59 citations · 149 across the 23 of their papers we have counts for
24 papers
A Volume of Fluid Immersed Boundary Method for Industrial Polymer Mixing
Emilia Capuano, Daniele Cerroni, Holger Marschall +3
This work develops advanced numerical methods for free-surface simulations of polymer mixing processes, integrating a Volume of Fluid (VOF) interface-capturing approach with a non-…
Learning cardiac activation and repolarization times with operator learning
Edoardo Centofanti, Giovanni Ziarelli, Nicola Parolini +3
Solving partial or ordinary differential equation models in cardiac electrophysiology is a computationally demanding task, particularly when high-resolution meshes are required to…
SEIHRDV: a multi-age multi-group epidemiological model and its validation on the COVID-19 epidemics in Italy
Luca Dede', Nicola Parolini, Alfio Quarteroni +2
We propose a novel epidemiological model, referred to as SEIHRDV, for the numerical simulation of the COVID-19 epidemic, which we validate using data from Italy starting in Septemb…
A model learning framework for inferring the dynamics of transmission rate depending on exogenous variables for epidemic forecasts
Giovanni Ziarelli, Stefano Pagani, Nicola Parolini +2
In this work, we aim to formalize a novel scientific machine learning framework to reconstruct the hidden dynamics of the transmission rate, whose inaccurate extrapolation can sign…
A posteriori error analysis for a coupled Stokes-poroelastic system with multiple compartments
Ivan Fumagalli, Nicola Parolini, Marco Verani
The discretization of fluid-poromechanics systems is typically highly demanding in terms of computational effort. This is particularly true for models of multiphysics flows in the…
Learning epidemic trajectories through Kernel Operator Learning: from modelling to optimal control
Giovanni Ziarelli, Nicola Parolini, Marco Verani
Since infectious pathogens start spreading into a susceptible population, mathematical models can provide policy makers with reliable forecasts and scenario analyses, which can be…
Structure-preserving neural networks in data-driven rheological models
Nicola Parolini, Andrea Poiatti, Julian Vene' +1
In this paper we address the importance and the impact of employing structure preserving neural networks as surrogate of the analytical physics-based models typically employed to d…
Polytopal discontinuous Galerkin discretization of brain multiphysics flow dynamics
Ivan Fumagalli, Mattia Corti, Nicola Parolini +1
A comprehensive mathematical model of the multiphysics flow of blood and Cerebrospinal Fluid (CSF) in the brain can be expressed as the coupling of a poromechanics system and Stoke…
Level set-fitted polytopal meshes with application to structural topology optimization
Nicola Ferro, Stefano Micheletti, Nicola Parolini +3
We propose a method to modify a polygonal mesh in order to fit the zero-isoline of a level set function by extending a standard body-fitted strategy to a tessellation with arbitrar…
The Rhie-Chow stabilized Box Method for the Stokes problem
G. Negrini, N. Parolini, M. Verani
The Finite Volume method (FVM) is widely adopted in many different applications because of its built-in conservation properties, its ability to deal with arbitrary mesh and its com…
AeroSPEED: a high order acoustic solver for aeroacoustic applications
Alberto Artoni, Paola F. Antonietti, Roberto Corradi +5
We propose AeroSPEED, a solver based on the Spectral Element Method (SEM) that solves the aeroacoustic Lighthill's wave equation. First, the fluid solution is computed employing a…
A hybrid finite volume -- spectral element method for aeroacoustic problems
Alberto Artoni, Paola F. Antonietti, Ilario Mazzieri +2
We propose a hybrid Finite Volume (FV) - Spectral Element Method (SEM) for modelling aeroacoustic phenomena based on the Lighthill's acoustic analogy. First the fluid solution is c…
Optimized numerical solutions of SIRDVW multiage model controlling SARS-CoV-2 vaccine roll out: an application to the Italian scenario
Giovanni Ziarelli, Luca Dede', Nicola Parolini +2
In the context of SARS-CoV-2 pandemic, mathematical modelling has played a fundamental role for making forecasts, simulating scenarios and evaluating the impact of preventive polit…
Non-isothermal non-Newtonian fluids: the stationary case
Maurizio Grasselli, Nicola Parolini, Andrea Poiatti +1
The stationary Navier-Stokes equations for a non-Newtonian incompressible fluid are coupled with the stationary heat equation and subject to Dirichlet type boundary conditions. The…
Modelling the COVID-19 epidemic and the vaccination campaign in Italy by the SUIHTER model
Nicola Parolini, Luca Dede', Giovanni Ardenghi +1
Several epidemiological models have been proposed to study the evolution of COVID-19 pandemic. In this paper, we propose an extension of the SUIHTER model, first introduced in [Par…
An efficient and accurate implicit DG solver for the incompressible Navier-Stokes equations
Giuseppe Orlando, Alessandro Della Rocca, Paolo Francesco Barbante +2
We propose an efficient, accurate and robust implicit solver for the incompressible Navier-Stokes equations, based on a DG spatial discretization and on the TR-BDF2 method for time…
Simulation of viscoelastic Cosserat rods based on the geometrically exact dynamics of special Euclidean strands
G. G. Giusteri, E. Miglio, N. Parolini +2
We propose a method for the description and simulation of the nonlinear dynamics of slender structures modeled as Cosserat rods. It is based on interpreting the strains and the gen…
A diffuse interface box method for elliptic problems
G. Negrini, N. Parolini, M. Verani
We introduce a diffuse interface box method (DIBM) for the numerical approximation on complex geometries of elliptic problems with Dirichlet boundary conditions. We derive a priori…
SUIHTER: A new mathematical model for COVID-19. Application to the analysis of the second epidemic outbreak in Italy
Nicola Parolini, Luca Dede', Paola F. Antonietti +6
The COVID-19 epidemic is the last of a long list of pandemics that have affected humankind in the last century. In this paper, we propose a novel mathematical epidemiological model…
A Mathematical Dashboard for the Analysis of Italian COVID-19 Epidemic Data
Nicola Parolini, Giovanni Ardenghi, Luca Dede' +1
An analysis of the COVID-19 epidemic is proposed on the basis of the epiMOX dashboard (publicly accessible at https://www.epimox.polimi.it) that deals with data of the epidemic tre…
Optimal control in ink-jet printing via instantaneous control
Ivan Fumagalli, Nicola Parolini, Marco Verani
This paper concerns the optimal control of a free surface flow with moving contact line, inspired by an application in ink-jet printing. Surface tension, contact angle and wall fri…
Topology optimization of multiple anisotropic materials, with application to self-assembling diblock copolymers
Francesco Regazzoni, Nicola Parolini, Marco Verani
We propose a solution strategy for a multimaterial minimum compliance topology optimization problem, which consists in finding the optimal allocation of a finite number of candidat…
Shape optimization for Stokes flow: a reference domain approach
Ivan Fumagalli, Nicola Parolini, Marco Verani
In this paper we analyze a shape optimization problem, with Stokes equations as the state problem, defined on a domain with a part of the boundary that is described as the graph of…
Multiphysics simulation of corona discharge induced ionic wind
Davide Cagnoni, Francesco Agostini, Thomas Christen +3
Ionic wind devices or electrostatic fluid accelerators are becoming of increasing interest as tools for thermal management, in particular for semiconductor devices. In this work, w…