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math.NA2026
A Nonlinear Physics-based Reduced Order Model with Convolutional-based Operator Compression
Anna Ivagnes, Giovanni Stabile, Gianluigi Rozza
Reduced-order models (ROMs) are widely used to accelerate the solution of parametrized partial differential equations, with projection-based methods relying on a linear representat…
math.NA2026
An efficient hyper reduced-order model for segregated solvers for geometrical parametrization problems
Valentin Nkana Ngan, Giovanni Stabile, Andrea Mola +1
We propose an efficient hyper-reduced order model (HROM) designed for segregated finite-volume solvers in geometrically parametrized problems. The method follows a discretize-then-…