{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Example - 04 - Venus Aerocapture: Part 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this example, you will learn to create a drag modulation vehicle object and compute the theoretical corridor width available for drag modulation aerocapture at Venus.\n",
    "\n",
    "For reference, we will re-create a figure from the paper \"Putnam and Braun, Drag-Modulation Flight-Control System Options for Planetary Aerocapture, Journal of Spacecraft and Rockets, Vol. 51, No. 1, 2014. DOI: 10.2514/1.A32589\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import AMAT and required libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from AMAT.planet import Planet\n",
    "from AMAT.vehicle import Vehicle\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import rcParams\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a planet object\n",
    "planet=Planet(\"VENUS\")    \n",
    "\n",
    "# Load an nominal atmospheric profile with height, temp, pressure, density data\n",
    "planet.loadAtmosphereModel('../atmdata/Venus/venus-gram-avg.dat', 0 , 1 ,2, 3)\n",
    "\n",
    "# The reference paper uses 150 km as entry interface altitude (vs 180 km as pre-defined in AMAT).\n",
    "# Hence reset planet.h_skip to 150 km\n",
    "planet.h_skip = 150000.0 \n",
    "# Create a vehicle object flying in the target planet atmosphere\n",
    "vehicle=Vehicle('DMVehicle', 1500.0, 50.0, 0.0, 3.1416, 0.0, 0.10, planet)\n",
    "\n",
    "# Set vehicle conditions at entry interface\n",
    "# Note that the EFPA initial value is arbitrary. It will be computed and reset later.\n",
    "vehicle.setInitialState(150.0,0.0,0.0,11.0,0.0,-4.5,0.0,0.0)\n",
    "vehicle.setSolverParams(1E-6)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image(filename='../plots/putnam-2014-reference.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is the figure that we want to reproduce using AMAT. Let us start setting up the simulation parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define the AI velocity and ballistic ratio range\n",
    "VAI_array = np.linspace(11,14,7)\n",
    "BR_array  = np.array([2.0,5.0,10.0,20.0])\n",
    "\n",
    "# NOTE: You will get a FileExistsError if you run this as such. Re-name the directory to something else.\n",
    "\n",
    "# Create a directory in ../data/ to store the data\n",
    "os.makedirs('../data/putnamBraun2013')\n",
    "\n",
    "# Store the speed range and ballistic coefficient range \n",
    "np.savetxt('../data/putnamBraun2013/VAI_array.txt',VAI_array)\n",
    "np.savetxt('../data/putnamBraun2013/BR_array.txt' , BR_array)\n",
    "\n",
    "# Create two empty matrices to store the TCW values\n",
    "TCW_array1 = np.zeros((len(VAI_array),len(BR_array))) \n",
    "TCW_array2 = np.zeros((len(VAI_array),len(BR_array))) \n",
    "\n",
    "# Define the two values for beta_1 used in the paper.\n",
    "beta11 = 5.0\n",
    "beta12 = 10.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running beta1=5.0\n",
      "VAI: 11.0 km/s, BETA RATIO: 20.0 TCW: 0.6330942395761667 deg.\n",
      "VAI: 14.0 km/s, BETA RATIO: 20.0 TCW: 0.7133574859435612 deg.\n",
      "Running beta1=10.0\n",
      "VAI: 11.0 km/s, BETA RATIO: 20.0 TCW: 0.6273882169480203 deg.\n",
      "VAI: 14.0 km/s, BETA RATIO: 20.0 TCW: 0.7018732332253421 deg.\n",
      "Done!\n"
     ]
    }
   ],
   "source": [
    "# Compute the corridor width values to create the figure.\n",
    "# NOTE: This calculation will take several minutes.\n",
    "print('Running beta1=5.0')\n",
    "\n",
    "for i in range(0,len(VAI_array)):\n",
    "    for j in range(0,len(BR_array)):\n",
    "        vehicle.setInitialState(150.0,0.0,0.0,VAI_array[i],0.0,-4.5,0.0,0.0)\n",
    "        vehicle.setDragModulationVehicleParams(beta11,BR_array[j])\n",
    "        TCW_array1[i,j] = vehicle.computeTCWD(2400.0, 0.1,-80.0,-4.0,1E-10,400.0)\n",
    "        print('VAI: '+str(VAI_array[i])+' km/s, BETA RATIO: '+str(BR_array[j])+' TCW: '+str(TCW_array1[i,j])+' deg.')\n",
    "\n",
    "np.savetxt('../data/putnamBraun2013/TCW_array1.txt', TCW_array1)\n",
    "\n",
    "print('Running beta1=10.0')\n",
