ − Πhσ) v dx = 0 ∀v ∈ P0(Th)
R. G. Durán Métodos mixtos para problemas degenerados
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MIXED FEM APPROXIMATION
A fundamental tool for the error analysis is the well knownRaviart-Thomas operator defined by∫
FΠhτ · n dS =
∫Fτ · n dS
for all face F .Πh satisfies
∫Ω
div (σ − Πhσ) v dx = 0 ∀v ∈ P0(Th)
R. G. Durán Métodos mixtos para problemas degenerados
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MIXED FEM APPROXIMATION
Introducing the subspace
RT0,ΓN (Th) = RT0(Th) ∩ HΓN (div ,Ω),
and the orthogonal projection onto piecewise constants PΓN ,
the mixed finite element approximation is given by(σh,uh) ∈ RT0(Th)× P0(Th) satisfying
σh · n = PΓN f on ΓN
and∫
Ω ω−1 σh · τ dx −
∫Ω uh div τ dx = 0 ∀τ ∈ RT0,ΓN (Th)∫
Ω v div σh dx =∫
Ω gv dx ∀v ∈ P0(Th)
R. G. Durán Métodos mixtos para problemas degenerados
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MIXED FEM APPROXIMATION
Introducing the subspace
RT0,ΓN (Th) = RT0(Th) ∩ HΓN (div ,Ω),
and the orthogonal projection onto piecewise constants PΓN ,the mixed finite element approximation is given by(σh,uh) ∈ RT0(Th)× P0(Th) satisfying
σh · n = PΓN f on ΓN
and∫
Ω ω−1 σh · τ dx −
∫Ω uh div τ dx = 0 ∀τ ∈ RT0,ΓN (Th)∫
Ω v div σh dx =∫
Ω gv dx ∀v ∈ P0(Th)
R. G. Durán Métodos mixtos para problemas degenerados
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ERROR ESTIMATES
‖σ − σh‖L2ω−1 (Ω) ≤ 2‖σ − Πhσ‖L2
ω−1 (Ω)
and
‖u − uh‖L2ω(Ω) ≤ C
‖u − Phu‖L2
ω(Ω) + ‖σ − Πhσ‖L2ω−1 (Ω)
where Ph is the orthogonal L2 projection onto P0(Th).
The arguments are standard but we need the existence ofτ ∈ H1
ω−1(Ω) solution of
div τ = (Phu − uh)ω
satisfying
‖τ‖H1ω−1 (Ω) ≤ C‖(Phu − uh)ω‖L2
ω−1 (Ω)
R. G. Durán Métodos mixtos para problemas degenerados
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ERROR ESTIMATES
‖σ − σh‖L2ω−1 (Ω) ≤ 2‖σ − Πhσ‖L2
ω−1 (Ω)
and
‖u − uh‖L2ω(Ω) ≤ C
‖u − Phu‖L2
ω(Ω) + ‖σ − Πhσ‖L2ω−1 (Ω)
where Ph is the orthogonal L2 projection onto P0(Th).
The arguments are standard but we need the existence ofτ ∈ H1
ω−1(Ω) solution of
div τ = (Phu − uh)ω
satisfying
‖τ‖H1ω−1 (Ω) ≤ C‖(Phu − uh)ω‖L2
ω−1 (Ω)
R. G. Durán Métodos mixtos para problemas degenerados
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WHAT DO WE HAVE TO PROVE?
We need estimates for:
‖σ − Πhσ‖L2ω−1
‖u − Phu‖L2ω(Ω)
And we need a continuous right inverse of
div : H10,ω−1 → L2
ω−1
Moreover, we want anisotropic error estimates (for example forthe application to the fractional Laplacian).
R. G. Durán Métodos mixtos para problemas degenerados
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WHAT DO WE HAVE TO PROVE?
We need estimates for:
‖σ − Πhσ‖L2ω−1
‖u − Phu‖L2ω(Ω)
And we need a continuous right inverse of
div : H10,ω−1 → L2
ω−1
Moreover, we want anisotropic error estimates (for example forthe application to the fractional Laplacian).
R. G. Durán Métodos mixtos para problemas degenerados
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WHAT DO WE HAVE TO PROVE?
We need estimates for:
‖σ − Πhσ‖L2ω−1
‖u − Phu‖L2ω(Ω)
And we need a continuous right inverse of
div : H10,ω−1 → L2
ω−1
Moreover, we want anisotropic error estimates (for example forthe application to the fractional Laplacian).
