{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "40732e7b",
   "metadata": {},
   "source": [
    "# Section 3.2 - Mars SmallSat Aerocapture - Tradespace Exploration"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e543e74f",
   "metadata": {},
   "source": [
    "We use aerocapture feasibility charts to explore the design trade space for aerocapture at Mars using drag modulation aerocapture."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d0e0065d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from AMAT.planet import Planet\n",
    "from AMAT.vehicle import Vehicle\n",
    "\n",
    "import numpy as np\n",
    "from scipy import interpolate\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import rcParams\n",
    "from matplotlib.patches import Polygon\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6173d083",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a planet object\n",
    "planet=Planet(\"MARS\")\n",
    "planet.h_skip = 120000.0\n",
    "\n",
    "# Load an nominal atmospheric profile with height, temp, pressure, density data\n",
    "planet.loadAtmosphereModel('../../../atmdata/Mars/mars-gram-avg.dat', 0 , 1 ,2, 3)\n",
    "\n",
    "vinf_kms_array  = np.linspace( 0.0,   10.0,   11)\n",
    "betaRatio_array = np.linspace( 1.0,   21.0 ,  11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "abc66f65",
   "metadata": {},
   "outputs": [],
   "source": [
    "beta1 = 20.0\n",
    "runID = 'mars-smallsat-dm'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8a4869ee",
   "metadata": {},
   "outputs": [],
   "source": [
    "v0_kms_array    = np.zeros(len(vinf_kms_array))\n",
    "v0_kms_array[:] = np.sqrt(1.0*(vinf_kms_array[:]*1E3)**2.0 + 2*np.ones(len(vinf_kms_array))*planet.GM/(planet.RP+120.0*1.0E3))/1.0E3\n",
    "\n",
    "overShootLimit_array  = np.zeros((len(v0_kms_array),len(betaRatio_array)))\n",
    "underShootLimit_array = np.zeros((len(v0_kms_array),len(betaRatio_array)))\n",
    "exitflag_os_array     = np.zeros((len(v0_kms_array),len(betaRatio_array)))\n",
    "exitflag_us_array     = np.zeros((len(v0_kms_array),len(betaRatio_array)))\n",
    "TCW_array             = np.zeros((len(v0_kms_array),len(betaRatio_array)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "67764875",
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(0,len(v0_kms_array)):\n",
    "    for j in range(0,len(betaRatio_array)):\n",
    "        vehicle=Vehicle('DMVehicle', 100.0, beta1, 0.0, 1.767, 0.0, 0.35, planet)\n",
    "        vehicle.setInitialState(120.0,0.0,0.0,v0_kms_array[i],0.0,-4.5,0.0,0.0)\n",
    "        vehicle.setSolverParams(1E-6)\n",
    "        vehicle.setDragModulationVehicleParams(beta1,betaRatio_array[j])\n",
    "\n",
    "        underShootLimit_array[i,j], exitflag_us_array[i,j] = vehicle.findUnderShootLimitD(2400.0, 2.0, -80.0,-4.0,1E-10,400.0)\n",
    "        overShootLimit_array[i,j] , exitflag_os_array[i,j] = vehicle.findOverShootLimitD (2400.0, 2.0, -80.0,-4.0,1E-10,400.0)\n",
    "\n",
    "        TCW_array[i,j]    = overShootLimit_array[i,j] - underShootLimit_array[i,j]\n",
    "\n",
    "        print('VINF: '+str(vinf_kms_array[i])+' km/s, BETA RATIO: '+str(betaRatio_array[j])+' TCW: '+str(TCW_array[i,j])+' deg.')\n",
    "\n",
    "np.savetxt('../../../data/acta-astronautica/smallsat-mission-concepts/mars/'+runID+'vinf_kms_array.txt',vinf_kms_array)\n",
    "np.savetxt('../../../data/acta-astronautica/smallsat-mission-concepts/mars/'+runID+'v0_kms_array.txt',v0_kms_array)\n",
    "np.savetxt('../../../data/acta-astronautica/smallsat-mission-concepts/mars/'+runID+'betaRatio_array.txt',betaRatio_array)\n",
    "np.savetxt('../../../data/acta-astronautica/smallsat-mission-concepts/mars/'+runID+'overShootLimit_array.txt',overShootLimit_array)\n",
    "np.savetxt('../../../data/acta-astronautica/smallsat-mission-concepts/mars/'+runID+'exitflag_os_array.txt',exitflag_os_array)\n",
    "np.savetxt('../../../data/acta-astronautica/smallsat-mission-concepts/mars/'+runID+'underShootLimit_array.txt',underShootLimit_array)\n",
    "np.savetxt('../../../data/acta-astronautica/smallsat-mission-concepts/mars/'+runID+'exitflag_us_array.txt',exitflag_us_array)\n",
