{
 "cells": [
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   "cell_type": "markdown",
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   "source": [
    "# Setup a Panelled Radiation Pressure Model\n",
    "## Objectives\n",
    "This example demonstrates how to setup a panelled radiation pressure model (sometimes also called n-plate model) for a simple box-wing satellite.\n",
    "\n",
    "The example introduces the basic steps that are required to define a plated radiation pressure target model. It showcases the different options that are available to define plate geometries available in the [vehicle_systems](https://py.api.tudat.space/en/latest/vehicle_systems.html) module and specify their radiative properties from the [radiation_pressure](https://py.api.tudat.space/en/latest/radiation_pressure.html) module.\n",
    "A cannonball target model is created along-side the plated model to highlight the differences between the two model setups.\n",
    "\n",
    "## Pre-Requisites\n",
    "This examples assumes that you are familiar with the necessary steps how to setup a simple orbit propagation in Tudat.\n",
    "If you would like to revisit these steps, take a look at the [Keplerian orbit propagation example](https://docs.tudat.space/en/latest/_src_getting_started/_src_examples/tudatpy-examples/propagation/keplerian_satellite_orbit.html) and in particular the [perturbed orbit propagation example](https://docs.tudat.space/en/latest/_src_getting_started/_src_examples/tudatpy-examples/propagation/perturbed_satellite_orbit.html)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a2d9c889",
   "metadata": {},
   "source": [
    "## Import statements and SPICE setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1a3e92d7",
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    "execution": {
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   "source": [
    "# Load standard modules\n",
    "import numpy as np\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "# Load tudatpy modules\n",
    "from tudatpy.interface import spice\n",
    "from tudatpy import dynamics\n",
    "from tudatpy.dynamics import environment\n",
    "from tudatpy.dynamics import environment_setup, propagation_setup, simulator\n",
    "from tudatpy.util import result2array\n",
    "from tudatpy.astro.time_representation import DateTime\n",
    "\n",
    "# Load spice kernels\n",
    "spice.load_standard_kernels()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c469059b",
   "metadata": {},
   "source": [
    "## Environment setup\n",
    "Let’s create the environment for our simulation. In this example an Earth-orbiting spacecraft will be modelled, following the previous examples.\n",
    "Since we will also consider the radiation pressure acceleration by the Sun, we will create both the Sun and the Earth using the default settings.\n",
    "\n",
    "Note that the default radiation source model assigned to the Sun is based on a constant luminosity, as listed in the [default environment models](https://docs.tudat.space/en/latest/_src_user_guide/state_propagation/environment_setup/default_env_models.html#radiation-source). Other options for solar radiation pressure as well as planetary radiation pressure exist, see the [radiation source models](https://docs.tudat.space/en/latest/_src_user_guide/state_propagation/propagation_setup/translational/radiation_pressure_acceleration.html#radiation-source-models) section in the user guide."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "81ea6c12",
   "metadata": {
    "execution": {
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   "source": [
    "# Define string names for bodies to be created from default.\n",
    "bodies_to_create = [\"Sun\", \"Earth\"]\n",
    "\n",
    "# Use \"Earth\"/\"J2000\" as global frame origin and orientation.\n",
    "global_frame_origin = \"Earth\"\n",
    "global_frame_orientation = \"J2000\"\n",
    "\n",
    "# Create default body settings\n",
    "body_settings = environment_setup.get_default_body_settings(\n",
    "    bodies_to_create, global_frame_origin, global_frame_orientation\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "daaba176",
   "metadata": {},
   "source": [
    "### Create the vehicle\n",
