# RCAIDE/Library/Plots/Performance/Aerodynamics/plot_surface_pressures.py
#
#
# Created: Jul 2023, M. Clarke
# ----------------------------------------------------------------------------------------------------------------------
# IMPORT
# ----------------------------------------------------------------------------------------------------------------------
from RCAIDE.Framework.Core import Units
import matplotlib.pyplot as plt
from matplotlib.colors import TwoSlopeNorm
import numpy as np
# ----------------------------------------------------------------------------------------------------------------------
# PLOTS
# ----------------------------------------------------------------------------------------------------------------------
[docs]
def plot_pressure_coefficient_distribution(results,
save_figure = False,
save_filename = "Pressure_Coefficient_Distribution",
minimum_Cp = -1,
maximum_Cp = 1,
discretization = 20,
file_type = ".png"):
"""
Creates contour plots of differential surface pressure distributions (CP_lower -CP_upper) on aircraft lifting surfaces.
Parameters
----------
results : Results
RCAIDE results data structure containing:
- segments[i].conditions.aerodynamics
Aerodynamic data containing:
- coefficients.differential_surface_pressure[ti]
Pressure coefficient at each control point
- segments[i].analyses.vehicle
Vehicle data containing:
- vortex_distribution
Distribution data with:
- n_cw : array
Number of chordwise panels per wing
- n_sw : array
Number of spanwise panels per wing
- n_w : int
Number of wings
- XC, YC : arrays
Control point coordinates
- X : array
Surface point x-coordinates
- wings : list
Wing components with:
- vertical : bool
Flag for vertical surfaces
- symmetric : bool
Flag for symmetric surfaces
save_figure : bool, optional
Flag for saving the figure (default: False)
save_filename : str, optional
Name of file for saved figure (default: "Surface_Pressure")
file_type : str, optional
File extension for saved figure (default: ".png")
Returns
-------
None
Notes
-----
Creates visualization showing:
- Surface pressure distributions
- Spanwise pressure variations
- Chordwise pressure variations
- Wing geometry outlines
**Definitions**
'Pressure Coefficient'
Non-dimensional pressure difference
'Control Point'
Location where pressure is evaluated
'Lifting Surface'
Wing, tail, or other aerodynamic surface
'Planform'
Top-view shape of lifting surface
See Also
--------
RCAIDE.Library.Plots.Aerodynamics.plot_lift_distribution : Spanwise lift analysis
RCAIDE.Library.Plots.Aerodynamics.plot_aerodynamic_coefficients : Overall coefficient plots
"""
VD = results.vortex_distribution
CP = results.aerodynamics.coefficients.differential_surface_pressure
n_cw = VD.n_cw
n_sw = VD.n_sw
b_pts = np.concatenate(([0], np.cumsum(VD.n_sw[0] * VD.n_cw[0])))
for ti in range(len(CP)):
figure_name = r'$\Delta$ $C_P$ Surface Distribution_' + str(ti + 1)
fig = plt.figure(figure_name)
axes = plt.subplot(1, 1, 1)
x_max = max(VD.XC[ti]) + 2
y_max = max(VD.YC[ti]) + 2
axes.set_ylim(x_max, 0)
axes.set_xlim(-y_max, y_max)
fig_w = 10.0
fig_h = fig_w * (x_max / (2 * y_max)) if y_max > 0 else fig_w
fig.set_size_inches(fig_w, fig_h)
AoA = results.aerodynamics.angles.alpha[ti, 0]
CL = results.aerodynamics.coefficients.lift.total[ti, 0]
CD = results.aerodynamics.coefficients.drag.total[ti, 0]
figure_title = 'AoA: ' + str(round(AoA / Units.degree, 4)) + ', CL: ' + str(round(CL, 2)) + ', CD: ' + str(round(CD, 4))
fig.suptitle(figure_title, fontsize=16)
for i in range(VD.n_w[0][0]):
n_pts = (n_sw[ti, i] + 1) * (n_cw[ti, i] + 1)
xc_pts = VD.X[ti, i * n_pts:(i + 1) * n_pts]
x_pts = np.reshape(np.atleast_2d(VD.XC[ti, b_pts[i]:b_pts[i + 1]]).T, (n_sw[ti, i], -1))
y_pts = np.reshape(np.atleast_2d(VD.YC[ti, b_pts[i]:b_pts[i + 1]]).T, (n_sw[ti, i], -1))
z_pts = np.reshape(np.atleast_2d(CP[ti, b_pts[i]:b_pts[i + 1]]).T, (n_sw[ti, i], -1))
x_pts_p = x_pts * ((n_cw[ti, i] + 1) / n_cw[ti, i]) - x_pts[0, 0] * ((n_cw[ti, i] + 1) / n_cw[ti, i]) + xc_pts[0]
norm = TwoSlopeNorm(vmin=minimum_Cp, vcenter=0, vmax=maximum_Cp)
levels = np.linspace(minimum_Cp, maximum_Cp, discretization)
CS = axes.contourf(y_pts, x_pts_p, z_pts, levels=levels, cmap='coolwarm', norm=norm, extend='both')
cbar = fig.colorbar(CS, ax=axes)
cbar.ax.set_ylabel(r'$\Delta$ $C_{P}$', rotation=0)
plt.axis('off')
plt.grid(None)
if save_figure:
plt.savefig(save_filename + '_' + str(ti + 1) + file_type)
return
