docs/source/mdpi-aerospace-notebooks/smallsat-mission-concepts/section-3-5-mars-smallsat-effect-of-mean-density-variations.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "114a1dbe",
   "metadata": {},
   "source": [
    "# Section 3.5 - Mars SmallSat Aerocapture - Target EFPA Selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "37f5208f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from AMAT.planet import Planet\n",
    "from AMAT.vehicle import Vehicle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4b1b412c",
   "metadata": {},
   "outputs": [],
   "source": [
    "planet = Planet('MARS')\n",
    "planet.loadAtmosphereModel('../../../atmdata/Mars/mars-gram-avg.dat', 0 , 1 ,2, 3)\n",
    "planet.h_skip = 120e3\n",
    "planet.h_low  = 10e3\n",
    "planet.h_trap = 10e3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9f0caad5",
   "metadata": {},
   "outputs": [],
   "source": [
    "ATM_height, ATM_density_low, ATM_density_avg, ATM_density_high, ATM_density_pert = planet.loadMonteCarloDensityFile2('../../../atmdata/Mars/LAT00N.txt', 0, 1, 2, 3, 4, heightInKmFlag=True)\n",
    "density_int_low = planet.loadAtmosphereModel6(ATM_height, ATM_density_low, ATM_density_avg, ATM_density_high, -3.0, 156, 1)\n",
    "density_int_avg = planet.loadAtmosphereModel6(ATM_height, ATM_density_low, ATM_density_avg, ATM_density_high,  0.0, 156, 1)\n",
    "density_int_hig = planet.loadAtmosphereModel6(ATM_height, ATM_density_low, ATM_density_avg, ATM_density_high, +3.0, 156, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "18aed1c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "planet1 = Planet('MARS')\n",
    "planet2 = Planet('MARS')\n",
    "planet3 = Planet('MARS')\n",
    "\n",
    "planet1.density_int = density_int_low\n",
    "planet2.density_int = density_int_avg\n",
    "planet3.density_int = density_int_hig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "428b1ce0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "daecd996",
   "metadata": {},
   "outputs": [],
   "source": [
    "h_array = np.linspace(0, 120e3, 1001)\n",
    "\n",
    "d_min_arr = planet1.densityvectorized(h_array)\n",
    "d_avg_arr = planet2.densityvectorized(h_array)\n",
    "d_max_arr = planet3.densityvectorized(h_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "4ae9c5ec",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "The PostScript backend does not support transparency; partially transparent artists will be rendered opaque.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 450x355 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "fig.set_size_inches([4.5, 3.55])\n",
    "\n",
    "plt.rc('font',family='Times New Roman')\n",
    "params = {'mathtext.default': 'regular' }\n",
    "plt.rcParams.update(params)\n",
    "\n",
    "plt.plot(d_min_arr, h_array*1E-3, 'b-', linewidth=1.0, label=\"Minimum \"+r\"$(-3\\sigma)$\")\n",
    "plt.plot(d_avg_arr, h_array*1E-3, 'g-', linewidth=1.0, label=\"Average\")\n",
    "plt.plot(d_max_arr, h_array*1E-3, 'r-', linewidth=1.0, label=\"Maximum \"+r\"$(+3\\sigma)$\")\n",
    "plt.xlabel(\"Density, kg/m\"+r\"$^3$\",fontsize=12)\n",
    "plt.ylabel(\"Altitude, km\",fontsize=12)\n",
    "plt.xscale('log')\n",
    "plt.yticks(fontsize=12)\n",
    "plt.xticks(np.logspace(-9, -1, 9), fontsize=12)\n",
    "plt.grid('on',linestyle='-', linewidth=0.2)\n",
    "\n",
    "ax=plt.gca()\n",
    "ax.xaxis.set_tick_params(direction='in', which='both')\n",
    "ax.yaxis.set_tick_params(direction='in', which='both')\n",
