25 citations · 28 across the 3 of their papers we have counts for
4 papers
A Comparative Study of Finite-Volume-based Coupled and Segregated Reduced-Order Models for Incompressible Flows in Parametrized Domains
Andrea Buffolini, Davide Oberto, Gianluigi Rozza
This work presents a comparative analysis of Reduced-Order Models (ROMs) applied to incompressible fluid dynamics within geometrically parametrized domains. Two distinct reduced-or…
Machine Learning enhanced parametric Reynolds-averaged Navier-Stokes equations at the full- and reduced-order levels
Davide Oberto, Maria Strazzullo, Stefano Berrone
In this contribution, we focus on the Reynolds-averaged Navier-Stokes (RANS) models and their exploitation to build reliable reduced-order models to further accelerate predictions…
The lowest-order Neural Approximated Virtual Element Method
Stefano Berrone, Davide Oberto, Moreno Pintore +1
We introduce the Neural Approximated Virtual Element Method, a novel polygonal method that relies on neural networks to eliminate the need for projection and stabilization operator…
A data-driven approach for the closure of RANS models by the divergence of the Reynolds Stress Tensor
Stefano Berrone, Davide Oberto
In the present paper a new data-driven model is proposed to close and increase accuracy of RANS equations. The divergence of the Reynolds Stress Tensor (RST) is obtained through a…