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🦅 Project ICARUS: The HALE Evolution (1.0 & 2.0 Combined)

A Multi-Stage Aerospace Engineering Stack: From Structural Foundations to AI-Driven Autonomy.

🚀 The ICARUS Journey: Evolution from 1.0 to 2.0

This repository demonstrates a complete engineering lifecycle. It transitions from traditional aerospace design (ICARUS 1.0) to advanced AI-augmented autonomy (ICARUS 2.0).

🛠️ Phase 1.0: Structural & Aerodynamic Foundations

  • CAD/Geometry: Developed high-fidelity 3.0m wing models in OpenVSP.
  • Structural Certification: Performed FEA stress analysis in PrePoMax/CalculiX to certify the airframe under max aero-loads.
  • CFD Validation: Conducted aerodynamic simulations in OpenFOAM to establish baseline Lift/Drag polar data.

🧠 Phase 2.0: AI-Driven Autonomy & Optimization

  • Neural Design Optimizer: Integrated a Neural Network (MLP) to programmatically evolve wing geometry, achieving a +12% efficiency gain.
  • Shadow Pilot (RL): Developed a MAVLink-AI bridge for real-time attitude control using reinforcement learning principles.
  • Digital Twin Health Monitor: Implemented a Random Forest classifier for predictive maintenance and flutter detection.

🏗️ Technical Performance & Visuals

1. Structural Engineering (FEA)

FEA Stress Analysis PrePoMax FEA results showing stress distribution on the HALE airframe under max aero-load.

2. AI-Driven Wing Optimization

Optimization Results Neural Network convergence plot showing +12% lift efficiency gain through evolved wing geometry.

Parameter Baseline (Initial) Optimized (Final) Improvement
Wing Span 3.00 m 3.16 m +5.3%
L/D Ratio 14.2 15.9 +11.9%
Max Stress 9.77e4 Pa 9.42e4 Pa -3.6%

3. Digital Twin & Shadow AI Pilot

Digital Twin Simulation Real-time mission telemetry featuring the Shadow AI Attitude Controller and Structural Health Monitor.

🛠️ Installation & Reproduction

To run the ICARUS optimization and health monitoring stack:

Prerequisites

  • Python: 3.10+
  • Environment: ArduPilot SITL / Mission Planner (optional for flight)
  • Tools: OpenVSP (for geometry visualization)

Setup Guide

  1. Clone the repository:

    git clone https://github.com/yogesh031020/Project-ICARUS.git
    cd Project-ICARUS
  2. Install core dependencies:

    pip install numpy pandas scikit-learn pymavlink matplotlib torch
  3. Run the AI Design Optimizer:

    python icarus_optimizer.py
  4. Launch the Health Monitoring System:

    python icarus_health_monitor.py

📂 Repository Structure

  • icarus_brain.py: Core Neural Network logic for aerodynamic prediction.
  • icarus_ai_pilot.py: MAVLink-based attitude control interface.
  • icarus_health_monitor.py: Random Forest classifier for structural failure detection.
  • geometry/: OpenVSP (.vsp3) source models for the airframe.
  • results/: High-resolution engineering data and visuals.

Developed by Yogesh E S - Aeronautical Engineer.

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AI-Driven HALE UAV Design Optimization, Structural Certification, and Autonomous Flight Simulation

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