{
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   "source": [
    "## Tutorial 23 - Aircraft Aerodynamic Analysis\n",
    "Welcome to this tutorial on performing aerodynamic analysis of a turbofan aircraft using RCAIDE. This guide will walk you through the code, explain its components, and highlight where modifications can be made to customize the simulation for different vehicle designs.\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Header and Imports\n",
    "\n",
    "\n",
    "The **Imports** section is divided into two parts: general-purpose Python libraries and simulation-specific libraries."
   ]
  },
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   "source": [
    "import matplotlib.cm as cm   \n",
    "import numpy as np\n",
    "from copy import deepcopy\n",
    "import matplotlib.pyplot  as plt\n",
    "import os"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. RCAIDE Imports\n",
    "\n",
    "The **RCAIDE Imports** section includes the core modules needed for the simulation. These libraries provide specialized classes and tools for building, analyzing, and running aircraft models.\n",
    "\n",
    "### Key Imports:\n",
    "\n",
    "1. **RCAIDE**: The core package is imported directly. This approach allows us to access specific classes and methods from RCAIDE without repeatedly importing individual components at the top of the script.\n",
    "\n",
    "2. **`Units` Module**: The Units module is a standardized way to handle unit conversions within RCAIDE. It ensures consistent units across all inputs and outputs, reducing the likelihood of conversion errors."
   ]
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  {
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   "source": [
    "import RCAIDE\n",
    "from RCAIDE.Framework.Core import Units , Data   \n",
    "from RCAIDE.Library.Methods.Powertrain.Propulsors.Turbofan          import design_turbofan\n",
    "from RCAIDE.Library.Methods.Performance                            import aircraft_aerodynamic_analysis \n",
    "from RCAIDE.Library.Methods.Geometry.Planform                      import segment_properties \n",
    "from RCAIDE.Library.Plots                                          import *        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Vehicle Setup\n",
    "\n",
    "The **`vehicle_setup`** function defines the baseline configuration of the aircraft. This section builds the vehicle step-by-step by specifying its components, geometric properties, and high-level parameters.\n",
    "\n",
    "A detailed description of the vehicle setup is provided in the [Tutorial 1](tutorial_01_turbofan_aircraft.ipynb)."
   ]
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   "source": [
    "def vehicle_setup(): \n",
    "    \n",
    "    # ------------------------------------------------------------------\n",
    "    #   Initialize the Vehicle\n",
    "    # ------------------------------------------------------------------    \n",
    "    \n",
    "    vehicle = RCAIDE.Vehicle()\n",
    "    vehicle.tag = 'Boeing_737-800'\n",
    "    # ################################################# Vehicle-level Properties #################################################   \n",
    "    vehicle.mass_properties.max_takeoff               = 79015.8 * Units.kilogram  \n",
    "    vehicle.mass_properties.takeoff                   = 79015.8 * Units.kilogram    \n",
    "    vehicle.mass_properties.operating_empty           = 62746.4 * Units.kilogram  \n",
    "    vehicle.mass_properties.max_zero_fuel             = 62732.0 * Units.kilogram \n",
    "    vehicle.mass_properties.cargo                     = 10000.  * Units.kilogram  \n",
    "    vehicle.mass_properties.center_of_gravity         = [[21,0, 0, 0]]\n",
    "    vehicle.flight_envelope.ultimate_load             = 3.75\n",
    "    vehicle.flight_envelope.positive_limit_load       = 2.5 \n",
    "    vehicle.flight_envelope.design_mach_number        = 0.78 \n",
    "    vehicle.flight_envelope.design_cruise_altitude    = 35000*Units.feet\n",
    "    vehicle.flight_envelope.design_range              = 3500 * Units.nmi\n",
    "    vehicle.reference_area                            = 124.862 * Units['meters**2']   \n",
    "    vehicle.passengers                                = 170\n",
    "    vehicle.systems.control                           = \"fully powered\" \n",
    "    vehicle.systems.accessories                       = \"medium range\"\n",
    "    \n",
    "     # ################################################# Landing Gear #############################################################   \n",
    "    # ------------------------------------------------------------------        \n",
    "    #  Landing Gear\n",
    "    # ------------------------------------------------------------------  \n",
    "    main_gear               = RCAIDE.Library.Components.Landing_Gear.Main_Landing_Gear()\n",
    "    main_gear.tire_diameter = 1.12000 * Units.m\n",
    "    main_gear.strut_length  = 1.8 * Units.m \n",
    "    main_gear.units         = 2    # Number of main landing gear\n",
    "    main_gear.wheels        = 2    # Number of wheels on the main landing gear\n",
    "    vehicle.append_component(main_gear)  \n",
    "\n",
    "    nose_gear               = RCAIDE.Library.Components.Landing_Gear.Nose_Landing_Gear()       \n",
    "    nose_gear.tire_diameter = 0.6858 * Units.m\n",
    "    nose_gear.units         = 1    # Number of nose landing gear\n",
