4 papers
From Fixed Grids to Moving Particles:A Transferable Latent Operator for Fluid Dynamics
Meng Li, Chuqi Chen, Zhengqing Gao +4
Lagrangian modeling is vital to fluid dynamics, as it characterizes particle transport and complements the Eulerian representation. However, Lagrangian trajectories are less common…
Enhancing Future Prediction of Linear and Nonlinear Reduced-Order Models for Transport-Dominated Problems Using Lagrangian Data
Meng Li, Yang Xiang, Zhichao Peng
Designing effective reduced-order models (ROMs) for parametrized transport-dominated problems remains challenging because of the well-known Kolmogorov barrier. Autoencoder-based no…
Adaptive and hybrid reduced order models to mitigate Kolmogorov barrier in a multiscale kinetic transport equation
Tianyu Jin, Zhichao Peng, Yang Xiang
In this work, we develop reduced order models (ROMs) to predict solutions to a multiscale kinetic transport equation with a diffusion limit under the parametric setting. When the u…
A fast neural hybrid Newton solver adapted to implicit methods for nonlinear dynamics
Tianyu Jin, Georg Maierhofer, Katharina Schratz +1
The use of implicit time-stepping schemes for the numerical approximation of solutions to stiff nonlinear time-evolution equations brings well-known advantages including, typically…