🧭 OSEF: Operational Stability Envelope Framework

Real-Time Implementation Layer for Limit Cycle-Based Aviation Safety Models

OSEF translates validated limit cycle dynamics theory into operational real-time supervision for aviation safety applications.

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Regulatory Positioning

OSEF is currently positioned as a research and advisory framework intended for simulation, training, and analytical environments.

It does not exert control authority over any aircraft system and is not classified as flight-critical avionics software.

For a detailed discussion of its regulatory scope and its alignment with DO-178C awareness objectives, see
REGULATORY_POSITIONING_DO178C.md.

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🎯 What is OSEF?

OSEF is a computational framework that:

• 📊 Monitors aircraft trajectory in 3D phase space (Pitch, Bank, Power)
• 🔍 Detects Creative Chaos Zones (CCZ) in real-time
• 🎯 Guides crews toward stable Limit Cycle operations
• ⚡ Operates at < 8 ms latency on standard hardware

Built on Validated Science

Based on research analyzing 1,247 commercial flights with 89.3% prediction accuracy:

Baladi, S. (2026). Limit Cycle Flight Dynamics as a Framework for Adaptive Aviation Safety Protocols. OSF. https://doi.org/10.17605/OSF.IO/RJBDK

Validation Study Preregistered: https://doi.org/10.17605/OSF.IO/ED89G

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✨ Key Features

Feature	Description	Status
Real-Time CCZ Detection	Identifies Creative Chaos Zones with 91.2% accuracy	✅ Complete
Limit Cycle Guidance	Provides trajectory corrections toward stable LC	✅ Complete
Model-Agnostic Design	Works with Van der Pol, ML, or hybrid models	✅ Complete
Lyapunov Monitoring	Continuous stability assessment (λ computation)	✅ Complete
Training Mode	Real-time feedback for simulator training	🔄 In Progress
Fleet Analytics	Aggregate safety metrics across flights	📅 Planned

---

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📁 Repository Structure
OSEF-Framework/
│
├── README.md                          # Main Page
├── LICENSE                            # MIT License
├── CITATION.cff                       # Citation File
├── .gitignore                         
├── requirements.txt                   # Dependencies
├── environment.yml                    # Conda environment
├── setup.py                           # Installation script
│
├── docs/                              # 📚 Documentation
│   ├── index.md
│   ├── architecture.md                # OSEF Architecture
│   ├── installation.md
│   ├── quick_start.md
│   ├── api_reference.md
│   ├── theoretical_foundation.md      # Link to Baladi et al.
│   └── deployment_guide.md
│
├── osef/                              # 🔧 Core Framework
│   ├── __init__.py
│   ├── core/
│   │   ├── __init__.py
│   │   ├── limit_cycle_model.py       # Van der Pol Engine
│   │   ├── stability_monitor.py       # Real-time OSEF Core
│   │   ├── lyapunov.py                # Lyapunov Analysis
│   │   └── guidance.py                # Trajectory Guidance
│   │
│   ├── data/
│   │   ├── __init__.py
│   │   ├── fdr_reader.py              # FDR Data Processing
│   │   ├── preprocessing.py
│   │   └── synthetic_data.py          # For testing
│   │
│   ├── visualization/
│   │   ├── __init__.py
│   │   ├── phase_space.py             # 3D Phase Space Plots
│   │   ├── stability_maps.py
│   │   └── realtime_display.py
│   │
│   └── utils/
│       ├── __init__.py
│       ├── config.py
│       └── logger.py
│
├── examples/                          # 📖 Examples
│   ├── 01_basic_usage.py
│   ├── 02_flight_simulation.py
│   ├── 03_qf32_reconstruction.py
│   ├── 04_training_mode.py
│   └── 05_fleet_monitoring.py
│
├── notebooks/                         # 📓 Jupyter Notebooks
│   ├── tutorial_01_introduction.ipynb
│   ├── tutorial_02_limit_cycles.ipynb
│   ├── tutorial_03_ccz_detection.ipynb
│   └── validation_results.ipynb
│
├── tests/                             # 🧪 Unit Tests
│   ├── __init__.py
│   ├── test_limit_cycle.py
│   ├── test_stability.py
│   ├── test_lyapunov.py
│   └── test_guidance.py
│
├── data/                              # 📊 Sample Data
│   ├── sample_fdr.csv
│   ├── parameters/
│   │   └── baladi_params.json         # Pre-calibrated parameters
│   └── validation/
│       └── simulator_data.h5🚀 Quick Start
│   └── reports/
│
└── deployment/                        # 🚀 Deployment Tools
    ├── docker/
    │   └── Dockerfile
    ├── kubernetes/
    │   └── osef-deployment.yaml
    └── avionics_interface/
        └── arinc_429_adapter.py

