potential_flow_joukowski — MATH complex op

• Data kinds: none → cimage (an op determined by its arguments alone — it takes no image or data input)

• Call: import fullseye as fs; fs.ledger.potential_flow_joukowski(alpha_deg=5.0, speed=1.0, chord_b=1.0, centre_offset=(-0.09+0.09j), centre=0j, half_width=3.0, shape=(256, 256)) (to call the implementation directly, import mathops; mathops.potential_flow_joukowski(alpha_deg=5.0, speed=1.0, chord_b=1.0, centre_offset=(-0.09+0.09j), centre=0j, half_width=3.0, shape=(256, 256)); from the registry, opsmath.get("potential_flow_joukowski"))

Usage

Inviscid flow past a Joukowski aerofoil, as a complex velocity field.

Returns the complex velocity `w(z) = dW/dz = u - i*v` sampled over a

window of the physical plane. Inside the solid body the field is set to

exactly `0 (there is no flow there), so field == 0` is the body mask

and nothing is silently `nan`.

The construction is the classical one: flow past a circle of radius

`a = |chord_b - centre_offset| centred at centre_offset`, plus the

circulation the Kutta condition demands, pushed through the Joukowski

map `z = zeta + chord_b**2 / zeta`. The window is inverted back to the

circle plane by choosing, of the two preimages, the one outside the circle.

★What makes this checkable rather than merely plotted:

• The field is holomorphic outside the body, so this family's own

`cplx_cr_residual` must read ~0 on it — an existing operator is the

oracle, and it is not the formula used to build the field.

• The Kutta condition is the whole point: `dW/dzeta` vanishes at the

trailing edge exactly where `dz/dzeta` does, so the velocity there

stays finite. Perturb the circulation by any amount and the trailing-edge

velocity diverges — the gate has a control group.

• `Re(closed integral of w dz)` around the body is the circulation, and

it is path independent (Cauchy) — a big rectangle and a small one

must agree.

• Far from the body `w -> speed * exp(-i*alpha), decaying like 1/|z|`.

• The zeroed region is the aerofoil, whose area the shoelace formula on

`cplx_joukowski` of the circle gives independently.

Parameters

----------

alpha_deg : float

Angle of attack in degrees.

speed : float > 0

Free-stream speed.

chord_b : float > 0

Half the flat-plate chord; the map is `zeta + chord_b**2/zeta`.

centre_offset : complex

Circle centre. Negative real part thickens, positive imaginary part

cambers. The default is a thin cambered section.

centre, half_width, shape :

The window in the physical plane, as in :func:cplx_plane_grid.

Raises `ValueError: speed <= 0`; non-finite angle; a circle that

does not enclose `-chord_b` (the image would fold over itself) or whose

centre is at or beyond `+chord_b`; degenerate window.

HALCON: no operator.

Family-wide input contract (fail-closed)

Every mathops op validates its input before computing (nothing slips through silently):

• **complex input raises ValueError** — coercing to float64 silently discards the imaginary part (numpy only emits a ComplexWarning and returns a plausible-looking wrong real number). State .real/.imag/abs() explicitly, or use complexops, which handles complex data.

• **masked arrays with masked elements raise ValueError** — the implicit conversion that peels off the mask and uses the raw values underneath is refused. Say explicitly whether to fill or to drop.

• **NaN/Inf raises ValueError on every input** (refused with the count stated — it propagates through the whole result).

• Shapes are strict: 1-D and 2-D are never implicitly promoted or broadcast (a matrix in a vector slot, or a vector in a matrix slot, raises ValueError; reshape explicitly).

• Size cap: ops that take a matrix, and the stat_histogram bins, raise ValueError beyond mathops.MAX_ELEMENTS (2^26 ≈ 67 million elements).

Detailed usage guide

• math_metrology family guide

References (sample data, literature)

• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).

• Operator provenance and references — the sources of the research/methods this op family came from.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

• poc_complex_plane_fields — py -3.11 examples/poc_complex_plane_fields.py

Ops the type connects to (they accept cimage as input)

cplx_cr_residual · cplx_domain_colour · mandelbrot_interior

Same category (complex)

cplx_contour_circle · cplx_poly_eval · cplx_contour_integral · cplx_winding_number · cplx_cauchy_value · cplx_argument_principle · cplx_laurent_coeffs · cplx_joukowski


*Provenance: mathops.py — MATH operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.