A graphics-accelerated deep neural network approach for turbomachinery flows based on large eddy simulation
Z Tong, J Xin, J Song, XE Cao - Physics of Fluids, 2023 - pubs.aip.org
In turbomachinery, strongly unsteady rotor–stator interaction triggers complex three-
dimensional turbulent flow phenomena such as flow separation and vortex dynamics. Large …
dimensional turbulent flow phenomena such as flow separation and vortex dynamics. Large …
A priori assessment of nonlocal data-driven wall modeling in large eddy simulation
G Tabe Jamaat, Y Hattori - Physics of Fluids, 2023 - pubs.aip.org
In the present study, a priori assessment is performed on the ability of the convolutional
neural network (CNN) for wall-modeling in large eddy simulation. The data used for the …
neural network (CNN) for wall-modeling in large eddy simulation. The data used for the …
Influence of adversarial training on super-resolution turbulence reconstruction
Supervised super-resolution deep convolutional neural networks (CNNs) have gained
significant attention for their potential in reconstructing velocity and scalar fields in turbulent …
significant attention for their potential in reconstructing velocity and scalar fields in turbulent …
[HTML][HTML] Recent Advancements in Large Eddy Simulations of Compressible Real Gas Flows
N Padmanabhan - 2024 - intechopen.com
This chapter explores some of the recent advancements in the field of computational fluid
dynamics, specifically with respect to large eddy simulations. We start by introducing some …
dynamics, specifically with respect to large eddy simulations. We start by introducing some …
[PDF][PDF] Turbulence Modeling for Large Eddy Simulation by Data-driven Approach
JG Tabe - tohoku.repo.nii.ac.jp
The numerical investigation of the turbulent flows is of cardinal importance as they can be
found almost everywhere either in nature or industries. Therefore, it is crucial to conduct …
found almost everywhere either in nature or industries. Therefore, it is crucial to conduct …