Welcome to G2Aero’s documentation!
G2Aero is a flexible and practical tool for design and deformation of 2D airfoils and 3D blades using data-driven approaches. G2Aero utilizes the geometry of matrix manifolds – specifically the Grassmannian – to build a novel framework for representing physics-based separable deformations of shapes. G2Aero offers the flexibility to generate perturbations in a customizable way over any portion of the blade. The G2Aero framework utilizes data-driven methods based on a curated database of physically relevant airfoils. Specific tools include:
principal geodesic analysis over normal coordinate neighborhoods of matrix manifolds;
a variety of data-regularized deformations to nominal 2D airfoil shapes;
Riemannian interpolation connecting a sequence of airfoil cross-sections to build 3D blades from 2D data;
consistent perturbations over the span of interpolated 3D blades based on dominant modes from the data-driven analysis.
Organization
Documentation is currently organized into three main categories:
How To Guides: User guides covering basic topics and use cases for the G2Aero software
Explanation: Information and research sources for basic concepts used in G2Aero
Technical Reference: Programming details on the G2Aero API and functions
New users may find it helpful to review the Getting started materials first.
Citations
If you use this software in your research or publications, please use the following BibTeX citations:
@article{Doronina_JOSS_2023,
author = {Olga A. Doronina and Zachary J. Grey and Andrew Glaws},
title = {G2Aero: A Python package for separable shape tensors},
journal = {Journal of Open Source Software},
publisher = {The Open Journal},
year = {2023},
volume = {8},
number = {89},
pages = {5408},
doi = {10.21105/joss.05408},
url = {https://doi.org/10.21105/joss.05408},
}
@article{GreyJCDE2023,
author = {Grey, Zachary J and Doronina, Olga A and Glaws, Andrew},
title = "{Separable shape tensors for aerodynamic design}",
journal = {Journal of Computational Design and Engineering},
volume = {10},
number = {1},
pages = {468-487},
year = {2023},
month = {01},
doi = {10.1093/jcde/qwac140},
url = {https://doi.org/10.1093/jcde/qwac140},
}
@inproceedings{grassmannian2022,
title={Grassmannian Shape Representations for Aerodynamic Applications},
author={Olga Doronina and Zachary Grey and Andrew Glaws},
booktitle={AAAI 2022 Workshop on AI for Design and Manufacturing (ADAM)},
year={2022},
url={https://openreview.net/forum?id=1RRU6ud9YC}
}