1 citations · 1 across the 4 of their papers we have counts for
4 papers
White-box machine learning for uncovering physically interpretable dimensionless governing equations for granular materials
Xu Han, Lu Jing, Chung-Yee Kwok +2
Granular material has significant implications for industrial and geophysical processes. A long-lasting challenge, however, is seeking a unified rheology for its solid- and liquid-…
Multiscale super-resolution reconstruction of fluid flows with deep neural networks
Gengchao Yang, Renyu Luo, Qinghe Yao +2
We present a novel multiscale super-resolution framework (SRLBM) that applies deep learning directly to the mesoscopic density distribution functions of the lattice Boltzmann metho…
A CNN-based particle tracking method for large-scale fluid simulations with Lagrangian-Eulerian approaches
Xuan Luo, Zichao Jiang, Yi Zhang +4
A novel particle tracking method based on a convolutional neural network (CNN) is proposed to improve the efficiency of Lagrangian-Eulerian (L-E) approaches. Relying on the success…
A moving least square immersed boundary method for SPH with thin-walled structures
ZhuoLin Wang, Zichao Jiang, Yi Zhang +4
This paper presents a novel method for smoothed particle hydrodynamics (SPH) with thin-walled structures. Inspired by the direct forcing immersed boundary method, this method emplo…