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import numpy as np
from gaussPlanetaryEquations import intGaussPlanetaryEq
import matplotlib.pyplot as plt
from rv2orbele import getM
import os
def main():
tag_runCurtisCheck = False
tag_runHW = True
if tag_runCurtisCheck:
rp = 6678 # km
ra = 9940 # km
RAAN = np.deg2rad(45) # rad
i = np.deg2rad(28) # rad
AoP = np.deg2rad(30) # rad
theta = np.deg2rad(40) # rad
GM = 3.986 * 10 ** 5 # km3/s2
J2 = 0.00108
R = 6370 # km
a = (rp + ra)/2
e = (ra - rp)/(ra + rp)
h = np.sqrt(GM * a * (1 - e ** 2))
eles = [a, e, i, RAAN, AoP, h, theta]
# Get M0
M0 = getM(eles)
# Time
hrs2sec = 60 * 60
tEnd = 48 * hrs2sec # s
dT = 10 # s
ele_IC = [a, e, i, RAAN, AoP, h, M0]
# Returns [da_dt, de_dt, di_dt, dRAAN_dt, dAoP_dt, dM_dt]
dEles_dt = intGaussPlanetaryEq(ele_IC, GM, J2, R, tEnd, dT)
# plot dEles_dt on subplots
t = np.arange(0, tEnd, dT)
fig, axs = plt.subplots(5, 1)
fig.set_size_inches(10, 10)
# SMA
axs[0].plot(t/hrs2sec, dEles_dt[0])
axs[0].set_ylabel("a [km]")
# Eccentricity
axs[1].plot(t/hrs2sec, dEles_dt[1])
axs[1].set_ylabel("e")
# Inclination
axs[2].plot(t/hrs2sec, np.rad2deg(dEles_dt[2]))
axs[2].set_ylabel("i [deg]")
# RAAN
axs[3].plot(t/hrs2sec, np.rad2deg(dEles_dt[3]))
axs[3].set_ylabel("$\Omega$")
# AoP
axs[4].plot(t/hrs2sec, np.rad2deg(dEles_dt[4]))
axs[4].set_ylabel("$\omega$")
axs[4].set_xlabel("Time [hrs]")
for ax in axs:
ax.grid()
# turn off x tick labels for all but bottom plot
for ax in axs[:-1]:
ax.set_xticklabels([])
plt.tight_layout()
plt.show()
if tag_runHW:
# Givens
a = 26600 # km
i = 1.10654 # rad
e = 0.74
AoP = np.deg2rad(5) # rad
RAAN = np.deg2rad(90) # rad
M0 = np.deg2rad(10) # rad
GM = 3.986 * 10 ** 5 # km3/s2.
J2 = 0.00108
R = 6370 # km
T = 2*np.pi*np.sqrt(a**3/GM) # s
n = 2*np.pi/T
# Time
hrs2sec = 60 * 60
day2sec = 24 * hrs2sec
tEnd = 10*day2sec # s
dT = 2*60 # s
h = np.sqrt(GM*a*(1-e**2))
ele_IC = [a, e, i, RAAN, AoP, h, M0]
# Returns [da_dt, de_dt, di_dt, dRAAN_dt, dAoP_dt, dM_dt]
dEles_dt, time = intGaussPlanetaryEq(ele_IC, GM, J2, R, tEnd, dT)
# little omega trend
little_omega_slope = (3/4*n*J2*R**2/a**2*(5*np.cos(i)**2 - 1)/(1-e**2)**2)
Big_omega_slope = -3 / 2 * n * J2 * (R / a) ** 2 * np.cos(i) / (1 - e ** 2) ** 2
little_omega_trend = little_omega_slope*time + np.deg2rad(5.025)
Big_omega_trend = Big_omega_slope*time + RAAN
# plot dEles_dt on subplots
t = np.arange(0, tEnd, dT)
fig, axs = plt.subplots(5, 1)
axs[0].plot(t/day2sec, dEles_dt[0])
axs[0].set_ylabel("a [km]")
axs[1].plot(t/day2sec, dEles_dt[1])
axs[1].set_ylabel("e")
axs[2].plot(t/day2sec, np.rad2deg(dEles_dt[2]))
axs[2].set_ylabel("i [deg]")
axs[3].plot(t/day2sec, np.rad2deg(dEles_dt[3]))
# plot trend line
axs[3].plot(t/day2sec, np.rad2deg(Big_omega_trend))
axs[3].legend(["$\Omega$", "$\Omega$ secular solution"])
axs[3].set_ylabel("$\Omega$ [deg]")
axs[4].plot(t/day2sec, np.rad2deg(dEles_dt[4]))
# plot trend line
axs[4].plot(t / day2sec, np.rad2deg(little_omega_trend))
axs[4].legend(["$\omega$", "$\omega$ secular solution"])
axs[4].set_ylabel("$\omega$ [deg]")
axs[4].set_xlabel("Time [days]")
fig.tight_layout(pad=1.0)
for ax in axs:
ax.grid()
ax.autoscale(enable=True, axis='x', tight=True)
# turn off x tick labels for all but bottom plot
for ax in axs[:-1]:
ax.set_xticklabels([])
# make figure bigger
fig.set_size_inches(10, 10)
plt.subplots_adjust(left=0.1,
bottom=0.075,
right=0.95,
top=0.99,
wspace=0.4,import
hspace=0.2)
plt.savefig(os.path.join("./figs", "prob3_10days.png"))
plt.show()
if __name__ == "__main__":
main()