    "np.savetxt('../../../data/acta-astronautica/smallsat-mission-concepts/mars/'+runID+'TCW_array.txt',TCW_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f3832ee0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "V_infty: 0.0 km/s, BR: 1.0 G_MAX: 0.8802169883233952 QDOT_MAX: 12.299433180911738 J_MAX: 2452.610893056963 STAG. PRES: 0.001708753559306077\n",
      "V_infty: 0.0 km/s, BR: 3.0 G_MAX: 0.8802169883233952 QDOT_MAX: 15.798017276304611 J_MAX: 2452.610893056963 STAG. PRES: 0.001708753559306077\n",
      "V_infty: 0.0 km/s, BR: 5.0 G_MAX: 0.8802169883233952 QDOT_MAX: 17.258172599537417 J_MAX: 2452.610893056963 STAG. PRES: 0.001708753559306077\n",
      "V_infty: 0.0 km/s, BR: 7.0 G_MAX: 0.8802169883233952 QDOT_MAX: 18.099831481865703 J_MAX: 2452.610893056963 STAG. PRES: 0.001708753559306077\n",
      "V_infty: 0.0 km/s, BR: 9.0 G_MAX: 0.8802169883233952 QDOT_MAX: 18.702861979243437 J_MAX: 2452.610893056963 STAG. PRES: 0.001708753559306077\n",
      "V_infty: 0.0 km/s, BR: 11.0 G_MAX: 0.8802169883233952 QDOT_MAX: 19.157507566573663 J_MAX: 2452.610893056963 STAG. PRES: 0.001708753559306077\n",
      "V_infty: 0.0 km/s, BR: 13.0 G_MAX: 0.8802169883233952 QDOT_MAX: 19.52223610157443 J_MAX: 2452.610893056963 STAG. PRES: 0.001708753559306077\n",
      "V_infty: 0.0 km/s, BR: 15.0 G_MAX: 0.8802169883233952 QDOT_MAX: 19.825553544367676 J_MAX: 2452.610893056963 STAG. PRES: 0.001708753559306077\n",
      "V_infty: 0.0 km/s, BR: 17.0 G_MAX: 0.8802169883233952 QDOT_MAX: 20.076608738618578 J_MAX: 2452.610893056963 STAG. PRES: 0.001708753559306077\n",
      "V_infty: 0.0 km/s, BR: 19.0 G_MAX: 0.8802169883233952 QDOT_MAX: 20.29427853270561 J_MAX: 2452.610893056963 STAG. PRES: 0.001708753559306077\n",
      "V_infty: 0.0 km/s, BR: 21.0 G_MAX: 0.8802169883233952 QDOT_MAX: 20.492565007324007 J_MAX: 2452.610893056963 STAG. PRES: 0.001708753559306077\n",
      "V_infty: 1.0 km/s, BR: 1.0 G_MAX: 0.9838018321759852 QDOT_MAX: 13.286106469834941 J_MAX: 2569.0237601355398 STAG. PRES: 0.0019096681257546682\n",
      "V_infty: 1.0 km/s, BR: 3.0 G_MAX: 0.9838018321759852 QDOT_MAX: 17.063593357608102 J_MAX: 2569.0237601355398 STAG. PRES: 0.0019096681257546682\n",
      "V_infty: 1.0 km/s, BR: 5.0 G_MAX: 0.9838018321759852 QDOT_MAX: 18.596268345051726 J_MAX: 2569.0237601355398 STAG. PRES: 0.0019096681257546682\n",
      "V_infty: 1.0 km/s, BR: 7.0 G_MAX: 0.9838018321759852 QDOT_MAX: 19.489351761554847 J_MAX: 2569.0237601355398 STAG. PRES: 0.0019096681257546682\n",
      "V_infty: 1.0 km/s, BR: 9.0 G_MAX: 0.9838018321759852 QDOT_MAX: 20.11901809293889 J_MAX: 2569.0237601355398 STAG. PRES: 0.0019096681257546682\n",
      "V_infty: 1.0 km/s, BR: 11.0 G_MAX: 0.9838018321759852 QDOT_MAX: 20.59068028796914 J_MAX: 2569.0237601355398 STAG. PRES: 0.0019096681257546682\n",
      "V_infty: 1.0 km/s, BR: 13.0 G_MAX: 0.9838018321759852 QDOT_MAX: 20.975536488610587 J_MAX: 2569.0237601355398 STAG. PRES: 0.0019096681257546682\n",
      "V_infty: 1.0 km/s, BR: 15.0 G_MAX: 0.9838018321759852 QDOT_MAX: 21.297368632676267 J_MAX: 2569.0237601355398 STAG. PRES: 0.0019096681257546682\n",
      "V_infty: 1.0 km/s, BR: 17.0 G_MAX: 0.9838018321759852 QDOT_MAX: 21.57325154953119 J_MAX: 2569.0237601355398 STAG. PRES: 0.0019096681257546682\n",
      "V_infty: 1.0 km/s, BR: 19.0 G_MAX: 0.9838018321759852 QDOT_MAX: 21.798453513876588 J_MAX: 2569.0237601355398 STAG. PRES: 0.0019096681257546682\n",
      "V_infty: 1.0 km/s, BR: 21.0 G_MAX: 0.9838018321759852 QDOT_MAX: 22.004053687414597 J_MAX: 2569.0237601355398 STAG. PRES: 0.0019096681257546682\n",
      "V_infty: 2.0 km/s, BR: 1.0 G_MAX: 1.292258647598211 QDOT_MAX: 16.45313203834344 J_MAX: 2900.54443937752 STAG. PRES: 0.00250775054083841\n",
      "V_infty: 2.0 km/s, BR: 3.0 G_MAX: 1.292258647598211 QDOT_MAX: 21.01488138757287 J_MAX: 2900.54443937752 STAG. PRES: 0.00250775054083841\n",
      "V_infty: 2.0 km/s, BR: 5.0 G_MAX: 1.292258647598211 QDOT_MAX: 22.762826384149808 J_MAX: 2900.54443937752 STAG. PRES: 0.00250775054083841\n",
      "V_infty: 2.0 km/s, BR: 7.0 G_MAX: 1.292258647598211 QDOT_MAX: 23.82020071626924 J_MAX: 2900.54443937752 STAG. PRES: 0.00250775054083841\n",
