# RCAIDE/Library/Plots/Geometry/plot_3d_vehicle_vlm_panelization.py
#
#
# Created: Jul 2023, M. Clarke
# ----------------------------------------------------------------------------------------------------------------------
# IMPORT
# ----------------------------------------------------------------------------------------------------------------------
import numpy as np
import pyvista as pv
# ----------------------------------------------------------------------------------------------------------------------
# PLOTS
# ----------------------------------------------------------------------------------------------------------------------
[docs]
def plot_3d_vehicle_vlm_panelization(vortex_distribution,
alpha = 1.0,
plot_axis = False,
save_figure = False,
show_wing_control_points = True,
save_filename = "VLM_Panelization",
axis_limit = 100,
panel_color = 'grey',
show_figure = True):
"""
Creates a 3D visualization of vehicle vortex lattice method (VLM) panelization.
Parameters
----------
vortex_distribution : Data
RCAIDE vortex distribution data structure containing panel corner coordinates
alpha : float, optional
Transparency value between 0 and 1 (default: 1.0)
plot_axis : bool, optional
Flag to show coordinate axes (default: False)
save_figure : bool, optional
Flag for saving the figure (default: False)
show_wing_control_points : bool, optional
Flag to display VLM control points (default: True)
save_filename : str, optional
Name of file for saved figure (default: "VLM_Panelization")
axis_limit : float, optional
Axis plot limit (default: 100)
panel_color : str, optional
Color of VLM panels (default: 'grey')
show_figure : bool, optional
Flag to display the figure (default: True)
Returns
-------
plotter : pyvista.Plotter
Plotter handle containing the generated plot
Notes
-----
Creates an interactive 3D visualization showing:
- VLM panels on lifting surfaces
- Control points (optional)
**Major Assumptions**
* Lifting surfaces are represented by flat panels
* Control points are at 3/4 chord of each panel
* Vortex lines are at 1/4 chord of each panel
**Definitions**
'Control Point'
Location where boundary condition is enforced
'Vortex Line'
Line of bound vorticity representing lift
'Panel'
Discrete element of lifting surface
"""
VD = vortex_distribution
n_cp = len(VD.XA1[0])
# -------------------------------------------------------------------------
# Build quad mesh for VLM panels
# -------------------------------------------------------------------------
# Each panel has 4 corners ordered: A1, A2, B2, B1 (counter-clockwise quad)
points = np.zeros((n_cp * 4, 3))
faces = np.zeros((n_cp, 5), dtype=int) # [4, i0, i1, i2, i3]
for i in range(n_cp):
base = i * 4
points[base + 0] = [VD.XA1[0][i], VD.YA1[0][i], VD.ZA1[0][i]]
points[base + 1] = [VD.XA2[0][i], VD.YA2[0][i], VD.ZA2[0][i]]
points[base + 2] = [VD.XB2[0][i], VD.YB2[0][i], VD.ZB2[0][i]]
points[base + 3] = [VD.XB1[0][i], VD.YB1[0][i], VD.ZB1[0][i]]
faces[i] = [4, base, base + 1, base + 2, base + 3]
panel_mesh = pv.PolyData(points, faces.ravel())
# -------------------------------------------------------------------------
# Initialize plotter
# -------------------------------------------------------------------------
if save_figure:
plotter = pv.Plotter(off_screen=True)
else:
plotter = pv.Plotter()
plotter.add_mesh(panel_mesh, color=panel_color, opacity=alpha,
show_edges=True, edge_color='black', line_width=0.5)
# -------------------------------------------------------------------------
# Control points
# -------------------------------------------------------------------------
if show_wing_control_points:
ctrl_pts = np.column_stack([VD.XC[0], VD.YC[0], VD.ZC[0]])
ctrl_cloud = pv.PolyData(ctrl_pts)
plotter.add_mesh(ctrl_cloud, color='red', point_size=6,
render_points_as_spheres=True, opacity=0.8)
# -------------------------------------------------------------------------
# Camera and display settings
# -------------------------------------------------------------------------
plotter.camera_position = [(-1.5 * axis_limit, -1.5 * axis_limit, 0.8 * axis_limit),
(axis_limit, 0, 0),
(0, 0, 1)]
plotter.window_size = [1500, 1500]
plotter.set_background('white')
if not plot_axis:
plotter.hide_axes()
if save_figure:
plotter.screenshot(save_filename + ".png")
elif show_figure:
plotter.show()
return plotter