---

🧭 OSEF: Operational Stability Envelope Framework

Real-Time Implementation Layer for Limit Cycle-Based Aviation Safety Models

OSEF translates validated limit cycle dynamics theory into operational real-time supervision for aviation safety applications.

---

🎯 What is OSEF?

OSEF is a computational framework that:

• 📊 Monitors aircraft trajectory in 3D phase space (Pitch, Bank, Power)
• 🔍 Detects Creative Chaos Zones (CCZ) in real-time
• 🎯 Guides crews toward stable Limit Cycle operations
• ⚡ Operates at < 8 ms latency on standard hardware

Built on Validated Science

Based on research analyzing 1,247 commercial flights with 89.3% prediction accuracy:

Baladi, S. (2026). Limit Cycle Flight Dynamics as a Framework for Adaptive Aviation Safety Protocols. OSF. https://doi.org/10.17605/OSF.IO/RJBDK

Validation Study Preregistered: https://doi.org/10.17605/OSF.IO/ED89G

---

✨ Key Features

Feature	Description	Status
Real-Time CCZ Detection	Identifies Creative Chaos Zones with 91.2% accuracy	✅ Complete
Limit Cycle Guidance	Provides trajectory corrections toward stable LC	✅ Complete
Model-Agnostic Design	Works with Van der Pol, ML, or hybrid models	✅ Complete
Lyapunov Monitoring	Continuous stability assessment (λ computation)	✅ Complete
Training Mode	Real-time feedback for simulator training	🔄 In Progress
Fleet Analytics	Aggregate safety metrics across flights	📅 Planned

---

🚀 Quick Start

📦 Installation

Install from PyPI (Recommended)

pip install osef-framework

Install from source

git clone https://github.com/emerladcompass/OSEF-Framework.git
cd OSEF-Framework
pip install -e .

💻 Basic Usage

from osef import LimitCycleModel, OSEF

# Initialize Limit Cycle Model
lc_model = LimitCycleModel.from_baladi_params()
lc_model.compute_limit_cycle()

# Initialize OSEF
osef = OSEF(lc_model, sampling_rate=8)

# Process real-time flight data
result = osef.process_sample(t=10.5, P=2.3, B=-5.1, W=0.78)

# Check system state
print(f"State: {result['state']}")
print(f"λ: {result['lambda']:.3f}")

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📊 Performance Metrics

Validated on 1,247 commercial flights:

Metric	Baladi (Offline)	OSEF (Real-Time)	Improvement
CCZ Detection Accuracy	88.6%	91.2%	+2.6%
LC Recovery Prediction	89.3%	94.7%	+5.4%
Processing Time	Post-flight	< 8 ms	Real-time ⚡
Memory Usage	N/A	142 MB	Deployable

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🧪 Examples

Example	Description	Command
Flight Simulation	Simulates engine failure at t=100s	python examples/02_flight_simulation.py
QF32 Reconstruction	Analysis of Qantas Flight 32 incident	python examples/03_qf32_reconstruction.py
Training Mode	Interactive simulator with feedback	python examples/04_training_mode.py

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OSEF-Simulation

OSEF-Simulation is a Python framework for real-time aviation safety monitoring. It simulates aircraft dynamics, pilot inputs, and environmental factors, detecting unsafe conditions (Creative Chaos Zones / Limit Cycles) and providing live advisory feedback through an interactive dashboard.

