Python code supporting Physics-informed deep learning for simultaneous surrogate modelling and PDE-constrained optimization of an airfoil geometry'

Python code supporting Physics-informed deep learning for simultaneous surrogate modelling and PDE-constrained optimization of an airfoil geometry'

Repository URI

https://www.repository.cam.ac.uk/handle/1810/348011

Repository DOI

https://doi.org/10.17863/CAM.95425

Files

PINN_Airfoil.py (60.96 KB)

Type

Authors

Sengupta, ushnish

Description

Python code; single file

Keywords

airfoil, automatic differentiation, deep learning, physics-informed neural network, shape optimization, surrogate model

Rights and licensing

Attribution 4.0 International (CC BY 4.0)

Except where otherwised noted, this item's license is described as Attribution 4.0 International (CC BY 4.0)

Sponsorship

European Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (766264)
Royal Society (NIF\R1\192317)

Royal Society (grant number NIF\R1\192317) Marie Sklodowska-Curie grant agreement No 766264

Relationships

Supplements:

https://www.repository.cam.ac.uk/handle/1810/348119

https://doi.org/10.1016/j.cma.2023.116042

Collections

Research Data - Engineering