guemesturb / raseedgan

GANs-based PIV resolution enhancement without the need of high-resolution input

This notebook covers the Python implementation of a generative adversarial network (GAN) for enhancing the resolution of particle-image-velocimetry (PIV) images from incomplete high-resolution pairs. Particle tracking velocimetry is the experimental technique used to acquire those incomplete high-resolution images. The article associate to his work can be found at [to be published].

Four different cases are available:

• Cylinder wake: direct-numerical simulation (DNS) data generated from Taira and Colonius (2007) and Kutz et al. (2016).
• Turbulent-channel flow: DNS data from a turbulent channel flow with friction Reynolds number $Re_{\tau}=1000$ available at Johns Hopkins Turbulence Database.
• Turbulent boundary layer flow: experimental data of a turbulent boundary layer with friction Reynolds number $Re_{\tau}\approx 900$ acquired in the water-tunnel facility at Universidad Carlos III de Madrid.
• Blunt-body wake: experimental data of the flow around a blunt body acquired in the wind-tunnel facility at Universidad Carlos III de Madrid.

Installation

Use the package manager pip to install the required dependencies.

pip install -r requirements.txt

Usage

To generate the tfrecord files, execute:

guest@vegeta:~$ python run_generate_tfrecords.py -c channel -u 4

To run the training procedure, execute:

guest@vegeta:~$ python run_training --case channel --upsampling 4 --model_name architecture01 --learning_rate 1e-4

To compute the prediction of the testing dataset, execute:

guest@vegeta:~$ python run_predictions -c channel -u 4 -m architecture01 -l 1e-4

Publications

This repository has been used for the following scientific publications:

To be a nnounced

Authorship

This repository has been developed in the Experimental Aerodynamics and Propulsion group at Universidad Carloss III de Madrid. The following researches and students are acknowledged for their contributions:

• Alejandro Güemes
• Stefano Discetti
• Carlos Sanmiguel

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

Creative Commons