7 citations · 11 across the 3 of their papers we have counts for
4 papers
A segregated reduced order model of a pressure-based solver for turbulent compressible flows
Matteo Zancanaro, Valentin Nkana Ngan, Giovanni Stabile +1
This article provides a reduced-order modelling framework for turbulent compressible flows discretized by the use of finite volume approaches. The basic idea behind this work is th…
Hybrid neural network reduced order modelling for turbulent flows with geometric parameters
Matteo Zancanaro, Markus Mrosek, Giovanni Stabile +2
Geometrically parametrized Partial Differential Equations are nowadays widely used in many different fields as, for example, shape optimization processes or patient specific surger…
Hierarchical Model Reduction Techniques for Flow Modeling in a Parametrized Setting
Matteo Zancanaro, Francesco Ballarin, Simona Perotto +1
In this work we focus on two different methods to deal with parametrized partial differential equations in an efficient and accurate way. Starting from high fidelity approximations…
Efficient Geometrical parametrization for Finite-Volume based Reduced Order Methods
Giovanni Stabile, Matteo Zancanaro, Gianluigi Rozza
In this work, we present an approach for the efficient treatment of parametrized geometries in the context of POD-Galerkin reduced order methods based on Finite Volume full order a…