# RCAIDE/Library/Plots/Performance/Aerodynamics/plot_rotor_conditions.py
#
#
# Created: Jul 2023, M. Clarke
# ----------------------------------------------------------------------------------------------------------------------
# IMPORT
# ----------------------------------------------------------------------------------------------------------------------
from RCAIDE.Framework.Core import Units
from RCAIDE.Library.Plots.Common import set_axes, plot_style, segment_colors
import matplotlib.pyplot as plt
import numpy as np
# ----------------------------------------------------------------------------------------------------------------------
# PLOTS
# ----------------------------------------------------------------------------------------------------------------------
[docs]
def plot_rotor_conditions(results,
save_figure = False,
show_legend=True,
save_filename = "Rotor_Conditions",
file_type = ".png",
width = 11, height = 7):
"""
Generate plots of key rotor operating conditions over time.
Parameters
----------
results : Data
Mission results data structure containing:
- results.segments[0].analyses.vehicle.networks
save_figure : bool, optional
Save figure to file if True, default False
show_legend : bool, optional
Display segment legend if True, default True
save_filename : str, optional
Name for saved figure file, default "Rotor_Conditions"
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 a 2x2 subplot figure showing:
- Top left: RPM vs time (minutes)
- Top right: Rotor tilt angle (degrees) vs time
- Bottom left: Thrust (N) vs time
- Bottom right: Torque (N-m) vs time
Each mission segment uses a different color from the inferno colormap.
Multiple rotors are distinguished by different markers.
**Definitions**
'RPM'
Rotor rotational speed in revolutions per minute
'Thrust Vector Angle'
Angle between rotor thrust vector and vertical
See Also
--------
RCAIDE.Library.Plots.Common.set_axes : Standardized axis formatting
RCAIDE.Library.Plots.Common.plot_style : RCAIDE plot styling
RCAIDE.Library.Analysis.Performance.propulsion : Analysis modules
"""
save_filename_1 = save_filename + '_1'
save_filename_2 = save_filename + '_2'
# 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 = segment_colors(len(results.segments))
fig_1 = plt.figure(save_filename_1)
fig_1.set_size_inches(width,height)
axis_1_1 = fig_1.add_subplot(2,2,1)
axis_1_2 = fig_1.add_subplot(2,2,2)
axis_1_3 = fig_1.add_subplot(2,2,3)
axis_1_4 = fig_1.add_subplot(2,2,4)
fig_2 = plt.figure(save_filename_2)
fig_2.set_size_inches(width,height)
axis_2_1 = fig_2.add_subplot(2,2,1)
axis_2_2 = fig_2.add_subplot(2,2,2)
axis_2_3 = fig_2.add_subplot(2,2,3)
axis_2_4 = fig_2.add_subplot(2,2,4)
for network in results.segments[0].analyses.vehicle.networks:
for p_i, propulsor in enumerate(network.propulsors):
if (p_i == 0) or (network.identical_propulsors == False):
plot_propulsor_data(results,propulsor, axis_1_1, axis_1_2, axis_1_3, axis_1_4, axis_2_1, axis_2_2, axis_2_3, axis_2_4,line_colors,ps,p_i)
if show_legend:
leg = fig_1.legend(bbox_to_anchor=(0.5, 0.95), loc='upper center', ncol = 4)
leg.set_title('Flight Segment', prop={'size': ps.legend_font_size, 'weight': 'heavy'})
leg = fig_2.legend(bbox_to_anchor=(0.5, 0.95), loc='upper center', ncol = 4)
leg.set_title('Flight Segment', prop={'size': ps.legend_font_size, 'weight': 'heavy'})
# Adjusting the sub-plots for legend
fig_1.tight_layout()
fig_1.subplots_adjust(top=0.8)
fig_2.tight_layout()
fig_2.subplots_adjust(top=0.8)
# set title of plot
title_text = 'Rotor Performance'
fig_1.suptitle(title_text)
fig_2.suptitle(title_text)
if save_figure:
plt.savefig(save_filename_1 + file_type)
plt.savefig(save_filename_2 + file_type)
return (fig_1, fig_2)
[docs]
def plot_propulsor_data(results, propulsor, axis_1_1, axis_1_2, axis_1_3, axis_1_4, axis_2_1, axis_2_2, axis_2_3, axis_2_4, line_colors, ps, p_i):
"""
Plot operating conditions data for a single propulsor across mission segments.