    "    nose_gear.wheels        = 2    # Number of wheels on the nose landing gear\n",
    "    nose_gear.strut_length  = 1.3 * Units.m \n",
    "    vehicle.append_component(nose_gear)\n",
    "    # ################################################# Wings ##################################################################### \n",
    "    # ------------------------------------------------------------------\n",
    "    #   Main Wing\n",
    "    # ------------------------------------------------------------------\n",
    " \n",
    "    wing                                  = RCAIDE.Library.Components.Wings.Main_Wing()\n",
    "    wing.tag                              = 'main_wing' \n",
    "    wing.aspect_ratio                     = 10.18\n",
    "    wing.sweeps.quarter_chord             = 25 * Units.deg\n",
    "    wing.thickness_to_chord               = 0.1\n",
    "    wing.taper                            = 0.1 \n",
    "    wing.spans.projected                  = 34.32 \n",
    "    wing.chords.root                      = 7.760 * Units.meter\n",
    "    wing.chords.tip                       = 0.782 * Units.meter\n",
    "    wing.chords.mean_aerodynamic          = 4.235 * Units.meter \n",
    "    wing.areas.reference                  = 124.862\n",
    "    wing.areas.wetted                     = 225.08 \n",
    "    wing.twists.root                      = 4.0 * Units.degrees\n",
    "    wing.twists.tip                       = 0.0 * Units.degrees \n",
    "    wing.origin                           = [[13.61,0,-0.5]]\n",
    "    wing.aerodynamic_center               = [0,0,0] \n",
    "    wing.vertical                         = False\n",
    "    wing.symmetric                        = True\n",
    "    wing.high_lift                        = True \n",
    "    wing.dynamic_pressure_ratio           = 1.0\n",
    "    # Wing Segments\n",
    "    root_airfoil                          = RCAIDE.Library.Components.Airfoils.Airfoil()\n",
    "    ospath                                = os.path.abspath(os.path.join('Notebook'))\n",
    "    separator                             = os.path.sep\n",
    "    rel_path = os.path.dirname(ospath) + separator + '..' + separator + '..' + separator + 'VnV' + separator + 'Vehicles' + separator\n",
    "    root_airfoil.coordinate_file          = rel_path  + 'Airfoils' + separator + 'B737a.txt'\n",
    "    segment                               = RCAIDE.Library.Components.Wings.Segments.Segment()\n",
    "    segment.tag                           = 'Root'\n",
    "    segment.percent_span_location         = 0.0\n",
    "    segment.twist                         = 4. * Units.deg\n",
    "    segment.root_chord_percent            = 1.\n",
    "    segment.thickness_to_chord            = 0.1\n",
    "    segment.dihedral_outboard             = 2.5 * Units.degrees\n",
    "    segment.sweeps.quarter_chord          = 28.225 * Units.degrees\n",
    "    segment.thickness_to_chord            = .1\n",
    "    segment.append_airfoil(root_airfoil)\n",
    "    wing.append_segment(segment)\n",
    "\n",
    "    yehudi_airfoil                        = RCAIDE.Library.Components.Airfoils.Airfoil()\n",
    "    yehudi_airfoil.coordinate_file        = rel_path+ 'Airfoils' + separator + 'B737b.txt'\n",
    "    segment                               = RCAIDE.Library.Components.Wings.Segments.Segment()\n",
    "    segment.tag                           = 'Yehudi'\n",
    "    segment.percent_span_location         = 0.324\n",
    "    segment.twist                         = 0.047193 * Units.deg\n",
    "    segment.root_chord_percent            = 0.5\n",
    "    segment.thickness_to_chord            = 0.1\n",
    "    segment.dihedral_outboard             = 5.5 * Units.degrees\n",
    "    segment.sweeps.quarter_chord          = 25. * Units.degrees\n",
    "    segment.thickness_to_chord            = .1\n",
    "    segment.append_airfoil(yehudi_airfoil)\n",
    "    wing.append_segment(segment)\n",
    "\n",
    "    mid_airfoil                           = RCAIDE.Library.Components.Airfoils.Airfoil()\n",
    "    mid_airfoil.coordinate_file           = rel_path + 'Airfoils' + separator + 'B737c.txt'\n",
    "    segment                               = RCAIDE.Library.Components.Wings.Segments.Segment()\n",
    "    segment.tag                           = 'Section_2'\n",
    "    segment.percent_span_location         = 0.963\n",
    "    segment.twist                         = 0.00258 * Units.deg\n",
    "    segment.root_chord_percent            = 0.220\n",
    "    segment.thickness_to_chord            = 0.1\n",
    "    segment.dihedral_outboard             = 5.5 * Units.degrees\n",
    "    segment.sweeps.quarter_chord          = 56.75 * Units.degrees\n",
    "    segment.thickness_to_chord            = .1\n",
    "    segment.append_airfoil(mid_airfoil)\n",
    "    wing.append_segment(segment)\n",
    "\n",
    "    tip_airfoil                           =  RCAIDE.Library.Components.Airfoils.Airfoil()\n",
    "    tip_airfoil.coordinate_file           = rel_path + 'Airfoils' + separator + 'B737d.txt'\n",
    "    segment                               = RCAIDE.Library.Components.Wings.Segments.Segment()\n",
    "    segment.tag                           = 'Tip'\n",
    "    segment.percent_span_location         = 1.\n",
    "    segment.twist                         = 0. * Units.degrees\n",
    "    segment.root_chord_percent            = 0.10077\n",
    "    segment.thickness_to_chord            = 0.1\n",
