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Conditional spatial finite-element rate for stochastic Galerkin

Statement

Assume the hypotheses of the stochastic Galerkin theorem with D⊂Rd, d≥2, and suppose the exact solution has the exact finite expansion u(y)=∑α∈Λuαψα(y),uα∈Hr(D)∩H01(D), for integers k≥0 and 1≤ℓ≤r≤k+1. Choose a fixed reference finite element whose polynomial space contains Pk and whose unisolvent degrees of freedom are bounded on Wℓ,2 of the reference cell; let its reference interpolant reproduce Pk and define local interpolants by affine pullback as in Local interpolation estimates on shape-regular affine meshes. Let {Th} be a shape-regular family of matching affine simplicial meshes as in Matching affine simplicial meshes and shape regularity, with maximum cell diameter h, and assume for each mesh that a globally conforming spatial interpolant Ih maps these coefficients into its finite-element space, restricts cellwise to those local interpolants, and preserves the zero boundary condition. These are the generic bounded-degree-of-freedom hypotheses of the local estimate. Then for the stochastic Galerkin solution UΛ,h, ∥u−UΛ,h∥Lρ2(H01(D))≤a∗a∗ Chr−1(∑α∈Λ∣uα∣Hr(D)2)1/2. The regularity and finite-expansion assumptions are explicit; this is not a general spatial rate for arbitrary random solutions.

Facts & Assumptions

Given: Uniform ellipticity, the exact finite expansion and coefficient regularity above, a shape-regular mesh, and a globally conforming interpolant with the stated cell restrictions.

[F1]

Stochastic Galerkin coercivity and Cea quasi-optimality gives the Galerkin error bounded by (a∗/a∗) times best approximation in the tensor space.

[F2]

Local interpolation estimates on shape-regular affine meshes with p=2, m=1, the fixed reference space containing Pk, bounded degrees of freedom on Wℓ,2, and ℓ≤r≤k+1 gives ∣v−IKv∣W1,2(K)≤ChKr−1∣v∣Wr,2(K). The generic theorem uses the boundedness hypothesis directly; the corollary does not infer nodal boundedness from point evaluation.

[F3]

Independent polynomial-chaos tensor products are orthonormal gives the orthonormal finite random basis.

Proof

1.1F3given

Define Wh(y)=∑α∈Λψα(y)Ihuα. Each interpolated coefficient belongs to the spatial finite-element subspace, so Wh∈VΛ,h. By [F3], orthogonality in the random variable gives ∥u−Wh∥Lρ2(V)2=∑α∈Λ∥uα−Ihuα∥V2.

1.2F2givenalgebra

For each coefficient and cell K, [F2] gives ∣uα−IKuα∣W1,2(K)≤ChKr−1∣uα∣Wr,2(K). Square, sum over the mesh cells, and use hK≤h to obtain ∥uα−Ihuα∥V≤Chr−1∣uα∣Hr(D). This uses the assumed cellwise conformity and disjoint cell interiors.

2.1F1step 1.1step 1.2algebra∎

Square the bounds from step 1.2, sum over the finite Λ, and use step 1.1 to get ∥u−Wh∥Lρ2(V)≤Chr−1(∑α∣uα∣Hr(D)2)1/2. Then [F1] bounds the Galerkin error by (a∗/a∗) times this particular approximation error, proving the claim.

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