activity
20172024
most citedA reduced order variational multiscale approach for turbulent flows

89 citations · 880 across the 47 of their papers we have counts for

collaborators

47 papers

math.NA2024

Projection-based Reduced Order Modelling for Unsteady Parametrized Optimal Control Problems in 3D Cardiovascular Flows

Surabhi Rathore, Pasquale Claudio Africa, Francesco Ballarin +3

This paper presents a projection-based reduced order modelling (ROM) framework for unsteady parametrized optimal control problems (OCPs) arising from cardiovascular (CV) ap…

math.NA2023★ 5 cited

Approximate Deconvolution Leray Reduced Order Model for Convection-Dominated Flows

Anna Sanfilippo, Ian Moore, Francesco Ballarin +1

In this paper, we propose a novel ROM stabilization strategy for under-resolved convection-dominated flows, the approximate deconvolution Leray ROM (ADL-ROM). The new ADL-ROM intro…

physics.flu-dyn2023

Mathematical modelling and computational reduction of molten glass fluid flow in a furnace melting basin

Francesco Ballarin, Enrique Delgado Ávila, Andrea Mola +1

In this work, we present the modelling and numerical simulation of a molten glass fluid flow in a furnace melting basin. We first derive a model for a molten glass fluid flow and p…

math.NA2023★ 2 cited

New Feedback Control and Adaptive Evolve-Filter-Relax Regularization for the Navier-Stokes Equations in the Convection-Dominated Regime

Maria Strazzullo, Francesco Ballarin, Traian Iliescu +1

We propose, analyze, and investigate numerically a novel feedback control strategy for high Reynolds number flows. For both the continuous and the discrete (finite element) setting…

cond-mat.soft2023★ 2 cited

A finite element implementation of finite deformation surface and bulk poroelasticity

Jaemin Kim, Ida Ang, Francesco Ballarin +2

We present a theoretical and computational model for the behavior of a porous solid undergoing two interdependent processes, the finite deformation of a solid and species migration…

math.NA2023★ 5 cited

Model Order Reduction for Deforming Domain Problems in a Time-Continuous Space-Time Setting

Fabian Key, Max von Danwitz, Francesco Ballarin +1

In the context of simulation-based methods, multiple challenges arise, two of which are considered in this work. As a first challenge, problems including time-dependent phenomena w…

math.NA2023★ 1 cited

Weighted reduced order methods for uncertainty quantification in computational fluid dynamics

Julien Genovese, Francesco Ballarin, Gianluigi Rozza +1

In this manuscript we propose and analyze weighted reduced order methods for stochastic Stokes and Navier-Stokes problems depending on random input data (such as forcing terms, phy…

math.NA2023

Reduced Basis, Embedded Methods and Parametrized Levelset Geometry

Efthymios N. Karatzas, Giovanni Stabile, Francesco Ballarin +1

In this chapter we examine reduced order techniques for geometrical parametrized heat exchange systems, Poisson, and flows based on Stokes, steady and unsteady incompressible Navie…

math.NA2022★ 17 cited

An optimisation-based domain-decomposition reduced order model for the incompressible Navier-Stokes equations

Ivan Prusak, Monica Nonino, Davide Torlo +2

The aim of this work is to present a model reduction technique in the framework of optimal control problems for partial differential equations. We combine two approaches used for r…

math.AP2022★ 3 cited

Elastic membranes spanning deformable boundaries

Francesco Ballarin, Giulia Bevilacqua, Luca Lussardi +1

We perform a variational analysis of an elastic membrane spanning a closed curve which may sustain bending and torsion. First, we deal with parametrized curves and linear elastic m…

physics.flu-dyn2022★ 1 cited

Isogeometric Hierarchical Model Reduction for advection-diffusion process simulation in microchannels

Simona Perotto, Gloria Bellini, Francesco Ballarin +3

Microfluidics proved to be a key technology in various applications, allowing to reproduce large-scale laboratory settings at a more sustainable small-scale. The current effort is…

cs.CE2022★ 22 cited

Reduced order modeling for flow and transport problems with Barlow Twins self-supervised learning

Teeratorn Kadeethum, Francesco Ballarin, Daniel O'Malley +3

We propose a unified data-driven reduced order model (ROM) that bridges the performance gap between linear and nonlinear manifold approaches. Deep learning ROM (DL-ROM) using deep-…

physics.med-ph2022★ 31 cited

Data-driven reduced order modelling for patient-specific hemodynamics of coronary artery bypass grafts with physical and geometrical parameters

