Details of flow field are highly relevant to understand the mechanism of turbulence, but
obtaining high-resolution turbulence often requires enormous computing resources …

The reconstruction of accurate and robust unsteady flow fields from sparse and noisy data in
real-life engineering tasks is challenging, particularly when sensors are randomly placed. To …

Obtaining reliable flow data is essential for the fluid mechanics analysis and control, and
various measurement techniques have been proposed to achieve this goal. However …

Hydrofoils play a crucial role in enhancing the efficiency of fluid machinery designed for
ocean environments, reducing lift-induced drag and contributing to improved overall …

Complete and clear global wind turbine wake data is very important for the study of wind
turbine wake characteristics in increasingly large offshore wind farms. Existing wake …

Data center thermal management requires a good understanding of critical cooling airflow
path. While CFD modeling excels at portraying airflow and temperature fields, it is often …

Deep learning has recently gained attention in the atmospheric and oceanic sciences for its
potential to improve the accuracy of numerical simulations or to reduce computational costs …

This study proposes a convolutional neural network (CNN) that enhances the resolution of
instantaneous snapshots of three-dimensional air temperature and wind velocity fields …

Computational fluid dynamics is a cornerstone of the modern aerospace industry, providing
important insights through aerodynamic analysis while reducing the need for expensive …

In turbomachinery, strongly unsteady rotor–stator interaction triggers complex three-
dimensional turbulent flow phenomena such as flow separation and vortex dynamics. Large …