      "V_infty: 2.0 km/s, BR: 9.0 G_MAX: 1.292258647598211 QDOT_MAX: 24.537315698305992 J_MAX: 2900.54443937752 STAG. PRES: 0.00250775054083841\n",
      "V_infty: 2.0 km/s, BR: 11.0 G_MAX: 1.292258647598211 QDOT_MAX: 25.102376038181774 J_MAX: 2900.54443937752 STAG. PRES: 0.00250775054083841\n",
      "V_infty: 2.0 km/s, BR: 13.0 G_MAX: 1.292258647598211 QDOT_MAX: 25.537434573256082 J_MAX: 2900.54443937752 STAG. PRES: 0.00250775054083841\n",
      "V_infty: 2.0 km/s, BR: 15.0 G_MAX: 1.292258647598211 QDOT_MAX: 25.916746113058156 J_MAX: 2900.54443937752 STAG. PRES: 0.00250775054083841\n",
      "V_infty: 2.0 km/s, BR: 17.0 G_MAX: 1.292258647598211 QDOT_MAX: 26.225308601524997 J_MAX: 2900.54443937752 STAG. PRES: 0.00250775054083841\n",
      "V_infty: 2.0 km/s, BR: 19.0 G_MAX: 1.292258647598211 QDOT_MAX: 26.485287929900462 J_MAX: 2900.54443937752 STAG. PRES: 0.00250775054083841\n",
      "V_infty: 2.0 km/s, BR: 21.0 G_MAX: 1.292258647598211 QDOT_MAX: 26.715527820971825 J_MAX: 2900.54443937752 STAG. PRES: 0.00250775054083841\n",
      "V_infty: 3.0 km/s, BR: 1.0 G_MAX: 1.8259113297641725 QDOT_MAX: 22.48387668593143 J_MAX: 3419.20077318237 STAG. PRES: 0.0035421159441447747\n",
      "V_infty: 3.0 km/s, BR: 3.0 G_MAX: 1.8259113297641725 QDOT_MAX: 28.107330552638214 J_MAX: 3419.20077318237 STAG. PRES: 0.0035421159441447747\n",
      "V_infty: 3.0 km/s, BR: 5.0 G_MAX: 1.8259113297641725 QDOT_MAX: 30.28776728402224 J_MAX: 3419.20077318237 STAG. PRES: 0.0035421159441447747\n",
      "V_infty: 3.0 km/s, BR: 7.0 G_MAX: 1.8259113297641725 QDOT_MAX: 31.580012183790597 J_MAX: 3419.20077318237 STAG. PRES: 0.0035421159441447747\n",
      "V_infty: 3.0 km/s, BR: 9.0 G_MAX: 1.8259113297641725 QDOT_MAX: 32.50259272113666 J_MAX: 3419.20077318237 STAG. PRES: 0.0035421159441447747\n",
      "V_infty: 3.0 km/s, BR: 11.0 G_MAX: 1.8259113297641725 QDOT_MAX: 33.18330150223976 J_MAX: 3419.20077318237 STAG. PRES: 0.0035421159441447747\n",
      "V_infty: 3.0 km/s, BR: 13.0 G_MAX: 1.8259113297641725 QDOT_MAX: 33.70437285340171 J_MAX: 3419.20077318237 STAG. PRES: 0.0035421159441447747\n",
      "V_infty: 3.0 km/s, BR: 15.0 G_MAX: 1.8259113297641725 QDOT_MAX: 34.17789626582457 J_MAX: 3419.20077318237 STAG. PRES: 0.0035421159441447747\n",
      "V_infty: 3.0 km/s, BR: 17.0 G_MAX: 1.8259113297641725 QDOT_MAX: 34.533330681355665 J_MAX: 3419.20077318237 STAG. PRES: 0.0035421159441447747\n",
      "V_infty: 3.0 km/s, BR: 19.0 G_MAX: 1.8259113297641725 QDOT_MAX: 34.88520416178665 J_MAX: 3419.20077318237 STAG. PRES: 0.0035421159441447747\n",
      "V_infty: 3.0 km/s, BR: 21.0 G_MAX: 1.8259113297641725 QDOT_MAX: 35.17734323690694 J_MAX: 3419.20077318237 STAG. PRES: 0.0035421159441447747\n",
      "V_infty: 4.0 km/s, BR: 1.0 G_MAX: 2.6556218073588584 QDOT_MAX: 31.727372765077163 J_MAX: 4096.741687771771 STAG. PRES: 0.005150134553951027\n",
      "V_infty: 4.0 km/s, BR: 3.0 G_MAX: 2.6556218073588584 QDOT_MAX: 39.0619139862417 J_MAX: 4096.741687771771 STAG. PRES: 0.005150134553951027\n",
      "V_infty: 4.0 km/s, BR: 5.0 G_MAX: 2.6556218073588584 QDOT_MAX: 41.89485280941947 J_MAX: 4096.741687771771 STAG. PRES: 0.005150134553951027\n",
      "V_infty: 4.0 km/s, BR: 7.0 G_MAX: 2.6556218073588584 QDOT_MAX: 43.542218798305136 J_MAX: 4096.741687771771 STAG. PRES: 0.005150134553951027\n",
      "V_infty: 4.0 km/s, BR: 9.0 G_MAX: 2.6556218073588584 QDOT_MAX: 44.70199272737595 J_MAX: 4096.741687771771 STAG. PRES: 0.005150134553951027\n",
      "V_infty: 4.0 km/s, BR: 11.0 G_MAX: 2.6556218073588584 QDOT_MAX: 45.58746885500958 J_MAX: 4096.741687771771 STAG. PRES: 0.005150134553951027\n",
      "V_infty: 4.0 km/s, BR: 13.0 G_MAX: 2.6556218073588584 QDOT_MAX: 46.30467592218154 J_MAX: 4096.741687771771 STAG. PRES: 0.005150134553951027\n",
      "V_infty: 4.0 km/s, BR: 15.0 G_MAX: 2.6556218073588584 QDOT_MAX: 46.87548844935506 J_MAX: 4096.741687771771 STAG. PRES: 0.005150134553951027\n",
      "V_infty: 4.0 km/s, BR: 17.0 G_MAX: 2.6556218073588584 QDOT_MAX: 47.35871917456521 J_MAX: 4096.741687771771 STAG. PRES: 0.005150134553951027\n",
      "V_infty: 4.0 km/s, BR: 19.0 G_MAX: 2.6556218073588584 QDOT_MAX: 47.82026480405196 J_MAX: 4096.741687771771 STAG. PRES: 0.005150134553951027\n",