    "Two vehicle settings will be created from empty settings:\n",
    "\n",
    "- `Delfi-CB` will be setup with a cannonball target model\n",
    "- `Delfi-NP` will be setup with a plated (n-plate) target model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6fa45c76",
   "metadata": {
    "execution": {
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   "source": [
    "# Create empty body settings for the satellite\n",
    "body_settings.add_empty_settings(\"Delfi-CB\")\n",
    "body_settings.add_empty_settings(\"Delfi-NP\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "451e698b",
   "metadata": {},
   "source": [
    "## Create the cannonball target model settings\n",
    "\n",
    "The cannonball target model settings are created analogously as in the [perturbed orbit propagation example](https://docs.tudat.space/en/latest/_src_getting_started/_src_examples/tudatpy-examples/propagation/perturbed_satellite_orbit.html).\n",
    "\n",
    "The dimensions of a typical 3U cubesat are assumed, with an added solar-panel, that is always pointing at the Sun."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e371f3fc",
   "metadata": {
    "execution": {
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   "source": [
    "L = 0.3\n",
    "W = 0.1\n",
    "H = 0.1\n",
    "radiation_pressure_coefficient = 1.5\n",
    "\n",
    "# Average projection area of a 3U CubeSat + Solar panel\n",
    "reference_area_radiation = (4 * L * H + 2 * H * W) / 4 + L * H\n",
    "\n",
    "# Create cannonball radiation pressure settings\n",
    "occulting_bodies_dict = dict()\n",
    "occulting_bodies_dict[\"Sun\"] = [\"Earth\"]\n",
    "vehicle_target_settings = (\n",
    "    environment_setup.radiation_pressure.cannonball_radiation_target(\n",
    "        reference_area_radiation, radiation_pressure_coefficient, occulting_bodies_dict\n",
    "    )\n",
    ")\n",
    "\n",
    "# Add the radiation pressure interface to the body settings\n",
    "body_settings.get(\"Delfi-CB\").radiation_pressure_target_settings = (\n",
    "    vehicle_target_settings\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7bc59e3a",
   "metadata": {},
   "source": [
    "## Create the panelled target model settings\n",
    "\n",
    "The panelled target model is now created, following the same geometry as described previously.\n",
    "The definition of the panelled settings can be divided in six steps:\n",
    "\n",
    "1. Create **geometry settings** for all n panels using `*_panel_geometry()` functions of [vehicle_systems](https://py.api.tudat.space/en/latest/vehicle_systems.html) module\n",
    "2. Create **reflection law settings** for all panels using `*_body_panel_reflection()` functions of [radiation_pressure](https://py.api.tudat.space/en/latest/radiation_pressure.html) module\n",
    "3. **Merge geometry settings and reflection law settings** using [body_panel_settings()](https://py.api.tudat.space/en/latest/vehicle_systems.html#tudatpy.dynamics.environment_setup.vehicle_systems.body_panel_settings) function to create [BodyPanelSettings](https://py.api.tudat.space/en/latest/vehicle_systems.html#tudatpy.dynamics.environment_setup.vehicle_systems.BodyPanelSettings) for all n panels.\n",
    "4. **Merge all [BodyPanelSettings](https://py.api.tudat.space/en/latest/vehicle_systems.html#tudatpy.dynamics.environment_setup.vehicle_systems.BodyPanelSettings)** to create [FullPanelledBodySettings](https://py.api.tudat.space/en/latest/vehicle_systems.html#tudatpy.dynamics.environment_setup.vehicle_systems.FullPanelledBodySettings) using [full_panelled_body_settings()](https://py.api.tudat.space/en/latest/vehicle_systems.html#tudatpy.dynamics.environment_setup.vehicle_systems.full_panelled_body_settings) function.\n",
    "5. Add [FullPanelledBodySettings](https://py.api.tudat.space/en/latest/vehicle_systems.html#tudatpy.dynamics.environment_setup.vehicle_systems.FullPanelledBodySettings) to [vehicle_shape_settings](https://py.api.tudat.space/en/latest/environment_setup.html#tudatpy.dynamics.environment_setup.BodySettings.vehicle_shape_settings) attribute of spacecraft body settings\n",
