activity
20182026
most citedHull shape design optimization with parameter space and model reductions, and self-learning mesh morphing

48 citations · 67 across the 35 of their papers we have counts for

collaborators
Showing 2020Show all

7 papers · 1 filter

math.NA2020

Multi-fidelity data fusion for the approximation of scalar functions with low intrinsic dimensionality through active subspaces

Francesco Romor, Marco Tezzele, Gianluigi Rozza

Gaussian processes are employed for non-parametric regression in a Bayesian setting. They generalize linear regression, embedding the inputs in a latent manifold inside an infinite…

physics.flu-dyn2020

Reduced order models for the incompressible Navier-Stokes equations on collocated grids using a 'discretize-then-project' approach

Sabrina Kelbij Star, Benjamin Sanderse, Giovanni Stabile +2

A novel reduced order model (ROM) for incompressible flows is developed by performing a Galerkin projection based on a fully (space and time) discrete full order model (FOM) formul…

math.NA2020

A POD-Galerkin reduced order model for a LES filtering approach

Michele Girfoglio, Annalisa Quaini, Gianluigi Rozza

We propose a Proper Orthogonal Decomposition (POD)-Galerkin based Reduced Order Model (ROM) for a Leray model. For the implementation of the model, we combine a two-step algorithm…

math.NA2020

On the comparison of LES data-driven reduced order approaches for hydroacoustic analysis

Mahmoud Gadalla, Marta Cianferra, Marco Tezzele +3

In this work, Dynamic Mode Decomposition (DMD) and Proper Orthogonal Decomposition (POD) methodologies are applied to hydroacoustic dataset computed using Large Eddy Simulation (LE…

math.NA2020

MicroROM: An Efficient and Accurate Reduced Order Method to Solve Many-Query Problems in Micro-Motility

Nicola Giuliani, Martin W. Hess, Antonio DeSimone +1

In the study of micro-swimmers, both artificial and biological ones, many-query problems arise naturally. Even with the use of advanced high performance computing (HPC), it is not…

physics.flu-dyn2020

A POD-Galerkin reduced order model of a turbulent convective buoyant flow of sodium over a backward-facing step

Kelbij Star, Giovanni Stabile, Gianluigi Rozza +1

A Finite-Volume based POD-Galerkin reduced order modeling strategy for steady-state Reynolds averaged Navier--Stokes (RANS) simulation is extended for low-Prandtl number flow. The…