      "V_infty: 4.0 km/s, BR: 21.0 G_MAX: 2.6556218073588584 QDOT_MAX: 48.194492000356234 J_MAX: 4096.741687771771 STAG. PRES: 0.005150134553951027\n",
      "V_infty: 5.0 km/s, BR: 1.0 G_MAX: 3.7872559881702705 QDOT_MAX: 44.876515302136596 J_MAX: 4922.900201062396 STAG. PRES: 0.007342348590774492\n",
      "V_infty: 5.0 km/s, BR: 3.0 G_MAX: 3.7872559881702705 QDOT_MAX: 54.77273778373592 J_MAX: 4922.900201062396 STAG. PRES: 0.007342348590774492\n",
      "V_infty: 5.0 km/s, BR: 5.0 G_MAX: 3.7872559881702705 QDOT_MAX: 58.46514340789856 J_MAX: 4922.900201062396 STAG. PRES: 0.007342348590774492\n",
      "V_infty: 5.0 km/s, BR: 7.0 G_MAX: 3.7872559881702705 QDOT_MAX: 60.60030104917139 J_MAX: 4922.900201062396 STAG. PRES: 0.007342348590774492\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "V_infty: 5.0 km/s, BR: 9.0 G_MAX: 3.7872559881702705 QDOT_MAX: 62.18294269366363 J_MAX: 4922.900201062396 STAG. PRES: 0.007342348590774492\n",
      "V_infty: 5.0 km/s, BR: 11.0 G_MAX: 3.7872559881702705 QDOT_MAX: 63.34656454184943 J_MAX: 4922.900201062396 STAG. PRES: 0.007342348590774492\n",
      "V_infty: 5.0 km/s, BR: 13.0 G_MAX: 3.7872559881702705 QDOT_MAX: 64.27008443073703 J_MAX: 4922.900201062396 STAG. PRES: 0.007342348590774492\n",
      "V_infty: 5.0 km/s, BR: 15.0 G_MAX: 3.7872559881702705 QDOT_MAX: 64.99829582271471 J_MAX: 4922.900201062396 STAG. PRES: 0.007342348590774492\n",
      "V_infty: 5.0 km/s, BR: 17.0 G_MAX: 3.7872559881702705 QDOT_MAX: 65.73133296348114 J_MAX: 4922.900201062396 STAG. PRES: 0.007342348590774492\n",
      "V_infty: 5.0 km/s, BR: 19.0 G_MAX: 3.7872559881702705 QDOT_MAX: 66.30766668470055 J_MAX: 4922.900201062396 STAG. PRES: 0.007342348590774492\n",
      "V_infty: 5.0 km/s, BR: 21.0 G_MAX: 3.7872559881702705 QDOT_MAX: 66.74041666826393 J_MAX: 4922.900201062396 STAG. PRES: 0.007342348590774492\n",
      "V_infty: 6.0 km/s, BR: 1.0 G_MAX: 5.227929145302218 QDOT_MAX: 63.46812084187307 J_MAX: 5894.435316281576 STAG. PRES: 0.010132860400697477\n",
      "V_infty: 6.0 km/s, BR: 3.0 G_MAX: 5.227929145302218 QDOT_MAX: 76.21405435514988 J_MAX: 5894.435316281576 STAG. PRES: 0.010132860400697477\n",
      "V_infty: 6.0 km/s, BR: 5.0 G_MAX: 5.227929145302218 QDOT_MAX: 81.10077161980504 J_MAX: 5894.435316281576 STAG. PRES: 0.010132860400697477\n",
      "V_infty: 6.0 km/s, BR: 7.0 G_MAX: 5.227929145302218 QDOT_MAX: 83.98729732389532 J_MAX: 5894.435316281576 STAG. PRES: 0.010132860400697477\n",
      "V_infty: 6.0 km/s, BR: 9.0 G_MAX: 5.227929145302218 QDOT_MAX: 85.9991300601521 J_MAX: 5894.435316281576 STAG. PRES: 0.010132860400697477\n",
      "V_infty: 6.0 km/s, BR: 11.0 G_MAX: 5.227929145302218 QDOT_MAX: 87.49640623239803 J_MAX: 5894.435316281576 STAG. PRES: 0.010132860400697477\n",
      "V_infty: 6.0 km/s, BR: 13.0 G_MAX: 5.227929145302218 QDOT_MAX: 88.70484332355163 J_MAX: 5894.435316281576 STAG. PRES: 0.010132860400697477\n",
      "V_infty: 6.0 km/s, BR: 15.0 G_MAX: 5.227929145302218 QDOT_MAX: 89.83803844391937 J_MAX: 5894.435316281576 STAG. PRES: 0.010132860400697477\n",
      "V_infty: 6.0 km/s, BR: 17.0 G_MAX: 5.227929145302218 QDOT_MAX: 90.67284098752529 J_MAX: 5894.435316281576 STAG. PRES: 0.010132860400697477\n",
      "V_infty: 6.0 km/s, BR: 19.0 G_MAX: 5.227929145302218 QDOT_MAX: 91.38632353409926 J_MAX: 5894.435316281576 STAG. PRES: 0.010132860400697477\n",
      "V_infty: 6.0 km/s, BR: 21.0 G_MAX: 5.227929145302218 QDOT_MAX: 92.22683694311006 J_MAX: 5894.435316281576 STAG. PRES: 0.010132860400697477\n",
      "V_infty: 7.0 km/s, BR: 1.0 G_MAX: 7.0010671079297 QDOT_MAX: 87.93582264144091 J_MAX: 7010.201827137782 STAG. PRES: 0.013566773578925745\n",
      "V_infty: 7.0 km/s, BR: 3.0 G_MAX: 7.0010671079297 QDOT_MAX: 104.62778626050326 J_MAX: 7010.201827137782 STAG. PRES: 0.013566773578925745\n",
      "V_infty: 7.0 km/s, BR: 5.0 G_MAX: 7.0010671079297 QDOT_MAX: 110.88771727814694 J_MAX: 7010.201827137782 STAG. PRES: 0.013566773578925745\n",
      "V_infty: 7.0 km/s, BR: 7.0 G_MAX: 7.0010671079297 QDOT_MAX: 114.70249033273082 J_MAX: 7010.201827137782 STAG. PRES: 0.013566773578925745\n",
      "V_infty: 7.0 km/s, BR: 9.0 G_MAX: 7.0010671079297 QDOT_MAX: 117.1013604471338 J_MAX: 7010.201827137782 STAG. PRES: 0.013566773578925745\n",
