{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Example - 23 - PV Small Night - Venus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from AMAT.planet import Planet\n",
    "from AMAT.vehicle import Vehicle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook simulates the atmospheric entry of the Pioneer Venus Small Night probe.\n",
    "https://en.wikipedia.org/wiki/Pioneer_Venus_Multiprobe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set up the planet and atmosphere model.\n",
    "planet=Planet(\"VENUS\")    \n",
    "planet.loadAtmosphereModel('../atmdata/Venus/venus-gram-avg.dat', 0 , 1 , 2, 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set up the vehicle\n",
    "vehicle=Vehicle('PV-Small-Night', 91, 190, 0.00, 0.46, 0.0, 0.19, planet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set up entry parameters\n",
    "vehicle.setInitialState(180.0,0.0,0.0,11.54,0.0,-41.5,0.0,0.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set up solver\n",
    "vehicle.setSolverParams(1E-6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Propogate vehicle entry trajectory\n",
    "vehicle.propogateEntry (2400.0,0.1,0.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import rcParams to set figure font type\n",
    "from matplotlib import rcParams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 864x576 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(12,8))\n",
    "plt.rc('font',family='Times New Roman')\n",
    "params = {'mathtext.default': 'regular' }          \n",
    "plt.rcParams.update(params)\n",
    "\n",
    "plt.subplot(2, 2, 1)\n",
    "plt.plot(vehicle.v_kmsc, vehicle.h_kmc, 'k-', linewidth=2.0)\n",
    "plt.xlabel('Speed, km/s',fontsize=14)\n",
    "plt.ylabel('Altitude, km', fontsize=14)\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",
    "ax.tick_params(axis='x',labelsize=14)\n",
    "ax.tick_params(axis='y',labelsize=14)\n",
    "\n",
    "plt.subplot(2, 2, 2)\n",
    "plt.plot(vehicle.acc_net_g, vehicle.h_kmc, 'b-', linewidth=2.0)\n",
    "plt.xlabel('Deceleration, Earth g',fontsize=14)\n",
    "plt.ylabel('Altitude, km', fontsize=14)\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",
    "ax.tick_params(axis='x',labelsize=14)\n",
    "ax.tick_params(axis='y',labelsize=14)\n",
    "\n",
    "plt.subplot(2, 2, 3)\n",
    "plt.plot(vehicle.q_stag_total, vehicle.h_kmc,'r-', linewidth=2.0)\n",
    "plt.xlabel('Stagnation point heat-rate, '+r'$W/cm^2$',fontsize=14)\n",
    "plt.ylabel('Altitude, km', fontsize=14)\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",
    "ax.tick_params(axis='x',labelsize=14)\n",
    "ax.tick_params(axis='y',labelsize=14)\n",
    "\n",
    "\n",
    "plt.subplot(2, 2, 4)\n",
    "plt.plot(vehicle.heatload/1.0E3, vehicle.h_kmc, 'm-', linewidth=2.0)\n",
    "plt.xlabel('Stagnation point heat-load, '+r'$kJ/cm^2$',fontsize=14)\n",
    "plt.ylabel('Altitude, km', fontsize=14)\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",
    "ax.tick_params(axis='x',labelsize=14)\n",
    "ax.tick_params(axis='y',labelsize=14)\n",
    "\n",
    "plt.savefig('../plots/pv-small-night-venus.png',bbox_inches='tight')\n",
    "plt.savefig('../plots/pv-small-night-venus.pdf', dpi=300,bbox_inches='tight')\n",
    "plt.savefig('../plots/pv-small-night-venus.eps', dpi=300,bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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