activity
20132023
most citedPartitioning strategies for the interaction of a fluid with a poroelastic material based on a Nitsche's coupling approach

105 citations · 168 across the 10 of their papers we have counts for

collaborators

12 papers

math.NA2023

Robust Preconditioning of mixed-dimensional PDEs on 3d-1d domains coupled with Lagrange multipliers

Nunzio Dimola, Miroslav Kuchta, Kent-Andre Mardal +1

In the context of micro-circulation, the coexistence of two distinct length scales - the vascular radius and the tissue/organ scale - with a substantial difference in magnitude, po…

math.NA2023★ 1 cited

Reduced Lagrange multiplier approach for non-matching coupling of mixed-dimensional domains

Luca Heltai, Paolo Zunino

Many physical problems involving heterogeneous spatial scales, such as the flow through fractured porous media, the study of fiber-reinforced materials, or the modeling of the smal…

math.NA2023★ 2 cited

Uncertainty quantification for nonlinear solid mechanics using reduced order models with Gaussian process regression

Ludovica Cicci, Stefania Fresca, Mengwu Guo +2

Uncertainty quantification (UQ) tasks, such as sensitivity analysis and parameter estimation, entail a huge computational complexity when dealing with input-output maps involving t…

math.NA2022

Approximation bounds for convolutional neural networks in operator learning

Nicola Rares Franco, Stefania Fresca, Andrea Manzoni +1

Recently, deep Convolutional Neural Networks (CNNs) have proven to be successful when employed in areas such as reduced order modeling of parametrized PDEs. Despite their accuracy…

math.NA2022★ 1 cited

Mesh-Informed Neural Networks for Operator Learning in Finite Element Spaces

Nicola Rares Franco, Andrea Manzoni, Paolo Zunino

Thanks to their universal approximation properties and new efficient training strategies, Deep Neural Networks are becoming a valuable tool for the approximation of mathematical op…

math.NA2021★ 50 cited

A Deep Learning approach to Reduced Order Modelling of Parameter Dependent Partial Differential Equations

Nicola R. Franco, Andrea Manzoni, Paolo Zunino

Within the framework of parameter dependent PDEs, we develop a constructive approach based on Deep Neural Networks for the efficient approximation of the parameter-to-solution map.…

math.NA2020

Iterative splitting schemes for a soft material poromechanics model

Jakub W. Both, Nicolas A. Barnafi, Florin A. Radu +2

We address numerical solvers for a poromechanics model particularly adapted for soft materials, as it generally respects thermodynamics principles and energy balance. Considering t…

math.NA2020

Analysis and approximation of mixed-dimensional PDEs on 3D-1D domains coupled with Lagrange multipliers

Miroslav Kuchta, Federica Laurino, Kent-Andre Mardal +1

Coupled partial differential equations defined on domains with different dimensionality are usually called mixed dimensional PDEs. We address mixed dimensional PDEs on three-dimens…

math.NA2017

A Lagrange multiplier method for a Stokes-Biot fluid-poroelastic structure interaction model

Ilona Ambartsumyan, Eldar Khattatov, Ivan Yotov +1

We study a finite element computational model for solving the coupled problem arising in the interaction between a free fluid and a fluid in a poroelastic medium. The free fluid is…

math.AP2014★ 1 cited

Inertial Motions of a Rigid Body with a cavity filled with a viscous liquid

Giovanni P. Galdi, Giusy Mazzone, Paolo Zunino

We study inertial motions of the coupled system, S, constituted by a rigid body containing a cavity that is completely filled with a viscous liquid. We show that for data of arbitr…

math.NA2014★ 105 cited

Partitioning strategies for the interaction of a fluid with a poroelastic material based on a Nitsche's coupling approach

Martina Bukac, Ivan Yotov, Rana Zakerzadeh +1

We develop a computational model to study the interaction of a fluid with a poroelastic material. The coupling of Stokes and Biot equations represents a prototype problem for these…

math.NA2013★ 8 cited

Explicit partitioning strategies for the interaction between a fluid and a multilayered poroelastic structure: an operator-splitting approach

Martina Bukac, Paolo Zunino, Ivan Yotov

We study the interaction between an incompressible, viscous, Newtonian fluid and a multilayered structure, which consists of a thin elastic layer and a thick poroelastic material.…