R. G. Durán Métodos mixtos para problemas degenerados
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WHAT DO WE HAVE TO PROVE?
We need estimates for:
‖σ − Πhσ‖L2ω−1
‖u − Phu‖L2ω(Ω)
And we need a continuous right inverse of
div : H10,ω−1 → L2
ω−1
Moreover, we want anisotropic error estimates (for example forthe application to the fractional Laplacian).
R. G. Durán Métodos mixtos para problemas degenerados
![Page 129: Métodos de elementos finitos mixtos para problemas no ... PDFs/Duran...Title Métodos de elementos finitos mixtos para problemas no uniformemente elípticos Author Ricardo G. Durán](https://reader036.fdocumentos.tips/reader036/viewer/2022081400/607a011d28dc4a58853c74e6/html5/thumbnails/129.jpg)
ANISOTROPIC WEIGHTED ESTIMATES
As we have seen, error estimates follows from Poincaré typeinequalities.
What can be said in the anisotropic case?
Strong A2 condition or As2:
[ω]As2
:= supR
(1|R|
∫Rω dx
)(1|R|
∫Rω−1 dx
)<∞
where the sup is taken over all rectangles with sides parallel tothe coordinate axes.
R. G. Durán Métodos mixtos para problemas degenerados
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ANISOTROPIC WEIGHTED ESTIMATES
As we have seen, error estimates follows from Poincaré typeinequalities.
What can be said in the anisotropic case?
Strong A2 condition or As2:
[ω]As2
:= supR
(1|R|
∫Rω dx
)(1|R|
∫Rω−1 dx
)<∞
where the sup is taken over all rectangles with sides parallel tothe coordinate axes.
R. G. Durán Métodos mixtos para problemas degenerados
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ANISOTROPIC WEIGHTED ESTIMATES
As we have seen, error estimates follows from Poincaré typeinequalities.
What can be said in the anisotropic case?
Strong A2 condition or As2:
[ω]As2
:= supR
(1|R|
∫Rω dx
)(1|R|
∫Rω−1 dx
)<∞
where the sup is taken over all rectangles with sides parallel tothe coordinate axes.
R. G. Durán Métodos mixtos para problemas degenerados
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ANISOTROPIC WEIGHTED ESTIMATES
Consider an arbitrary rectangle
R = [a1,b1]× · · · × [an,bn] hi = bi − ai
di(x) := min(bi − xi), (xi − ai).
It is known that the constant in the improved Poincaré inequalityfor R blows up when the ratio between outer and inner diametergoes to infinity.
However, we have the following anisotropic version if the weightbelongs to the smaller class As
2.
R. G. Durán Métodos mixtos para problemas degenerados
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ANISOTROPIC WEIGHTED ESTIMATES
Consider an arbitrary rectangle
R = [a1,b1]× · · · × [an,bn] hi = bi − ai
di(x) := min(bi − xi), (xi − ai).
It is known that the constant in the improved Poincaré inequalityfor R blows up when the ratio between outer and inner diametergoes to infinity.
However, we have the following anisotropic version if the weightbelongs to the smaller class As
2.
R. G. Durán Métodos mixtos para problemas degenerados
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ANISOTROPIC WEIGHTED ESTIMATES
Consider an arbitrary rectangle
R = [a1,b1]× · · · × [an,bn] hi = bi − ai
di(x) := min(bi − xi), (xi − ai).
It is known that the constant in the improved Poincaré inequalityfor R blows up when the ratio between outer and inner diametergoes to infinity.
However, we have the following anisotropic version if the weightbelongs to the smaller class As
2.
R. G. Durán Métodos mixtos para problemas degenerados
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ANISOTROPIC WEIGHTED ESTIMATES
For ω ∈ As2,
‖v − vR‖L2ω(R) ≤ Cω
n∑i=1
∥∥∥∥di∂v∂xi
∥∥∥∥L2ω(R)
Indeed, it follows immediately from the improved Poincaréinequality that, if Q is the unitary cube,
‖v − vQ‖L2ω(Q) ≤ Cω
n∑i=1
∥∥∥∥di∂v∂xi
∥∥∥∥L2ω(Q)
Then, the above anisotropic version for R follows by standardarguments making the change of variables xi = hi xi and usingthat, for ω(x) := ω(x), ω ∈ As
2 =⇒ ω ∈ As2.
