Showing physics.flu-dynShow all
3 papers · 1 filter
physics.flu-dyn2025
Deep Operator Learning for High-Fidelity Fluid Flow Field Reconstruction from Sparse Sensor Measurements
Hiep Vo Dang, Phong C. H. Nguyen
Reconstructing high-fidelity fluid flow fields from sparse sensor measurements is vital for many science and engineering applications but remains challenging because of dimensional…
physics.flu-dyn2025★ 1 cited
Multi-resolution Physics-Aware Recurrent Convolutional Neural Network for Complex Flows
Xinlun Cheng, Joseph Choi, H. S. Udaykumar +1
We present MRPARCv2, Multi-resolution Physics-Aware Recurrent Convolutional Neural Network, designed to model complex flows by embedding the structure of advection-diffusion-reacti…
physics.flu-dyn2024
FLRNet: A Deep Learning Method for Regressive Reconstruction of Flow Field From Limited Sensor Measurements
Phong C. H. Nguyen, Joseph B. Choi, Quang-Trung Luu
Many applications in computational and experimental fluid mechanics require effective methods for reconstructing the flow fields from limited sensor data. However, this task remain…