    "    segment.dihedral_outboard             = 0.\n",
    "    segment.sweeps.quarter_chord          = 0.\n",
    "    segment.thickness_to_chord            = .1\n",
    "    segment.append_airfoil(tip_airfoil)\n",
    "    wing.append_segment(segment)\n",
    "    \n",
    "    # Fill out more segment properties automatically\n",
    "    wing = segment_properties(wing)    \n",
    "    # control surfaces -------------------------------------------\n",
    "    slat                          = RCAIDE.Library.Components.Wings.Control_Surfaces.Slat()\n",
    "    slat.tag                      = 'slat'\n",
    "    slat.span_fraction_start      = 0.2\n",
    "    slat.span_fraction_end        = 0.963\n",
    "    slat.deflection               = 0.0 * Units.degrees\n",
    "    slat.chord_fraction           = 0.075\n",
    "    wing.append_control_surface(slat)\n",
    "\n",
    "    flap                          = RCAIDE.Library.Components.Wings.Control_Surfaces.Flap()\n",
    "    flap.tag                      = 'flap'\n",
    "    flap.span_fraction_start      = 0.2\n",
    "    flap.span_fraction_end        = 0.7\n",
    "    flap.deflection               = 0.0 * Units.degrees\n",
    "    flap.configuration_type       = 'double_slotted'\n",
    "    flap.chord_fraction           = 0.30\n",
    "    wing.append_control_surface(flap)\n",
    "\n",
    "    aileron                       = RCAIDE.Library.Components.Wings.Control_Surfaces.Aileron()\n",
    "    aileron.tag                   = 'aileron'\n",
    "    aileron.span_fraction_start   = 0.7\n",
    "    aileron.span_fraction_end     = 0.963\n",
    "    aileron.deflection            = 0.0 * Units.degrees\n",
    "    aileron.chord_fraction        = 0.16\n",
    "    wing.append_control_surface(aileron)\n",
    "\n",
    "    # add to vehicle\n",
    "    vehicle.append_component(wing)\n",
    "     # ------------------------------------------------------------------\n",
    "    #  Horizontal Stabilizer\n",
    "    # ------------------------------------------------------------------\n",
    "\n",
    "    wing     = RCAIDE.Library.Components.Wings.Horizontal_Tail()\n",
    "    wing.tag = 'horizontal_stabilizer'\n",
    "\n",
    "    wing.aspect_ratio            = 4.99\n",
    "    wing.sweeps.quarter_chord    = 28.2250 * Units.deg  \n",
    "    wing.thickness_to_chord      = 0.08\n",
    "    wing.taper                   = 0.3333  \n",
    "    wing.spans.projected         = 14.4 \n",
    "    wing.chords.root             = 4.2731 \n",
    "    wing.chords.tip              = 1.4243 \n",
    "    wing.chords.mean_aerodynamic = 8.0 \n",
    "    wing.areas.reference         = 41.49\n",
    "    wing.areas.exposed           = 59.354    # Exposed area of the horizontal tail\n",
    "    wing.areas.wetted            = 71.81     # Wetted area of the horizontal tail\n",
    "    wing.twists.root             = 3.0 * Units.degrees\n",
    "    wing.twists.tip              = 3.0 * Units.degrees \n",
    "    wing.origin                  = [[33.02,0,1.466]]\n",
    "    wing.aerodynamic_center      = [0,0,0] \n",
    "    wing.vertical                = False\n",
    "    wing.symmetric               = True \n",
    "    wing.dynamic_pressure_ratio  = 0.9\n",
    "\n",
    "\n",
    "    # Wing Segments\n",
    "    segment                        = RCAIDE.Library.Components.Wings.Segments.Segment()\n",
    "    segment.tag                    = 'root_segment'\n",
    "    segment.percent_span_location  = 0.0\n",
    "    segment.twist                  = 0. * Units.deg\n",
    "    segment.root_chord_percent     = 1.0\n",
    "    segment.dihedral_outboard      = 8.63 * Units.degrees\n",
    "    segment.sweeps.quarter_chord   = 28.2250  * Units.degrees \n",
    "    segment.thickness_to_chord     = .1\n",
    "    wing.append_segment(segment)\n",
    "\n",
    "    segment                        = RCAIDE.Library.Components.Wings.Segments.Segment()\n",
    "    segment.tag                    = 'tip_segment'\n",
    "    segment.percent_span_location  = 1.\n",
    "    segment.twist                  = 0. * Units.deg\n",
    "    segment.root_chord_percent     = 0.3333               \n",
    "    segment.dihedral_outboard      = 0 * Units.degrees\n",
    "    segment.sweeps.quarter_chord   = 0 * Units.degrees  \n",
    "    segment.thickness_to_chord     = .1\n",
    "    wing.append_segment(segment)\n",
    "    \n",
    "    # Fill out more segment properties automatically\n",
    "    wing = segment_properties(wing)        \n",
    "\n",
    "    # control surfaces -------------------------------------------\n",
    "    elevator                       = RCAIDE.Library.Components.Wings.Control_Surfaces.Elevator()\n",
    "    elevator.tag                   = 'elevator'\n",
    "    elevator.span_fraction_start   = 0.09\n",
    "    elevator.span_fraction_end     = 0.92\n",
    "    elevator.deflection            = 0.0  * Units.deg\n",
    "    elevator.chord_fraction        = 0.3\n",
    "    wing.append_control_surface(elevator)\n",
    "\n",
    "    # add to vehicle\n",
    "    vehicle.append_component(wing)\n",
    "\n",
    "    # ------------------------------------------------------------------\n",
    "    #   Vertical Stabilizer\n",
    "    # ------------------------------------------------------------------\n",
    "\n",
    "    wing = RCAIDE.Library.Components.Wings.Vertical_Tail()\n",
    "    wing.tag = 'vertical_stabilizer'\n",
    "\n",
