Comments (2)
This says there are two separate inputs, each with one evaluation mode
inputs = [
OperatorField(basis, [EvaluationMode.interpolation], "adv"),
OperatorField(basis, [EvaluationMode.gradient], "gradent of deformation"),
OperatorField(basis, [EvaluationMode.quadratureweights], "quadrature weights"),
]
I think you need
inputs = [
OperatorField(basis, [EvaluationMode.interpolation, EvaluationMode.gradient], "adv and gradent of deformation"),
OperatorField(basis, [EvaluationMode.quadratureweights], "quadrature weights"),
]
That will combine the first two inputs in the weak form. Something like this, I think
function advdiffusionweakform(udu::Array{Float64}, w::Array{Float64})
u = udu[1]
du = udu[2:end]
dv = parameters.wind * u * w[1] + du * w[1]
return [dv]
end
from lfatoolkit.jl.
Thanks, that works!
I also found a similar example in the advection_supg, which uses Matrix{Float64} in the weakform function. Somehow that only works for 1D problem.
from lfatoolkit.jl.
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