Space Engineering & Astrodynamics Portfolio

Welcome to my comprehensive repository of Orbital Mechanics and Interplanetary Mission Design projects. This portfolio showcases a variety of advanced aerospace engineering applications, ranging from high-fidelity numerical orbit propagation to optimal interplanetary transfer design, developed using Python and MATLAB.

Key Projects

1. High-Fidelity Orbit Propagation & Perturbation Analysis (GONETS-M 24)

Language: Python | Libraries: NumPy, Matplotlib, SGP4, PyYAML

This project implements a software suite for satellite orbit propagation, validated against the SGP4 reference model.

• Numerical Integration Engines: Custom implementation of Euler, Heun, and 4th-Order Runge-Kutta (RK4) solvers for orbital ODEs.
• Perturbation Modeling:
  • Geopotential ($J_2$): Modeling Earth's non-spherical mass distribution.
  • Solar Radiation Pressure (SRP): High-fidelity model including penumbra/umbra shadowing (Doornbos algorithm).
  • Atmospheric Drag: Exponential density model accounting for Earth's rotating atmosphere.
  • Third-Body Gravity: Gravitational influence of the Sun and Moon using JPL Horizons ephemeris data.
• State Vector Optimization: Implementation of Grid Search and Gradient-based algorithms to minimize the Cumulative Global Position Difference (CGPD) between numerical models and SGP4 data.

2. Interplanetary Transfer Design: Asteroid 1991VH Mission and Earth-Venus transfer

Language: MATLAB, Python (TudatPy)

A detailed study on designing optimal orbital maneuvers for a mission from a Geostationary Transfer Orbit (GTO) to a parking orbit around asteroid 1991VH.

• Transfer Strategies: Comparative analysis of Bitangent, Bi-elliptic, and Plane Change maneuvers.
• Global Optimization: Utilization of Genetic Algorithms (GA) and exhaustive Grid Searches to find launch windows and impulse sequences that minimize total $\Delta V$ and Time of Flight (TOF).
• Visualization: Custom 3D plotting tools for visualizing complex orbital transfers and arrival geometries.

A study of the interplanetary transfer from Earth to Venus with various strategies:

• Lambert Problem Solver: Determination of optimal trajectories between Earth and Jupiter within fixed time windows.
• Perturbation Benchmarking: Evaluating the impact of planetary perturbations on the spacecraft's trajectory compared to idealized Lambert arcs, with an advanced model.
• Optimized transfer $\Delta$ V: Analyzed impulsive and low-thrust maneouvres, with single- and multi-arc propagations.
• SPICE Integration: Leveraging NAIF SPICE kernels for precise planetary ephemeris and coordinate frame transformations.

3. JUICE Jovian System Analysis (JupitEr ICy moons Explorer)

Language: Python | Tools: SPICE Kernels, TudatPy, NumPy

Analysis of the Jovian system dynamics for ESA's JUICE mission.

• Perturbation analysis: Study of influence of other Jupiter's moons and relevant perturbations.
• Effect of center of propagation: Demonstration of the influence of the center of propagation on the obtained results.

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Technical Skill Set

• Scientific Programming: Python (Advanced NumPy, SciPy), MATLAB.
• Astrodinamics: Numerical ODE Integration, Orbital Mechanics (Keplerian, Lambert), Perturbation Modeling (Spherical harmonics, SRP, Drag, 3rd Body).
• Industry Tools: NAIF SPICE Kernels, SGP4/TLE Models, Tudat (Delft University of Technology Astrodynamics Toolbox).
• Data Science & Optimization: Stochastic/Deterministic Optimization, Scientific Data Visualization, Statistical Error Analysis (GPD/CGPD).

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📁 Repository Structure

.
├── orbit_dynamics/
│   ├── GONETS_M24/         # Low- and Higher-fidelity Python orbit propagator
│   └── JUICE/              # JUICE perturbed orbit dynamics around Ganymede 
├── interplanetary_mission_design/
│   ├── asteroid_1991VH/    # MATLAB optimal transfer from GTO to Parking orbit about Asteroid 1991VH
│   └── Earth_venus/# Interplanetary transfer study (Python/Tudat) from Earth to Venus
└── README.md

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How to Use

Each project directory contains its own configuration and entry-point scripts:

• Python Projects: Install dependencies via pip install numpy matplotlib pyyaml. Run python run_propagation.py in the respective folder to start simulations.
• MATLAB Projects: Open the asteroid_1991VH_transfer/Code directory in MATLAB and run Scenario_*.m to visualize the transfer scenarios.

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Author

Giovanni Pieroni*

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Projects developed as part of advanced Astrodynamics and Interplanetary Mission Design curricula at TU Delft.

* Interplanetary transfer to Asteroid 1991VH was made in collaboration with Alessandro Ponti (@PontiAle)