conservation diagnostics 1helicity 1incompressible flow 1Oldroyd-B 1partitioned training 1physics-informed neural networks 1
From the 1 of 3 linked papers with an AI index.
3 papers
physics.flu-dyn2026
Invariant Guided PINN for Fluid Flow Computation
Zheng Lu, Jiwei Jia, Bora Aniruddha +2
The paper introduces an invariant‑guided physics‑informed neural network (IG‑PINN) that trains on spatial subdomains or temporal slabs and then applies a global correction to impro…
math.NA2026
ResiPhy-MDNF: A Residual-Based Physics-Aware Multilevel Discrete Neural Field Framework for PDE-Constrained Inverse Problems
Zheng Lu, Jiwei Jia, Young Ju Lee
Inverse problems governed by partial differential equations are difficult when observations are sparse and the unknown coefficient field contains both large- and small-scale struct…
math.NA2026
R-PINN: Recovery-type a-posteriori estimator enhanced adaptive PINN
Rongxin Lu, Jiwei Jia, Young Ju Lee +2
In recent years, with the advancements in machine learning and neural networks, algorithms using physics-informed neural networks (PINNs) to solve PDEs have gained widespread appli…