This repository contains our complete solution to the Powered Lift Wing & Thrust Plant Design problem statement presented by LAT Aerospace during Inter IIT Tech Meet 14.0.
The objective was to design an innovative powered-lift fixed-wing architecture capable of generating extremely high lift coefficients while maintaining efficient cruise performance for future Short Take-Off and Landing (STOL) aircraft.
Our solution combines:
- Distributed Electric Propulsion (DEP)
- Blown Flap Technology
- Mathematical Aerodynamic Modeling
- Blade Element Momentum Theory (BEMT)
- Computational Fluid Dynamics (CFD)
- Structural Analysis
- Numerical Optimization
The entire design pipeline was built from first principles and validated using analytical models together with CFD simulations.
Design a fixed-wing aircraft integrated with a thrust-producing system capable of generating exceptionally high lift coefficients while satisfying stringent performance constraints.
Target metrics included:
- Lift Coefficient (CL) ≥ 6.5
- Lift-to-Drag Ratio > 5 (Takeoff)
- Lift-to-Drag Ratio > 20 (Cruise)
- Minimum Lift = 15 kg @ 20 m/s
- Fixed-wing only
- No Tilt Rotor
- No VTOL
- Powered Lift mandatory
Instead of directly selecting a conventional STOL configuration, we first performed a comparative study of several high-lift architectures.
- Channel Wing
- Prandtl-D (Bell Spanload)
- Joined Wing
- Distributed Electric Propulsion (DEP)
- Blown Flaps
- Electric Ducted Fans (EDF)
- Open Propellers
After evaluating aerodynamic performance, manufacturability, structural complexity, controllability, and safety, we selected:
Distributed Electric Propulsion (DEP) with Blown Flaps
This architecture provided the best balance between
- High Lift
- Redundancy
- Mechanical Simplicity
- Cruise Efficiency
- Control Authority
The project was divided into multiple interconnected modules.
- Airfoil selection
- Thin Airfoil Theory
- Camber optimization
- Flap modeling
- Blown flap mathematical formulation
- Finite wing corrections
A comparative analysis was performed between
- Open Propellers
- Electric Ducted Fans
The propulsion model was developed using
- Momentum Theory
- Blade Element Theory
- Blade Element Momentum Theory (BEMT)
The mathematical model predicts
- Thrust
- Torque
- Efficiency
- Power Consumption
The solver was validated against published NACA experimental datasets.
Custom Python solvers were developed for
- Propeller optimization
- Airfoil optimization
- Blade geometry
- Pitch distribution
- Performance prediction
Libraries used include
- NumPy
- SciPy
- Matplotlib
CFD simulations were performed using ANSYS Fluent for
- Propeller Validation
- Wing Validation
- Flap Performance
- Blown Wing Analysis
Studies included
- Mesh Independence
- Pressure Distribution
- Velocity Contours
- Streamlines
- Lift & Drag Validation
Structural feasibility of the wing was also analyzed to ensure the high-lift configuration remained mechanically practical.
This repository contains tools for Propulsion (BEMT/XFOIL-based propeller analysis) and Wing Aerodynamics (VLM/VSM/DEP studies).
- requirements.txt - Python dependencies for the project
- README.md - Project documentation
- Additional Files - Organized files for the project
Tools for Propeller Design, Analysis, and Optimization using Blade Element Momentum Theory (BEMT) and XFOIL.
- Airfoils/ - Airfoil coordinate data for propeller sections
- Propeller/ - Our Arbitrary propeller geometry and related data
- bemt_dynamic_airfoil_optimization.py - BEMT-based Collective and RPM optimization for an arbitrary propeller (with data given in
Propeller/) - bemt_general_optimization.py - BEMT-based Collective and RPM optimization for a propeller with a general airfoil (NACA4412)
- bemt_rmit.py - Comparison of our algorithm to the performance observed in the Paper by RMIT
- bemt_with_xfoil.py - BEMT coupled with XFOIL for viscous airfoil data
- propeller_data.csv - The propeller performance measurements as observed in the Paper by RMIT
- xfoil_final.py - Python wrapper for running XFOIL
- xfoil.exe - XFOIL executable (Windows)
Contains 2D/3D wing aerodynamic solvers, DEP (Distributed Electric Propulsion) simulations, and vortex methods.
- Airfoils/ - Airfoil coordinate files for wing analysis
- DEP_2D.py - 2D DEP aerodynamic analysis
- DEP_cruise.py - Cruise condition analysis for our chosen DEP configuration
- DEP_takeoff.py - Takeoff condition analysis for our chosen DEP configuration
- DEP_paper_2D_flat.py - In the paper by Spence, they mentioned a formula for a flat blown airfoil. This evaluates that formula to get the
Claccording to his observations. - helper.py - Shared utility function to read camber line from csv
- VLM_2d.ipynb - 2D Vortex Lattice Method notebook
- VSM_wing.py - Full Vortex Sheet Method wing model
- VSM_wing_simplified.py - A slightly simplified version of VSM solver
Wing aerodynamic analysis Excluding jet/propeller slipstream effects for baseline comparisons.
- Airfoils/ - Airfoil datasets
- Gamma.py - Circulation distribution calculation
- extraction.py - Data extraction and post-processing
- helper.py - Utility functions
Simulation of the optimal takeoff conditions as described by the output of propulsion/bemt_dynamic_airfoil_optimization.py.
Simulation of a 3D wing as described by the output of wing_no_jet/Gamma.py.
Simulation of the optimal wing as described by the output of wing/DEP_takeoff.py.
# Tools & Software
| Tool | Purpose |
|------|----------|
| Python | Mathematical Modeling |
| NumPy | Numerical Computation |
| SciPy | Optimization |
| Matplotlib | Visualization |
| XFOIL | Airfoil Analysis |
| ANSYS Fluent | CFD |
| OpenVSP | Geometry Development |
| AVL | Preliminary Stability Analysis |
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# Highlights
- Complete mathematical model for DEP-based STOL aircraft
- Blade Element Momentum Theory implementation
- Airfoil and flap analytical model
- CFD validation of propulsion system
- CFD validation of blown-wing concept
- Structural feasibility analysis
- Constraint optimization framework
- Research-backed design decisions
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# Results
The proposed architecture successfully demonstrated
- High lift capability through blown flaps
- Efficient DEP-based propulsion
- Good agreement between analytical models and CFD
- Parameterized optimization framework for future improvements
The workflow can be extended for
- Aircraft optimization
- Autonomous STOL vehicles
- Regional Air Mobility (RAM)
- Urban Air Mobility (UAM)
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# Future Work
- Multi-objective optimization
- Wind tunnel validation
- Aeroelastic analysis
- Flight control integration
- Reinforcement Learning assisted optimization
- Multi-disciplinary Design Optimization (MDO)
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# References
This project builds upon literature including
- Blade Element Momentum Theory
- Thin Airfoil Theory
- NASA STOL research
- NACA Propeller Experiments
- Distributed Electric Propulsion studies
Complete references are available in the final report.
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# Team
**Team 99**
Inter IIT Tech Meet 14.0
Powered Lift Wing & Thrust Plant Design
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## Acknowledgements
We sincerely thank **LAT Aerospace** and the **Inter IIT Tech Meet 14.0 Organizing Committee** for presenting an open-ended engineering challenge that encouraged innovation in aerodynamics, propulsion, optimization, and computational analysis.
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# Project Structure
pip install -r requirements.txt
cd propulsion
python bemt_general_optimization.pyThis can be extrapolated to run all other files as well.