Modeling Advection-Dominated Flows with Space-Local Reduced-Order Models
Toby van Gastelen, Wouter Edeling, Benjamin Sanderse

TL;DR
This paper introduces a space-local POD method for reduced-order modeling of advection-dominated flows, improving generalization, stability, and computational efficiency over traditional global POD techniques.
Contribution
The paper presents a novel space-local POD approach with overlapping subdomains, enhancing ROM accuracy and stability for advection-dominated flows compared to standard methods.
Findings
Better generalization to unseen flow conditions
Inherits energy conservation and stability properties
Enables larger time steps in simulations
Abstract
Reduced-order models (ROMs) are often used to accelerate the simulation of large physical systems. However, traditional ROM techniques, such as those based on proper orthogonal decomposition (POD), often struggle with advection-dominated flows due to the slow singular value decay. This results in high computational costs and potential instabilities. This paper proposes a novel approach using space-local POD to address the challenges arising from the slow singular value decay. Instead of global basis functions, our method employs local basis functions that are applied across the domain, analogous to the finite element method, but with a data-driven basis. By dividing the domain into subdomains and applying the space-local POD, we achieve a representation that is sparse and that generalizes better outside the training regime. This allows the use of a larger number of basis functions…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsModel Reduction and Neural Networks · Fluid Dynamics and Vibration Analysis · Fluid Dynamics and Turbulent Flows