    "    wing.aspect_ratio            = 1.98865\n",
    "    wing.sweeps.quarter_chord    = 31.2  * Units.deg   \n",
    "    wing.thickness_to_chord      = 0.08\n",
    "    wing.taper                   = 0.1183\n",
    "\n",
    "    wing.spans.projected         = 8.33\n",
    "    wing.total_length            = wing.spans.projected \n",
    "    \n",
    "    wing.chords.root             = 10.1 \n",
    "    wing.chords.tip              = 1.20 \n",
    "    wing.chords.mean_aerodynamic = 4.0\n",
    "\n",
    "    wing.areas.reference         = 34.89\n",
    "    wing.areas.wetted            = 57.25 \n",
    "    \n",
    "    wing.twists.root             = 0.0 * Units.degrees\n",
    "    wing.twists.tip              = 0.0 * Units.degrees\n",
    "\n",
    "    wing.origin                  = [[26.944,0,1.54]]\n",
    "    wing.aerodynamic_center      = [0,0,0]\n",
    "\n",
    "    wing.vertical                = True\n",
    "    wing.symmetric               = False\n",
    "    wing.t_tail                  = False\n",
    "\n",
    "    wing.dynamic_pressure_ratio  = 1.0\n",
    "\n",
    "\n",
    "    # Wing Segments\n",
    "    segment                               = RCAIDE.Library.Components.Wings.Segments.Segment()\n",
    "    segment.tag                           = 'root'\n",
    "    segment.percent_span_location         = 0.0\n",
    "    segment.twist                         = 0. * Units.deg\n",
    "    segment.root_chord_percent            = 1.\n",
    "    segment.dihedral_outboard             = 0 * Units.degrees\n",
    "    segment.sweeps.quarter_chord          = 61.485 * Units.degrees  \n",
    "    segment.thickness_to_chord            = .1\n",
    "    wing.append_segment(segment)\n",
    "\n",
    "    segment                               = RCAIDE.Library.Components.Wings.Segments.Segment()\n",
    "    segment.tag                           = 'segment_1'\n",
    "    segment.percent_span_location         = 0.2962\n",
    "    segment.twist                         = 0. * Units.deg\n",
    "    segment.root_chord_percent            = 0.45\n",
    "    segment.dihedral_outboard             = 0. * Units.degrees\n",
    "    segment.sweeps.quarter_chord          = 31.2 * Units.degrees   \n",
    "    segment.thickness_to_chord            = .1\n",
    "    wing.append_segment(segment)\n",
    "\n",
    "    segment                               = RCAIDE.Library.Components.Wings.Segments.Segment()\n",
    "    segment.tag                           = 'segment_2'\n",
    "    segment.percent_span_location         = 1.0\n",
    "    segment.twist                         = 0. * Units.deg\n",
    "    segment.root_chord_percent            = 0.1183 \n",
    "    segment.dihedral_outboard             = 0.0 * Units.degrees\n",
    "    segment.sweeps.quarter_chord          = 0.0    \n",
    "    segment.thickness_to_chord            = .1  \n",
    "    wing.append_segment(segment)\n",
    "    \n",
    "    \n",
    "    # Fill out more segment properties automatically\n",
    "    wing = segment_properties(wing)        \n",
    "\n",
    "    # add to vehicle\n",
    "    vehicle.append_component(wing)\n",
    "     # ################################################# Fuselage ################################################################ \n",
    "    \n",
    "    fuselage                                    = RCAIDE.Library.Components.Fuselages.Tube_Fuselage() \n",
    "    fuselage.number_coach_seats                 = vehicle.passengers \n",
    "    fuselage.seats_abreast                      = 6\n",
    "    fuselage.seat_pitch                         = 1     * Units.meter \n",
    "    fuselage.fineness.nose                      = 1.6\n",
    "    fuselage.fineness.tail                      = 2. \n",
    "    fuselage.lengths.nose                       = 6.4   * Units.meter\n",
    "    fuselage.lengths.tail                       = 8.0   * Units.meter\n",
    "    fuselage.lengths.total                      = 38.02 * Units.meter  \n",
    "    fuselage.lengths.fore_space                 = 6.    * Units.meter\n",
    "    fuselage.lengths.aft_space                  = 5.    * Units.meter\n",
    "    fuselage.width                              = 3.74  * Units.meter\n",
    "    fuselage.heights.maximum                    = 3.74  * Units.meter\n",
    "    fuselage.effective_diameter                 = 3.74     * Units.meter\n",
    "    fuselage.areas.side_projected               = 142.1948 * Units['meters**2'] \n",
    "    fuselage.areas.wetted                       = 446.718  * Units['meters**2'] \n",
    "    fuselage.areas.front_projected              = 12.57    * Units['meters**2']  \n",
    "    fuselage.differential_pressure              = 5.0e4 * Units.pascal \n",
    "    fuselage.heights.at_quarter_length          = 3.74 * Units.meter\n",
    "    fuselage.heights.at_three_quarters_length   = 3.65 * Units.meter\n",
    "    fuselage.heights.at_wing_root_quarter_chord = 3.74 * Units.meter\n",
    "\n",
    "    # Segment  \n",
    "    segment                                     = RCAIDE.Library.Components.Fuselages.Segments.Segment()  \n",
    "    segment.tag                                 = 'segment_0'    \n",
    "    segment.percent_x_location                  = 0.0000\n",
    "    segment.percent_z_location                  = -0.00144 \n",
    "    segment.height                              = 0.0100 \n",
    "    segment.width                               = 0.0100  \n",