    "ax.xaxis.set_tick_params(width=2, length=4)\n",
    "ax.yaxis.set_tick_params(width=2, length=4)\n",
    "ax.xaxis.set_tick_params(width=1, length=4, which='minor')\n",
    "ax.yaxis.set_tick_params(width=1, length=4, which='minor')\n",
    "ax.xaxis.grid(which='major', color='k', linestyle='dotted', linewidth=0.5)\n",
    "ax.xaxis.grid(which='minor', color='k', linestyle='dotted', linewidth=0.0)\n",
    "ax.yaxis.grid(which='major', color='k', linestyle='dotted', linewidth=0.5)\n",
    "ax.yaxis.grid(which='minor', color='k', linestyle='dotted', linewidth=0.0)\n",
    "\n",
    "for axis in ['top', 'bottom', 'left', 'right']:\n",
    "    ax.spines[axis].set_linewidth(2)\n",
    "\n",
    "plt.legend(loc='upper right', fontsize=10, framealpha=0.8)\n",
    "\n",
    "plt.savefig('../../../data/acta-astronautica/smallsat-mission-concepts/mars/mars-mean-density-variations.png', dpi= 300,bbox_inches='tight')\n",
    "plt.savefig('../../../data/acta-astronautica/smallsat-mission-concepts/mars/mars-mean-density-variations.pdf', dpi=300,bbox_inches='tight')\n",
    "plt.savefig('../../../data/acta-astronautica/smallsat-mission-concepts/mars/mars-mean-density-variations.eps', dpi=300,bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da2df389",
   "metadata": {},
   "source": [
    "## Compute corridor bounds for low, avg, and high density atm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "e6d5c1ec",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overshoot  limit : -9.0353 deg\n",
      "Undershoot limit : -10.0824 deg\n",
      "TCW: 1.0471 deg\n"
     ]
    }
   ],
   "source": [
    "planet.density_int = density_int_low\n",
    "\n",
    "# Set up a vehicle object\n",
    "vehicle1=Vehicle('MarsSmallSat1', 37, 20, 0.0, 1.767, 0.0, 0.1, planet)\n",
    "vehicle1.setInitialState(120.0,88.15,-0.65,5.3581,8.5458,-9.4,0.0,0.0)\n",
    "vehicle1.setSolverParams(1E-6)\n",
    "vehicle1.setDragModulationVehicleParams(20, 7.5)\n",
    "\n",
    "underShootLimit, exitflag_us = vehicle1.findUnderShootLimitD2(2400.0, 0.1, -20.0,-5.0, 1E-10, 2000.0)\n",
    "overShootLimit , exitflag_os = vehicle1.findOverShootLimitD2(2400.0, 0.1, -20.0,-5.0, 1E-10,  2000.0)\n",
    "\n",
    "print(\"Overshoot  limit : \"+str('{:.4f}'.format(overShootLimit))+ \" deg\")\n",
    "print(\"Undershoot limit : \"+str('{:.4f}'.format(underShootLimit))+ \" deg\")\n",
    "print(\"TCW: \"+ str('{:.4f}'.format(overShootLimit-underShootLimit))+ \" deg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "26e8cdf8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overshoot  limit : -8.8386 deg\n",
      "Undershoot limit : -9.9917 deg\n",
      "TCW: 1.1531 deg\n"
     ]
    }
   ],
   "source": [
    "planet.density_int = density_int_avg\n",
    "\n",
    "# Set up a vehicle object\n",
    "vehicle1=Vehicle('MarsSmallSat1', 37, 20, 0.0, 1.767, 0.0, 0.1, planet)\n",
    "vehicle1.setInitialState(120.0,88.15,-0.65,5.3581,8.5458,-9.4,0.0,0.0)\n",
    "vehicle1.setSolverParams(1E-6)\n",
    "vehicle1.setDragModulationVehicleParams(20, 7.5)\n",
    "\n",
    "underShootLimit, exitflag_us = vehicle1.findUnderShootLimitD2(2400.0, 0.1, -20.0,-5.0, 1E-10, 2000.0)\n",
    "overShootLimit , exitflag_os = vehicle1.findOverShootLimitD2(2400.0, 0.1, -20.0,-5.0, 1E-10,  2000.0)\n",
    "\n",
    "print(\"Overshoot  limit : \"+str('{:.4f}'.format(overShootLimit))+ \" deg\")\n",
    "print(\"Undershoot limit : \"+str('{:.4f}'.format(underShootLimit))+ \" deg\")\n",
