3 papers
physics.flu-dyn2026
Acoustics-based Active Control of Unsteady Flow Dynamics using Reinforcement Learning Driven Synthetic Jets
Siddharth Rout, Khai Phan, Chao-An Lin
Flow generated noise are caused shear flows and, hence, they can be used as feedback to control the flow. Existing flow control uses state variables like velocity, pressure, or vor…
cs.LG2025
Impact of Loss Weight and Model Complexity on Physics-Informed Neural Networks for Computational Fluid Dynamics
Yi En Chou, Te Hsin Liu, Chao-An Lin
Physics Informed Neural Networks offer a mesh free framework for solving PDEs but are highly sensitive to loss weight selection. We propose two dimensional analysis based weighting…
cs.LG2025
Multi-level datasets training method in Physics-Informed Neural Networks
Yao-Hsuan Tsai, Hsiao-Tung Juan, Pao-Hsiung Chiu +1
Physics-Informed Neural Networks have emerged as a promising methodology for solving PDEs, gaining significant attention in computer science and various physics-related fields. Des…