R. G. Durán Métodos mixtos para problemas degenerados
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ANISOTROPIC WEIGHTED ESTIMATES
For ω ∈ As2,
‖v − vR‖L2ω(R) ≤ Cω
n∑i=1
∥∥∥∥di∂v∂xi
∥∥∥∥L2ω(R)
Indeed, it follows immediately from the improved Poincaréinequality that, if Q is the unitary cube,
‖v − vQ‖L2ω(Q) ≤ Cω
n∑i=1
∥∥∥∥di∂v∂xi
∥∥∥∥L2ω(Q)
Then, the above anisotropic version for R follows by standardarguments making the change of variables xi = hi xi and usingthat, for ω(x) := ω(x), ω ∈ As
2 =⇒ ω ∈ As2.
R. G. Durán Métodos mixtos para problemas degenerados
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ANISOTROPIC WEIGHTED ESTIMATES
For ω ∈ As2,
‖v − vR‖L2ω(R) ≤ Cω
n∑i=1
∥∥∥∥di∂v∂xi
∥∥∥∥L2ω(R)
Indeed, it follows immediately from the improved Poincaréinequality that, if Q is the unitary cube,
‖v − vQ‖L2ω(Q) ≤ Cω
n∑i=1
∥∥∥∥di∂v∂xi
∥∥∥∥L2ω(Q)
Then, the above anisotropic version for R follows by standardarguments making the change of variables xi = hi xi and usingthat, for ω(x) := ω(x), ω ∈ As
2 =⇒ ω ∈ As2.
R. G. Durán Métodos mixtos para problemas degenerados
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GENERALIZED WEIGHTED POINCARÉINEQUALITIES
For ω ∈ As2 and F the face contained in x1 = a1 we have
‖v − vF‖L2ω(R) ≤ Cω
∥∥∥∥(b1 − x1)∂v∂x1
∥∥∥∥L2ω(R)
+n∑
i=2
∥∥∥∥di∂v∂xi
∥∥∥∥L2ω(R)
Proof:
By a simple integration by parts we have
1|F |
∫F
v dS =1|R|
∫R
v dx +1|R|
∫R
(x1 − b1)∂v∂x1
dx
R. G. Durán Métodos mixtos para problemas degenerados
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GENERALIZED WEIGHTED POINCARÉINEQUALITIES
For ω ∈ As2 and F the face contained in x1 = a1 we have
‖v − vF‖L2ω(R) ≤ Cω
∥∥∥∥(b1 − x1)∂v∂x1
∥∥∥∥L2ω(R)
+n∑
i=2
∥∥∥∥di∂v∂xi
∥∥∥∥L2ω(R)
Proof:
By a simple integration by parts we have
1|F |
∫F
v dS =1|R|
∫R
v dx +1|R|
∫R
(x1 − b1)∂v∂x1
dx
R. G. Durán Métodos mixtos para problemas degenerados
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GENERALIZED WEIGHTED POINCARÉINEQUALITIES
Then,
v − vF = v − vR −1|R|
∫R
(x1 − b1)∂v∂x1
dx
and therefore,
‖v−vF‖L2ω(R) ≤ ‖v−vR‖L2
ω(R)+
∫R
(b1−x1)
∣∣∣∣ ∂v∂x1
∣∣∣∣ dx1|R|
(∫Rω dx
)1/2
but, multiplying and dividing by ω1/2 and using the Schwarzinequality we obtain∫
R(b1 − x1)
∣∣∣∣ ∂v∂x1
∣∣∣∣ dx ≤∥∥∥∥(b1 − x1)
∂v∂x1
∥∥∥∥L2ω(R)
(∫Rω−1 dx
)1/2
R. G. Durán Métodos mixtos para problemas degenerados
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GENERALIZED WEIGHTED POINCARÉINEQUALITIES
then,
‖v − vF‖L2ω(R) ≤ ‖v − vR‖L2
ω(R) + [ω]1/2As
2
∥∥∥∥(b1 − x1)∂v∂x1
∥∥∥∥L2ω(R)
and therefore
‖v − vF‖L2ω(R) ≤ Cω
∥∥∥∥(b1 − x1)∂v∂x1
∥∥∥∥L2ω(R)
+n∑
i=2
∥∥∥∥di∂v∂xi
∥∥∥∥L2ω(R)
R. G. Durán Métodos mixtos para problemas degenerados
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GENERALIZED WEIGHTED POINCARÉINEQUALITIES
then,
‖v − vF‖L2ω(R) ≤ ‖v − vR‖L2
ω(R) + [ω]1/2As
2
∥∥∥∥(b1 − x1)∂v∂x1
∥∥∥∥L2ω(R)
and therefore
‖v − vF‖L2ω(R) ≤ Cω
∥∥∥∥(b1 − x1)∂v∂x1
∥∥∥∥L2ω(R)
+n∑
i=2
∥∥∥∥di∂v∂xi
∥∥∥∥L2ω(R)
R. G. Durán Métodos mixtos para problemas degenerados
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ERROR ESTIMATES FOR RT INTERPOLATION
Since σj − Πσj has vanishing mean value on the face definedby xj = aj we obtain the following error estimate for theRaviart-Thomas interpolation of lowest order:
For ω ∈ As2 and 1 ≤ j ≤ n,
‖σj − Πhσj‖L2ω(R) ≤ Cω
n∑i=1
∥∥∥∥(bi − ai)∂σj
∂xi
∥∥∥∥L2ω(R)
R. G. Durán Métodos mixtos para problemas degenerados
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ERROR ESTIMATES FOR RT INTERPOLATION