    "    fuselage.segments.append(segment)   \n",
    "    \n",
    "    # Segment  \n",
    "    segment                                     = RCAIDE.Library.Components.Fuselages.Segments.Segment() \n",
    "    segment.tag                                 = 'segment_1'    \n",
    "    segment.percent_x_location                  = 0.00576 \n",
    "    segment.percent_z_location                  = -0.00144 \n",
    "    segment.height                              = 0.7500\n",
    "    segment.width                               = 0.6500\n",
    "    fuselage.segments.append(segment)   \n",
    "    \n",
    "    # Segment                                   \n",
    "    segment                                     = RCAIDE.Library.Components.Fuselages.Segments.Segment()\n",
    "    segment.tag                                 = 'segment_2'   \n",
    "    segment.percent_x_location                  = 0.02017 \n",
    "    segment.percent_z_location                  = 0.00000 \n",
    "    segment.height                              = 1.52783 \n",
    "    segment.width                               = 1.20043 \n",
    "    fuselage.segments.append(segment)      \n",
    "    \n",
    "    # Segment                                   \n",
    "    segment                                     = RCAIDE.Library.Components.Fuselages.Segments.Segment() \n",
    "    segment.tag                                 = 'segment_3'   \n",
    "    segment.percent_x_location                  = 0.03170 \n",
    "    segment.percent_z_location                  = 0.00000 \n",
    "    segment.height                              = 1.96435 \n",
    "    segment.width                               = 1.52783 \n",
    "    fuselage.segments.append(segment)   \n",
    "\n",
    "    # Segment                                   \n",
    "    segment                                     = RCAIDE.Library.Components.Fuselages.Segments.Segment()\n",
    "    segment.tag                                 = 'segment_4'   \n",
    "    segment.percent_x_location                  = 0.04899 \t\n",
    "    segment.percent_z_location                  = 0.00431 \n",
    "    segment.height                              = 2.72826 \n",
    "    segment.width                               = 1.96435 \n",
    "    fuselage.segments.append(segment)   \n",
    "    \n",
    "    # Segment                                   \n",
    "    segment                                     = RCAIDE.Library.Components.Fuselages.Segments.Segment()\n",
    "    segment.tag                                 = 'segment_5'   \n",
    "    segment.percent_x_location                  = 0.07781 \n",
    "    segment.percent_z_location                  = 0.00861 \n",
    "    segment.height                              = 3.49217 \n",
    "    segment.width                               = 2.61913 \n",
    "    fuselage.segments.append(segment)     \n",
    "    \n",
    "    # Segment                                   \n",
    "    segment                                     = RCAIDE.Library.Components.Fuselages.Segments.Segment() \n",
    "    segment.tag                                 = 'segment_6'   \n",
    "    segment.percent_x_location                  = 0.10375 \n",
    "    segment.percent_z_location                  = 0.01005 \n",
    "    segment.height                              = 3.70130 \n",
    "    segment.width                               = 3.05565 \n",
    "    fuselage.segments.append(segment)             \n",
    "     \n",
    "    # Segment                                   \n",
    "    segment                                     = RCAIDE.Library.Components.Fuselages.Segments.Segment()\n",
    "    segment.tag                                 = 'segment_7'   \n",
    "    segment.percent_x_location                  = 0.16427 \n",
    "    segment.percent_z_location                  = 0.01148 \n",
    "    segment.height                              = 3.92870 \n",
    "    segment.width                               = 3.71043 \n",
    "    fuselage.segments.append(segment)    \n",
    "    \n",
    "    # Segment                                   \n",
    "    segment                                     = RCAIDE.Library.Components.Fuselages.Segments.Segment() \n",
    "    segment.tag                                 = 'segment_8'   \n",
    "    segment.percent_x_location                  = 0.22478 \n",
    "    segment.percent_z_location                  = 0.01148 \n",
    "    segment.height                              = 3.92870 \n",
    "    segment.width                               = 3.92870 \n",
    "    fuselage.segments.append(segment)   \n",
    "    \n",
    "    # Segment                                   \n",
    "    segment                                     = RCAIDE.Library.Components.Fuselages.Segments.Segment()\n",
    "    segment.tag                                 = 'segment_9'     \n",
    "    segment.percent_x_location                  = 0.69164 \n",
    "    segment.percent_z_location                  = 0.01292\n",
    "    segment.height                              = 3.81957\n",
    "    segment.width                               = 3.81957\n",
    "    fuselage.segments.append(segment)     \n",
    "        \n",
    "    # Segment                                   \n",
    "    segment                                     = RCAIDE.Library.Components.Fuselages.Segments.Segment()\n",
    "    segment.tag                                 = 'segment_10'     \n",
