Author

G. Rozza

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Preprint Sep 2026

A Comparative Study of Finite-Volume-based Coupled and Segregated Reduced-Order Models for Incompressible Flows in Parametrized Domains

This work presents a comparative analysis of Reduced-Order Models (ROMs) applied to incompressible fluid dynamics within geometrically parametrized domains. Two distinct reduced-order solution strategies are investigated and compared: a monolithic coupled solver and a segregated SIMPLE-based algorithm. Their performanc...

Andrea Buffolini, Davide Oberto, G. Rozza · 0 citations

Preprint Sep 2026

Active Subspace-Guided Free-Form Deformation with Sinkhorn Autoencoders for Reduced-Order Modelling of Parametrised Shape Problems

Geometrically parametrised PDEs arise in shape optimisation, where solving a PDE over many deformed domains at manageable cost is a central challenge. Free-form Deformation (FFD) parametrises shape variations through a lattice of control points, but the resulting parameter space is typically high-dimensional, with most...

G. Padula, C. Giovannini, G. Rozza et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Cluster Attention Neural Operators for Solving Parametric Partial Differential Equations

Traditional simulations of parametric partial differential equations (PDEs) rely on repetitive computations for each parameter, which makes high-fidelity design impractical. Neural operators address this issue by learning solution operators, accelerating parameter-space mapping by orders of magnitude. Recent Transforme...

Ming Zhong, A. Colanera, G. Rozza et al. · 0 citations

Review Open access Jul 2026

Applicable methodologies for modelling of heat and mass transfer phenomena in tumble dryers: A review

Tumble dryers are convenient but energy-intensive, and their performance depends on coupled heat and mass transfer within the drum and air circuit. This review evaluates mathematical modeling approaches for these processes, spanning 0-D lumped-parameter models, 1-D heat and moisture transfer models, and kinematic and i...

Sajad Salavati, A. Hajisharifi, M. Girfoglio et al. · Thermal Science and Engineer... · 0 citations

Jul 2026

A Dynamical Approximation Scheme on the Stiefel manifold for Wasserstein Gradient Flows

We propose a meshless Lagrangian dynamical method for approximating Wasserstein gradient flows (WGFs). The evolving measure is represented as the pushforward of the initial measure $\mu_0$ through a transport map in the weighted Hilbert space $L^2_{\mu_0}$. We approximate this map in time-dependent linear subspaces of...

Isabella Carla Gonnella, O. Mula, F. Pichi et al. · arXiv.org · 0 citations

Preprint Jul 2026

Convolutional Symmetric AutoEncoders: enhancing latent stability via differential geometry

This work introduces a novel class of symmetric Convolutional AutoEncoders (CAEs) designed to embody the primary properties of manifold parametrization mappings and demonstrates significantly improved predictive capabilities when integrated into a ROM framework.

Gaspare LI Causi, Niccolò Tonicello, Luca Magri et al. · 0 citations