Since σj − Πσj has vanishing mean value on the face definedby xj = aj we obtain the following error estimate for theRaviart-Thomas interpolation of lowest order:
For ω ∈ As2 and 1 ≤ j ≤ n,
‖σj − Πhσj‖L2ω(R) ≤ Cω
n∑i=1
∥∥∥∥(bi − ai)∂σj
∂xi
∥∥∥∥L2ω(R)
R. G. Durán Métodos mixtos para problemas degenerados
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ANISOTROPIC ELEMENTS
Question: which ω are in As2?
ω ∈ As2 iff w belongs to A2 of one variable for each variable
uniformly in the other variables (Kurtz).
Observe that this is the case for the weight yα, −1 < α < 1appearing in the fractional laplacian.
Or more generally,
ω(x) = ω1(x1) · · ·ωn(xn)
withωi(xi) ∈ A2(R)
R. G. Durán Métodos mixtos para problemas degenerados
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ANISOTROPIC ELEMENTS
Question: which ω are in As2?
ω ∈ As2 iff w belongs to A2 of one variable for each variable
uniformly in the other variables (Kurtz).
Observe that this is the case for the weight yα, −1 < α < 1appearing in the fractional laplacian.
Or more generally,
ω(x) = ω1(x1) · · ·ωn(xn)
withωi(xi) ∈ A2(R)
R. G. Durán Métodos mixtos para problemas degenerados
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ANISOTROPIC ELEMENTS
Question: which ω are in As2?
ω ∈ As2 iff w belongs to A2 of one variable for each variable
uniformly in the other variables (Kurtz).
Observe that this is the case for the weight yα, −1 < α < 1appearing in the fractional laplacian.
Or more generally,
ω(x) = ω1(x1) · · ·ωn(xn)
withωi(xi) ∈ A2(R)
R. G. Durán Métodos mixtos para problemas degenerados
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ANISOTROPIC ELEMENTS
Question: which ω are in As2?
ω ∈ As2 iff w belongs to A2 of one variable for each variable
uniformly in the other variables (Kurtz).
Observe that this is the case for the weight yα, −1 < α < 1appearing in the fractional laplacian.
Or more generally,
ω(x) = ω1(x1) · · ·ωn(xn)
withωi(xi) ∈ A2(R)
R. G. Durán Métodos mixtos para problemas degenerados
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RIGHT INVERSE OF THE DIVERGENCE
To finish the error analysis we need also to show the existenceof a solution of
div τ = v
satisfying‖τ‖H1
ω(Ω) ≤ C‖v‖L2ω(Ω)
But, the same representation formula given above define theBogovski solution:
τ (x) =
∫Ω
G(x , y)v(y) dy
The estimate for ‖τ‖H1ω(Ω) can be proved using the continuity of
Calderón-Zygmund integral operators in weighted norms for A2weights.
R. G. Durán Métodos mixtos para problemas degenerados
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RIGHT INVERSE OF THE DIVERGENCE
To finish the error analysis we need also to show the existenceof a solution of
div τ = v
satisfying‖τ‖H1
ω(Ω) ≤ C‖v‖L2ω(Ω)
But, the same representation formula given above define theBogovski solution:
τ (x) =
∫Ω
G(x , y)v(y) dy
The estimate for ‖τ‖H1ω(Ω) can be proved using the continuity of
Calderón-Zygmund integral operators in weighted norms for A2weights.
R. G. Durán Métodos mixtos para problemas degenerados
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RIGHT INVERSE OF THE DIVERGENCE
To finish the error analysis we need also to show the existenceof a solution of
div τ = v
satisfying‖τ‖H1
ω(Ω) ≤ C‖v‖L2ω(Ω)
But, the same representation formula given above define theBogovski solution:
τ (x) =
∫Ω
G(x , y)v(y) dy
The estimate for ‖τ‖H1ω(Ω) can be proved using the continuity of
Calderón-Zygmund integral operators in weighted norms for A2weights.
