# RCAIDE/Library/Plots/Thermal_Management/plot_cross_flow_heat_exchanger_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_heat_exchanger_system_conditions
# ----------------------------------------------------------------------------------------------------------------------
[docs]
def plot_cross_flow_heat_exchanger_conditions(cross_flow_hex, results, coolant_line,
save_figure = False,
show_legend = True,
save_filename = "Cross_Flow_HEX_Conditions",
file_type = ".png",
width = 11, height = 7):
"""
Creates a multi-panel visualization of cross-flow heat exchanger operating conditions.
Parameters
----------
cross_flow_hex : Component
Cross-flow heat exchanger component containing:
- tag : str
Unique identifier for the heat exchanger
results : Results
RCAIDE results data structure containing:
- segments[i].conditions.energy[coolant_line.tag][cross_flow_hex.tag]
Heat exchanger data containing:
- coolant_mass_flow_rate[:,0]
Coolant flow rate in kg/s
- effectiveness_HEX[:,0]
Heat exchanger effectiveness
- power[:,0]
Heat transfer rate in watts
- air_inlet_pressure[:,0]
Air-side inlet pressure in Pa
- inlet_air_temperature[:,0]
Air inlet temperature in K
- air_mass_flow_rate[:,0]
Air flow rate in kg/s
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: "Cross_Flow_HEX_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 containing six subplots arranged in a 3x2 grid:
Notes
-----
Creates visualization showing:
* Thermal performance metrics
* Flow conditions for both fluids
* Heat transfer characteristics
* Operating pressures and temperatures
**Definitions**
'Effectiveness'
Ratio of actual to maximum possible heat transfer
'NTU'
Dimensionless measure of heat exchanger size
'Capacity Ratio'
Ratio of minimum to maximum heat capacity rates
'Mass Flow Rate'
Mass of fluid flowing per unit time
See Also
--------
RCAIDE.Library.Plots.Thermal_Management.plot_thermal_management_performance : Overall system performance
RCAIDE.Library.Plots.Thermal_Management.plot_air_cooled_conditions : Air-cooled 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(3,2,1)
axis_2 = plt.subplot(3,2,2)
axis_3 = plt.subplot(3,2,3)
axis_4 = plt.subplot(3,2,4)
axis_5 = plt.subplot(3,2,5)
axis_6 = plt.subplot(3,2,6)
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
cross_flow_hex_conditions = results.segments[i].conditions.energy[coolant_line.tag][cross_flow_hex.tag]
coolant_mass_flow_rate = cross_flow_hex_conditions.coolant_mass_flow_rate[:,0]
effectiveness_HEX = cross_flow_hex_conditions.effectiveness_HEX[:,0]
power = cross_flow_hex_conditions.power[:,0]
inlet_air_pressure = cross_flow_hex_conditions.air_inlet_pressure[:,0]
inlet_air_temperature = cross_flow_hex_conditions.inlet_air_temperature[:,0]
air_mass_flow_rate = cross_flow_hex_conditions.air_mass_flow_rate[:,0]
if i == 0:
axis_1.plot(time, effectiveness_HEX, color = line_colors[i], marker = ps.markers[b_i], linewidth = ps.line_width, label = cross_flow_hex.tag)
else:
axis_1.plot(time, effectiveness_HEX, 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, inlet_air_temperature, color = line_colors[i], marker = ps.markers[b_i], linewidth = ps.line_width)
axis_2.set_ylabel(r'Air Temp. (K)')
set_axes(axis_2)
axis_3.plot(time, coolant_mass_flow_rate, color = line_colors[i], marker = ps.markers[b_i], linewidth = ps.line_width)
axis_3.set_ylabel(r'Coolant $\dot{m}$ (kg/s)')
set_axes(axis_3)
axis_4.plot(time, air_mass_flow_rate, color = line_colors[i], marker = ps.markers[b_i], linewidth = ps.line_width)
axis_4.set_ylabel(r'Air $\dot{m}$ (kg/s)')
set_axes(axis_4)
axis_5.plot(time, power/1000, color = line_colors[i], marker = ps.markers[b_i], linewidth = ps.line_width)
axis_5.set_ylabel(r'HEX Power (KW)')
axis_5.set_xlabel(r'Time (mins)')
set_axes(axis_5)
axis_6.plot(time, inlet_air_pressure/10e6 , color = line_colors[i], marker = ps.markers[b_i], linewidth = ps.line_width)
axis_6.set_ylabel(r'Air Pres. (MPa)')
axis_6.set_xlabel(r'Time (mins)')
set_axes(axis_6)
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 = 'Heat_Exchanger_System'
fig.suptitle(title_text)
if save_figure:
plt.savefig(save_filename + cross_flow_hex.tag + file_type)
return fig