    "6. Create **panelled radiation pressure target settings** and define occulting bodies using [panelled_radiation_target()](https://py.api.tudat.space/en/latest/radiation_pressure.html#tudatpy.dynamics.environment_setup.radiation_pressure.panelled_radiation_target) function. Note: Since the panel settings are part of the [vehicle_shape_settings](https://py.api.tudat.space/en/latest/environment_setup.html#tudatpy.dynamics.environment_setup.BodySettings.vehicle_shape_settings) attribute of the body settings, this function does not take the panel settings as user-input.\n",
    "\n",
    "Note: If you would like to define a standard box-wing spacecraft model, take a look at the [box_wing_panelled_body_settings()](https://py.api.tudat.space/en/latest/vehicle_systems.html#tudatpy.dynamics.environment_setup.vehicle_systems.box_wing_panelled_body_settings) function, which takes care of steps 1-4.\n",
    "\n",
    "In addition to the steps outlined above, the spacecraft needs to have a rotation model defined. See the [rotation_model](https://py.api.tudat.space/en/latest/rotation_model.html) module for different options."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4fd59cdc",
   "metadata": {},
   "source": [
    "### Define rotation model\n",
    "\n",
    "Before defining all the panel geometries, the rotation model of the spacecraft is defined, which determines the orientation of the body-fixed spacecraft frame with respect to the inertial space.\n",
    "\n",
    "It is assumed that the body-fixed x-axis of the spacecraft is colinear to the velocity vector. Since the spacecraft is in a nearly circular orbit, this corresponds to an approximately nadir-pointing attitude.\n",
    "The selected rotation model is therefore defined based on the orbital state using the [orbital_state_direction_based()](https://py.api.tudat.space/en/latest/rotation_model.html#tudatpy.dynamics.environment_setup.rotation_model.orbital_state_direction_based) model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "445be5e4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-16T07:42:03.019796Z",
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     "shell.execute_reply": "2025-09-16T07:42:03.021440Z"
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   "source": [
    "rotation_model_settings = (\n",
    "    environment_setup.rotation_model.orbital_state_direction_based(\n",
    "        central_body=\"Earth\",\n",
    "        is_colinear_with_velocity=True,\n",
    "        direction_is_opposite_to_vector=False,\n",
    "        base_frame=\"J2000\",\n",
    "        target_frame=\"DelfiBF\",\n",
    "    )\n",
    ")\n",
    "body_settings.get(\"Delfi-NP\").rotation_model_settings = rotation_model_settings"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0e0da206",
   "metadata": {},
   "source": [
    "### 1. Create geometry settings\n",
    "\n",
    "In the first step, the geometry settings of all panels are created.\n",
    "This includes the outward normal vector of the panel surface (either fixed in a frame or time-varying) and the corresponding area of the panel.\n",
    "\n",
    "Three options are available to define panel geometries:\n",
    "\n",
    "- [frame_fixed_panel_geometry()](https://py.api.tudat.space/en/latest/vehicle_systems.html#tudatpy.dynamics.environment_setup.vehicle_systems.frame_fixed_panel_geometry)\n",
    "- [time_varying_panel_geometry()](https://py.api.tudat.space/en/latest/vehicle_systems.html#tudatpy.dynamics.environment_setup.vehicle_systems.time_varying_panel_geometry)\n",
    "- [body_tracking_panel_geometry()](https://py.api.tudat.space/en/latest/vehicle_systems.html#tudatpy.dynamics.environment_setup.vehicle_systems.body_tracking_panel_geometry)\n",
    "\n",
    "For our 3U cubesat with an additional solar panel, 7 panels need to be defined.\n",
    "As all cubesat sidewalls have constant orientation in the body-frame, the `frame_fixed_panel_geometry` will be used for these.\n",
    "The solar panel will be defined such that it always tracks the Sun.\n",
    "Conveniently, this can be defined using the `body_tracking_panel_geometry` function.\n",
    "\n",
    "Note: For higher fidelity applications, the solar panel may be defined based on a spacecraft frame kernel using SPICE.\n",
    "In this case, the `frame_fixed_panel_geometry` can be used with the `frame_orientation` argument defined accordingly."
