activity
20202024
most citedHigh-fidelity reconstruction of turbulent flow from spatially limited data using enhanced super-resolution generative adversarial network

103 citations · 274 across the 15 of their papers we have counts for

collaborators

15 papers

physics.flu-dyn2024★ 1 cited

Efficient Active Flow Control Strategy for Confined Square Cylinder Wake Using Deep Learning-Based Surrogate Model and Reinforcement Learning

Meng Zhang, Mustafa Z. Yousif, Minze Xu +3

This study presents a deep learning model-based reinforcement learning (DL-MBRL) approach for active control of two-dimensional (2D) wake flow past a square cylinder using antiphas…

physics.flu-dyn2024

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…

physics.flu-dyn2024

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…

physics.flu-dyn2023

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…

physics.flu-dyn2023

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…

physics.flu-dyn2023

An exhaustive review of studies on bio-inspired convergent-divergent riblets

Arash Mohammadikarachi, Mustafa Z. Yousif, Bagus Nugroho +1

Inspired by the unique textures of shark skin and bird flight feathers and tails, the convergent-divergent surface pattern holds promise in modulating boundary layer structures. Th…

physics.flu-dyn2023

Active flow control over a finite wall-mounted square cylinder by using multiple plasma actuators

Mustafa Z. Yousif, Yifan Yang, Haifeng Zhou +3

The present study aims to investigate the effectiveness of plasma actuators in controlling the flow around a finite wall-mounted square cylinder (FWMSC) with a longitudinal aspect…

physics.flu-dyn2023★ 1 cited

Predicting unavailable parameters from existing velocity fields of turbulent flows using a GAN-based model

Linqi Yu, Mustafa Z. Yousif, Young-Woo Lee +4

In this study, an efficient deep-learning model is developed to predict unavailable parameters, e.g., streamwise velocity, temperature, and pressure from available velocity compone…

physics.flu-dyn2023

Physics-guided deep reinforcement learning for flow field denoising

Mustafa Z. Yousif, Meng Zhang, Yifan Yang +3

A multi-agent deep reinforcement learning (DRL)-based model is presented in this study to reconstruct flow fields from noisy data. A combination of the reinforcement learning with…

physics.flu-dyn2022★ 3 cited

A deep-learning approach for reconstructing 3D turbulent flows from 2D observation data

Mustafa Z. Yousif, Linqi Yu, Sergio Hoyas +2

Turbulence is a complex phenomenon that has a chaotic nature with multiple spatio-temporal scales, making predictions of turbulent flows a challenging topic. Nowadays, an abundance…

physics.flu-dyn2022★ 89 cited

A transformer-based synthetic-inflow generator for spatially-developing turbulent boundary layers

Mustafa Z. Yousif, Meng Zhang, Linqi Yu +2

This study proposes a newly-developed deep-learning-based method to generate turbulent inflow conditions for spatially-developing turbulent boundary layer (TBL) simulations. A comb…

physics.flu-dyn2021★ 75 cited

Super-resolution reconstruction of turbulent flow at various Reynolds numbers based on generative adversarial networks

Mustafa Z. Yousif, Linqi Yu, Hee-Chang Lim

This study presents a deep learning-based framework to reconstruct high-resolution turbulent velocity fields from extremely low-resolution data at various Reynolds numbers using th…

physics.flu-dyn2021

Artificial neural network-based reduced-order modeling for turbulent wake of a finite wall-mounted square cylinder

Mustafa Z. Yousif, Hee Chang Lim

This study presents an artificial neural network and proper orthogonal decomposition (POD)-based reduced-order model (ROM) of turbulent flow around a finite wall-mounted square cyl…

physics.flu-dyn2021★ 103 cited

High-fidelity reconstruction of turbulent flow from spatially limited data using enhanced super-resolution generative adversarial network

Mustafa Z. Yousif, Linqi Yu, HeeChang Lim

In this study, a deep learning-based approach is applied with the aim of reconstructing high-resolution turbulent flow fields using minimal flow fields data. A multi-scale enhanced…

physics.flu-dyn2020★ 2 cited

On the characteristics of the turbulent wake behind a wall-mounted square cylinder

Mustafa Zhuhair Gheni Yousif, HeeChang Lim

The turbulent flow past a wall-mounted square cylinder with an aspect ratio of four was investigated with the aid of Spalart-Allmaras improved delayed detached-eddy simulation (S-A…