mirror of
https://github.com/JuliaFEM/JuliaFEM.jl.git
synced 2026-09-19 01:48:47 +00:00
Jukka Aho
d428686658
Align `update_geometry_cache!` with element caches that carry continuum-specific data and surface scalar basis values needed for mass kernels. - Remove unused `kernel::AbstractKernel` parameter and narrow `element_cache` to `ContinuumElementCache`. - Evaluate `get_basis_functions` each IP, storing `N_data` beside `∇N_data`. - Rewrite docstring around concrete fields (`X`, `N_data`, `∇N_data`, `detJ_w`) and zero-allocation guarantees.
73 lines
2.2 KiB
Julia
73 lines
2.2 KiB
Julia
# This file is a part of JuliaFEM.
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# License is MIT: see https://github.com/JuliaFEM/JuliaFEM.jl/blob/master/LICENSE.md
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"""
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Geometry cache update functions for continuum elements.
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Extracts node coordinates and computes physical gradients and Jacobian data.
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"""
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using Tensors
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"""
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update_geometry_cache!(geometry_cache, element_cache, elem_id, mesh) -> Nothing
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Update `geometry_cache` for the element `elem_id` of `mesh`. The cache
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fields written are:
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- `geometry_cache.X` — node coordinates (one entry per element node)
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- `geometry_cache.N_data[ip, k]` — basis values
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- `geometry_cache.∇N_data[ip, k]` — physical gradients `∇N`
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- `geometry_cache.detJ_w[ip]` — `det(J) * w` for integration
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The function is allocation-free; it reads topology, basis, and the
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integration points from `element_cache` and writes back into the
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pre-allocated `geometry_cache` arrays. For each integration point the
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Jacobian `J = X ⊗ ∇_ξ N` is built on the fly, then physical gradients
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are obtained via `J^{-T} · ∇_ξ N`.
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"""
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@inline function update_geometry_cache!(
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geometry_cache::GeometryCache,
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element_cache::ContinuumElementCache,
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elem_id::Int,
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mesh::AbstractMesh,
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)
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conn = mesh.connectivity[elem_id]
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nnodes = length(conn)
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# Extract node coordinates (mesh.nodes already contains Vec{3}).
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# Indexed loop avoids the iterator allocation that `enumerate` introduces.
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@inbounds for i in 1:nnodes
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node = conn[i]
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geometry_cache.X[i] = mesh.nodes[node]
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end
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ips = element_cache.ips
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nips = length(ips)
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@inbounds for ip_idx in 1:nips
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ip = ips[ip_idx]
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ξ = ip.coords
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N_vals = get_basis_functions( element_cache.topology, element_cache.basis, ξ)
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dN_dξ = get_basis_derivatives(element_cache.topology, element_cache.basis, ξ)
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# Jacobian J = X ⊗ ∇_ξ N
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J = geometry_cache.X[1] ⊗ dN_dξ[1]
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for i in 2:nnodes
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J += geometry_cache.X[i] ⊗ dN_dξ[i]
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end
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J_inv_T = transpose(inv(J))
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for k in 1:nnodes
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geometry_cache.N_data[ip_idx, k] = N_vals[k]
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geometry_cache.∇N_data[ip_idx, k] = J_inv_T ⋅ dN_dξ[k]
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end
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geometry_cache.detJ_w[ip_idx] = det(J) * ip.weight
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end
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return nothing
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end
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