# RCAIDE/Library/Plots/Thermal_Management/plot_air_cooled_conditions.py
#
#
# Created: Sep 2024, S. Shekar
# ----------------------------------------------------------------------------------------------------------------------
# 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
# ----------------------------------------------------------------------------------------------------------------------
# plot_air_cooled_conditions
# ----------------------------------------------------------------------------------------------------------------------
[docs]
def plot_air_cooled_conditions(air_cooled, results, coolant_line,
save_figure = False,
show_legend = True,
save_filename = "Air_Cooled_Conditions",
file_type = ".png",
width = 11, height = 7):
"""
Creates a multi-panel visualization of air-cooled heat exchanger performance.
Parameters
----------
air_cooled : Component
Air-cooled heat exchanger component containing:
* tag : str
Unique identifier for the heat exchanger
results : Results
RCAIDE results data structure containing:
* segments[i].conditions.frames.inertial.time[:,0]
Time history for each segment
* segments[i].conditions.energy[coolant_line.tag][air_cooled.tag]
Heat exchanger performance data containing:
* effectiveness[:,0]
Heat exchanger effectiveness
* total_heat_removed[:,0]
Total heat transfer rate
coolant_line : Component
Coolant line component containing:
* tag : str
Unique identifier for the coolant circuit
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: "Air_Cooled_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
Handle to the generated figure
Notes
-----
Creates visualization showing:
* Heat exchanger performance metrics
* Thermal effectiveness evolution
* Heat transfer rate history
* Time history for each segment
**Definitions**
'Effectiveness'
Ratio of actual to maximum possible heat transfer
'Heat Transfer Rate'
Rate of thermal energy transfer between fluids
'Heat Capacity Rate'
Product of mass flow rate and specific heat
See Also
--------
RCAIDE.Library.Plots.Thermal_Management.plot_thermal_management_performance : Overall system performance
RCAIDE.Library.Plots.Thermal_Management.plot_cross_flow_heat_exchanger_conditions : Cross-flow heat exchanger 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)
axis_1 = plt.subplot(2,1,1)
axis_2 = plt.subplot(2,1,2)
for network in results.segments[0].analyses.energy.vehicle.networks:
busses = network.busses
for bus in busses:
for b_i, battery in enumerate(bus.battery_modules):
if b_i == 0 or bus.identical_battery_modules == False:
for i in range(len(results.segments)):
time = results.segments[i].conditions.frames.inertial.time[:,0] / Units.min
air_cooled_conditions = results.segments[i].conditions.energy[coolant_line.tag][air_cooled.tag]
effectiveness = air_cooled_conditions.effectiveness[:,0]
total_heat_removed = air_cooled_conditions.total_heat_removed[:,0]
if i == 0:
axis_1.plot(time, effectiveness, color = line_colors[i], marker = ps.markers[b_i], linewidth = ps.line_width, label = battery.tag)
else:
axis_1.plot(time, effectiveness, color = line_colors[i], marker = ps.markers[b_i], linewidth = ps.line_width)
axis_1.set_ylabel(r'Effectiveness')
set_axes(axis_1)
axis_2.plot(time, total_heat_removed, color = line_colors[i], marker = ps.markers[b_i], linewidth = ps.line_width)
axis_2.set_ylabel(r'Total Heat Removed (W)')
set_axes(axis_2)
if show_legend:
leg = fig.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.tight_layout()
fig.subplots_adjust(top=0.8)
# set title of plot
title_text = 'Air_Cooled_Properties'
fig.suptitle(title_text)
if save_figure:
plt.savefig(save_filename + air_cooled.tag + file_type)
return fig
