3 papers
math.NA2025
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…
math-ph2012
Self-sustaining oscillations of a falling sphere through Johnson-Segalman fluids
Young-Ju Lee, Chen-Song Zhang
We confirm numerically that the Johnson-Segalman model is able to reproduce the continual oscillations of the falling sphere observed in some viscoelastic models. The empirical cho…
math.NA2012
A Scalable Auxiliary Space Preconditioner for High-Order Finite Element Methods
Young-Ju Lee, Wei Leng, Chen-Song Zhang
In this paper, we revisit an auxiliary space preconditioning method proposed by Xu [Computing 56, 1996], in which low-order finite element spaces are employed as auxiliary spaces f…