   ]
  },
  {
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   "execution_count": 6,
   "id": "a7d8ca2e",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2025-09-16T07:42:03.025149Z"
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   "source": [
    "panel_geometry_top = environment_setup.vehicle_systems.frame_fixed_panel_geometry(\n",
    "    surface_normal=np.array([0.0, 0.0, -1.0]), area=L * W\n",
    ")\n",
    "panel_geometry_bottom = environment_setup.vehicle_systems.frame_fixed_panel_geometry(\n",
    "    surface_normal=np.array([0.0, 0.0, 1.0]), area=L * W\n",
    ")\n",
    "panel_geometry_front = environment_setup.vehicle_systems.frame_fixed_panel_geometry(\n",
    "    surface_normal=np.array([1.0, 0.0, 0.0]), area=W * H\n",
    ")\n",
    "panel_geometry_back = environment_setup.vehicle_systems.frame_fixed_panel_geometry(\n",
    "    surface_normal=np.array([-1.0, 0.0, 0.0]), area=W * H\n",
    ")\n",
    "panel_geometry_left = environment_setup.vehicle_systems.frame_fixed_panel_geometry(\n",
    "    surface_normal=np.array([0.0, -1.0, 0.0]), area=L * H\n",
    ")\n",
    "panel_geometry_right = environment_setup.vehicle_systems.frame_fixed_panel_geometry(\n",
    "    surface_normal=np.array([0.0, 1.0, 0.0]), area=L * H\n",
    ")\n",
    "\n",
    "solar_panel_geometry = environment_setup.vehicle_systems.body_tracking_panel_geometry(\n",
    "    body_to_track=\"Sun\", towards_tracked_body=True, area=L * W * 2\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd46de6d",
   "metadata": {},
   "source": [
    "### 2. - 3. Create reflection law settings and merge geometry and reflection law settings\n",
    "To define the panel settings, the reflection law needs to be defined for all panels.\n",
    "In this simplified model, a Lambertian reflection law is assumed for the spacecraft body (no specular reflections), while the solar panels reflect incoming radiation in both specular and diffuse components.\n",
    "\n",
    "Having defined the reflection laws, the geometry settings of all n plates are then combined with the corresponding reflection law using the [body_panel_settings()](https://py.api.tudat.space/en/latest/vehicle_systems.html#tudatpy.dynamics.environment_setup.vehicle_systems.body_panel_settings) function and stored in a combined list."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9db4031b",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2025-09-16T07:42:03.028415Z"
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   },
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   "source": [
    "body_reflection_law_settings = (\n",
    "    environment_setup.radiation_pressure.lambertian_body_panel_reflection(\n",
    "        reflectivity=0.5\n",
    "    )\n",
    ")\n",
    "\n",
    "solar_panel_reflection_law_settings = (\n",
    "    environment_setup.radiation_pressure.specular_diffuse_body_panel_reflection(\n",
    "        specular_reflectivity=0.5,\n",
    "        diffuse_reflectivity=0.5,\n",
    "        with_instantaneous_reradiation=True,\n",
    "    )\n",
    ")\n",
    "\n",
    "panel_geometries = [\n",
    "    panel_geometry_top,\n",
    "    panel_geometry_bottom,\n",
    "    panel_geometry_front,\n",
    "    panel_geometry_back,\n",
    "    panel_geometry_left,\n",
    "    panel_geometry_right,\n",
    "]\n",
    "\n",
    "panel_settings = [\n",
    "    environment_setup.vehicle_systems.body_panel_settings(\n",
    "        panel_geometry, body_reflection_law_settings\n",
    "    )\n",
    "    for panel_geometry in panel_geometries\n",
    "]\n",
    "\n",
    "panel_settings.append(\n",
    "    environment_setup.vehicle_systems.body_panel_settings(\n",
    "        solar_panel_geometry, solar_panel_reflection_law_settings\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34e8dd87",
