mirror of
https://github.com/JuliaFEM/JuliaFEM.jl.git
synced 2026-09-01 00:36:24 +00:00
Jukka Aho
86 lines
2.3 KiB
Julia
86 lines
2.3 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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abstract AbstractProblem
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type FieldProblem{T<:AbstractProblem}
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name :: ASCIIString
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dim :: Int
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elements :: Vector{Element}
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end
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type BoundaryProblem{T<:AbstractProblem}
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name :: ASCIIString
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parent_field_name :: ASCIIString
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parent_field_dim :: Int
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dim :: Int
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elements :: Vector{Element}
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end
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typealias Problem FieldProblem
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typealias AllProblems Union{FieldProblem, BoundaryProblem}
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function get_elements(problem::AllProblems)
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return problem.elements
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end
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""" Return the dimension of the unknown field of this problem. """
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function get_unknown_field_dimension(problem::Problem)
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return problem.dim
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end
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""" Return the name of the unknown field of this problem. """
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function get_unknown_field_name{P<:AbstractProblem}(problem::Problem{P})
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return get_unknown_field_name(P)
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end
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function Base.push!(problem::AllProblems, element::Element)
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push!(problem.elements, element)
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end
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# TODO: better place for utility functions?
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""" Calculate "nodal" vector from set of elements.
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For example element 1 with dofs [1, 2, 3, 4] has [1, 1, 1, 1] and
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element 2 with dofs [3, 4, 5, 6] has [2, 2, 2, 2] the result will
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be sparse matrix with values [1, 1, 3, 3, 2, 2].
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Parameters
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----------
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field_name
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name of field, e.g. "geometry"
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field_dim
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degrees of freedom / node
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elements
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elements used to calculate vector
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time
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"""
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function calculate_nodal_vector{T}(field_name::ASCIIString, field_dim::Int, elements::Vector{Element{T}}, time::Real)
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A = SparseMatrixCOO()
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b = SparseMatrixCOO()
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for element in elements
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haskey(element, field_name) || continue
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gdofs = get_gdofs(element, 1)
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# info("gdofs = $gdofs")
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for ip in get_integration_points(element, Val{2})
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J = get_jacobian(element, ip, time)
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w = ip.weight*norm(J)
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f = element(field_name, ip, time)
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N = element(ip, time)
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add!(A, gdofs, gdofs, w*kron(N', N))
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for dim=1:field_dim
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add!(b, gdofs, w*f[dim]*N, dim)
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end
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end
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end
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A = sparse(A)
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b = sparse(b)
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nz = sort(unique(rowvals(A)))
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x = zeros(size(b)...)
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x[nz, :] = A[nz,nz] \ b[nz, :]
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return vec(transpose(x))
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end
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