    "    segment.percent_x_location                  = 0.71758 \n",
    "    segment.percent_z_location                  = 0.01292\n",
    "    segment.height                              = 3.81957\n",
    "    segment.width                               = 3.81957\n",
    "    fuselage.segments.append(segment)   \n",
    "        \n",
    "    # Segment                                   \n",
    "    segment                                     = RCAIDE.Library.Components.Fuselages.Segments.Segment()\n",
    "    segment.tag                                 = 'segment_11'     \n",
    "    segment.percent_x_location                  = 0.78098 \n",
    "    segment.percent_z_location                  = 0.01722\n",
    "    segment.height                              = 3.49217\n",
    "    segment.width                               = 3.71043\n",
    "    fuselage.segments.append(segment)    \n",
    "        \n",
    "    # Segment                                   \n",
    "    segment                                     = RCAIDE.Library.Components.Fuselages.Segments.Segment()\n",
    "    segment.tag                                 = 'segment_12'     \n",
    "    segment.percent_x_location                  = 0.85303\n",
    "    segment.percent_z_location                  = 0.02296\n",
    "    segment.height                              = 3.05565\n",
    "    segment.width                               = 3.16478\n",
    "    fuselage.segments.append(segment)             \n",
    "        \n",
    "    # Segment                                   \n",
    "    segment                                     = RCAIDE.Library.Components.Fuselages.Segments.Segment()\n",
    "    segment.tag                                 = 'segment_13'     \n",
    "    segment.percent_x_location                  = 0.91931 \n",
    "    segment.percent_z_location                  = 0.03157\n",
    "    segment.height                              = 2.40087\n",
    "    segment.width                               = 1.96435\n",
    "    fuselage.segments.append(segment)               \n",
    "        \n",
    "    # Segment                                   \n",
    "    segment                                     = RCAIDE.Library.Components.Fuselages.Segments.Segment() \n",
    "    segment.tag                                 = 'segment_14'     \n",
    "    segment.percent_x_location                  = 1.00 \n",
    "    segment.percent_z_location                  = 0.04593\n",
    "    segment.height                              = 1.09130\n",
    "    segment.width                               = 0.21826\n",
    "    fuselage.segments.append(segment)       \n",
    "    \n",
    "    # add to vehicle\n",
    "    vehicle.append_component(fuselage)\n",
    "\n",
    "    # ################################################# Energy Network #######################################################          \n",
    "    #------------------------------------------------------------------------------------------------------------------------- \n",
    "    #  Turbofan Network\n",
    "    #-------------------------------------------------------------------------------------------------------------------------   \n",
    "    net                                         = RCAIDE.Framework.Networks.Fuel() \n",
    "    \n",
    "    #------------------------------------------------------------------------------------------------------------------------- \n",
    "    # Fuel Distrubition Line \n",
    "    #------------------------------------------------------------------------------------------------------------------------- \n",
    "    fuel_line                                   = RCAIDE.Library.Components.Powertrain.Distributors.Fuel_Line()  \n",
    "    \n",
    "    #------------------------------------------------------------------------------------------------------------------------------------  \n",
    "    # Propulsor: Starboard Propulsor\n",
    "    #------------------------------------------------------------------------------------------------------------------------------------         \n",
    "    turbofan                                    = RCAIDE.Library.Components.Powertrain.Propulsors.Turbofan() \n",
    "    turbofan.tag                                = 'starboard_propulsor'\n",
    "    turbofan.active_fuel_tanks                  = ['fuel_tank']   \n",
    "    turbofan.origin                             = [[13.72, 4.86,-1.1]] \n",
    "    turbofan.engine_length                      = 2.71     \n",
    "    turbofan.bypass_ratio                       = 5.4    \n",
    "    turbofan.design_altitude                    = 35000.0*Units.ft\n",
    "    turbofan.design_mach_number                 = 0.78   \n",
    "    turbofan.design_thrust                      = 35000.0* Units.N \n",
    "             \n",
    "    # fan                \n",
    "    fan                                         = RCAIDE.Library.Components.Powertrain.Converters.Fan()   \n",
    "    fan.tag                                     = 'fan'\n",
    "    fan.polytropic_efficiency                   = 0.93\n",
    "    fan.pressure_ratio                          = 1.7   \n",
    "    turbofan.fan                                = fan        \n",
    "                   \n",
    "    # working fluid                   \n",
    "    turbofan.working_fluid                      = RCAIDE.Library.Attributes.Gases.Air() \n",