   "metadata": {},
   "source": [
    "### 4. - 6. Merge body panel settings, assign to spacecraft and define target settings\n",
    "\n",
    "In the last steps, the spacecraft panel settings are defined using the [full_panelled_body_settings()](https://py.api.tudat.space/en/latest/vehicle_systems.html#tudatpy.dynamics.environment_setup.vehicle_systems.full_panelled_body_settings) function, which combines all separate panel settings.\n",
    "These settings can then be assigned to the spacecraft body settings.\n",
    "\n",
    "Finally, the radiation target model settings are defined.\n",
    "Note that these settings do not define the panel model itself (which is defined in the [vehicle_shape_settings](https://py.api.tudat.space/en/latest/environment_setup.html#tudatpy.dynamics.environment_setup.BodySettings.vehicle_shape_settings)), but rather that the spacecraft should use a paneled target model, which is (internally) taken from the vehicle shape settings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a028640d",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2025-09-16T07:42:03.031305Z"
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   },
   "outputs": [],
   "source": [
    "vehicle_system_settings = environment_setup.vehicle_systems.full_panelled_body_settings(\n",
    "    panel_settings\n",
    ")\n",
    "\n",
    "# Note: The previous manual setup is equivalent to using the box-wing setup function\n",
    "# vehicle_system_settings = environment_setup.vehicle_systems.box_wing_body_settings(\n",
    "#     L,\n",
    "#     W,\n",
    "#     H,\n",
    "#     solar_array_area=L * W * 2,\n",
    "#     box_specular_reflectivity=0.0,\n",
    "#     box_diffuse_reflectivity=0.5,\n",
    "#     solar_array_specular_reflectivity=0.5,\n",
    "#     solar_array_diffuse_reflectivity=0.5,\n",
    "# )\n",
    "\n",
    "body_settings.get(\"Delfi-NP\").vehicle_shape_settings = vehicle_system_settings\n",
    "\n",
    "# Define that Delfi-NP should use be modelled as panelled_radiation_target\n",
    "plated_target_settings = environment_setup.radiation_pressure.panelled_radiation_target(\n",
    "    occulting_bodies_dict\n",
    ")\n",
    "\n",
    "body_settings.get(\"Delfi-NP\").radiation_pressure_target_settings = (\n",
    "    plated_target_settings\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21439921",
   "metadata": {},
   "source": [
    "## Define propatation setup\n",
    "\n",
    "With the radiation pressure target models being defined, the remaining propagation setup follows the [perturbed orbit propagation example](https://docs.tudat.space/en/latest/_src_getting_started/_src_examples/tudatpy-examples/propagation/perturbed_satellite_orbit.html) closely."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "92c5fa60-e34f-4a71-a45a-488b58924de7",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2025-09-16T07:42:03.040270Z"
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   },
   "outputs": [],
   "source": [
    "bodies = environment_setup.create_system_of_bodies(body_settings)\n",
    "bodies.get(\"Delfi-CB\").mass = 2.2  # kg\n",
    "bodies.get(\"Delfi-NP\").mass = 2.2  # kg\n",
    "\n",
    "# Define bodies that are propagated\n",
    "bodies_to_propagate = [\"Delfi-CB\", \"Delfi-NP\"]\n",
    "\n",
    "# Define central bodies of propagation\n",
    "central_bodies = [\"Earth\", \"Earth\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c914f44e",
   "metadata": {},
   "source": [
    "### Create the acceleration model\n",
    "\n",
    "To show the effects of the different radiation pressure target models, Earth is only considered as a point mass, while the Sun exerts a radiation pressure acceleration."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "68b9d09e",
   "metadata": {
    "execution": {
