Mercurial > repos > public > sbplib_julia
diff src/SbpOperators/volumeops/laplace/laplace.jl @ 1751:f3d7e2d7a43f feature/sbp_operators/laplace_curvilinear
Merge feature/grids/manifolds
author | Jonatan Werpers <jonatan@werpers.com> |
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date | Wed, 11 Sep 2024 16:26:19 +0200 |
parents | 29b96fc75bee b5690ab5f0b8 |
children | 1f42944d4a72 |
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--- a/src/SbpOperators/volumeops/laplace/laplace.jl Mon Sep 09 09:01:57 2024 +0200 +++ b/src/SbpOperators/volumeops/laplace/laplace.jl Wed Sep 11 16:26:19 2024 +0200 @@ -83,7 +83,7 @@ condition. `H_tuning` and `R_tuning` are used to specify the strength of the penalty. -See also: [`sat`](@ref),[`DirichletCondition`](@ref), [`positivity_decomposition`](@ref). +See also: [`sat`](@ref), [`DirichletCondition`](@ref), [`positivity_decomposition`](@ref). """ function sat_tensors(Δ::Laplace, g::Grid, bc::DirichletCondition; H_tuning = 1., R_tuning = 1.) id = boundary(bc) @@ -92,7 +92,7 @@ Hᵧ = inner_product(boundary_grid(g, id), set) e = boundary_restriction(g, set, id) d = normal_derivative(g, set, id) - B = positivity_decomposition(Δ, g, bc; H_tuning, R_tuning) + B = positivity_decomposition(Δ, g, boundary(bc); H_tuning, R_tuning) penalty_tensor = H⁻¹∘(d' - B*e')∘Hᵧ return penalty_tensor, e end @@ -117,7 +117,7 @@ end """ - positivity_decomposition(Δ::Laplace, g::Grid, bc::DirichletCondition; H_tuning, R_tuning) + positivity_decomposition(Δ::Laplace, g::Grid, b::BoundaryIdentifier; H_tuning, R_tuning) Constructs the scalar `B` such that `d' - 1/2*B*e'` is symmetric positive definite with respect to the boundary quadrature. Here `d` is the normal @@ -125,28 +125,26 @@ to form a symmetric and energy stable penalty for a Dirichlet condition. The parameters `H_tuning` and `R_tuning` are used to specify the strength of the penalty and must be greater than 1. For details we refer to -https://doi.org/10.1016/j.jcp.2020.109294 +<https://doi.org/10.1016/j.jcp.2020.109294> """ -function positivity_decomposition(Δ::Laplace, g::Grid, bc::DirichletCondition; H_tuning, R_tuning) +function positivity_decomposition(Δ::Laplace, g::Grid, b::BoundaryIdentifier; H_tuning, R_tuning) @assert(H_tuning ≥ 1.) @assert(R_tuning ≥ 1.) - Nτ_H, τ_R = positivity_limits(Δ,g,bc) + Nτ_H, τ_R = positivity_limits(Δ,g,b) return H_tuning*Nτ_H + R_tuning*τ_R end -# TODO: We should consider implementing a proper BoundaryIdentifier for EquidistantGrid and then -# change bc::BoundaryCondition to id::BoundaryIdentifier -function positivity_limits(Δ::Laplace, g::EquidistantGrid, bc::DirichletCondition) +function positivity_limits(Δ::Laplace, g::EquidistantGrid, b::BoundaryIdentifier) h = spacing(g) θ_H = parse_scalar(Δ.stencil_set["H"]["closure"][1]) θ_R = parse_scalar(Δ.stencil_set["D2"]["positivity"]["theta_R"]) - τ_H = 1/(h*θ_H) - τ_R = 1/(h*θ_R) + τ_H = one(eltype(Δ))/(h*θ_H) + τ_R = one(eltype(Δ))/(h*θ_R) return τ_H, τ_R end -function positivity_limits(Δ::Laplace, g::TensorGrid, bc::DirichletCondition) - τ_H, τ_R = positivity_limits(Δ, g.grids[grid_id(boundary(bc))], bc) +function positivity_limits(Δ::Laplace, g::TensorGrid, b::BoundaryIdentifier) + τ_H, τ_R = positivity_limits(Δ, g.grids[grid_id(b)], b) return τ_H*ndims(g), τ_R end