Convolutional Neural Networks for LPV-Approximations of Semi-discrete Navier-Stokes Equations
收藏NIAID Data Ecosystem2026-03-13 收录
下载链接：
https://zenodo.org/record/6401953
下载链接
链接失效反馈官方服务：
资源简介：
A `python` module with
* a dynamic setup of *Convolutional Neural Networks* in `PyTorch`
* an interface to `FEniCS` to generate data from FEM simulations of flows and
* a numerical realization of FEM norm in the training neural networks
developed to design very low-dimensional LPV approximations of incompressible Navier-Stokes equations.
These files contain the core module and the scripts that produce the numerical examples of the paper with doi:10.3389/fams.2022.879140
> Benner, Heiland, Bahmani (2022): *Convolutional Neural Networks for Very Low-dimensional LPV Approximations of Incompressible Navier-Stokes Equations*
创建时间：
2022-04-12