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     "iopub.status.idle": "2025-09-16T07:42:03.043574Z",
     "shell.execute_reply": "2025-09-16T07:42:03.043361Z"
    }
   },
   "outputs": [],
   "source": [
    "# Define accelerations acting on Delfi-C3 by Sun and Earth.\n",
    "accelerations_settings_delfi_c3 = dict(\n",
    "    Sun=[\n",
    "        propagation_setup.acceleration.radiation_pressure(),\n",
    "    ],\n",
    "    Earth=[\n",
    "        propagation_setup.acceleration.point_mass_gravity(),\n",
    "    ],\n",
    ")\n",
    "\n",
    "# Create global accelerations settings dictionary.\n",
    "acceleration_settings = {\n",
    "    \"Delfi-CB\": accelerations_settings_delfi_c3,\n",
    "    \"Delfi-NP\": accelerations_settings_delfi_c3,\n",
    "}\n",
    "\n",
    "# Create acceleration models.\n",
    "acceleration_models = propagation_setup.create_acceleration_models(\n",
    "    bodies, acceleration_settings, bodies_to_propagate, central_bodies\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae748fda",
   "metadata": {},
   "source": [
    "### Define the initial state\n",
    "As in previous examples, we will retrieve the initial state of Delfi-C3 using its Two-Line-Elements (TLE) the date of its launch (April the 28th, 2008). The TLE strings are obtained from [space-track.org](https://www.space-track.org)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "0a4ac7c1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-16T07:42:03.044548Z",
     "iopub.status.busy": "2025-09-16T07:42:03.044464Z",
     "iopub.status.idle": "2025-09-16T07:42:03.046516Z",
     "shell.execute_reply": "2025-09-16T07:42:03.046252Z"
    }
   },
   "outputs": [],
   "source": [
    "# Set simulation start and end epochs\n",
    "simulation_start_epoch = DateTime(2008, 4, 28).epoch()\n",
    "simulation_end_epoch = DateTime(2008, 4, 29).epoch()\n",
    "\n",
    "# Retrieve the initial state of Delfi-C3 using Two-Line-Elements (TLEs)\n",
    "delfi_tle = environment.Tle(\n",
    "    \"1 32789U 07021G   08119.60740078 -.00000054  00000-0  00000+0 0  9999\",\n",
    "    \"2 32789 098.0082 179.6267 0015321 307.2977 051.0656 14.81417433    68\",\n",
    ")\n",
    "delfi_ephemeris = environment.TleEphemeris(\"Earth\", \"J2000\", delfi_tle, False)\n",
    "initial_state = np.hstack([delfi_ephemeris.cartesian_state(simulation_start_epoch)] * 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0316441f",
   "metadata": {},
   "source": [
    "### Create propagator settings\n",
    "For a brief analysis, both the Keplerian state and the radiation pressure acceleration will be saved as dependent variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "10464030",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-16T07:42:03.047526Z",
     "iopub.status.busy": "2025-09-16T07:42:03.047438Z",
     "iopub.status.idle": "2025-09-16T07:42:03.049870Z",
     "shell.execute_reply": "2025-09-16T07:42:03.049634Z"
    }
   },
   "outputs": [],
   "source": [
    "# Define list of dependent variables to save\n",
    "dependent_variables_to_save = [\n",
    "    propagation_setup.dependent_variable.keplerian_state(\"Delfi-CB\", \"Earth\"),\n",
    "    propagation_setup.dependent_variable.keplerian_state(\"Delfi-NP\", \"Earth\"),\n",
    "    propagation_setup.dependent_variable.single_acceleration(\n",
    "        propagation_setup.acceleration.radiation_pressure_type, \"Delfi-CB\", \"Sun\"\n",
    "    ),\n",
    "    propagation_setup.dependent_variable.single_acceleration(\n",
    "        propagation_setup.acceleration.radiation_pressure_type, \"Delfi-NP\", \"Sun\"\n",
    "    ),\n",
    "]\n",
    "\n",
    "# Create termination settings\n",
    "termination_condition = propagation_setup.propagator.time_termination(\n",
    "    simulation_end_epoch\n",
    ")\n",
    "\n",
    "# Create numerical integrator settings\n",
