mirror of
https://github.com/JuliaFEM/JuliaFEM.jl.git
synced 2026-08-06 04:21:33 +00:00
Jukka Aho
bec6642693
Now assemble! takes a vector of elements as input. This makes it possible to preallocate memory for common matrices making code super fast.
48 lines
1.5 KiB
Julia
48 lines
1.5 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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# http://ahojukka5.github.io/posts/finite-element-solution-for-one-element-problem/
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using JuliaFEM
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using JuliaFEM.Testing
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@testset "test 2d linear elasticity local matrices" begin
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element = Element(Quad4, [1, 2, 3, 4])
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X = Dict{Int64, Vector{Float64}}(
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1 => [0.0, 0.0],
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2 => [1.0, 0.0],
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3 => [1.0, 1.0],
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4 => [0.0, 1.0])
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u = Dict{Int64, Vector{Float64}}(
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1 => [0.0, 0.0],
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2 => [0.0, 0.0],
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3 => [0.0, 0.0],
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4 => [0.0, 0.0])
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update!(element, "geometry", X)
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update!(element, "displacement", u)
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update!(element, "youngs modulus" => 288.0, "poissons ratio" => 1/3)
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update!(element, "displacement load", DCTI([4.0, 8.0]))
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problem = Problem(Elasticity, "[0x1] x [0x1] block", 2)
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update!(problem.properties, "formulation" => "plane_stress")
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add_elements!(problem, [element])
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assemble!(problem)
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K = full(problem.assembly.K)
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f = vec(full(problem.assembly.f))
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K_expected = [
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144 54 -90 0 -72 -54 18 0
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54 144 0 18 -54 -72 0 -90
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-90 0 144 -54 18 0 -72 54
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0 18 -54 144 0 -90 54 -72
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-72 -54 18 0 144 54 -90 0
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-54 -72 0 -90 54 144 0 18
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18 0 -72 54 -90 0 144 -54
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0 -90 54 -72 0 18 -54 144]
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f_expected = [1, 2, 1, 2, 1, 2, 1, 2]
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@test isapprox(K, K_expected)
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@test isapprox(f, f_expected)
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end
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