mirror of
https://github.com/JuliaFEM/JuliaFEM.jl.git
synced 2026-08-13 23:54:18 +00:00
Jukka Aho
90 lines
2.8 KiB
Julia
90 lines
2.8 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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using JuliaFEM
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using JuliaFEM.Test
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function test_linearsolver()
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el1 = Quad4([1, 2, 3, 4])
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el1["geometry"] = Vector[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0]]
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el1["temperature thermal conductivity"] = 6.0
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el1["density"] = 36.0
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el2 = Seg2([1, 2])
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el2["geometry"] = Vector[[0.0, 0.0], [1.0, 0.0]]
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el2["temperature flux"] = (
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(0.0 => 0.0),
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(1.0 => 600.0)
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)
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field_problem = HeatProblem()
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push!(field_problem, el1)
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push!(field_problem, el2)
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el3 = Seg2([3, 4])
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el3["geometry"] = Vector[[1.0, 1.0], [0.0, 1.0]]
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el3["temperature"] = 0.0
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boundary_problem = DirichletProblem("temperature", 1)
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push!(boundary_problem, el3)
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# Create a solver for a set of problems
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solver = LinearSolver()
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push!(solver, field_problem)
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push!(solver, boundary_problem)
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# Solve problem at time t=1.0 and update fields
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solver(1.0)
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# Postprocess.
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# Interpolate temperature field along boundary of Γ₁ at time t=1.0
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xi = [0.0, -1.0]
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X = el2("geometry", xi, 1.0)
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T = el2("temperature", xi, 1.0)
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info("Temperature at point X = $X is T = $T")
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@test isapprox(T, 100.0)
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end
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function test_solvers()
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K = [
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440.0 150.0 -260.0 -30.0 40.0 30.0 -220.0 -150.0
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150.0 440.0 30.0 40.0 -30.0 -260.0 -150.0 -220.0
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-260.0 30.0 440.0 -150.0 -220.0 150.0 40.0 -30.0
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-30.0 40.0 -150.0 440.0 150.0 -220.0 30.0 -260.0
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40.0 -30.0 -220.0 150.0 440.0 -150.0 -260.0 30.0
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30.0 -260.0 150.0 -220.0 -150.0 440.0 -30.0 40.0
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-220.0 -150.0 40.0 30.0 -260.0 -30.0 440.0 150.0
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-150.0 -220.0 -30.0 -260.0 30.0 40.0 150.0 440.0]
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C = 1/3*[
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1.0 0.0 0.0 0.0 0.5 0.0 0.0 0.0
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0.0 1.0 0.0 0.0 0.0 0.5 0.0 0.0
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0.0 0.0 1.0 0.0 0.0 0.0 0.5 0.0
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0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.5
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0.5 0.0 0.0 0.0 1.0 0.0 0.0 0.0
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0.0 0.5 0.0 0.0 0.0 1.0 0.0 0.0
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0.0 0.0 0.5 0.0 0.0 0.0 1.0 0.0
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0.0 0.0 0.0 0.5 0.0 0.0 0.0 1.0]
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f = zeros(8)
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g = 1/100 * [-5.0, 5.0, 10.0, -10.0, -5.0, 5.0, 10.0, -10.0]
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K = sparse(K)
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C = sparse(C)
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f = sparse(f)
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g = sparse(g)
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expected = [-0.1, 0.1, 0.2, -0.2, -0.1, 0.1, 0.2, -0.2]
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u1, la1 = solve(K, f, C, g, Val{:UMFPACK})
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@test isapprox(u1, expected)
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u2, la2 = solve(K, f, C, g, Val{:CHOLMOD})
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@test isapprox(u2, expected)
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# FIXME: how to dynamically include packages only if they are installed?
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#include(Pkg.dir("JuliaFEM"*"/src/petsc.jl"))
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u3, la3 = solve(K, f, C, g, Val{:PETSc_GMRES})
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@test isapprox(u3, expected)
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end
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