Pierfrancesco Siena, Michele Girfoglio, Francesco Ballarin +1

In this work the development of a machine learning-based Reduced Order Model (ROM) for the investigation of hemodynamics in a patient-specific configuration of Coronary Artery Bypa…

math.NA2022★ 15 cited

Projection based semi--implicit partitioned Reduced Basis Method for non parametrized and parametrized Fluid--Structure Interaction problems

Monica Nonino, Francesco Ballarin, Gianluigi Rozza +1

We present a partitioned Model Order Reduction method for multiphysics problems, that is based on a semi-implicit treatment of the coupling conditions, and on a projection scheme.…

math.NA2021★ 23 cited

Finite element based model order reduction for parametrized one-way coupled steady state linear thermomechanical problems

Nirav Vasant Shah, Michele Girfoglio, Peregrina Quintela +4

This contribution focuses on the development of Model Order Reduction (MOR) for one-way coupled steady state linear thermomechanical problems in a finite element setting. We apply…

physics.flu-dyn2021★ 1 cited

Consistency of the Full and Reduced Order Models for Evolve-Filter-Relax Regularization of Convection-Dominated, Marginally-Resolved Flows

Maria Strazzullo, Michele Girfoglio, Francesco Ballarin +2

Numerical stabilization is often used to eliminate (alleviate) the spurious oscillations generally produced by full order models (FOMs) in under-resolved or marginally-resolved sim…

physics.flu-dyn2021★ 83 cited

An artificial neural network approach to bifurcating phenomena in computational fluid dynamics

Federico Pichi, Francesco Ballarin, Gianluigi Rozza +1

This work deals with the investigation of bifurcating fluid phenomena using a reduced order modelling setting aided by artificial neural networks. We discuss the POD-NN approach de…

math.NA2021★ 27 cited

An optimal control approach to determine resistance-type boundary conditions from in-vivo data for cardiovascular simulations

Elisa Fevola, Francesco Ballarin, Laura Jiménez-Juan +4

The choice of appropriate boundary conditions is a fundamental step in computational fluid dynamics (CFD) simulations of the cardiovascular system. Boundary conditions, in fact, hi…

math.NA2021★ 31 cited

A monolithic and a partitioned Reduced Basis Method for Fluid-Structure Interaction problems

Monica Nonino, Francesco Ballarin, Gianluigi Rozza

The aim of this work is to present an overview about the combination of the Reduced Basis Method (RBM) with two different approaches for Fluid-Structure Interaction (FSI) problems,…

math.NA2021★ 2 cited

A Certified Reduced Basis Method for Linear Parametrized Parabolic Optimal Control Problems in Space-Time Formulation

Maria Strazzullo, Francesco Ballarin, Gianluigi Rozza

In this work, we propose to efficiently solve time dependent parametrized optimal control problems governed by parabolic partial differential equations through the certified reduce…

math.NA2021★ 5 cited

A Reduced basis stabilization for the unsteady Stokes and Navier-Stokes equations

Shafqat Ali, Francesco Ballarin, Gianluigi Rozza

In the Reduced Basis approximation of Stokes and Navier-Stokes problems, the Galerkin projection on the reduced spaces does not necessarily preserved the inf-sup stability even if…

math.NA2021★ 3 cited

A weighted POD-reduction approach for parametrized PDE-constrained Optimal Control Problems with random inputs and applications to environmental sciences

Giuseppe Carere, Maria Strazzullo, Francesco Ballarin +2

Reduced basis approximations of Optimal Control Problems (OCPs) governed by steady partial differential equations (PDEs) with random parametric inputs are analyzed and constructed.…

math.NA2021★ 19 cited

Non-intrusive reduced order modeling of poroelasticity of heterogeneous media based on a discontinuous Galerkin approximation

T. Kadeethum, F. Ballarin, N. Bouklas

We present a non-intrusive model reduction framework for linear poroelasticity problems in heterogeneous porous media using proper orthogonal decomposition (POD) and neural network…

math.NA2020★ 7 cited

Space-time POD-Galerkin approach for parametric flow control

Francesco Ballarin, Gianluigi Rozza, Maria Strazzullo

In this contribution we propose reduced order methods to fast and reliably solve parametrized optimal control problems governed by time dependent nonlinear partial differential equ…