    "print(\"TCW: \"+ str('{:.4f}'.format(overShootLimit-underShootLimit))+ \" deg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "1c1f4050",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overshoot  limit : -8.6511 deg\n",
      "Undershoot limit : -9.9033 deg\n",
      "TCW: 1.2522 deg\n"
     ]
    }
   ],
   "source": [
    "planet.density_int = density_int_hig\n",
    "\n",
    "# Set up a vehicle object\n",
    "vehicle1=Vehicle('MarsSmallSat1', 37, 20, 0.0, 1.767, 0.0, 0.1, planet)\n",
    "vehicle1.setInitialState(120.0,88.15,-0.65,5.3581,8.5458,-9.4,0.0,0.0)\n",
    "vehicle1.setSolverParams(1E-6)\n",
    "vehicle1.setDragModulationVehicleParams(20, 7.5)\n",
    "\n",
    "underShootLimit, exitflag_us = vehicle1.findUnderShootLimitD2(2400.0, 0.1, -20.0,-5.0, 1E-10, 2000.0)\n",
    "overShootLimit , exitflag_os = vehicle1.findOverShootLimitD2(2400.0, 0.1, -20.0,-5.0, 1E-10,  2000.0)\n",
    "\n",
    "print(\"Overshoot  limit : \"+str('{:.4f}'.format(overShootLimit))+ \" deg\")\n",
    "print(\"Undershoot limit : \"+str('{:.4f}'.format(underShootLimit))+ \" deg\")\n",
    "print(\"TCW: \"+ str('{:.4f}'.format(overShootLimit-underShootLimit))+ \" deg\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f48632d",
   "metadata": {},
   "source": [
    "## Target EFPA selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5f769dbe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 625x325 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.patches import Polygon\n",
    "\n",
    "fig = plt.figure()\n",
    "fig.set_size_inches([6.25,3.25])\n",
    "plt.rc('font',family='Times New Roman')\n",
    "params = {'mathtext.default': 'regular' }\n",
    "plt.rcParams.update(params)\n",
    "\n",
    "ax = plt.gca()\n",
    "\n",
    "\n",
    "x1 = [1.0, 1.0, 2.0, 2.0]\n",
    "y1 = [-10.0824, -9.0353 , -9.0353 , -10.0824]\n",
    "\n",
    "x2 = [2.0, 2.0, 3.0, 3.0]\n",
    "y2 = [-9.9917 , -8.8386, -8.8386,  -9.9917]\n",
    "\n",
    "x3 = [3.0, 3.0, 4.0, 4.0]\n",
    "y3 = [-9.9033 , -8.6511 , -8.6511 , -9.9033 ]\n",
    "\n",
    "\n",
    "\n",
    "poly1 = Polygon( list(zip(x1,y1)), facecolor='xkcd:blue', edgecolor='k')\n",
    "ax.add_patch(poly1)\n",
    "\n",
    "poly2 = Polygon( list(zip(x2,y2)), facecolor='xkcd:green', edgecolor='k')\n",
    "ax.add_patch(poly2)\n",
    "\n",
    "poly3 = Polygon( list(zip(x3,y3)), facecolor='xkcd:red', edgecolor='k')\n",
    "ax.add_patch(poly3)\n",
    "\n",
    "\n",
    "plt.ylabel(\"Entry flight-path angle, deg\",fontsize=12)\n",
    "plt.xlabel(\"Atmospheric density\",fontsize=12)\n",
    "\n",
    "plt.tick_params(axis='x',          # changes apply to the x-axis\n",
    "                which='both',      # both major and minor ticks are affected\n",
    "    bottom=False,      # ticks along the bottom edge are off\n",
    "    top=False,         # ticks along the top edge are off\n",
    "    labelbottom=False)\n",
    "\n",
    "plt.axhline(y=-9.0353, linewidth=2.0, linestyle='solid' ,color='xkcd:blue')\n",
    "plt.axhline(y=-9.9033, linewidth=2.0, linestyle='solid' ,color='xkcd:red')\n",
    "plt.axhline(y=-9.25, linewidth=2.0, linestyle='dashdot' ,color='xkcd:black')\n",
    "plt.axhline(y=-9.05, linewidth=2.0, linestyle='dotted' ,color='xkcd:black')\n",
    "plt.axhline(y=-9.45, linewidth=2.0, linestyle='dotted' ,color='xkcd:black')\n",
    "\n",
    "ax.tick_params(direction='in')\n",
    "ax.yaxis.set_ticks_position('both')\n",
    "plt.yticks(fontsize=12)\n",
    "\n",
    "ax=plt.gca()\n",
