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Truncate the SVD in the least-squares Kulfan fit so crowded stations give bounded weights #342

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Truncate the SVD in the least-squares Kulfan fit so crowded stations give bounded weights #342

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Truncate the SVD in the least-squares Kulfan fit
1-Bort-1 Sep 16, 2026
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Merge branch 'main' into agent/295-the-kulfan-least-squares-fit-has-n…
1-Bort-1 Sep 17, 2026
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4 changes: 4 additions & 0 deletions CHANGELOG.md
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Expand Up @@ -20,6 +20,10 @@

- The `VSMSolution` docstring gives `lift_dist`, `drag_dist` and `panel_moment_dist` in
the per-unit-span units they hold, [N/m] and [Nm/m], instead of [N] and [Nm].
- `fit_kulfan_parameters` with `LeastSquaresFit` drops singular values below `1e-4`
times the largest, so a contour whose stations crowd into a narrow band of the chord
fits to an airfoil-sized shape instead of weights that resample it to 1e4 scale.

@1-Bort-1 1-Bort-1 Sep 16, 2026

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MINOR: The entry says a crowded contour now fits to an airfoil-sized shape, but the card's own table shows the 0.03-band case still comes out 15× too thick. The entry should say the weights are bounded, not that the shape is correct, or users will trust sections that are still wrong.

Fits of well-spread stations are unchanged.

## VortexStepMethod v5.1.1 2026-09-12

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10 changes: 6 additions & 4 deletions src/airfoil_aero/kulfan.jl
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Expand Up @@ -106,6 +106,8 @@ function leading_edge_basis(x::AbstractVector{T}, n_weights::Int) where T
return x .* max.(1 .- x, zero(T)).^(n_weights + 0.5)
end

const KULFAN_FIT_RTOL = 1e-4 # [-] singular values dropped below this times the largest

"""
fit_kulfan_parameters(x::Vector, y::Vector, method::KulfanFitMethod)
fit_kulfan_parameters(x::Vector, y::Vector; n_weights=8)
Expand All @@ -128,7 +130,8 @@ end

Least-squares fit matching AeroSandbox's `get_kulfan_parameters`: both surfaces
share a single least-squares system with a shared leading-edge weight and a
trailing-edge thickness.
trailing-edge thickness. Singular values below `1e-4` times the largest are dropped, so
stations crowded into part of the chord give bounded weights.
"""
function fit_kulfan_parameters(x::Vector{T}, y::Vector{T},
method::LeastSquaresFit) where T
Expand All @@ -144,12 +147,11 @@ function fit_kulfan_parameters(x::Vector{T}, y::Vector{T},
te_col = ifelse.(is_upper, xv ./ 2, .-xv ./ 2)

A = hcat((.!is_upper) .* CS, is_upper .* CS, le_col, te_col)
coeffs = A \ y_norm
coeffs = pinv(A; rtol=KULFAN_FIT_RTOL) * y_norm

@1-Bort-1 1-Bort-1 Sep 16, 2026

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MINOR: Truncation happens silently, so a degenerate contour now gives a plausible-looking but wrong section instead of an obviously broken one, and nothing downstream checks it. Without the resampler or thickness fixes in this branch or a tracked issue for them, the failure gets harder to spot.

TE_thickness = coeffs[end]

if TE_thickness < 0
A = hcat((.!is_upper) .* CS, is_upper .* CS, le_col)
coeffs = A \ y_norm
coeffs = pinv(A[:, 1:end-1]; rtol=KULFAN_FIT_RTOL) * y_norm
TE_thickness = zero(T)
end

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12 changes: 12 additions & 0 deletions test/airfoil_aero/test_airfoil_aero.jl
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Expand Up @@ -43,6 +43,18 @@ end
@test params.TE_thickness ≈ 0.0 atol = 1e-12
end

@testset "Fit to stations crowded into a narrow band stays airfoil-sized" begin
spread = (1 .- cos.(range(0, pi, 121))) ./ 2
crowded = vcat(0.0, range(0.30, 0.31, 118), 1.0)
surface(weights, xs) = class_function(xs) .* (bernstein_basis(xs, 7) * weights)
y_upper = surface(fill(0.2, 8), crowded) .+ 0.005 .* sin.(40pi .* crowded)
y_lower = surface(fill(-0.1, 8), spread)
x = vcat(reverse(crowded), spread[2:end])
y = vcat(reverse(y_upper), y_lower[2:end])
_, y_fit = kulfan_to_coordinates(fit_kulfan_parameters(x, y))
@test maximum(abs, y_fit) < 2 * maximum(abs, y)
end

@testset "Shrink-wrap encloses points with clearance" begin
xn, yn, _ = normalize_airfoil(collect(float.(xr)), collect(float.(yr)))
cloud_to_wrap(xw, yw) = minimum(
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