9 papers
Hybrid coupling with operator inference and the overlapping Schwarz alternating method
Irina Tezaur, Eric Parish, Anthony Gruber +3
This paper presents a novel hybrid approach for coupling subdomain-local non-intrusive Operator Inference (OpInf) reduced order models (ROMs) with each other and with subdomain-loc…
Flexible and Stable Dynamics Discovery with Onsager's Variational Principle
Anthony Gruber, Ritoban Roy-Chowdhury, Irina Tezaur +1
Variational principles specify the dynamics of a physical system via the extremization of associated functional data. Onsager's variational principle (OVP), which characterizes dis…
On the role of relaxation and acceleration in the non-overlapping Schwarz alternating method for coupling
Giulia Sambataro, Irina Tezaur
The purpose of this paper is to study the influence of relaxation and acceleration techniques on the convergence behavior of the non-overlapping Schwarz algorithm with alternating…
NN-OpInf: an operator inference approach using structure-preserving composable neural networks
Eric Parish, Anthony Gruber, Patrick Blonigan +1
We propose neural network operator inference (NN-OpInf): a structure-preserving, composable, and minimally restrictive operator inference framework for the non-intrusive reduced-or…
Domain Decomposition-Based Coupling of High-Fidelity Finite Element and Reduced Order Operator Inference Models Using the Schwarz Alternating Method
Ian Moore, Anthony Gruber, Chris Wentland +1
We propose a novel hybrid domain decomposition method that couples sub-domain-local high-fidelity finite element (FE) models with reduced order models (ROMs) using the Schwarz alte…
Transmission Conditions for the Non-Overlapping Schwarz Coupling of Full Order and Operator Inference Models
Cameron Rodriguez, Irina Tezaur, Alejandro Mota +3
This work investigates transmission conditions for the domain decomposition-based coupling of subdomain-local models using the non-overlapping Schwarz alternating method (NO-SAM).…