UAV_MBSE (Unmanned Aerial Vehicle Model-Based Systems Engineering) is a project aimed at applying MBSE methodologies to the design, analysis, and validation of UAV systems. This repository contains all relevant models, documentation, and code necessary for the development and simulation of UAVs using MBSE techniques.

• Introduction
• Installation
• Usage
• Features
• Documentation
• Contributing
• License
• Acknowledgements

This project leverages Model-Based Systems Engineering (MBSE) to streamline the development process of UAVs. By utilizing MBSE, we aim to enhance the consistency, traceability, and integration of UAV system models throughout the development lifecycle.

.
├── LICENSE
├── README.md
├── pyproject.toml
├── consts.py
├── main.py
├── requirements_base.txt
├── requirements_full.txt
├── data
│   ├── airfoils
│   │   ├── FX 73-CL2-152.dat
│   │   ├── GOE 383 AIRFOIL.dat
│   │   └── NACA 0009.dat
│   ├── analysis
│   │   └── Mobula_T1-16_0 m_s-VLM2.xml
│   ├── databases
│   │   ├── airfoil_coordinates_db.zip
│   │   └── airfoil_polars_db.zip
│   ├── materials
│   │   └── xml_libraries
│   │       └── Materiales_Engineering_Data.xml
│   ├── output
│   │   └── Mobula.html
│   └── xml
│       ├── Mobula2.xml
│       ├── Mobula_TE.xml
│       ├── Mobula.xml
│       └── test_sample.xml
├── mathematica
│   ├── AreaIntegrals-GreenStokes.nb
│   ├── Export to Python.nb
│   └── ThesisTestRotatingFrames.nb
├── scripts
│   ├── cantileaver_beam.py
│   ├── file_leading_edge.py
│   ├── file_renamer.py
│   ├── interpolation_applications.py
│   ├── poc_add_plot_synchronization.py
│   └── reflection_plots.py
├── src
│   ├── __init__.py
│   ├── aerodynamics
│   │   ├── __init__.py
│   │   ├── airfoil_polar_features.py
│   │   ├── airfoil.py
│   │   ├── analisis_importer.py
│   │   └── data_structures.py
│   ├── geometry
│   │   ├── __init__.py
│   │   ├── aircraft_geometry.py
│   │   ├── spatial_array.py
│   │   └── surfaces.py
│   ├── materials
│   │   ├── __init__.py
│   │   └── materials_library.py
│   ├── propulsion
│   │   ├── __init__.py
│   │   └── propeller_importer.py
│   ├── structures
│   │   ├── __init__.py
│   │   ├── fem_solver.py
│   │   ├── inertia_tensor.py
│   │   ├── spar.py
│   │   ├── structural_model.py
│   │   └── temp_abc.py
│   ├── utils
│   │   ├── __init__.py
│   │   ├── interpolation.py
│   │   ├── intersection.py
│   │   ├── transformations.py
│   │   ├── units.py
│   │   └── xml_parser.py
│   └── visualization
│       ├── __init__.py
│       ├── aircraft_plotter.py
│       ├── base_class.py
│       ├── matplotlib_plotter.py
│       └── plotly_plotter.py
└── tests
    ├── test_intersection_algorithms.py
    ├── test_linear_interpolation.py
    ├── test_spar_creation.py
    ├── test_te_gap_algorithm.py
    └── test_xml_parser.py

19 directories, 72 files

Made with tree command:

tree -I '__pycache__|legacy'

Before downloading the repository make sure to have installed python, git and git-lfs (Large File System). Optionally, for development purposes it is recommended to install Visual Studio Code as an IDE.

git-lfs is only neccessary if you want to download the databases .zip files:

• data/databases/airfoil_coordinates_db.zip
• data/databases/airfoil_polars_db.zip

On Debian-based distributions.

Install git:

sudo apt install git-all

Install git-lfs: https://github.com/git-lfs/git-lfs/blob/main/INSTALLING.md

Install git and git-lfs:

Git LFS is included in the distribution of Git for Windows: https://gitforwindows.org/

To set up the project locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/Michallote/UAV_MBSE.git
   cd UAV_MBSE

2. Download the databases:

   git lfs fetch --all
   git lfs pull

3. It is highly advisable to create a virtual environment for this project:

   python -m venv .venv

   Here, .venv is the name of the virtual environment directory. You can name it anything you like.

4. Activate the virtual environment: Activating the virtual environment will isolate your Python/Django setup and ensure that all the dependencies are maintained within this environment. The activation command differs based on your operating system.

   • On Windows:

     .venv\Scripts\activate

   • On macOS and Linux:

     source .venv/bin/activate

5. Install the necessary dependencies:

   For running scripts only:

   pip install -r requirements_base.txt

   For development:

   pip install -r requirements_dev.txt

Instructions on how to use the project:

1. Navigate to the project directory:

   cd UAV_MBSE

2. Run the main script:

   python main.py

3. For additional functionality and running simulations, refer to the documentation provided in the docs directory.

• Model-Based Design: Utilize MBSE methodologies for UAV design.
• Simulation: Perform comprehensive simulations of UAV models.
• Analysis Tools: Tools for analyzing UAV performance and design.
• Integration: Seamless integration with other MBSE tools and platforms.

Detailed documentation is available in the docs directory. This includes user guides, API documentation, and model descriptions.

We welcome contributions from the community. To contribute:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Commit your changes (git commit -am 'Add new feature').
4. Push to the branch (git push origin feature-branch).
5. Create a new Pull Request.

Please ensure that your code adheres to the coding standards and includes appropriate tests.

This project is licensed under the MIT License. See the LICENSE file for more details.

We would like to thank all contributors and supporters of this project.

For more information, please visit the project repository.