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🚀 AEGIS-75 High-Power Rocket Flight Simulation

A physics-based 6-Degree-of-Freedom (6-DOF) flight simulation of the AEGIS-75 high-power sounding rocket developed using RocketPy. This project models rocket propulsion, aerodynamics, atmospheric conditions, stability, and dual-deployment parachute recovery to predict flight performance under realistic launch conditions.

📌 Project Overview

The objective of this project is to design, model, and simulate a 75 mm diameter high-power sounding rocket using RocketPy. The simulation evaluates the rocket's flight dynamics, propulsion performance, aerodynamic stability, and recovery sequence before physical implementation.

The project demonstrates the application of computational tools in preliminary rocket design and performance analysis.

✨ Features

  • 🚀 Complete 6-DOF rocket flight simulation
  • 🔥 AeroTech M1850W solid rocket motor modelling
  • 🌎 Real atmospheric forecast (GFS weather model)
  • 📈 Aerodynamic stability analysis
  • 📊 Custom power-on and power-off drag models
  • 🪂 Dual-deployment parachute recovery
  • 📉 Flight trajectory and performance visualization
  • 📍 Google Earth trajectory export (KML)

🛠 Technologies Used

  • Python
  • RocketPy
  • NumPy
  • Matplotlib
  • Google Colab

🚀 Rocket Specifications

Parameter Value
Rocket Name AEGIS-75
Diameter 75 mm
Length 3.10 m
Empty Mass 18.0 kg
Loaded Mass 22.87 kg
Nose Cone Von Kármán
Fin Configuration Four Trapezoidal Fins
Recovery System Dual Deployment
Launch Rail Length 6.0 m
Launch Inclination 85°

🔥 Motor Specifications

Parameter Value
Motor AeroTech M1850W
Burn Time 4.01 s
Propellant Mass 2.956 kg
Average Thrust 1679.50 N
Maximum Thrust 2411 N
Total Impulse 6734.78 Ns
Average Exhaust Velocity 2278.41 m/s

🌎 Launch Environment

The simulation was performed using RocketPy's Forecast Atmospheric Model (GFS).

Parameter Value
Latitude 19.15025°
Longitude 73.23245°
Elevation 72.6 m
Surface Wind Speed 2.48 m/s
Surface Temperature 298.13 K
Launch Date 30 June 2026

📊 Simulation Results

Parameter Result
Apogee 699.83 m
Burnout Altitude 385.41 m (AGL)
Burnout Velocity 118.58 m/s
Maximum Velocity 128.90 m/s
Maximum Mach Number 0.373
Rail Exit Velocity 27.36 m/s
Burn Time 4.01 s
Maximum Motor Acceleration 95.79 m/s² (9.77 g)
Maximum Stability Margin 12.753 calibers

📈 Engineering Analysis

The following analyses were performed:

  • Rocket Geometry
  • Atmospheric Conditions
  • Aerodynamic Drag Analysis
  • Stability Analysis
  • 3D Flight Trajectory
  • Elevation Profile
  • Linear Kinematics
  • Angular Motion
  • Aerodynamic Forces
  • Dynamic Pressure
  • Energy Analysis
  • Parachute Recovery Sequence

📷 Simulation Outputs

Rocket Geometry

Rocket Geometry

3D Flight Trajectory

Trajectory

Google Earth Elevation Profile

Elevation

Linear Kinematics

Elevation

Stability Analysis

Elevation

Aerodynamic Forces

Elevation

Energy Analysis

Elevation

📂 Repository Structure

AEGIS-75-Rocket-Simulation/

── notebook/ └── AEGIS75_RocketPy.ipynb

── motor/ └── AeroTech_M1850W.rse

── airfoil/ └── NACA0012-radians.txt

── drag_curves/ ├── powerOnDragCurve.csv └── powerOffDragCurve.csv

── results/ ├── trajectory.kml ├── plots/ └── images

── report/ └── Project Aegis 75.pdf

── README.md


# ▶️ Getting Started
### Clone the Repository

```bash
git clone https://github.com/Anuj-777/AEGIS-75-Rocket-Simulation

Install Dependencies

pip install rocketpy numpy matplotlib

Run the Simulation

Open the notebook in Google Colab or Jupyter Notebook and execute all cells sequentially.

🔍 Key Learnings

Through this project, the following concepts were explored:

  • High-Power Rocket Design
  • Flight Dynamics
  • Six-Degree-of-Freedom Simulation
  • Aerodynamic Stability
  • Solid Rocket Propulsion
  • Atmospheric Modelling
  • Numerical Simulation using Python
  • Data Visualization
  • Engineering Performance Analysis

🚀 Future Improvements

  • Replace estimated aerodynamic coefficients with CFD/OpenRocket data.
  • Validate simulation results using experimental flight data.
  • Perform Monte Carlo analysis for wind and manufacturing uncertainties.
  • Optimize fin geometry for improved aerodynamic performance.
  • Integrate telemetry and sensor fusion for hardware-in-the-loop simulation.

👨‍💻 Author

Anuj Mangaj

Aerospace Engineering Student | IIT KHARAGPUR

Interests

  • Flight Dynamics
  • Rocket Propulsion
  • Mechanism Design
  • Aerospace Structures
  • Embedded Systems
  • Control Systems
  • Numerical Simulation

📄 License

This project is licensed under the MIT License.

⭐ Acknowledgements

  • RocketPy Development Team
  • AeroTech Rocket Motors
  • Open-source Aerospace Community

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