    "fixed_step_size = 10.0\n",
    "integrator_settings = propagation_setup.integrator.runge_kutta_fixed_step(\n",
    "    fixed_step_size, coefficient_set=propagation_setup.integrator.CoefficientSets.rk_4\n",
    ")\n",
    "\n",
    "# Create propagation settings\n",
    "propagator_settings = propagation_setup.propagator.translational(\n",
    "    central_bodies,\n",
    "    acceleration_models,\n",
    "    bodies_to_propagate,\n",
    "    initial_state,\n",
    "    simulation_start_epoch,\n",
    "    integrator_settings,\n",
    "    termination_condition,\n",
    "    output_variables=dependent_variables_to_save,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ea0510e",
   "metadata": {},
   "source": [
    "## Propagate the orbit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b65f903a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-16T07:42:03.050885Z",
     "iopub.status.busy": "2025-09-16T07:42:03.050800Z",
     "iopub.status.idle": "2025-09-16T07:42:03.401605Z",
     "shell.execute_reply": "2025-09-16T07:42:03.401275Z"
    }
   },
   "outputs": [],
   "source": [
    "# Create simulation object and propagate the dynamics\n",
    "dynamics_simulator = simulator.create_dynamics_simulator(bodies, propagator_settings)\n",
    "\n",
    "# Extract the resulting state and dependent variable history and convert it to an ndarray\n",
    "states = dynamics_simulator.propagation_results.state_history\n",
    "states_array = result2array(states)\n",
    "dep_vars = dynamics_simulator.propagation_results.dependent_variable_history\n",
    "dep_vars_array = result2array(dep_vars)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4288a662",
   "metadata": {},
   "source": [
    "## Post-process the propagation results\n",
    "The results of the propagation are then processed to a more user-friendly form.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "bdb125ca",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-16T07:42:03.402741Z",
     "iopub.status.busy": "2025-09-16T07:42:03.402616Z",
     "iopub.status.idle": "2025-09-16T07:42:03.432413Z",
     "shell.execute_reply": "2025-09-16T07:42:03.431932Z"
    }
   },
   "outputs": [],
   "source": [
    "from tudatpy.astro.frame_conversion import inertial_to_rsw_rotation_matrix\n",
    "\n",
    "relative_time_hours = (states_array[:, 0] - states_array[0, 0]) / 3600.0\n",
    "\n",
    "states_cb = states_array[:, 1:7]\n",
    "states_np = states_array[:, 7:13]\n",
    "\n",
    "inertial_to_rsw_rotation_matrices = [\n",
    "    inertial_to_rsw_rotation_matrix(state) for state in states_cb\n",
    "]\n",
    "\n",
    "nb_state_differences_inertial = states_np - states_cb\n",
    "pos_norm = np.linalg.norm(nb_state_differences_inertial[:, 0:3], axis=1)\n",
    "vel_norm = np.linalg.norm(nb_state_differences_inertial[:, 3:6], axis=1)\n",
    "\n",
    "nb_state_differences_rsw = np.array(\n",
    "    [\n",
    "        rot_mat @ state_difference[:3]\n",
    "        for rot_mat, state_difference in zip(\n",
    "            inertial_to_rsw_rotation_matrices, nb_state_differences_inertial\n",
    "        )\n",
    "    ]\n",
    ")\n",
    "\n",
    "acceleration_cb = dep_vars_array[:, 13:16]\n",
    "acceleration_np = dep_vars_array[:, 16:19]\n",
    "\n",
    "acceleration_norm_cb = np.linalg.norm(acceleration_cb, axis=1)\n",
    "acceleration_norm_np = np.linalg.norm(acceleration_np, axis=1)\n",
    "\n",
    "acceleration_difference_inertial = acceleration_np - acceleration_cb\n",
    "\n",
    "acceleration_difference_rsw = np.array(\n",
    "    [\n",
    "        rot_mat @ acc_diff\n",
    "        for rot_mat, acc_diff in zip(\n",
    "            inertial_to_rsw_rotation_matrices, acceleration_difference_inertial\n",
    "        )\n",
    "    ]\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71fd17d6",
