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20182022
most citedNon-linear manifold ROM with Convolutional Autoencoders and Reduced Over-Collocation method

9 citations · 9 across the 5 of their papers we have counts for

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11 papers · 1 filter

math.NA2022

Novel Methodologies for Solving the Inverse Unsteady Heat Transfer Problem of Estimating the Boundary Heat Flux in Continuous Casting Molds

Umberto Emil Morelli, Patricia Barral, Peregrina Quintela +2

In this work, we investigate the estimation of the transient mold-slab heat flux in continuous casting molds given some thermocouples measurements in the mold plates. Mathematicall…

math.NA20229 cited

Non-linear manifold ROM with Convolutional Autoencoders and Reduced Over-Collocation method

Francesco Romor, Giovanni Stabile, Gianluigi Rozza

Non-affine parametric dependencies, nonlinearities and advection-dominated regimes of the model of interest can result in a slow Kolmogorov n-width decay, which precludes the reali…

math.NA2021

An efficient FV-based Virtual Boundary Method for the simulation of fluid-solid interaction

Michele Girfoglio, Giovanni Stabile, Andrea Mola +1

In this work, the Immersed Boundary Method (IBM) with feedback forcing introduced by Goldstein et al. (1993) and often referred in the literature as the Virtual Boundary Method (VB…

math.NA2021

A numerical approach for heat flux estimation in thin slabs continuous casting molds using data assimilation

Umberto Emil Morelli, Patricia Barral, Peregrina Quintela +2

In the present work, we consider the industrial problem of estimating in real-time the mold-steel heat flux in continuous casting mold. We approach this problem by first considerin…

math.NA2020

On the comparison of LES data-driven reduced order approaches for hydroacoustic analysis

Mahmoud Gadalla, Marta Cianferra, Marco Tezzele +3

In this work, Dynamic Mode Decomposition (DMD) and Proper Orthogonal Decomposition (POD) methodologies are applied to hydroacoustic dataset computed using Large Eddy Simulation (LE…

math.NA2020

Enhancing CFD predictions in shape design problems by model and parameter space reduction

Marco Tezzele, Nicola Demo, Giovanni Stabile +2

In this work we present an advanced computational pipeline for the approximation and prediction of the lift coefficient of a parametrized airfoil profile. The non-intrusive reduced…