    "    ram                                         = RCAIDE.Library.Components.Powertrain.Converters.Ram()\n",
    "    ram.tag                                     = 'ram' \n",
    "    turbofan.ram                                = ram \n",
    "          \n",
    "    # inlet nozzle          \n",
    "    inlet_nozzle                                = RCAIDE.Library.Components.Powertrain.Converters.Compression_Nozzle()\n",
    "    inlet_nozzle.tag                            = 'inlet nozzle'\n",
    "    inlet_nozzle.polytropic_efficiency          = 0.98\n",
    "    inlet_nozzle.pressure_ratio                 = 0.98 \n",
    "    turbofan.inlet_nozzle                       = inlet_nozzle \n",
    "\n",
    "    # low pressure compressor    \n",
    "    low_pressure_compressor                       = RCAIDE.Library.Components.Powertrain.Converters.Compressor()    \n",
    "    low_pressure_compressor.tag                   = 'lpc'\n",
    "    low_pressure_compressor.polytropic_efficiency = 0.91\n",
    "    low_pressure_compressor.pressure_ratio        = 1.9   \n",
    "    turbofan.low_pressure_compressor              = low_pressure_compressor\n",
    "\n",
    "    # high pressure compressor  \n",
    "    high_pressure_compressor                       = RCAIDE.Library.Components.Powertrain.Converters.Compressor()    \n",
    "    high_pressure_compressor.tag                   = 'hpc'\n",
    "    high_pressure_compressor.polytropic_efficiency = 0.91\n",
    "    high_pressure_compressor.pressure_ratio        = 10.0    \n",
    "    turbofan.high_pressure_compressor              = high_pressure_compressor\n",
    "\n",
    "    # low pressure turbine  \n",
    "    low_pressure_turbine                           = RCAIDE.Library.Components.Powertrain.Converters.Turbine()   \n",
    "    low_pressure_turbine.tag                       ='lpt'\n",
    "    low_pressure_turbine.mechanical_efficiency     = 0.99\n",
    "    low_pressure_turbine.polytropic_efficiency     = 0.93 \n",
    "    turbofan.low_pressure_turbine                  = low_pressure_turbine\n",
    "   \n",
    "    # high pressure turbine     \n",
    "    high_pressure_turbine                          = RCAIDE.Library.Components.Powertrain.Converters.Turbine()   \n",
    "    high_pressure_turbine.tag                      ='hpt'\n",
    "    high_pressure_turbine.mechanical_efficiency    = 0.99\n",
    "    high_pressure_turbine.polytropic_efficiency    = 0.93 \n",
    "    turbofan.high_pressure_turbine                 = high_pressure_turbine \n",
    "\n",
    "    # combustor  \n",
    "    combustor                                      = RCAIDE.Library.Components.Powertrain.Converters.Combustor()   \n",
    "    combustor.tag                                  = 'Comb'\n",
    "    combustor.efficiency                           = 0.99 \n",
    "    combustor.alphac                               = 1.0     \n",
    "    combustor.turbine_inlet_temperature            = 1500\n",
    "    combustor.pressure_ratio                       = 0.95\n",
    "    combustor.fuel_data                            = RCAIDE.Library.Attributes.Propellants.Jet_A1()  \n",
    "    turbofan.combustor                             = combustor\n",
    "\n",
    "    # core nozzle\n",
    "    core_nozzle                                    = RCAIDE.Library.Components.Powertrain.Converters.Expansion_Nozzle()   \n",
    "    core_nozzle.tag                                = 'core nozzle'\n",
    "    core_nozzle.polytropic_efficiency              = 0.95\n",
    "    core_nozzle.pressure_ratio                     = 0.99  \n",
    "    turbofan.core_nozzle                           = core_nozzle\n",
    "             \n",
    "    # fan nozzle             \n",
    "    fan_nozzle                                     = RCAIDE.Library.Components.Powertrain.Converters.Expansion_Nozzle()   \n",
    "    fan_nozzle.tag                                 = 'fan nozzle'\n",
    "    fan_nozzle.polytropic_efficiency               = 0.95\n",
    "    fan_nozzle.pressure_ratio                      = 0.99 \n",
    "    turbofan.fan_nozzle                            = fan_nozzle \n",
    "    \n",
    "    # design turbofan\n",
    "    design_turbofan(turbofan)  \n",
    "    # append propulsor to distribution line  \n",
    "   \n",
    " \n",
    "    # Nacelle \n",
    "    nacelle                                     = RCAIDE.Library.Components.Nacelles.Body_of_Revolution_Nacelle()\n",
    "    nacelle.diameter                            = 2.05\n",
    "    nacelle.length                              = 2.71\n",
    "    nacelle.tag                                 = 'nacelle_1'\n",
    "    nacelle.inlet_diameter                      = 2.0\n",
    "    nacelle.origin                              = [[13.5,4.38,-1.5]] \n",
    "    nacelle.areas.wetted                        = 1.1*np.pi*nacelle.diameter*nacelle.length \n",
    "    nacelle_airfoil                             = RCAIDE.Library.Components.Airfoils.NACA_4_Series_Airfoil()\n",
    "    nacelle_airfoil.NACA_4_Series_code          = '2410'\n",
    "    nacelle.append_airfoil(nacelle_airfoil)  \n",
    "    turbofan.nacelle                            = nacelle\n",
    "\n",
    "    # append propulsor to network    \n",
    "    net.propulsors.append(turbofan)  \n",
    "\n",
    "    #------------------------------------------------------------------------------------------------------------------------------------  \n",
    "    # Propulsor: Port Propulsor\n",
