1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2025
LT-PINN: Lagrangian Topology-conscious Physics-informed Neural Network for Boundary-focused Engineering Optimization
Yuanye Zhou, Zhaokun Wang, Kai Zhou +2
Physics-informed neural networks (PINNs) have emerged as a powerful meshless tool for topology optimization, capable of simultaneously determining optimal topologies and physical s…
eess.IV2025
Aneumo: A Large-Scale Multimodal Aneurysm Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks
Xigui Li, Yuanye Zhou, Feiyang Xiao +16
Intracranial aneurysms (IAs) are serious cerebrovascular lesions found in approximately 5\% of the general population. Their rupture may lead to high mortality. Current methods for…
physics.flu-dyn2024★ 1 cited
An unstructured adaptive mesh refinement for steady flows based on physics-informed neural networks
Yongzheng Zhu, Shiji Zhao, Yuanye Zhou +2
Mesh generation is essential for accurate and efficient computational fluid dynamics simulations. To resolve critical features in the flow, adaptive mesh refinement (AMR) is routin…