      "V_infty: 7.0 km/s, BR: 11.0 G_MAX: 7.0010671079297 QDOT_MAX: 119.35104365006556 J_MAX: 7010.201827137782 STAG. PRES: 0.013566773578925745\n",
      "V_infty: 7.0 km/s, BR: 13.0 G_MAX: 7.0010671079297 QDOT_MAX: 120.87372266737007 J_MAX: 7010.201827137782 STAG. PRES: 0.013566773578925745\n",
      "V_infty: 7.0 km/s, BR: 15.0 G_MAX: 7.0010671079297 QDOT_MAX: 122.19755844059095 J_MAX: 7010.201827137782 STAG. PRES: 0.013566773578925745\n",
      "V_infty: 7.0 km/s, BR: 17.0 G_MAX: 7.0010671079297 QDOT_MAX: 123.62111512049795 J_MAX: 7010.201827137782 STAG. PRES: 0.013566773578925745\n",
      "V_infty: 7.0 km/s, BR: 19.0 G_MAX: 7.0010671079297 QDOT_MAX: 124.69880008531256 J_MAX: 7010.201827137782 STAG. PRES: 0.013566773578925745\n",
      "V_infty: 7.0 km/s, BR: 21.0 G_MAX: 7.0010671079297 QDOT_MAX: 125.50626604057734 J_MAX: 7010.201827137782 STAG. PRES: 0.013566773578925745\n",
      "V_infty: 8.0 km/s, BR: 1.0 G_MAX: 9.104871040862236 QDOT_MAX: 119.47897943096713 J_MAX: 8270.011706981604 STAG. PRES: 0.017640083281896677\n",
      "V_infty: 8.0 km/s, BR: 3.0 G_MAX: 9.104871040862236 QDOT_MAX: 140.88872596656054 J_MAX: 8270.011706981604 STAG. PRES: 0.017640083281896677\n",
      "V_infty: 8.0 km/s, BR: 5.0 G_MAX: 9.104871040862236 QDOT_MAX: 148.77094111167912 J_MAX: 8270.011706981604 STAG. PRES: 0.017640083281896677\n",
      "V_infty: 8.0 km/s, BR: 7.0 G_MAX: 9.104871040862236 QDOT_MAX: 153.9180979283062 J_MAX: 8270.011706981604 STAG. PRES: 0.017640083281896677\n",
      "V_infty: 8.0 km/s, BR: 9.0 G_MAX: 9.104871040862236 QDOT_MAX: 157.02745143315624 J_MAX: 8270.011706981604 STAG. PRES: 0.017640083281896677\n",
      "V_infty: 8.0 km/s, BR: 11.0 G_MAX: 9.104871040862236 QDOT_MAX: 159.9999206756808 J_MAX: 8270.011706981604 STAG. PRES: 0.017640083281896677\n",
      "V_infty: 8.0 km/s, BR: 13.0 G_MAX: 9.104871040862236 QDOT_MAX: 162.00108695667657 J_MAX: 8270.011706981604 STAG. PRES: 0.017640083281896677\n",
      "V_infty: 8.0 km/s, BR: 15.0 G_MAX: 9.104871040862236 QDOT_MAX: 163.53535688229584 J_MAX: 8270.011706981604 STAG. PRES: 0.017640083281896677\n",
      "V_infty: 8.0 km/s, BR: 17.0 G_MAX: 9.104871040862236 QDOT_MAX: 165.51765839020703 J_MAX: 8270.011706981604 STAG. PRES: 0.017640083281896677\n",
      "V_infty: 8.0 km/s, BR: 19.0 G_MAX: 9.104871040862236 QDOT_MAX: 167.04520189995392 J_MAX: 8270.011706981604 STAG. PRES: 0.017640083281896677\n",
      "V_infty: 8.0 km/s, BR: 21.0 G_MAX: 9.104871040862236 QDOT_MAX: 168.21195539865383 J_MAX: 8270.011706981604 STAG. PRES: 0.017640083281896677\n",
      "V_infty: 9.0 km/s, BR: 1.0 G_MAX: 11.528034195425901 QDOT_MAX: 158.9507341633341 J_MAX: 9673.746160496585 STAG. PRES: 0.022332463228912258\n",
      "V_infty: 9.0 km/s, BR: 3.0 G_MAX: 11.528034195425901 QDOT_MAX: 186.29130192116975 J_MAX: 9673.746160496585 STAG. PRES: 0.022332463228912258\n",
      "V_infty: 9.0 km/s, BR: 5.0 G_MAX: 11.528034195425901 QDOT_MAX: 196.65483772964578 J_MAX: 9673.746160496585 STAG. PRES: 0.022332463228912258\n",
      "V_infty: 9.0 km/s, BR: 7.0 G_MAX: 11.528034195425901 QDOT_MAX: 202.60814301172775 J_MAX: 9673.746160496585 STAG. PRES: 0.022332463228912258\n",
      "V_infty: 9.0 km/s, BR: 9.0 G_MAX: 11.528034195425901 QDOT_MAX: 207.26688550435304 J_MAX: 9673.746160496585 STAG. PRES: 0.022332463228912258\n",
      "V_infty: 9.0 km/s, BR: 11.0 G_MAX: 11.528034195425901 QDOT_MAX: 209.9700198724151 J_MAX: 9673.746160496585 STAG. PRES: 0.022332463228912258\n",
      "V_infty: 9.0 km/s, BR: 13.0 G_MAX: 11.528034195425901 QDOT_MAX: 213.32735403755765 J_MAX: 9673.746160496585 STAG. PRES: 0.022332463228912258\n",
      "V_infty: 9.0 km/s, BR: 15.0 G_MAX: 11.528034195425901 QDOT_MAX: 215.99728836425746 J_MAX: 9673.746160496585 STAG. PRES: 0.022332463228912258\n",
      "V_infty: 9.0 km/s, BR: 17.0 G_MAX: 11.528034195425901 QDOT_MAX: 217.909062994625 J_MAX: 9673.746160496585 STAG. PRES: 0.022332463228912258\n",
      "V_infty: 9.0 km/s, BR: 19.0 G_MAX: 11.528034195425901 QDOT_MAX: 219.35470067586087 J_MAX: 9673.746160496585 STAG. PRES: 0.022332463228912258\n",
      "V_infty: 9.0 km/s, BR: 21.0 G_MAX: 11.528034195425901 QDOT_MAX: 220.45129046186048 J_MAX: 9673.746160496585 STAG. PRES: 0.022332463228912258\n",