    "    #------------------------------------------------------------------------------------------------------------------------------------      \n",
    "    # copy turbofan\n",
    "    turbofan_2                                  = deepcopy(turbofan)\n",
    "    turbofan_2.active_fuel_tanks                = ['fuel_tank'] \n",
    "    turbofan_2.tag                              = 'port_propulsor' \n",
    "    turbofan_2.origin                           = [[13.72,-4.38,-1.1]]  # change origin \n",
    "    turbofan_2.nacelle.origin                   = [[13.5,-4.38,-1.5]]\n",
    "         \n",
    "    # append propulsor to network\n",
    "    net.propulsors.append(turbofan_2)\n",
    "  \n",
    "    #------------------------------------------------------------------------------------------------------------------------- \n",
    "    #  Energy Source: Fuel Tank\n",
    "    #------------------------------------------------------------------------------------------------------------------------- \n",
    "    # fuel tank\n",
    "    fuel_tank                                        = RCAIDE.Library.Components.Powertrain.Sources.Fuel_Tanks.Fuel_Tank()\n",
    "    fuel_tank.origin                                 = vehicle.wings.main_wing.origin  \n",
    "    fuel_tank.fuel                                   = RCAIDE.Library.Attributes.Propellants.Jet_A1()   \n",
    "    fuel_tank.fuel.mass_properties.mass              = vehicle.mass_properties.max_takeoff-vehicle.mass_properties.max_fuel\n",
    "    fuel_tank.fuel.origin                            = vehicle.wings.main_wing.mass_properties.center_of_gravity      \n",
    "    fuel_tank.fuel.mass_properties.center_of_gravity = vehicle.wings.main_wing.aerodynamic_center\n",
    "    fuel_tank.volume                                 = fuel_tank.fuel.mass_properties.mass/fuel_tank.fuel.density   \n",
    "    fuel_line.fuel_tanks.append(fuel_tank)\n",
    "    \n",
    "    #------------------------------------------------------------------------------------------------------------------------------------   \n",
    "    # Assign propulsors to fuel line to network      \n",
    "    fuel_line.assigned_propulsors =  [[turbofan.tag, turbofan_2.tag]]\n",
    "\n",
    "    #------------------------------------------------------------------------------------------------------------------------------------   \n",
    "    # Append fuel line to fuel line to network      \n",
    "    net.fuel_lines.append(fuel_line)        \n",
    "    \n",
    "    # Append energy network to aircraft \n",
    "    vehicle.append_energy_network(net)       \n",
    "    #------------------------------------------------------------------------------------------------------------------------- \n",
    "    # Done ! \n",
    "    #------------------------------------------------------------------------------------------------------------------------- \n",
    "      \n",
    "    return vehicle"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Aerodynamic Analysis\n",
    "\n",
    "With the vehicle setup complete, we can now perform the aerodynamic analysis. This involves evaluating the aerodynamic performance of the aircraft over a range of Mach numbers and angles of attack.\n",
    "\n",
    "### Steps for Analysis\n",
    "\n",
    "1. **Define Input Parameters**:\n",
    "   - Specify a range of Mach numbers and angles of attack (`AoA`) for the analysis.\n",
    "\n",
    "2. **Run the Aerodynamic Analysis**:\n",
    "   - Use the `aircraft_aerodynamic_analysis` function to calculate key aerodynamic parameter, such as:\n",
    "     - Lift Coefficient (`C_L`)\n",
    "   - Perform the analysis for all combinations of Mach numbers and angles of attack.\n",
    "\n",
    "3. **Organize Results**:\n",
    "   - Store the computed aerodynamic data in a structured format, such as a dictionary or DataFrame, for easier visualization and interpretation.\n",
    "\n",
    "4. **Visualize Results**:\n",
    "   - Use the `plot_aircraft_aerodynamics` function to generate plots of the aerodynamic parameters across the defined ranges."
   ]
  },
  {
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",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vehicle                           = vehicle_setup()  \n",
    "Mach_number_range                 = np.atleast_2d(np.linspace(0.1, 0.9, 10)).T\n",
    "angle_of_attack_range             = np.atleast_2d(np.linspace(-5, 12, 18)).T*Units.degrees \n",
    "control_surface_deflection_range  = np.atleast_2d(np.linspace(0,30,7)).T*Units.degrees \n",
    "aerodynamics_analysis_routine     = RCAIDE.Framework.Analyses.Aerodynamics.Vortex_Lattice_Method()\n",
    "aerodynamics_analysis_routine.vehicle = vehicle\n",
    "    \n",
    "results                           = aircraft_aerodynamic_analysis(aerodynamics_analysis = aerodynamics_analysis_routine,\n",
    "                                                                      angle_of_attack_range = angle_of_attack_range,\n",
    "                                                                      Mach_number_range = Mach_number_range,\n",
    "                                                                      control_surface_deflection_range= control_surface_deflection_range)\n",
    "  \n",
    "plot_aircraft_aerodynamics(results) "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "testingenv",
   "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": "3.13.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}