Parameters
----------
results : Data
Mission results data structure containing:
- results.segments[i].conditions with fields:
- energy[propulsor_tag][thrustor_tag].rpm
- energy[propulsor_tag][thrustor_tag].thrust
- energy[propulsor_tag][thrustor_tag].torque
- energy[propulsor_tag].commanded_thrust_vector_angle
- frames.inertial.time
propulsor : Data
Propulsor data structure containing:
- tag : str
Identifier for the propulsor
- rotor/propeller : Data
Thrustor component data
axis_1 : matplotlib.axes.Axes
Axis for RPM plot
axis_2 : matplotlib.axes.Axes
Axis for rotor angle plot
axis_3 : matplotlib.axes.Axes
Axis for thrust plot
axis_4 : matplotlib.axes.Axes
Axis for torque plot
line_colors : array
Array of RGB colors for different segments
ps : Data
Plot style data structure with fields:
- markers : list
Marker styles for different propulsors
- line_width : float
Width for plot lines
p_i : int
Index of current propulsor for marker selection
Returns
-------
None
Notes
-----
Helper function for plot_rotor_conditions that handles plotting
data for a single propulsor (rotor or propeller) across all mission
segments.
The function:
- Identifies thrustor type (rotor vs propeller)
- Extracts time histories for each segment
- Plots RPM, angle, thrust, and torque vs time
- Applies consistent styling
- Adds legend for first segment only
- Converts units as needed (time to minutes, angles to degrees)
See Also
--------
RCAIDE.Library.Plots.Aerodynamics.plot_rotor_conditions : Main plotting function
"""
if 'rotor' in propulsor:
thrustor = propulsor.rotor
elif 'propeller' in propulsor:
thrustor = propulsor.propeller
for i in range(len(results.segments)):
time = results.segments[i].conditions.frames.inertial.time[:,0] / Units.min
rpm = results.segments[i].conditions.energy.converters[thrustor.tag].rpm[:,0]
eta = results.segments[i].conditions.energy.converters[thrustor.tag].efficiency[:,0]
angle = results.segments[i].conditions.energy.converters[thrustor.tag].commanded_thrust_vector_angle[:,0]
beta = results.segments[i].conditions.energy.converters[thrustor.tag].blade_pitch_command[:,0]
DL = results.segments[i].conditions.energy.converters[thrustor.tag].disc_loading[:,0]
PL = results.segments[i].conditions.energy.converters[thrustor.tag].power_loading[:,0]
thrust = np.linalg.norm(results.segments[i].conditions.energy.converters[thrustor.tag].thrust , axis =1)
torque = results.segments[i].conditions.energy.converters[thrustor.tag].torque[:,0]
if p_i == 0 and i ==0:
axis_1_1.plot(time,DL, color = line_colors[i], marker = ps.markers[p_i], linewidth = ps.line_width, label = thrustor.tag)
axis_2_1.plot(time,rpm, color = line_colors[i], marker = ps.markers[p_i] , linewidth = ps.line_width, label = thrustor.tag)
else:
axis_1_1.plot(time,DL, color = line_colors[i], marker = ps.markers[p_i], linewidth = ps.line_width)
axis_2_1.plot(time,rpm, color = line_colors[i], marker = ps.markers[p_i] , linewidth = ps.line_width)
axis_1_1.set_ylabel(r'Disc Loading (N/m^2)')
set_axes(axis_1_1)
axis_2_1.set_ylabel(r'RPM')
set_axes(axis_2_1)
axis_1_2.plot(time,PL, color = line_colors[i], marker = ps.markers[p_i], linewidth = ps.line_width)
axis_1_2.set_xlabel('Time (mins)')
axis_1_2.set_ylabel(r'Power Loading (N/W)')
set_axes(axis_1_2)
axis_1_3.plot(time,thrust, color = line_colors[i], marker = ps.markers[p_i] , linewidth = ps.line_width)
axis_1_3.set_ylabel(r'Thrust (N)')
set_axes(axis_1_3)
axis_1_4.plot(time,torque, color = line_colors[i], marker = ps.markers[p_i] , linewidth = ps.line_width)
axis_1_4.set_ylabel(r'Torque (N-m)')
set_axes(axis_1_4)
axis_2_2.plot(time, angle/Units.degrees, color = line_colors[i], marker = ps.markers[p_i] , linewidth = ps.line_width)
axis_2_2.set_ylabel(r'Thrust Vector (deg)')
set_axes(axis_2_2)
axis_2_3.plot(time,beta/Units.degrees, color = line_colors[i], marker = ps.markers[p_i] , linewidth = ps.line_width)
axis_2_3.set_ylabel(r'Pitch Command (deg)')
set_axes(axis_2_3)
axis_2_4.plot(time,eta, color = line_colors[i], marker = ps.markers[p_i] , linewidth = ps.line_width)
axis_2_4.set_ylabel(r'Efficiency')
set_axes(axis_2_4)
return