      "V_infty: 10.0 km/s, BR: 1.0 G_MAX: 14.304598311664126 QDOT_MAX: 207.7294817594725 J_MAX: 11216.931808408366 STAG. PRES: 0.02770830881406925\n",
      "V_infty: 10.0 km/s, BR: 3.0 G_MAX: 14.304598311664126 QDOT_MAX: 241.42819924126587 J_MAX: 11216.931808408366 STAG. PRES: 0.02770830881406925\n",
      "V_infty: 10.0 km/s, BR: 5.0 G_MAX: 14.304598311664126 QDOT_MAX: 254.6862088640615 J_MAX: 11216.931808408366 STAG. PRES: 0.02770830881406925\n",
      "V_infty: 10.0 km/s, BR: 7.0 G_MAX: 14.304598311664126 QDOT_MAX: 262.7062514907969 J_MAX: 11216.931808408366 STAG. PRES: 0.02770830881406925\n",
      "V_infty: 10.0 km/s, BR: 9.0 G_MAX: 14.304598311664126 QDOT_MAX: 268.1984750146885 J_MAX: 11216.931808408366 STAG. PRES: 0.02770830881406925\n",
      "V_infty: 10.0 km/s, BR: 11.0 G_MAX: 14.304598311664126 QDOT_MAX: 271.53748789869223 J_MAX: 11216.931808408366 STAG. PRES: 0.02770830881406925\n",
      "V_infty: 10.0 km/s, BR: 13.0 G_MAX: 14.304598311664126 QDOT_MAX: 276.18687261119214 J_MAX: 11216.931808408366 STAG. PRES: 0.02770830881406925\n",
      "V_infty: 10.0 km/s, BR: 15.0 G_MAX: 14.304598311664126 QDOT_MAX: 279.5264028214768 J_MAX: 11216.931808408366 STAG. PRES: 0.02770830881406925\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "V_infty: 10.0 km/s, BR: 17.0 G_MAX: 14.304598311664126 QDOT_MAX: 281.9513743438992 J_MAX: 11216.931808408366 STAG. PRES: 0.02770830881406925\n",
      "V_infty: 10.0 km/s, BR: 19.0 G_MAX: 14.304598311664126 QDOT_MAX: 283.8000991043289 J_MAX: 11216.931808408366 STAG. PRES: 0.02770830881406925\n",
      "V_infty: 10.0 km/s, BR: 21.0 G_MAX: 14.304598311664126 QDOT_MAX: 285.13162284891297 J_MAX: 11216.931808408366 STAG. PRES: 0.02770830881406925\n"
     ]
    }
   ],
   "source": [
    "acc_net_g_max_array       = np.zeros((len(v0_kms_array),len(betaRatio_array)))\n",
    "stag_pres_atm_max_array   = np.zeros((len(v0_kms_array),len(betaRatio_array)))\n",
    "q_stag_total_max_array    = np.zeros((len(v0_kms_array),len(betaRatio_array)))\n",
    "heatload_max_array        = np.zeros((len(v0_kms_array),len(betaRatio_array)))\n",
    "\n",
    "\n",
    "underShootLimit_array = np.loadtxt('../../../data/acta-astronautica/smallsat-mission-concepts/mars/'+runID+'underShootLimit_array.txt')\n",
    "overShootLimit_array = np.loadtxt('../../../data/acta-astronautica/smallsat-mission-concepts/mars/'+runID+'overShootLimit_array.txt')\n",
    "\n",
    "for i in range(0,len(v0_kms_array)):\n",
    "    for j in range(0,len(betaRatio_array)):\n",
    "        vehicle=Vehicle('DMVehicle', 100.0, beta1, 0.0, 1.767, 0.0, 0.35, planet)\n",
    "        vehicle.setInitialState(120.0,0.0,0.0,v0_kms_array[i],0.0,overShootLimit_array[i,j],0.0,0.0)\n",
    "        vehicle.setSolverParams(1E-6)\n",
    "\n",
    "        vehicle.propogateEntry (2400.0, 2.0, 0.0)\n",
    "\n",
    "        # Extract and save variables to plot\n",
    "        t_min_os         = vehicle.t_minc\n",
    "        h_km_os          = vehicle.h_kmc\n",
    "        acc_net_g_os     = vehicle.acc_net_g\n",
    "        q_stag_con_os    = vehicle.q_stag_con\n",
    "        q_stag_rad_os    = vehicle.q_stag_rad\n",
    "        rc_os            = vehicle.rc\n",
    "        vc_os            = vehicle.vc\n",
    "        stag_pres_atm_os = vehicle.computeStagPres(rc_os,vc_os)/(1.01325E5)\n",
    "        heatload_os      = vehicle.heatload\n",
    "\n",
    "\n",
    "        vehicle=Vehicle('DMVehicle', 100.0, beta1, 0.0, 1.767, 0.0, 0.35, planet)\n",
    "        vehicle.setInitialState(120.0,0.0,0.0,v0_kms_array[i],0.0,underShootLimit_array[i,j],0.0,0.0)\n",
    "        vehicle.setSolverParams( 1E-6)\n",
    "\n",
    "        vehicle.propogateEntry (2400.0, 2.0, 0.0)\n",
    "\n",
    "        # Extract and save variable to plot\n",
    "        t_min_us         = vehicle.t_minc\n",
    "        h_km_us          = vehicle.h_kmc\n",
    "        acc_net_g_us     = vehicle.acc_net_g\n",
    "        q_stag_con_us    = vehicle.q_stag_con\n",
    "        q_stag_rad_us    = vehicle.q_stag_rad\n",
    "        rc_us            = vehicle.rc\n",
    "        vc_us            = vehicle.vc\n",
    "        stag_pres_atm_us = vehicle.computeStagPres(rc_us,vc_us)/(1.01325E5)\n",
