Zobrazeno 1 - 10
of 140
pro vyhledávání: '"ICARDI, MATTEO"'
Physics-Informed Neural Networks (PINN) are a machine learning tool that can be used to solve direct and inverse problems related to models described by Partial Differential Equations. This paper proposes an adaptive inverse PINN applied to different
Externí odkaz:
http://arxiv.org/abs/2407.10654
We propose a new model reduction technique for multiscale scalar transport problems that exhibit dominant axial dynamics. To this aim, we rely on the separation of variables to combine a Hierarchical Model (HiMod) reduction with a two-scale asymptoti
Externí odkaz:
http://arxiv.org/abs/2401.06238
Problems with dominant advection, discontinuities, travelling features, or shape variations are widespread in computational mechanics. However, classical linear model reduction and interpolation methods typically fail to reproduce even relatively sma
Externí odkaz:
http://arxiv.org/abs/2304.14883
The reverse osmosis membrane module is an integral element of a desalination system as it determines the overall performance of the desalination plant. The fraction of clean water that can be recovered via this process is often limited by salt precip
Externí odkaz:
http://arxiv.org/abs/2301.13160
The modelling of electrokinetic flows is a critical aspect spanning many industrial applications and research fields. This has introduced great demand in flexible numerical solvers to describe these flows. The underlying phenomena are microscopic, no
Externí odkaz:
http://arxiv.org/abs/2212.13519
Coupled multi-physics problems are encountered in countless applications and pose significant numerical challenges. Although monolithic approaches offer possibly the best solution strategy, they often require ad-hoc preconditioners and numerical impl
Externí odkaz:
http://arxiv.org/abs/2212.11111
We present a flexible scalable open-source computational framework, named SECUReFoam, based on the finite-volume library OpenFOAM(R), for flow and transport problems in highly heterogeneous geological media and other porous materials. The framework c
Externí odkaz:
http://arxiv.org/abs/2212.10961
We present a numerical simulation study of advective-diffusive scalar transport in three-dimensional high-contrast discontinuous permeability fields, generated with a truncated pluri-Gaussian geostatistical approach. A range of permeability contrasts
Externí odkaz:
http://arxiv.org/abs/2206.07131
Autor:
Icardi, Matteo, Di Pasquale, Nicodemo, Crevacore, Eleonora, Marchisio, Daniele, Babler, Matthaus U.
Transport and particulate processes are ubiquitous in environmental, industrial and biological applications, often involving complex geometries and porous media. In this work we present a general population balance model for particle transport at the
Externí odkaz:
http://arxiv.org/abs/2107.00750
Publikováno v:
In Computers and Mathematics with Applications 1 May 2024 161:190-201
