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math.NA2025
Combining physics-based and data-driven models: advancing the frontiers of research with Scientific Machine Learning
Alfio Quarteroni, Paola Gervasio, Francesco Regazzoni
Scientific Machine Learning (SciML) is a recently emerged research field which combines physics-based and data-driven models for the numerical approximation of differential problem…
math.NA2024
A reduced order model for domain decompositions with non-conforming interfaces
Elena Zappon, Andrea Manzoni, Paola Gervasio +1
In this paper, we propose a reduced-order modeling strategy for two-way Dirichlet-Neumann parametric coupled problems solved with domain-decomposition (DD) sub-structuring methods.…
math.NA2024
A coupling concept for Stokes-Darcy systems: the ICDD method
Marco Discacciati, Paola Gervasio
We present a coupling framework for Stokes-Darcy systems valid for arbitrary flow direction at low Reynolds numbers and for isotropic porous media. The proposed method is based on…