4 papers
Self-Supervised Learning for Effective Denoising of Flow Fields
Linqi Yu, Mustafa Z. Yousif, Dan Zhou +3
In this study, we proposed an efficient approach based on a deep learning (DL) denoising autoencoder (DAE) model for denoising noisy flow fields. The DAE operates on a self-learnin…
Flow Reconstruction Using Spatially Restricted Domains Based on Enhanced Super-Resolution Generative Adversarial Networks
Mustafa Z. Yousif, Dan Zhou, Linqi Yu +4
This study aims to reconstruct the complete flow field from spatially restricted domain data by utilizing an Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) model…
Optimizing Flow Control with Deep Reinforcement Learning: Plasma Actuator Placement around a Square Cylinder
Mustafa Z Yousif, Kolesova Paraskovia, Yifang Yang +5
The present study proposes an active flow control (AFC) approach based on deep reinforcement learning (DRL) to optimize the performance of multiple plasma actuators on a square cyl…
A Swin-Transformer-based Model for Efficient Compression of Turbulent Flow Data
Meng Zhang, Mustafa Z Yousif, Linqi Yu +1
This study proposes a novel deep-learning-based method for generating reduced representations of turbulent flows that ensures efficient storage and transfer while maintaining high…