# RCAIDE/Library/Plots/Performance/Aerodynamics/plot_aerodynamic_coefficients.py
#
#
# Created: Jul 2023, M. Clarke
# ----------------------------------------------------------------------------------------------------------------------
# IMPORT
# ----------------------------------------------------------------------------------------------------------------------
from RCAIDE.Framework.Core import Units
from RCAIDE.Library.Plots.Common import set_axes, plot_style
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import numpy as np
# ----------------------------------------------------------------------------------------------------------------------
# PLOTS
# ----------------------------------------------------------------------------------------------------------------------
[docs]
def plot_aerodynamic_coefficients(results,
save_figure = False,
show_legend = True,
save_filename = "Aerodynamic_Coefficients",
file_type = ".png",
width = 11, height = 7):
"""
Creates a multi-panel visualization of aerodynamic coefficients throughout flight.
Parameters
----------
results : Results
RCAIDE results data structure containing:
- segments[i].conditions.aerodynamics.coefficients
Coefficient data containing:
- lift.total[:,0,None]
Total lift coefficient
- drag.total[:,0,None]
Total drag coefficient
- segments[i].conditions.aerodynamics.angles
Angle data containing:
- alpha[:,0]
Angle of attack in radians
- segments[i].conditions.frames.inertial.time[:,0]
Time history for each segment
- segments[i].tag
Segment identifier string
save_figure : bool, optional
Flag for saving the figure (default: False)
show_legend : bool, optional
Flag to display segment legend (default: True)
save_filename : str, optional
Name of file for saved figure (default: "Aerodynamic_Coefficients")
file_type : str, optional
File extension for saved figure (default: ".png")
width : float, optional
Figure width in inches (default: 11)
height : float, optional
Figure height in inches (default: 7)
Returns
-------
fig : matplotlib.figure.Figure
Notes
-----
Creates visualization showing:
- Aerodynamic performance metrics
- Flight attitude history
- Efficiency characteristics
- Time evolution of coefficients
**Major Assumptions**
* Quasi-steady aerodynamics
* Small angle approximations
* Incompressible flow
* Linear lift curve slope
* Negligible sideslip
**Definitions**
'Lift Coefficient'
Non-dimensional lift force
'Drag Coefficient'
Non-dimensional drag force
'Angle of Attack'
Angle between airflow and reference line
'L/D Ratio'
Measure of aerodynamic efficiency
See Also
--------
RCAIDE.Library.Plots.Aerodynamics.plot_aerodynamic_forces : Dimensional force plots
RCAIDE.Library.Plots.Aerodynamics.plot_drag_components : Drag breakdown analysis
"""
# get plotting style
ps = plot_style()
parameters = {'axes.labelsize': ps.axis_font_size,
'xtick.labelsize': ps.axis_font_size,
'ytick.labelsize': ps.axis_font_size,
'axes.titlesize': ps.title_font_size}
plt.rcParams.update(parameters)
# get line colors for plots
line_colors = cm.inferno(np.linspace(0,0.9,len(results.segments)))
fig = plt.figure(save_filename)
fig.set_size_inches(width,height)
for i in range(len(results.segments)):
time = results.segments[i].conditions.frames.inertial.time[:,0] / Units.min
cl = results.segments[i].conditions.aerodynamics.coefficients.lift.total[:,0,None]
cd = results.segments[i].conditions.aerodynamics.coefficients.drag.total[:,0,None]
aoa = results.segments[i].conditions.aerodynamics.angles.alpha[:,0] / Units.deg
l_d = cl/cd
segment_tag = results.segments[i].tag
segment_name = segment_tag.replace('_', ' ')
axis_1 = plt.subplot(2,2,1)
axis_1.plot(time, aoa, color = line_colors[i], marker = ps.markers[0],markersize = ps.marker_size, linewidth = ps.line_width, label = segment_name)
axis_1.set_ylabel(r'AoA (deg)')
axis_1.set_xlabel('Time (mins)')
axis_1.set_ylim([-5,15])
set_axes(axis_1)
axis_2 = plt.subplot(2,2,2)
axis_2.plot(time, l_d, color = line_colors[i], marker = ps.markers[0],markersize = ps.marker_size, linewidth = ps.line_width)
axis_2.set_ylabel(r'L/D')
axis_2.set_xlabel('Time (mins)')
set_axes(axis_2)
axis_3 = plt.subplot(2,2,3)
axis_3.plot(time, cl, color = line_colors[i], marker = ps.markers[0],markersize = ps.marker_size, linewidth = ps.line_width)
axis_3.set_xlabel('Time (mins)')
axis_3.set_ylabel(r'$C_L$')
set_axes(axis_3)
axis_4 = plt.subplot(2,2,4)
axis_4.plot(time, cd, color = line_colors[i], marker = ps.markers[0],markersize = ps.marker_size, linewidth = ps.line_width)
axis_4.set_xlabel('Time (mins)')
axis_4.set_ylabel(r'$C_D$')
axis_4.set_ylim([0,0.1])
set_axes(axis_4)
if show_legend:
leg = fig.legend(bbox_to_anchor=(0.5, 0.95), loc='upper center', ncol = 4)
# Adjusting the sub-plots for legend
fig.tight_layout()
fig.subplots_adjust(top=0.8)
if save_figure:
fig.savefig(save_filename + file_type)
return fig
