Zobrazeno 1 - 10
of 6 137
pro vyhledávání: '"Mustafa, Z."'
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 antiphase jets. The DL-MBRL framework alternates between interacting with a de
Externí odkaz:
http://arxiv.org/abs/2408.14232
Autor:
Yousif, Mustafa Z., Zhou, Dan, Yu, Linqi, Zhang, Meng, Mohammadikarachi, Arash, Lee, Jung Sub, Lim, Hee-Chang
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. The difficulty in flow field reconstruction lies in accurately captu
Externí odkaz:
http://arxiv.org/abs/2408.01658
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-learning principle and does not require clean data as training labels. Furthe
Externí odkaz:
http://arxiv.org/abs/2408.01659
Autor:
Yousif, Mustafa Z, Paraskovia, Kolesova, Yang, Yifang, Zhang, Meng, Yu, Linqi, Rabault, Jean, Vinuesa, Ricardo, Lim, HeeChang
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 cylinder. The investigation aims to modify the control inputs of the plas
Externí odkaz:
http://arxiv.org/abs/2309.09197
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 accuracy during decompression. A Swin-Transformer network combined wit
Externí odkaz:
http://arxiv.org/abs/2309.09192
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. This surface pattern exhibits protrusions precisely aligned obliquely (a
Externí odkaz:
http://arxiv.org/abs/2309.09138
Autor:
Mustafa Z. Mahmoud
Publikováno v:
BMC Medical Education, Vol 24, Iss 1, Pp 1-3 (2024)
Abstract The purpose of the following paper is to offer an update on the feasibility of using e-learning to sustain medical radiation technology education in light of Sudan’s ongoing crisis. The Sudanese acting Minister of Higher Education and Scie
Externí odkaz:
https://doaj.org/article/fdb882e6691f4288b86dd6a46af3132c
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 ratio of 4. The test is conducted in a small-scale closed return-type
Externí odkaz:
http://arxiv.org/abs/2304.10056
Autor:
Yu, Linqi, Yousif, Mustafa Z., Lee, Young-Woo, Zhu, Xiaojue, Zhang, Meng, Kolesova, Paraskovia, Lim, Hee-Chang
In this study, an efficient deep-learning model is developed to predict unavailable parameters, e.g., streamwise velocity, temperature, and pressure from available velocity components. This model, termed mapping generative adversarial network (M-GAN)
Externí odkaz:
http://arxiv.org/abs/2304.07762
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 pixel-wise rewards (PixelRL), physical constraints represented by the
Externí odkaz:
http://arxiv.org/abs/2302.09559