Publications by Andrea Manzoni

A Reduced Order Model for Domain Decompositions with Non-conforming Interfaces

In this paper, we propose a reduced-order modeling strategy for two-way Dirichlet-Neumann parametric coupled problems solved with domain-decomposition (DD) sub-structuring methods. We split the original coupled differential problem into two sub-problems wi ...

Springer/Plenum Publishers2024

Efficient approximation of cardiac mechanics through reduced-order modeling with deep learning-based operator approximation

Alfio Quarteroni, Andrea Manzoni

Reducing the computational time required by high-fidelity, full-order models (FOMs) for the solution of problems in cardiac mechanics is crucial to allow the translation of patient-specific simulations into clinical practice. Indeed, while FOMs, such as th ...

Wiley2023

POD-Enhanced Deep Learning-Based Reduced Order Models for the Real-Time Simulation of Cardiac Electrophysiology in the Left Atrium

Alfio Quarteroni, Andrea Manzoni

The numerical simulation of multiple scenarios easily becomes computationally prohibitive for cardiac electrophysiology (EP) problems if relying on usual high-fidelity, full order models (FOMs). Likewise, the use of traditional reduced order models (ROMs) ...

FRONTIERS MEDIA SA2021

Data integration for the numerical simulation of cardiac electrophysiology

Alfio Quarteroni, Andrea Manzoni, Luca Dede', Stefano Pagani

The increasing availability of extensive and accurate clinical data is rapidly shaping cardiovascular care by improving the understanding of physiological and pathological mechanisms of the cardiovascular system and opening new frontiers in designing thera ...

WILEY2021

A Computational Study of the Electrophysiological Substrate in Patients Suffering From Atrial Fibrillation

Alfio Quarteroni, Andrea Manzoni

In the context of cardiac electrophysiology, we propose a novel computational approach to highlight and explain the long-debated mechanisms behind atrial fibrillation (AF) and to reliably numerically predict its induction and sustainment. A key role is pla ...

FRONTIERS MEDIA SA2021

Outer loop and isthmus in ventricular tachycardia circuits: Characteristics and implications

Alfio Quarteroni, Andrea Manzoni, Luca Dede', Stefano Pagani

BACKGROUND The isthmus of ventricular tachycardia (VT) circuits has been extensively characterized. Few data exist regarding the contribution of the outer loop (OL) to the VT circuit. OBJECTIVE The purpose of this study was to characterize the electrophysi ...

2020

Deep learning-based reduced order models in cardiac electrophysiology

Alfio Quarteroni, Andrea Manzoni, Luca Dede'

Predicting the electrical behavior of the heart, from the cellular scale to the tissue level, relies on the numerical approximation of coupled nonlinear dynamical systems. These systems describe the cardiac action potential, that is the polarization/depola ...

2020

Multi space reduced basis preconditioners for parametrized Stokes equations

Alfio Quarteroni, Simone Deparis, Andrea Manzoni, Niccolò Dal Santo

We introduce a two-level preconditioner for the efficient solution of large scale saddle point linear systems arising from the finite element (FE) discretization of parametrized Stokes equations. This preconditioner extends the Multi Space Reduced Basis (M ...

PERGAMON-ELSEVIER SCIENCE LTD2019

A saddle point approach to an optimal boundary control problem for steady Navier-Stokes equations

Alfio Quarteroni, Andrea Manzoni

In this paper we propose a saddle point approach to solve boundary control problems for the steady Navier-Stokes equations with mixed Dirichlet-Neumann boundary conditions, both in two and three dimensions. We provide a comprehensive theoretical framework ...

2019

An algebraic least squares reduced basis method for the solution of nonaffinely parametrized Stokes equations

Alfio Quarteroni, Simone Deparis, Andrea Manzoni, Niccolò Dal Santo

In this paper we propose a new, purely algebraic, Petrov-Galerkin reduced basis (RB) method to solve the parametrized Stokes equations, where parameters serve to identify the (variable) domain geometry. Our method is obtained as an algebraic least squares ...

ELSEVIER SCIENCE SA2019