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substructuring, fixed tests, possibility to save to integration points

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Jukka Aho
2015-11-30 16:04:13 +02:00
parent 38239bfa20
commit 458caa4757
18 changed files with 371 additions and 530 deletions
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test/test_basis.jl
+42 -43
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@@ -6,93 +6,94 @@ module BasisTests
using JuliaFEM.Test
using JuliaFEM
using JuliaFEM: Basis, Field
using JuliaFEM: Increment, TimeStep
using JuliaFEM: AbstractElement, Element
function get_basis()
import JuliaFEM: get_basis, get_dbasis
basis(xi) = 1/4*[
abstract TestElement <: AbstractElement
function get_basis(::Type{TestElement}, xi::Vector{Float64})
1/4*[
(1-xi[1])*(1-xi[2])
(1+xi[1])*(1-xi[2])
(1+xi[1])*(1+xi[2])
(1-xi[1])*(1+xi[2])]'
dbasis(xi) = 1/4*[
end
function get_dbasis(::Type{TestElement}, xi::Vector{Float64})
1/4*[
-(1-xi[2]) (1-xi[2]) (1+xi[2]) -(1+xi[2])
-(1-xi[1]) -(1+xi[1]) (1+xi[1]) (1-xi[1])]
end
return Basis(basis, dbasis)
function get_element()
element = Element{TestElement}([1, 2, 3, 4])
element["geometry"] = Vector{Float64}[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0]]
element["temperature"] = Float64[1.0, 2.0, 3.0, 4.0]
element["displacement1"] = Vector{Float64}[[0.0, 0.0], [0.0, 0.0], [1/4, 0.0], [0.0, 0.0]]
element["displacement2"] = Vector{Float64}[[0.0, 0.0], [1.0, -1.0], [2.0, 3.0], [0.0, 0.0]]
return element
end
### Test interpolation in spatial domain
function test_basis_interpolation()
N = get_basis()
@test N([0.0, 0.0]) == 1/4*[1 1 1 1]
@test N([0.0, 0.0], 1.0) == 1/4*[1 1 1 1]
element = get_element()
info(element([0.0, 0.0]))
@test element([0.0, 0.0]) == 1/4*[1 1 1 1]
@test element([0.0, 0.0], 1.0) == 1/4*[1 1 1 1]
end
function test_basis_gradient_interpolation()
X = Increment([0.0 0.0; 1.0 0.0; 1.0 1.0; 0.0 1.0]')
# P(X) = [1.0, X[1], X[2], X[1]*X[2]]
# basis2, dbasis2 = JuliaFEM.calculate_lagrange_basis(P, X)
N = get_basis()
gradN = N(X, [0.0, 0.0], Val{:grad})
@test gradN == 1/2*[-1 1 1 -1; -1 -1 1 1]
# @test dN([0.0, 0.0]) == dbasis2([0.5, 0.5])
element = get_element()
grad = element([0.0, 0.0], Val{:grad})
info("grad = \n$grad")
@test grad == 1/2*[-1 1 1 -1; -1 -1 1 1]
end
function test_interpolation_of_scalar_increment_in_spatial_domain()
function test_interpolation_of_scalar_field_in_spatial_domain()
# in unit square: T(X,t) = t*(1 + X[1] + 3*X[2] - 2*X[1]*X[2])
element = get_element()
T_known(X) = 1 + X[1] + 3*X[2] - 2*X[1]*X[2]
T = Increment([1.0, 2.0, 3.0, 4.0])
N = get_basis()
T_interpolated = N(T, [0.0, 0.0])
T_interpolated = element("temperature", [0.0, 0.0])
@test T_interpolated == T_known([0.5, 0.5])
end
function test_interpolation_of_gradient_of_scalar_increment_in_spatial_domain()
function test_interpolation_of_gradient_of_scalar_field_in_spatial_domain()
# in unit square: grad(T)(X) = [1-2X[2], 3-2*X[1]]
X = Increment([0.0 0.0; 1.0 0.0; 1.0 1.0; 0.0 1.0]')
T = Increment([1.0, 2.0, 3.0, 4.0])
N = get_basis()
gradT = N(X, T, [0.0, 0.0], Val{:grad})
element = get_element()
gradT = element("temperature", [0.0, 0.0], Val{:grad})
gradT_expected(X) = [1-2*X[2] 3-2*X[1]]
@test gradT == gradT_expected([0.5, 0.5])
end
function test_interpolation_of_vector_field()
# in unit square, u(X,t) = [1/4*t*X[1]*X[2], 0, 0]
geometry = Increment([0.0 0.0; 1.0 0.0; 1.0 1.0; 0.0 1.0]')
displacement = Increment(Vector{Float64}[[0.0, 0.0], [0.0, 0.0], [1/4, 0.0], [0.0, 0.0]])
N = get_basis()
X = N(geometry, [0.0, 0.0])
u = N(displacement, [0.0, 0.0])
x = X+u
element = get_element()
u = element("displacement1", [0.0, 0.0])
# x = X+u
u_expected(X) = [1/4*X[1]*X[2], 0]
@test isapprox(x, [9/16, 1/2])
# @test isapprox(x, [9/16, 1/2])
@test isapprox(u, u_expected([0.5, 0.5]))
end
function test_interpolation_of_gradient_of_vector_field()
# in unit square, u(X) = t*[X[1]*(X[2]+1), X[1]*(4*X[2]-1)]
# => u_i,j = t*[X[2]+1 X[1]; 4*X[2]-1 4*X[1]]
X = Increment([0.0 0.0; 1.0 0.0; 1.0 1.0; 0.0 1.0]')
element = get_element()
# displacement = Field(
# (0.5, Vector[[0.0, 0.0], [0.5, -0.5], [1.0, 1.5], [0.0, 0.0]]),
# (1.5, Vector[[0.0, 0.0], [1.5, -1.5], [3.0, 4.5], [0.0, 0.0]]))
u = Increment([0.0 0.0; 1.0 -1.0; 2.0 3.0; 0.0 0.0]')
N = get_basis()
gradu(xi) = N(X, u, xi, Val{:grad})
gradu = element("displacement2", [0.0, 0.0], Val{:grad})
gradu_expected(X) = [X[2]+1 X[1]; 4*X[2]-1 4*X[1]]
@test isapprox(gradu([0.0, 0.0]), gradu_expected([0.5, 0.5]))
@test isapprox(gradu, gradu_expected([0.5, 0.5]))
end
### Test interpolation in time domain
#=
function test_linear_time_extrapolation_of_field()
#T_known(X,t) = t*(1 + X[1] + 3*X[2] - 2*X[1]*X[2])
T = Field(
@@ -188,8 +189,6 @@ function test_derivative_interpolation_in_temporal_basis_in_variable_velocity_ch
@test isa(velocity, Increment) == true
end
#=
function test_time_derivative_gradient_interpolation_of_field()
# in unit square, u(X) = t*[X[1]*(X[2]+1), X[1]*(4*X[2]-1)]
# => u_i,j = t*[X[2]+1 X[1]; 4*X[2]-1 4*X[1]]