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Transmission Conditions for the Non-Overlapping Schwarz Coupling of Full Order and Operator Inference Models

Published: September 6, 2025 | arXiv ID: 2509.12228v1

By: Cameron Rodriguez , Irina Tezaur , Alejandro Mota and more

Potential Business Impact:

Splits big problems into smaller, faster parts.

Business Areas:
Telecommunications Hardware

This work investigates transmission conditions for the domain decomposition-based coupling of subdomain-local models using the non-overlapping Schwarz alternating method (NO-SAM). Building on prior efforts involving overlapping SAM (O-SAM), we formulate and assess two NO-SAM variants, based on alternating Dirichlet-Neumann and Robin-Robin transmission conditions. For the subdomain-local models, we consider a mix of full order models (FOMs) and non-intrusive reduced order models (ROMs) constructed via an emerging model reduction technique known as operator inference (OpInf). Of particular novelty is the first application of NO-SAM to couple non-intrusive OpInf ROMs with each other, and with FOMs. Numerical studies on a one-dimensional linear elastic wave propagation benchmark problem demonstrate that transmission condition choice and parameter tuning significantly impact convergence rate, accuracy, and stability. Robin-Robin coupling often yields faster convergence than alternating Dirichlet-Neumann, though improper parameter selection can induce spurious oscillations at subdomain interfaces. For FOM-OpInf and OpInf-OpInf couplings, sufficient modal content in the ROM basis improves accuracy and mitigates instability, in some cases outperforming the coupled FOM-FOM reference solutions in both accuracy and efficiency. These findings highlight NO-SAM's potential for enabling flexible, non-intrusive, and efficient multi-model coupling across independently meshed subdomains, while emphasizing the need for careful interface condition design in higher-dimensional and predictive settings.

Country of Origin
🇺🇸 United States

Page Count
19 pages

Category
Mathematics:
Numerical Analysis (Math)