4 citations · 4 across the 4 of their papers we have counts for
5 papers
Cova-PINN: Cross-Domain Conservation Physics-Informed Neural Network for Fluid-Solid Conjugate Heat Transfer in Complex Geometries
Weizheng Zhang, Xunjie Xie, Hao Pan +1
Multi-domain physics-informed neural networks (PINNs) flexibly model medium-specific representations to solve fluid--solid conjugate heat transfer (CHT). However, standard multi-do…
A Multi-Agent Framework for Zero-Dimensional Reduced-Order Model Planning
Bingteng Sun, Hao Yin, Yiling Chen +9
Zero-dimensional reduced-order models (0D ROMs) are central to multi-dimensional design workflows for high-end complex equipment. However, the planning process currently relies on…
Flow Field Reconstruction via Voronoi-Enhanced Physics-Informed Neural Networks with End-to-End Sensor Placement Optimization
Renjie Xiao, Bingteng Sun, Yiling Chen +3
(short version abstract, full in article)High-fidelity flow field reconstruction is important in fluid dynamics, but it is challenged by sparse and spatiotemporally incomplete sens…
MUSA-PINN: Multi-scale Weak-form Physics-Informed Neural Networks for Fluid Flow in Complex Geometries
Weizheng Zhang, Xunjie Xie, Hao Pan +4
While Physics-Informed Neural Networks (PINNs) offer a mesh-free approach to solving fluid-flow PDEs, standard point-wise residual minimization suffers from convergence pathologies…
DualMS: Implicit Dual-Channel Minimal Surface Optimization for Heat Exchanger Design
Weizheng Zhang, Hao Pan, Lin Lu +4
Heat exchangers are critical components in a wide range of engineering applications, from energy systems to chemical processing, where efficient thermal management is essential. Th…