R. G. Durán Métodos mixtos para problemas degenerados
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ERROR ESTIMATES
In conclusion we obtain the forllowing error estimates for theRT0 approximation of
−div (ω∇u) = g in Ωu = 0 on ΓD
−ω∇u · n = f on ΓN
‖σ − σh‖2L2ω−1 (Ω)
≤ Cω
∑R∈Th
n∑i=1
∥∥∥∥(bi − xi)∂σ
∂xi
∥∥∥∥2
L2ω−1 (R)
or
‖σ − σh‖2L2ω−1 (Ω)
≤ Cω
∑R∈Th
n∑i=1
h2i
∥∥∥∥∂σ∂xi
∥∥∥∥2
L2ω−1 (R)
R. G. Durán Métodos mixtos para problemas degenerados
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FRACTIONAL LAPLACIAN
For this case we can prove that, if Ω is convex, fori , j = 1, · · · ,n,
∂σn+1
∂y,∂σn+1
∂xj,∂σi
∂xj∈ L2
y−α
while, for i = 1, · · · ,n
∂σi
∂y∈ L2
y−α+β
for β > 1− α.Therefore, we can obtain optimal order convergence using agraded mesh.
R. G. Durán Métodos mixtos para problemas degenerados
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FRACTIONAL LAPLACIAN
We use ∫|Dσ|2y−α+β ≤ C
for β > 1− α.
For the elements in the first band R = Rx × [0, y1] we use
‖σ − Πhσ‖2L2y−α
(R)≤ h2−β
1
∫|Dσ|2y−α+β
and we choose h1 = h2
2−β .
R. G. Durán Métodos mixtos para problemas degenerados
![Page 155: Métodos de elementos finitos mixtos para problemas no ... PDFs/Duran...Title Métodos de elementos finitos mixtos para problemas no uniformemente elípticos Author Ricardo G. Durán](https://reader036.fdocumentos.tips/reader036/viewer/2022081400/607a011d28dc4a58853c74e6/html5/thumbnails/155.jpg)
FRACTIONAL LAPLACIAN
For the rest of the elements R = Rx × [yj , yj+1] we chooseyj+1 = yj + hyγj
‖σ − Πhσ‖2L2y−α
(R)≤ (yj+1 − yj)
2∫|Dσ|2y−α dy
≤ h2y2γj
∫|Dσ|2y−α dy ≤ h2
∫|Dσ|2y−α+2γ dy
We have to choose γ = β/2. But we need also γ < 1.Then, we have to take1−α
2 < γ < 1
Remark: h ∼ 1/N where N is the number of nodes in the ydirection, i.e., the error estimate is optimal with respect to thenumber of nodes.
R. G. Durán Métodos mixtos para problemas degenerados
![Page 156: Métodos de elementos finitos mixtos para problemas no ... PDFs/Duran...Title Métodos de elementos finitos mixtos para problemas no uniformemente elípticos Author Ricardo G. Durán](https://reader036.fdocumentos.tips/reader036/viewer/2022081400/607a011d28dc4a58853c74e6/html5/thumbnails/156.jpg)
FRACTIONAL LAPLACIAN
For the rest of the elements R = Rx × [yj , yj+1] we chooseyj+1 = yj + hyγj
‖σ − Πhσ‖2L2y−α
(R)≤ (yj+1 − yj)
2∫|Dσ|2y−α dy
≤ h2y2γj
∫|Dσ|2y−α dy ≤ h2
∫|Dσ|2y−α+2γ dy
We have to choose γ = β/2. But we need also γ < 1.Then, we have to take1−α
2 < γ < 1
Remark: h ∼ 1/N where N is the number of nodes in the ydirection, i.e., the error estimate is optimal with respect to thenumber of nodes.
R. G. Durán Métodos mixtos para problemas degenerados
![Page 157: Métodos de elementos finitos mixtos para problemas no ... PDFs/Duran...Title Métodos de elementos finitos mixtos para problemas no uniformemente elípticos Author Ricardo G. Durán](https://reader036.fdocumentos.tips/reader036/viewer/2022081400/607a011d28dc4a58853c74e6/html5/thumbnails/157.jpg)
END
MUCHAS GRACIAS !
R. G. Durán Métodos mixtos para problemas degenerados