4 papers
UrbanFlow-3K: A Dataset of 3,000 Lattice-Boltzmann Simulations of Random Building Layouts
Hojin Lee, Andreas Lintermann, Sangseung Lee +1
The analysis of flow around buildings has gained significant research interest across various domains, including pedestrian safety, pollutant dispersion, natural ventilation, and b…
Engineering application of physics-informed neural networks for Saint-Venant torsion
Su Yeong Jo, Sanghyeon Park, Seungchan Ko +4
The Saint-Venant torsion theory is a classical theory for analyzing the torsional behavior of structural components, and it remains critically important in modern computational des…
Data-driven discovery of drag-inducing elements on a rough surface through convolutional neural networks
Heesoo Shin, Seyed Morteza Habibi Khorasani, Zhaoyu Shi +3
Understanding the influence of surface roughness on drag forces remains a significant challenge in fluid dynamics. This paper presents a convolutional neural network (CNN) that pre…
Drag prediction of rough-wall turbulent flow using data-driven regression
Zhaoyu Shi, Seyed Morteza Habibi Khorasani, Heesoo Shin +3
Efficient tools for predicting the drag of rough walls in turbulent flows would have a tremendous impact. However, methods for drag prediction rely on experiments or numerical simu…