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Comments (2)

jeremylt avatar jeremylt commented on July 17, 2024

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.

yslan avatar yslan commented on July 17, 2024

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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