1 citations · 1 across the 4 of their papers we have counts for
5 papers
Learning Long-Term Stable Operator Inference Reduced-Order Models of Fluid Flows through Online Spatial Filtering
Ian Moore, Ping-Hsuan Tsai, Anthony Gruber +4
This paper introduces an online evolve--filter--relax (EFR) strategy for long-term stability of Operator Inference (OpInf) reduced-order models (ROMs) of complex fluid flow simulat…
Digital Twins in Coronary Artery Disease: A Mathematical Roadmap
Alessandro Veneziani, Annalisa Quaini, Marco Tezzele +2
The combination of data and models, enhanced by AI methodologies, leads to the paradigm called Digital Twins. This concept is expected to bring unprecedented support to personalize…
StabOp: A Data-Driven Stabilization Operator for Reduced Order Modeling
Ping-Hsuan Tsai, Anna Ivagnes, Annalisa Quaini +2
Spatial filters have played a central role in large eddy simulation and, more recently, in reduced order model (ROM) stabilization for convection-dominated flows. Nevertheless, imp…
Defining Foundation Models for Computational Science: A Call for Clarity and Rigor
Youngsoo Choi, Siu Wun Cheung, Youngkyu Kim +9
The widespread success of foundation models in natural language processing and computer vision has inspired researchers to extend the concept to scientific machine learning and com…
Verifiability and Limit Consistency of Eddy Viscosity Large Eddy Simulation Reduced Order Models
Jorge Reyes, Ping-Hsuan Tsai, Ian Moore +2
Large eddy simulation reduced order models (LES-ROMs) are ROMs that leverage LES ideas (e.g., filtering and closure modeling) to construct accurate and efficient ROMs for convectio…