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Simone Deparis

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Publications associées (52)

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A numerical investigation of multi space reduced basis preconditioners for parametrized elliptic advection-diffusion equations

Simone Deparis, Andrea Manzoni, Niccolò Dal Santo

We analyze the numerical performance of a preconditioning technique recently proposed in [1] for the efficient solution of parametrized linear systems arising from the finite element (FE) discretization of parameter-dependent elliptic partial differential ...

Walter de Gruyter GmbH2017

Implicit coupling of one-dimensional and three-dimensional blood flow models with compliant vessels

Alfio Quarteroni, Simone Deparis, Adelmo Cristiano Innocenza Malossi, Paolo Crosetto

Simulating arterial trees in the cardiovascular system can be made by the help of different models, depending on the outputs of interest and the desired degree of accuracy. In particular, one-dimensional fluid-structure interaction models for arteries are ...

Society for Industrial and Applied Mathematics2013

PDE-Aware Deep Learning for Inverse Problems in Cardiac Electrophysiology

Alfio Quarteroni, Simone Deparis, Stefano Pagani, Riccardo Tenderini

In this work, we present a PDE-aware deep learning model for the numerical solution to the inverse problem of electrocardiography. The model both leverages data availability and exploits the knowledge of a physically based mathematical model, expressed by ...

2022

Parameter estimates for the Relaxed Dimensional Factorization preconditioner and application to hemodynamics

Alfio Quarteroni, Simone Deparis, Gwenol Grandperrin

We present new results on the Relaxed Dimensional Factorization (RDF) preconditioner for solving saddle point problems from incompressible flow simulations, first introduced in Benzi et al. (2011). This method contains a parameter α>0α>0, to be chosen by t ...

Elsevier2016

Reduced basis method for multi-parameter dependent steady Navier-Stokes equations: applications to natural convection in a cavity

Gianluigi Rozza, Simone Deparis

This work focuses on the approximation of parametric steady Navier-- Stokes equations by the reduced basis method. For a particular instance of the parameters under consideration, we are able to solve the underlying partial differential equations, compute ...

2009

Parallel subdomain solver strategies for the algebraic additive Schwarz preconditioner

Simone Deparis, Radu Popescu

Domain-decomposition (DD) methods are used in most, if not all, modern parallel implementations of finite element modeling software. In the solver stage, the algebraic additive Schwarz (AAS) domain-decomposition preconditioner represents a fundamental comp ...

Elsevier Science Bv2016

Analysis of morphological and haemodynamical indexes in abdominal aortic aneurysms as preliminary indicators of intraluminal thrombus deposition

Alfio Quarteroni, Simone Deparis, Claudia Maria Colciago

In this paper we study the correlation between the Wall Shear Stress (WSS), a haemodynamical index derived from numerical simulations, and an new index MFA-ILT for the characterisation of intraluminal thrombus (ILT) in presence of abdominal aortic aneurysm ...

2020

Multiphysics Computational Modeling in C-Heart

Simone Deparis

From basic science to translation, modern biomedical research demands computational models which integrate several interacting physical systems. This paper describes the infrastructural framework for generic multiphysics integration implemented in the soft ...

Siam Publications2016

Multi space reduced basis preconditioners for large-scale parametrized PDEs

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

In this work we introduce a new two-level preconditioner for the efficient solution of large-scale linear systems arising from the discretization of parametrized PDEs. The proposed preconditioner combines in a multiplicative way a reduced basis solver, whi ...

2018

Reduced Basis Methods and A Posteriori Error Estimators for Heat Transfer Problems

Gianluigi Rozza, Simone Deparis

This paper focuses on the parametric study of steady and unsteady forced and natural convection problems by the certified reduced basis method. These problems are characterized by an input-output relationship in which given an input parameter vector — mate ...

ASME2009

A parallel algorithm for the solution of large-scale nonconforming fluid-structure interaction problems in hemodynamics

Alfio Quarteroni, Simone Deparis, Davide Forti

In this work we address the numerical solution of large scale fluid-structure interaction problems when nonconforming grids and⁄or nonconforming finite elements discretizations are used at the interface separating the fluid and structure physical domains. ...

Global Science Press2017

Conservation of Forces and Total Work at the Interface Using the Internodes Method

Simone Deparis

The Internodes method is a general purpose method to deal with non-conforming discretizations of partial differential equations on 2D and 3D regions partitioned into disjoint subdomains. In this paper we are interested in measuring how much the Internodes ...

2022

DeepBND: A machine learning approach to enhance multiscale solid mechanics

Annalisa Buffa, Simone Deparis, Pablo Antolin Sanchez, Felipe Figueredo Rocha

Effective properties of materials with random heterogeneous structures are typically determined by homogenising the mechanical quantity of interest in a window of observation. The entire problem setting encompasses the solution of a local PDE and some aver ...

2023

Parallel preconditioners for the unsteady Navier-Stokes equations and applications to hemodynamics simulations

Alfio Quarteroni, Simone Deparis, Gwenol Grandperrin

We are interested in the numerical solution of the unsteady Navier-Stokes equations on large scale parallel architectures. We consider efficient preconditioners, such as the Pressure Convection-Diffusion (PCD), the Yosida preconditioner, the SIMPLE precond ...

Elsevier2014

Coupling non-conforming discretizations of PDEs by spectral approximation of the Lagrange multiplier space

Simone Deparis, Luca Pegolotti

This work focuses on the development of a non-conforming method for the coupling of PDEs based on weakly imposed transmission conditions: the continuity of the global solution is enforced by a finite number of Lagrange multipliers defined over the interfac ...

2019

Fluid Structure Interaction Simulations of Physiological Blood Flow in the Aorta

Dimitrios Kontaxakis, Alfio Quarteroni, Nikolaos Stergiopoulos, Simone Deparis, Philippe Reymond, Paolo Crosetto

The numerical tools to simulate blood flow in the cardiovascular system are constantly developing due to the great clinical interest and to scientific advances in mathematical models and computational power. The present work aims to address and validate ne ...

Elsevier2011

Physiological simulation of blood flow in the aorta: comparison of hemodynamic indices as predicted by 3-D FSI, 3-D rigid wall and 1-D models

Alfio Quarteroni, Nikolaos Stergiopoulos, Simone Deparis, Philippe Reymond, Paolo Crosetto

Interest in patient-specific blood-flow circulation modeling has increased substantially in recent years. The availability of clinical data for geometric and elastic properties together with efficient numerical methods has now made model rendering feasible ...

Elsevier2013

Can Knowledge Transfer Techniques Compensate for the Limited Myocardial Infarction Data by Leveraging Haemodynamics? An in silico Study

Annalisa Buffa, Simone Deparis, Emmanuel Abbé, Ortal Yona Senouf, Riccardo Tenderini

The goal of this work is to investigate the ability of transfer learning (TL) and multitask learning (MTL) algorithms to predict tasks related to myocardial infarction (MI) in a small-data regime, leveraging a larger dataset of haemodynamic targets. The da ...

Springer Nature2023

A spline-based hexahedral mesh generator for patient-specific coronary arteries

Annalisa Buffa, Simone Deparis, Jochen Peter Hinz, Fabio Marcinno

This paper presents a spline-based hexahedral mesh generator for tubular geometries commonly encountered in hæmodynamics studies, in particular coronary arteries. We focus on techniques for accurately meshing vessels with stenoses and aneurysms, as well as ...

2025

Data driven approximation of parametrized PDEs by reduced basis and neural networks

Simone Deparis, Luca Pegolotti, Niccolò Dal Santo

ACADEMIC PRESS INC ELSEVIER SCIENCE2020