✈️ Winglytics

Aerodynamic Analysis & Wing Design Tool for RC Aircraft

A comprehensive Python application for analyzing airfoils, scoring them based on mission requirements, and designing optimal wing configurations for remote control aircraft.

🌟 Features

• Airfoil Analysis: Uses NeuralFoil to analyze airfoils across ranges of angles of attack and Reynolds numbers
• Multi-Mission Scoring: Ranks airfoils based on payload, endurance, or trainer mission profiles
• Wing Design: Generates and evaluates wing configurations with different aspect ratios
• VLM Analysis: Performs Vortex Lattice Method analysis for accurate aerodynamic predictions
• Performance Filtering: Selects wings that meet MTOW (Maximum Takeoff Weight) requirements
• Interactive UI: Beautiful Streamlit interface for easy parameter configuration and visualization
• Comprehensive Plots: Visualizes CL, CD, L/D ratios, moment coefficients, and comparisons

📁 Project Structure

Wing parameter decide/
├── app.py                    # Main Streamlit UI application
├── config.py                 # Configuration and constants
├── utils.py                  # Utility functions
├── airfoil_analysis.py       # Airfoil analysis module
├── scoring.py                # Scoring and ranking module
├── wing_design.py            # Wing design and VLM analysis
├── visualization.py          # Plotting and visualization
├── requirements.txt          # Python dependencies
├── README.md                 # This file
└── wing analyzer.py          # Original monolithic script (legacy)

🚀 Installation

Prerequisites

• Python 3.8 or higher
• pip package manager

Setup

1. Clone or navigate to the project folder:

   cd "e:\Aeroclub\Wing parameter decide"

2. Install dependencies:

   pip install -r requirements.txt

3. Prepare airfoil files:

   • Place your .dat airfoil files in the designated folder
   • Default: E:\Aeroclub\Airfoils_twst
   • Update path in config.py if different

💻 Usage

Running the Streamlit Application

streamlit run app.py

This will open the application in your default web browser.

Application Workflow

1. Home Tab: Configure design parameters

   • Set MTOW (Maximum Takeoff Weight)
   • Set maximum wingspan constraint
   • Choose design velocity
   • Select mission type (payload/endurance/trainer)

2. Airfoil Analysis Tab: Analyze airfoils

   • Click "Start Airfoil Analysis"
   • Wait for NeuralFoil to analyze all airfoils
   • View and download results

3. Ranking & Selection Tab: Score airfoils

   • Review scoring weights for your mission
   • Calculate rankings
   • View top-ranked airfoils
   • Download ranked results

4. Wing Design Tab: Generate wing configurations

   • Generate configurations with different aspect ratios
   • Optionally run VLM analysis (time-intensive)
   • Filter wings meeting MTOW requirements
   • Download suitable wing designs

5. Visualizations Tab: Create plots

   • Single airfoil plots (CL, CD, L/D, CM vs alpha)
   • Compare multiple airfoils at specific Reynolds numbers
   • Export plots as needed

Using as Python Modules

You can also import and use the modules in your own scripts:

from airfoil_analysis import AirfoilAnalyzer
from scoring import AirfoilScorer
from wing_design import WingDesigner, WingAnalyzer
from visualization import AirfoilPlotter

# Analyze airfoils
analyzer = AirfoilAnalyzer(folder="path/to/airfoils", velocity=13)
db = analyzer.analyze_all_airfoils("output.csv")

# Score and rank
scorer = AirfoilScorer(application="payload")
ranked = scorer.rank_airfoils(combined_df)

# Design wings
designer = WingDesigner(velocity=13, max_wingspan=1.8)
configs = designer.generate_wing_configurations(ranked)

# Visualize
plotter = AirfoilPlotter(db)
plotter.plot_cl_vs_alpha("airfoil_name")

⚙️ Configuration

Edit config.py to customize:

• Analysis parameters: Alpha range, Reynolds range, NeuralFoil model size
• Design constraints: Default MTOW, wingspan limits, aspect ratios
• Scoring weights: Mission-specific criteria weights
• File paths: Input/output directories
• Physical constants: Air density, viscosity, etc.

Mission Type Scoring Weights

Payload Mission (optimized for carrying capacity):

• MAX_CL/CD: 25%
• Optimum_CL: 30%
• CL_max: 20%
• Others: 25%

Endurance Mission (optimized for flight time):

• MAX_CL/CD: 40%
• Optimum_CD: 20%
• Optimum_CL: 15%
• Others: 25%

Trainer Mission (optimized for gentle handling):

• angle_diff: 35%
• CL_at_0_deg: 20%
• CL_max: 20%
• Others: 25%

📊 Output Files

The application generates several CSV files in the output folder:

• neuralfoil_output.csv: Raw aerodynamic data for all airfoils
• ranked_airfoils.csv: Scored and ranked airfoils
• final_wing_data.csv: Wing configurations with VLM results
• suitable_wings.csv: Wings meeting MTOW requirements

🔧 Technical Details

Analysis Process

1. Airfoil Loading: Reads .dat coordinate files
2. Kulfan Transformation: Converts to parametric representation
3. NeuralFoil Analysis: Predicts CL, CD, CM across operating envelope
4. Feature Extraction: Identifies stall points, optimum L/D, zero-alpha performance
5. Normalization: Scales features to [0,1] range
6. Weighted Scoring: Applies mission-specific weights
7. Wing Generation: Creates configurations within constraints
8. VLM Analysis: Computes 3D aerodynamics (optional)
9. Performance Filtering: Selects designs meeting requirements

Key Algorithms

• NeuralFoil: Machine learning-based airfoil aerodynamics prediction
• VLM (Vortex Lattice Method): Potential flow solver for finite wings
• Multi-criteria scoring: Weighted sum of normalized features

📚 Dependencies

• aerosandbox: Aerodynamic analysis and VLM solver
• numpy: Numerical computations
• pandas: Data manipulation and analysis
• matplotlib: Plotting and visualization
• streamlit: Web-based user interface

🐛 Troubleshooting

"Airfoil folder not found"

• Verify the path in config.py or enter correct path in UI
• Ensure .dat files are present

"No airfoils meet MTOW requirement"

• Increase max wingspan constraint
• Reduce MTOW requirement
• Try different aspect ratios
• Check if VLM analysis ran correctly

VLM analysis fails

• Verify airfoil .dat files are valid
• Check for corrupted airfoil geometry
• Ensure sufficient memory for large batches

Slow performance

• Reduce number of airfoils
• Decrease Reynolds number points in config.py
• Skip VLM analysis for quick estimates
• Use smaller NeuralFoil model size

📝 License

This project is for educational and research purposes. Please cite AeroSandbox and NeuralFoil if used in publications.

🤝 Contributing

Contributions are welcome! Areas for improvement:

• Add tapered wing support
• Include structural analysis
• Export to CAD formats
• Support for multi-segment wings
• Optimization algorithms

📧 Contact

For questions or support related to this project, please refer to the AeroSandbox documentation:

• GitHub: https://github.com/peterdsharpe/AeroSandbox
• Documentation: https://peterdsharpe.github.io/AeroSandbox/

🙏 Acknowledgments

• AeroSandbox by Peter Sharpe - Aircraft design optimization framework
• NeuralFoil - Machine learning airfoil aerodynamics
• AEROCLUB NITTE - Original project development

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Made with ❤️ for RC aircraft enthusiasts