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R. Ausas

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Preprint Aug 2026

A Data-Driven Computational Framework for Incompressible Flow in Hydraulic Networks

The classical procedure for solving hydraulic networks relies on the assumption of constitutive equations, which state the relationship between the pressure gradient and fluxes along an edge. In this paper, we propose a data-driven framework that bypasses these constitutive models, formulating the incompressible flow p...

Pedro B. Bazon, Cristian G. Gebhardt, R. Ausas · 0 citations
Jul 2026

AlgMortar: a fully algebraic multiscale mortar preconditioner

Numerical experiments on fine-grid linear systems arising from finite-volume discretizations of Darcy flow problems show that the proposed AlgMortar approach exhibits good scalability and is competitive with state-of-the-art algebraic multigrid methods for challenging heterogeneous, high-contrast test cases, including...

Luan F. Santos, F. S. Sousa, R. Ausas et al. · 0 citations

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