   "metadata": {},
   "source": [
    "### Total acceleration over time\n",
    "Let's first plot the acceleration magnitudes for the cannonball and panelled model on the satellite over time. Additionally, we plot the magnitude of the position difference over time, to see how the difference in acceleration compounds."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f7c41d20",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-16T07:42:03.433642Z",
     "iopub.status.busy": "2025-09-16T07:42:03.433523Z",
     "iopub.status.idle": "2025-09-16T07:42:03.738128Z",
     "shell.execute_reply": "2025-09-16T07:42:03.737653Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Panelled vs. Cannonball Model')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.plot(relative_time_hours, acceleration_norm_cb, label=\"Cannonball\")\n",
    "ax.plot(relative_time_hours, acceleration_norm_np, linestyle=\"--\", label=\"Panelled\")\n",
    "\n",
    "ax2 = ax.twinx()\n",
    "ax2.plot(relative_time_hours, pos_norm, label=\"norm\", color=\"tab:green\")\n",
    "\n",
    "ax.legend()\n",
    "\n",
    "ax.set_xlabel(\"Relative time [hr]\")\n",
    "ax.set_ylabel(\"Acceleration Magnitude [$\\mathrm{m}/\\mathrm{s}^2$]\")\n",
    "ax2.set_ylabel(\"Position Difference Magnitude [m]\", color=\"tab:green\")\n",
    "ax2.tick_params(axis=\"y\", labelcolor=\"tab:green\")\n",
    "\n",
    "ax.set_title(\"Panelled vs. Cannonball Model\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9a436ea",
   "metadata": {},
   "source": [
    "### Acceleration difference in RSW components\n",
    "\n",
    "To get a more intuitive understanding how the models are different, we also plot the difference in acceleration and position in the RSW frame centered on the cannonball spacecraft.\n",
    "In this case, only the first 3.5 hours of the orbit are plotted (corresponding to roughly two orbital revolutions), as the pattern in the accelerations repeats once per orbit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "11abdbe8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-16T07:42:03.739476Z",
     "iopub.status.busy": "2025-09-16T07:42:03.739379Z",
     "iopub.status.idle": "2025-09-16T07:42:03.890520Z",
     "shell.execute_reply": "2025-09-16T07:42:03.890208Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0.98, 'Panelled - Cannonball Differences in RSW Frame during first two orbits')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "idx = np.searchsorted(relative_time_hours, 3.5)\n",
    "\n",
    "fig, axs = plt.subplots(2, sharex=True)\n",
    "\n",
    "axs[0].plot(\n",
    "    relative_time_hours[:idx],\n",
    "    nb_state_differences_rsw[:idx],\n",
    "    label=[\"radial\", \"tangential\", \"normal\"],\n",
    ")\n",
    "\n",
    "axs[1].scatter(\n",
    "    relative_time_hours[:idx],\n",
    "    acceleration_difference_rsw[:idx, 0],\n",
    "    label=\"radial\",\n",
    "    s=1,\n",
    ")\n",
    "axs[1].scatter(\n",
    "    relative_time_hours[:idx],\n",
    "    acceleration_difference_rsw[:idx, 1],\n",
    "    label=\"tangential\",\n",
    "    s=1,\n",
    ")\n",
    "axs[1].scatter(\n",
    "    relative_time_hours[:idx],\n",
    "    acceleration_difference_rsw[:idx, 2],\n",
    "    label=\"normal\",\n",
    "    s=1,\n",
    ")\n",
    "\n",
    "axs[0].set_ylabel(\"Position\\n Difference [m]\")\n",
    "axs[1].set_xlabel(\"Relative time [hr]\")\n",
    "axs[1].set_ylabel(\"Acceleration\\n Difference [$\\mathrm{m}/\\mathrm{s}^2$]\")\n",
    "\n",
    "axs[0].legend()\n",
    "\n",
    "fig.suptitle(\"Panelled - Cannonball Differences in RSW Frame during first two orbits\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "tudatpy10",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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