Thriving 
PY Automated multi-fidelity conceptual design and optimization pipeline for aerospace vehicles
HEALTH ? 90 / Healthy
Thriving PY // readme
YAADO — by MELprop
The project aims to be a user-friendly preliminary design and Multidisciplinary Design Optimization (MDO) environment for aerospace vehicles. YAADO’s goal is to enable everybody to use variable-fidelity design analysis tools to move your designs from paper and laptop to the sky.
Features
- Declarative Design: Build rockets and UAVs using simple TOML configurations — no Python programming required.
- Variable-Fidelity Aerodynamics: Seamlessly swap between empirical handbook formulas (DATCOM), Vortex Lattice Methods (AVL), 2D panel methods (XFOIL), and High-Fidelity CFD (SU2).
- Propulsion Analysis: Built-in 1-D thermodynamic engine cycle analysis and custom turbojet performance maps.
Getting Started
If you want to join the project please check
ONBOARDING.md. README is for end-users.
1. Installation
To use YAADO, clone the repository and install the environment. Because YAADO relies on heavily integrated physics engines, you must initialize the submodules:
git clone https://github.com/knnmelprop/YAADO.git
cd YAADO
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