lsv-panel 0.1.0

Linear strength vortex panel method from Katz & Plotkin, implemented in Rust with a Python API

LSV-Panel

A linear strength vortex panel method from Katz & Plotkin, implemented in Rust with a Python API.

Installation

To install on any operating system from PyPi, the recommended method is pip. First, create a virtual environment and activate. On macOS/Linux,

uv venv
source .venv/bin/activate

On Windows,

uv venv
.venv\Scripts\activate

Then, install the library using pip:

uv pip install lsv-panel

Usage

The following Python script can be executed assuming you have a Selig-format airfoil coordinate file called "n0012-il.txt" located in the same directory. This script plots the pressure coefficient distribution as a function of $x$.

import lsv_panel
import matplotlib.pyplot as plt
import numpy as np
import os
file_name = os.path.join("n0012-il.txt")
coords = np.loadtxt(file_name, skiprows=1)
co, cp, cl = lsv_panel.solve(coords, alpha_deg=5.0)
fig, ax = plt.subplots(2, 1, figsize=(8, 6))
ax[0].plot(np.array(co)[:, 0], np.array(cp), color="steelblue")
ax[0].set_xlabel(r"$x/c$", fontsize=16)
ax[0].set_ylabel(r"$C_p$", fontsize=16)
ax[0].invert_yaxis()
ax[0].text(0.4, -1.0, fr"$C_l={cl:.3f}$", size=16)
ax[1].plot(coords[:, 0], coords[:, 1], color="black")
ax[1].set_xlabel(r"$x/c$", fontsize=16)
ax[1].set_ylabel(r"$y/c$", fontsize=16)
ax[1].set_aspect("equal")
for a in ax:
    a.tick_params(axis="both", which="major", labelsize=12)

fig.set_tight_layout(True)
plt.show()

[!IMPORTANT] The third-party libraries numpy and matplotlib are not included in the base installation to minimize required storage space. To include these libraries in the installation, use uv pip install lsv-panel[dev]

The airfoil coordinate file should look something like the following. Of course, the line of code that loads the coordinates could be modified to accomodate different coordinate formats.

NACA 0012
1.000000  0.001260
0.999416  0.001342
...       ...
0.999416 -0.001342
1.000000 -0.001260

The outputs of the solve function have the following meanings:

• co: The collocation points of the panel method (the midpoint of each airfoil coordinate panel). The data type is a list of lists.
• cp: The pressure coefficient at each collocation point. The data type is a list.
• cl: The lift coefficient. The data type is a float.

Angle of Attack Sweep

from cycler import cycler
import lsv_panel
import matplotlib.pyplot as plt
import numpy as np
import os
file_name = os.path.join("n0012-il.txt")
coords = np.loadtxt(file_name, skiprows=1)
alpha_deg = np.linspace(0.0, 10.0, 6)
co_list, cp_list, cl_list = lsv_panel.sweep_alpha(
    coords, alpha_deg=alpha_deg
)
fig, ax = plt.subplots(3, 1, figsize=(8, 9))
color_cycle = cycler(color=[
    "indianred", 
    "coral", 
    "gold", 
    "mediumaquamarine", 
    "steelblue", 
    "violet"
])
ax[0].set_prop_cycle(color_cycle)
for co, cp, alf in zip(co_list, cp_list, alpha_deg):
    ax[0].plot(np.array(co)[:, 0], np.array(cp), label=fr"$\alpha={alf:.1f}^{{\circ}}$")

ax[0].set_xlabel(r"$x/c$", fontsize=16)
ax[0].set_ylabel(r"$C_p$", fontsize=16)
ax[0].invert_yaxis()
ax[0].legend(loc=1, prop=dict(size=14))
ax[1].plot(coords[:, 0], coords[:, 1], color="black")
ax[1].set_xlabel(r"$x/c$", fontsize=16)
ax[1].set_ylabel(r"$y/c$", fontsize=16)
ax[1].set_aspect("equal")
ax[2].plot(alpha_deg, cl_list, color="purple", ls="--", mfc="gray", mec="gray", marker="o")
ax[2].set_xlabel(r"$\alpha\,[^{\circ}]$", fontsize=16)
ax[2].set_ylabel(r"$C_l$", fontsize=16)
for a in ax:
    a.tick_params(axis="both", which="major", labelsize=12)

fig.set_tight_layout(True)
plt.show()