    "for i in range(0,len(VAI_array)):\n",
    "    for j in range(0,len(BR_array)):\n",
    "        vehicle.setInitialState(150.0,0.0,0.0,VAI_array[i],0.0,-4.5,0.0,0.0)\n",
    "        vehicle.setDragModulationVehicleParams(beta12,BR_array[j])\n",
    "        TCW_array2[i,j] = vehicle.computeTCWD(2400.0, 0.1,-80.0,-4.0,1E-10,400.0)\n",
    "        print('VAI: '+str(VAI_array[i])+' km/s, BETA RATIO: '+str(BR_array[j])+' TCW: '+str(TCW_array2[i,j])+' deg.')\n",
    "\n",
    "np.savetxt('../data/putnamBraun2013/TCW_array2.txt', TCW_array2)\n",
    "print('Done!')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load the data and make the plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 234x234 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "VAI_array  = np.loadtxt('../data/putnamBraun2013/VAI_array.txt')\n",
    "BR_array   = np.loadtxt('../data/putnamBraun2013/BR_array.txt')\n",
    "TCW_array1 = np.loadtxt('../data/putnamBraun2013/TCW_array1.txt')\n",
    "TCW_array2 = np.loadtxt('../data/putnamBraun2013/TCW_array2.txt')\n",
    "\n",
    "fig = plt.figure()\n",
    "fig.set_size_inches([3.25,3.25])\n",
    "plt.rc('font',family='Times New Roman')\n",
    "params = {'mathtext.default': 'regular' }          \n",
    "plt.rcParams.update(params)\n",
    "\n",
    "plt.plot(VAI_array, TCW_array1[:,0], linestyle='-', linewidth=0.75, marker='s',ms=6, markerfacecolor=\"None\", markeredgecolor='black', markeredgewidth=0.75, color='black', clip_on=False)\n",
    "plt.plot(VAI_array, TCW_array1[:,1], linestyle='-', linewidth=0.75, marker='^',ms=6, markerfacecolor=\"None\", markeredgecolor='black', markeredgewidth=0.75, color='black', clip_on=False)\n",
    "plt.plot(VAI_array, TCW_array1[:,2], linestyle='-', linewidth=0.75, marker='o',ms=6, markerfacecolor=\"None\", markeredgecolor='black', markeredgewidth=0.75, color='black', clip_on=False)\n",
    "plt.plot(VAI_array, TCW_array1[:,3], linestyle='-', linewidth=0.75, marker='v',ms=6, markerfacecolor=\"None\", markeredgecolor='black', markeredgewidth=0.75, color='black', clip_on=False)\n",
    "\n",
    "plt.plot(VAI_array, TCW_array2[:,0], linestyle='--', linewidth=0.75, marker='s',ms=6, markerfacecolor=\"None\", markeredgecolor='black', markeredgewidth=0.75, color='black', clip_on=False)\n",
    "plt.plot(VAI_array, TCW_array2[:,1], linestyle='--', linewidth=0.75, marker='^',ms=6, markerfacecolor=\"None\", markeredgecolor='black', markeredgewidth=0.75, color='black', clip_on=False)\n",
    "plt.plot(VAI_array, TCW_array2[:,2], linestyle='--', linewidth=0.75, marker='o',ms=6, markerfacecolor=\"None\", markeredgecolor='black', markeredgewidth=0.75, color='black', clip_on=False)\n",
    "plt.plot(VAI_array, TCW_array2[:,3], linestyle='--', linewidth=0.75, marker='v',ms=6, markerfacecolor=\"None\", markeredgecolor='black', markeredgewidth=0.75, color='black', clip_on=False)\n",
    "\n",
    "plt.xlabel('Entry velocity, km/s', fontsize=10)\n",
    "plt.ylabel('Corridor width, deg',fontsize=10)\n",
    "plt.yticks(np.arange(0, 0.9, step=0.2))\n",
    "plt.xticks(np.arange(11.0, 14.5, step=1.0))\n",
    "\n",
    "plt.xlim([11.0,14.0])\n",
    "plt.ylim([0.0,  0.8])\n",
    "\n",
    "ax = plt.gca()\n",
    "ax.tick_params(direction='in')\n",
    "ax.yaxis.set_ticks_position('both')\n",
    "ax.xaxis.set_ticks_position('both')\n",
    "plt.tick_params(direction='in')\n",
    "plt.tick_params(axis='x',labelsize=10)\n",
    "plt.tick_params(axis='y',labelsize=10)\n",
    "\n",
    "\n",
    "plt.savefig('../plots/putnam-braun-2013.png',bbox_inches='tight')\n",
    "plt.savefig('../plots/putnam-braun-2013.pdf', dpi=300,bbox_inches='tight')\n",
    "plt.savefig('../plots/putnam-braun-2013.eps', dpi=300,bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The plots are now saved in plots/putnam-braun-* and should match with the results from the paper."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Congratulations!** You have now computed the corridor widths for a drag modulation aerocapture vehicle at Venus. In the next example, we will create an aerocapture feasibility chart for Titan."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}