    "ax.xaxis.set_tick_params(direction='in', which='both')\n",
    "ax.yaxis.set_tick_params(direction='in', which='both')\n",
    "ax.xaxis.set_tick_params(width=1, length=4)\n",
    "ax.yaxis.set_tick_params(width=1, length=4)\n",
    "ax.xaxis.set_tick_params(width=1, length=4, which='minor')\n",
    "ax.yaxis.set_tick_params(width=1, length=4, which='minor')\n",
    "ax.xaxis.grid(which='major', color='k', linestyle='dotted', linewidth=0.5)\n",
    "ax.xaxis.grid(which='minor', color='k', linestyle='dotted', linewidth=0.0)\n",
    "ax.yaxis.grid(which='major', color='k', linestyle='dotted', linewidth=0.5)\n",
    "ax.yaxis.grid(which='minor', color='k', linestyle='dotted', linewidth=0.0)\n",
    "\n",
    "for axis in ['top', 'bottom', 'left', 'right']:\n",
    "    ax.spines[axis].set_linewidth(2)\n",
    "    \n",
    "\n",
    "plt.annotate(\"Overshoot limit for min. density atmosphere\", xy=(0.20, -9.05), xytext=(1.3, -8.45),\n",
    "               va=\"center\", ha=\"center\",\n",
    "               arrowprops=dict(arrowstyle='->, head_width=0.2', facecolor='blue'), fontsize=10, color='k',\n",
    "               bbox=dict(boxstyle='round,pad=0.2', fc='w', ec='k', alpha=1))\n",
    "\n",
    "plt.annotate(\"Undershoot limit for max. density atmosphere\"  , xy=(0.20, -9.9033),\n",
    "                                                                   xytext=(1.3, -10.550),\n",
    "                                                                   va=\"center\", ha=\"center\",\n",
    "                    arrowprops=dict(arrowstyle='->, head_width=0.2', facecolor='blue'), fontsize=10,color='k',\n",
    "                     bbox=dict(boxstyle='round,pad=0.2', fc='w', ec='k', alpha=1))\n",
    "\n",
    "plt.annotate(\"Target EFPA\"  , xy=(4.5, -9.27),\n",
    "                                                                   xytext=(4.5, -8.45),\n",
    "                                                                   va=\"center\", ha=\"center\",\n",
    "                    arrowprops=dict(arrowstyle='->, head_width=0.2', facecolor='blue'), fontsize=10,color='k',\n",
    "                     bbox=dict(boxstyle='round,pad=0.2', fc='w', ec='k', alpha=1))\n",
    "\n",
    "plt.annotate(\"Assumed delivery error\\n\" +r\"$\\pm 0.20$\"+ \" deg. \"+ r\"$3\\sigma$\"  , xy=(5.3, -9.02),\n",
    "                                                                   xytext=(5.3, -9.725),\n",
    "                                                                   va=\"center\", ha=\"center\",\n",
    "                    arrowprops=dict(arrowstyle='<->, head_width=0.4', facecolor='blue'), fontsize=10,color='k',\n",
    "                     bbox=dict(boxstyle='round,pad=0.2', fc='w', ec='k', alpha=1))\n",
    "\n",
    "ax.set_xlim([-1.5, 6.5])\n",
    "ax.set_ylim([-11, -8])\n",
    "\n",
    "plt.text(1.3, -10.25, 'Min', color='xkcd:blue', fontsize=10)\n",
    "plt.text(2.3, -10.15, 'Avg', color='xkcd:green', fontsize=10)\n",
    "plt.text(3.3, -10.05, 'Max', color='xkcd:red', fontsize=10)\n",
    "\n",
    "plt.savefig('../../../data/mdpi-aerospace/smallsat-mission-concepts/mars/mars-ac-efpa-selection.png', dpi= 300,bbox_inches='tight')\n",
    "plt.savefig('../../../data/mdpi-aerospace/smallsat-mission-concepts/mars/mars-ac-efpa-selection.pdf', dpi=300,bbox_inches='tight')\n",
    "plt.savefig('../../../data/mdpi-aerospace/smallsat-mission-concepts/mars/mars-ac-efpa-selection.eps', dpi=300,bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}