# RCAIDE/Library/Plots/Geometry/plot_3d_vehicle_vlm_panelization.py
#
#
# Created: Jul 2023, M. Clarke
# ----------------------------------------------------------------------------------------------------------------------
# IMPORT
# ----------------------------------------------------------------------------------------------------------------------
import RCAIDE
from RCAIDE.Library.Methods.Aerodynamics.Vortex_Lattice_Method import generate_vortex_distribution
from RCAIDE.Library.Plots.Geometry.Common.contour_surface_slice import contour_surface_slice
import numpy as np
import plotly.graph_objects as go
# ----------------------------------------------------------------------------------------------------------------------
# PLOTS
# ----------------------------------------------------------------------------------------------------------------------
[docs]
def plot_3d_vehicle_vlm_panelization(vehicle,
alpha = 1.0,
plot_axis = False,
save_figure = False,
show_wing_control_points = True,
save_filename = "VLM_Panelization",
min_x_axis_limit = -5,
max_x_axis_limit = 40,
min_y_axis_limit = -20,
max_y_axis_limit = 20,
min_z_axis_limit = -20,
max_z_axis_limit = 20,
show_figure = True):
"""
Creates a 3D visualization of vehicle vortex lattice method (VLM) panelization.
Parameters
----------
vehicle : Vehicle
RCAIDE vehicle data structure containing geometry information
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")
min_x_axis_limit : float, optional
Minimum x-axis plot limit (default: -5)
max_x_axis_limit : float, optional
Maximum x-axis plot limit (default: 40)
min_y_axis_limit : float, optional
Minimum y-axis plot limit (default: -20)
max_y_axis_limit : float, optional
Maximum y-axis plot limit (default: 20)
min_z_axis_limit : float, optional
Minimum z-axis plot limit (default: -20)
max_z_axis_limit : float, optional
Maximum z-axis plot limit (default: 20)
show_figure : bool, optional
Flag to display the figure (default: True)
Returns
-------
fig : plotly.graph_objects.Figure
Figure handle containing the generated plot
Notes
-----
Creates an interactive 3D visualization showing:
- VLM panels on lifting surfaces
- Control points (optional)
- Customizable view and axis limits
If vehicle's vortex distribution is not available, generates a new one with:
- 25 spanwise vortices
- 5 chordwise vortices
- Linear spanwise spacing
- No fuselage or nacelle modeling
**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
"""
# unpack vortex distribution
try:
VD = vehicle.vortex_distribution
except:
VL = RCAIDE.Framework.Analyses.Aerodynamics.Vortex_Lattice_Method()
VL.settings.number_of_spanwise_vortices = 25
VL.settings.number_of_chordwise_vortices = 5
VL.settings.spanwise_cosine_spacing = False
VL.settings.model_fuselage = False
VL.settings.model_nacelle = False
VD = generate_vortex_distribution(vehicle,VL.settings)
camera = dict(up=dict(x=0.5, y=0.5, z=1), center=dict(x=0, y=0, z=-.75), eye=dict(x=-1.5, y=-1.5, z=.8))
plot_data = []
# -------------------------------------------------------------------------
# PLOT VORTEX LATTICE
# -------------------------------------------------------------------------
n_cp = VD.n_cp
color_map = 'greys'
for i in range(n_cp):
X = np.array([[VD.XA1[i],VD.XA2[i]],[VD.XB1[i],VD.XB2[i]]])
Y = np.array([[VD.YA1[i],VD.YA2[i]],[VD.YB1[i],VD.YB2[i]]])
Z = np.array([[VD.ZA1[i],VD.ZA2[i]],[VD.ZB1[i],VD.ZB2[i]]])
values = np.ones_like(X)
verts = contour_surface_slice(X, Y, Z ,values,color_map)
plot_data.append(verts)
if show_wing_control_points:
ctrl_pts = go.Scatter3d(x=VD.XC, y=VD.YC, z=VD.ZC,
mode = 'markers',
marker= dict(size=6,color='red',opacity=0.8),
line = dict(color='red',width=2))
plot_data.append(ctrl_pts)
fig = go.Figure(data=plot_data)
fig.update_scenes(aspectmode = 'auto',
xaxis_visible=plot_axis,
yaxis_visible=plot_axis,
zaxis_visible=plot_axis
)
fig.update_layout(
width = 1500,
height = 1500,
scene = dict(
xaxis = dict(backgroundcolor="grey", gridcolor="white", showbackground=plot_axis,
zerolinecolor="white", range=[min_x_axis_limit,max_x_axis_limit]),
yaxis = dict(backgroundcolor="grey", gridcolor="white", showbackground=plot_axis,
zerolinecolor="white", range=[min_y_axis_limit,max_y_axis_limit]),
zaxis = dict(backgroundcolor="grey",gridcolor="white",showbackground=plot_axis,
zerolinecolor="white", range=[min_z_axis_limit,max_z_axis_limit])),
scene_camera=camera)
fig.update_coloraxes(showscale=False)
fig.update_traces(opacity = alpha)
if save_figure:
fig.write_image(save_filename + ".png")
if show_figure:
fig.write_html( save_filename + '.html', auto_open=True)
return fig
