Quiver plot of 2D potential flow around a circular cylinder
Fluid Dynamics
Example from the compendium of canonical charts
Python Code
"""Fluid Dynamics — Quiver plot of 2D potential flow around a circular cylinder."""
import numpy as np
import plotly.figure_factory as ff
import plotly.graph_objects as go
# Inviscid, irrotational (potential) flow around a unit-radius cylinder.
# Uniform freestream U∞=1, cylinder radius a=1 at origin.
# Velocity field (outside cylinder):
# u = U∞ [ 1 - a²(x²-y²)/(x²+y²)² ]
# v = U∞ [ -2a²·x·y / (x²+y²)² ]
U_INF = 1.0
A = 1.0
def velocity(x, y):
r2 = x**2 + y**2
# Mask interior of cylinder
outside = r2 > (A + 0.01)**2
r2 = np.where(outside, r2, np.nan)
u = U_INF * (1 - A**2 * (x**2 - y**2) / r2**2)
v = U_INF * (-2 * A**2 * x * y / r2**2)
return np.where(outside, u, 0.0), np.where(outside, v, 0.0)
def generate():
# Coarser grid for quiver (arrows would overlap on a dense grid)
x = np.linspace(-3.5, 3.5, 18)
y = np.linspace(-3.5, 3.5, 18)
X, Y = np.meshgrid(x, y)
U, V = velocity(X, Y)
# Mask points inside (or very near) cylinder for display
r2 = X**2 + Y**2
mask = r2 > (A + 0.2)**2
X_q = np.where(mask, X, np.nan).ravel()
Y_q = np.where(mask, Y, np.nan).ravel()
U_q = np.where(mask, U, np.nan).ravel()
V_q = np.where(mask, V, np.nan).ravel()
# Drop nan rows
keep = ~np.isnan(X_q)
X_q, Y_q, U_q, V_q = X_q[keep], Y_q[keep], U_q[keep], V_q[keep]
# Reshape back to 2D for ff.create_quiver (requires 2D arrays)
# Build 2D arrays by filtering rows/cols that are fully masked
xi = np.linspace(-3.5, 3.5, 18)
yi = np.linspace(-3.5, 3.5, 18)
Xi, Yi = np.meshgrid(xi, yi)
Ui, Vi = velocity(Xi, Yi)
ri2 = Xi**2 + Yi**2
inside = ri2 <= (A + 0.15)**2
Ui[inside] = np.nan
Vi[inside] = np.nan
# Normalize arrow lengths to show direction uniformly, scaled by magnitude
mag = np.sqrt(Ui**2 + Vi**2)
max_mag = np.nanmax(mag)
Ui_n = Ui / max_mag
Vi_n = Vi / max_mag
fig = ff.create_quiver(
Xi, Yi, Ui_n, Vi_n,
scale=0.22,
arrow_scale=0.35,
)
for trace in fig.data:
trace.line.color = VIOLET
trace.opacity = 0.75
# Cylinder outline
theta = np.linspace(0, 2 * np.pi, 200)
fig.add_trace(go.Scatter(
x=np.cos(theta), y=np.sin(theta),
mode="lines",
line=dict(color=TEAL, width=2),
fill="toself",
fillcolor="rgba(82,179,208,0.15)",
showlegend=False,
hoverinfo="skip",
))
# Stagnation-point markers
fig.add_trace(go.Scatter(
x=[-1, 1], y=[0, 0],
mode="markers",
marker=dict(size=8, color="#E9A23B", symbol="circle",
line=dict(color="white", width=1.5)),
name="Stagnation points",
hovertemplate="Stagnation point<br>(%{x:.0f}, %{y:.0f})<extra></extra>",
))
fig.update_layout(
xaxis=dict(
title="x / a",
range=[-3.8, 3.8],
scaleanchor="y",
showgrid=True,
zeroline=True,
),
yaxis=dict(
title="y / a",
range=[-3.8, 3.8],
),
legend=dict(orientation="h", y=1.06),
margin=dict(t=20, b=60, l=70, r=40),
height=580,
showlegend=True,
)
return fig
if __name__ == "__main__":
generate()
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