    "        heatload_us      = vehicle.heatload\n",
    "\n",
    "        q_stag_total_os  = q_stag_con_os + q_stag_rad_os\n",
    "        q_stag_total_us  = q_stag_con_us + q_stag_rad_us\n",
    "\n",
    "        acc_net_g_max_array[i,j]      = max(max(acc_net_g_os),max(acc_net_g_os))\n",
    "        stag_pres_atm_max_array[i,j]  = max(max(stag_pres_atm_os),max(stag_pres_atm_os))\n",
    "        q_stag_total_max_array[i,j]   = max(max(q_stag_total_os),max(q_stag_total_us))\n",
    "        heatload_max_array[i,j]       = max(max(heatload_os),max(heatload_os))\n",
    "\n",
    "        print(\"V_infty: \"+str(vinf_kms_array[i])+\" km/s\"+\", BR: \"+str(betaRatio_array[j])+\" G_MAX: \"+str(acc_net_g_max_array[i,j])+\" QDOT_MAX: \"+str(q_stag_total_max_array[i,j])+\" J_MAX: \"+str(heatload_max_array[i,j])+\" STAG. PRES: \"+str(stag_pres_atm_max_array[i,j]))\n",
    "\n",
    "np.savetxt('../../../data/acta-astronautica/smallsat-mission-concepts/mars/'+runID+'acc_net_g_max_array.txt',acc_net_g_max_array)\n",
    "np.savetxt('../../../data/acta-astronautica/smallsat-mission-concepts/mars/'+runID+'stag_pres_atm_max_array.txt',stag_pres_atm_max_array)\n",
    "np.savetxt('../../../data/acta-astronautica/smallsat-mission-concepts/mars/'+runID+'q_stag_total_max_array.txt',q_stag_total_max_array)\n",
    "np.savetxt('../../../data/acta-astronautica/smallsat-mission-concepts/mars/'+runID+'heatload_max_array.txt',heatload_max_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "004dd32d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.loadtxt('../../../data/acta-astronautica/smallsat-mission-concepts/mars/'+runID+'vinf_kms_array.txt')\n",
    "y = np.loadtxt('../../../data/acta-astronautica/smallsat-mission-concepts/mars/'+runID+'betaRatio_array.txt')\n",
    "\n",
    "Z1 = np.loadtxt('../../../data/acta-astronautica/smallsat-mission-concepts/mars/'+runID+'TCW_array.txt')\n",
    "G1 = np.loadtxt('../../../data/acta-astronautica/smallsat-mission-concepts/mars/'+runID+'acc_net_g_max_array.txt')\n",
    "Q1 = np.loadtxt('../../../data/acta-astronautica/smallsat-mission-concepts/mars/'+runID+'q_stag_total_max_array.txt')\n",
    "H1 = np.loadtxt('../../../data/acta-astronautica/smallsat-mission-concepts/mars/'+runID+'heatload_max_array.txt')\n",
    "S1 = np.loadtxt('../../../data/acta-astronautica/smallsat-mission-concepts/mars/'+runID+'stag_pres_atm_max_array.txt')\n",
    "\n",
    "\n",
    "f1 = interpolate.interp2d(x, y, np.transpose(Z1), kind='cubic')\n",
    "g1 = interpolate.interp2d(x, y, np.transpose(G1), kind='cubic')\n",
    "q1 = interpolate.interp2d(x, y, np.transpose(Q1), kind='cubic')\n",
    "h1 = interpolate.interp2d(x, y, np.transpose(H1), kind='cubic')\n",
    "s1 = interpolate.interp2d(x, y, np.transpose(S1), kind='cubic')\n",
    "\n",
    "\n",
    "x_new =  np.linspace( 0.0,   10,  110)\n",
    "y_new =  np.linspace( 0.0,   21 ,110)\n",
    "\n",
    "z1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "g1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "q1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "h1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "s1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "\n",
    "for i in range(0,len(x_new)):\n",
    "    for j in range(0,len(y_new)):\n",
    "\n",
    "        z1_new[i,j] = f1(x_new[i],y_new[j])\n",
    "        g1_new[i,j] = g1(x_new[i],y_new[j])\n",
    "        q1_new[i,j] = q1(x_new[i],y_new[j])\n",
    "        h1_new[i,j] = h1(x_new[i],y_new[j])\n",
    "        s1_new[i,j] = s1(x_new[i],y_new[j])\n",
    "\n",
    "\n",
    "Z1 = z1_new\n",
    "G1 = g1_new\n",
    "Q1 = q1_new\n",
    "S1 = s1_new\n",
    "H1 = h1_new/1000.0\n",
    "\n",
    "X, Y = np.meshgrid(x_new, y_new)\n",
    "\n",
    "Zlevels = np.array([0.5, 0.80, 1.0, 1.20, 1.40, 1.50])\n",
    "\n",
    "Glevels = np.array([3, 6])\n",
    "Qlevels = np.array([40, 60, 80, 120])\n",
    "Hlevels = np.array([6, 10])\n",
    "\n",
    "\n",
    "fig = plt.figure()\n",
    "fig.set_size_inches([5, 5])\n",
    "plt.rc('font',family='Times New Roman')\n",
    "params = {'mathtext.default': 'regular' }\n",
    "plt.rcParams.update(params)\n",
