{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Example - 24 - PV Small Day - 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 Day 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-Day', 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,-25.4,0.0,0.0)"
   ]
  },
  {
   "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": {
      "image/png": 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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-day-venus.png',bbox_inches='tight')\n",
    "plt.savefig('../plots/pv-small-day-venus.pdf', dpi=300,bbox_inches='tight')\n",
    "plt.savefig('../plots/pv-small-day-venus.eps', dpi=300,bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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