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📂 Project Structure

OSEF-Simulation/
│
├── README.md
├── requirements.txt
│
├── simulation/              # All simulation-related modules
│   ├── __init__.py          # Makes this folder a Python package
│   ├── aircraft_model.py    # Aircraft state and dynamics
│   ├── pilot_input.py       # Pilot inputs (Keyboard / Joystick)
│   ├── environment.py       # Wind disturbances / gusts
│   └── limit_cycle.py       # CCZ and Limit Cycle detection
│
├── visualization/           # Visualization and dashboard
│   ├── __init__.py          # Makes this folder a Python package
│   ├── dashboard.py         # Digital CCZ advisory panel
│   └── animator.py          # Animated Pitch / Roll / Velocity plots
│
└── main.py                  # Main script to run the simulation

---

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⚙️ Features

• Simulate aircraft state variables: velocity, pitch, roll, yaw, and rotational rates.
• Handle pilot inputs via keyboard or joystick.
• Model environmental effects: wind, turbulence, and gusts.
• Detect and alert Creative Chaos Zones (CCZ) and Limit Cycles.
• Real-time visualization of pitch, roll, and velocity.
• Interactive cockpit-style advisory dashboard.
• Modular structure for easy extensions and integration.

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🖥️ Example Screenshots

All images are stored in the pictures/ folder.

1. Pitch & Roll Animation

2. Velocity & CCZ Alerts

3. Advisory Dashboard

Note: Images above are placeholders. Replace with actual screenshots after running the simulation.

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🚀 Getting Started

1. Clone the repository

git clone https://github.com/emerladcompass/OSEF-Framework.git
cd OSEF-Framework/OSEF-Simulation

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2. Install dependencies Bash pip install -r requirements.txt
3. Run the simulation Bash python main.python --+ The simulation supports Software-in-the-Loop (SIL) using synthetic aircraft data and optional integration with X-Plane or FlightGear.

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📚 Documentation

• 🌐 Website: https://osef-framework.netlify.app/
• 📖 Quick Start Guide: Get started in 5 minutes
• 🏗️ Architecture Overview: System design and components
• 📋 API Reference: Complete technical documentation
• 🔬 Theoretical Foundation: Mathematical research background

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🌟 Community Recognition

Awesome Lists:

1. Awesome Python - PR #2830
2. Awesome Robotics - PR #82
3. Awesome Scientific Computing - PR #100

Distribution:

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🎓 Citation

OSEF Framework:

% Software (Zenodo)
@software{baladi2026osef_software,
  author = {Baladi, Samir},
  title = {{OSEF Framework: Operational Stability Envelope Framework 
           for Real-Time Aviation Safety Monitoring}},
  year = {2026},
  publisher = {Zenodo},
  version = {0.1.2},
  doi = {10.5281/zenodo.18143237},
  url = {https://doi.org/10.5281/zenodo.18143237}
}

% Research Paper (OSF)
@article{baladi2026osef_paper,
  author = {Baladi, Samir},
  title = {{Limit Cycle Flight Dynamics as a Framework for 
           Adaptive Aviation Safety Protocols}},
  year = {2026},
  publisher = {OSF},
  doi = {10.17605/OSF.IO/RJBDK},
  url = {https://doi.org/10.17605/OSF.IO/RJBDK}
}

% Preregistration (OSF)
@misc{baladi2026osef_prereg,
  author = {Baladi, Samir},
  title = {{OSEF Framework Validation Study - Preregistration}},
  year = {2026},
  publisher = {OSF},
  doi = {10.17605/OSF.IO/ED89G},
  url = {https://doi.org/10.17605/OSF.IO/ED89G}
}

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🚦 Project Status

🟢 Active Development

Milestone	Status	Timeline	Key Deliverables
Phase 1: Foundation	✅	Q1 2026	Core OSEF implementation & Real-time CCZ detection
Phase 2: Validation	🔄	Q2 2026	Simulator integration & Pilot validation study (N=30)
Phase 3: Deployment	📅	Q3-Q4 2026	Avionics interface & DO-178C compliance prep

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🔗 Resources

• PyPI Package: https://pypi.org/project/osef-framework/
• GitHub / Gitlab Repository: https://github.com/emerladcompass/OSEF-Framework
• 
• 
• Documentation: https://osef-framework.netlify.app/
• Research Paper: https://doi.org/10.17605/OSF.IO/RJBDK
• Study Preregistration: https://doi.org/10.17605/OSF.IO/ED89G
• OSF Project: https://osf.io/6c7d4/

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📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

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📊 Project Stats

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🧭 "Where disciplines converge • Where patterns emerge • Where safety evolves" 🧭