    "\n",
    "plt.xlim([0.0,10.0])\n",
    "plt.ylim([1.0,21.0])\n",
    "\n",
    "\n",
    "ZCS1 = plt.contour(X, Y, np.transpose(Z1), levels=Zlevels, colors='black')\n",
    "\n",
    "plt.clabel(ZCS1, inline=1, fontsize=12, colors='black',fmt='%.2f',inline_spacing=1)\n",
    "ZCS1.collections[0].set_linewidths(1.75)\n",
    "ZCS1.collections[1].set_linewidths(1.75)\n",
    "ZCS1.collections[2].set_linewidths(1.75)\n",
    "ZCS1.collections[3].set_linewidths(1.75)\n",
    "ZCS1.collections[4].set_linewidths(1.75)\n",
    "ZCS1.collections[5].set_linewidths(1.75)\n",
    "ZCS1.collections[0].set_label(r'$TCW, deg$')\n",
    "\n",
    "\n",
    "GCS1 = plt.contour(X, Y, np.transpose(G1), levels=Glevels, colors='blue',linestyles='dashed')\n",
    "\n",
    "Glabels=plt.clabel(GCS1, inline=1, fontsize=12, colors='blue',fmt='%d',inline_spacing=0)\n",
    "GCS1.collections[0].set_linewidths(1.5)\n",
    "GCS1.collections[0].set_linewidths(1.5)\n",
    "\n",
    "GCS1.collections[0].set_label(r'$g$'+r'-load')\n",
    "\n",
    "\n",
    "QCS1 = plt.contour(X, Y, np.transpose(Q1), levels=Qlevels, colors='red',linestyles='dotted')\n",
    "plt.clabel(QCS1, inline=1, fontsize=12, colors='red',fmt='%d',inline_spacing=0)\n",
    "QCS1.collections[0].set_linewidths(1.5)\n",
    "QCS1.collections[1].set_linewidths(1.5)\n",
    "QCS1.collections[2].set_linewidths(1.5)\n",
    "QCS1.collections[3].set_linewidths(1.5)\n",
    "QCS1.collections[0].set_label(r'$\\dot{q}$'+', '+r'$W/cm^2$')\n",
    "\n",
    "\n",
    "HCS1 = plt.contour(X, Y, np.transpose(H1), levels=Hlevels, colors='xkcd:brown',linestyles='dashdot')\n",
    "\n",
    "Hlabels=plt.clabel(HCS1, inline=1, fontsize=12, colors='xkcd:brown',fmt='%d',inline_spacing=0)\n",
    "HCS1.collections[0].set_linewidths(1.75)\n",
    "HCS1.collections[1].set_linewidths(1.75)\n",
    "HCS1.collections[0].set_label(r'$Q$'+', '+r'$kJ/cm^2$')\n",
    "\n",
    "params = {'mathtext.default': 'regular' }\n",
    "plt.rcParams.update(params)\n",
    "plt.ylabel(r'$\\beta_2$'+' / '+r'$ \\beta_1 $' ,fontsize=14)\n",
    "plt.xlabel(\"Arrival \"+r'$V_\\infty$'+r', km/s' ,fontsize=14)\n",
    "plt.yticks(np.array([1, 5, 10, 15, 20]),fontsize=14)\n",
    "plt.xticks(fontsize=14)\n",
    "ax = plt.gca()\n",
    "ax.xaxis.set_tick_params(direction='in', which='both')\n",
    "ax.yaxis.set_tick_params(direction='in', which='both')\n",
    "ax.xaxis.set_tick_params(width=1, length=4)\n",
    "ax.yaxis.set_tick_params(width=1, length=4)\n",
    "ax.xaxis.set_tick_params(width=1, length=4, which='minor')\n",
    "ax.yaxis.set_tick_params(width=1, length=4, which='minor')\n",
    "#plt.legend(loc='upper left', fontsize=16)\n",
    "from matplotlib.lines import Line2D\n",
    "colors = ['black', 'red', 'green']\n",
    "lines = [Line2D([0], [0], color='black', linewidth=1.75, linestyle='solid'),\n",
    "         Line2D([0], [0], color='blue',  linewidth=1.75, linestyle='dashed'),\n",
    "         Line2D([0], [0], color='red',  linewidth=1.75, linestyle='dotted'),\n",
    "         Line2D([0], [0], color='xkcd:brown',  linewidth=2.00, linestyle='dashdot')]\n",
    "labels = [r'$TCW, deg$', r'$g$'+r'-load', r'$\\dot{q}$'+', '+r'$W/cm^2$', r'$Q$'+', '+r'$kJ/cm^2$']\n",
    "plt.legend(lines, labels, loc='upper right',fontsize=12, framealpha=1)\n",
    "\n",
    "for l in Hlabels:\n",
    "    l.set_rotation(-90)\n",
    "for l in Glabels:\n",
    "    l.set_rotation(-90)\n",
    "\n",
    "for axis in ['top', 'bottom', 'left', 'right']:\n",
    "    ax.spines[axis].set_linewidth(1)\n",
    "\n",
    "plt.scatter(2.65, 7.5, marker=\"*\", s=300, color='xkcd:black', zorder=100)\n",
    "\n",
    "plt.savefig('../../../data/mdpi-aerospace/smallsat-mission-concepts/mars/mars-smallsat-ac-tradespace.png', dpi= 300,bbox_inches='tight')\n",
    "plt.savefig('../../../data/mdpi-aerospace/smallsat-mission-concepts/mars/mars-smallsat-ac-tradespace.pdf', dpi=300,bbox_inches='tight')\n",
    "plt.savefig('../../../data/mdpi-aerospace/smallsat-mission-concepts/mars/mars-smallsat-ac-tradespace.eps', dpi=300,bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  }
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