
A datadriven partitioned approach for the resolution of timedependent optimal control problems with dynamic mode decomposition
This work recasts timedependent optimal control problems governed by pa...
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Finite element based model order reduction for parametrized oneway coupled steady state linear thermomechanical problems
This contribution focuses on the development of Model Order Reduction (M...
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Multifidelity data fusion through parameter space reduction with applications to automotive engineering
Multifidelity models are of great importance due to their capability of...
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An extended physics informed neural network for preliminary analysis of parametric optimal control problems
In this work we propose an extension of physics informed supervised lear...
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An efficient FVbased Virtual Boundary Method for the simulation of fluidsolid interaction
In this work, the Immersed Boundary Method (IBM) with feedback forcing i...
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Neuralnetwork learning of SPOD latent dynamics
We aim to reconstruct the latent space dynamics of high dimensional syst...
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A Dimensionality Reduction Approach for Convolutional Neural Networks
The focus of this paper is the application of classical model order redu...
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A dynamic mode decomposition extension for the forecasting of parametric dynamical systems
Dynamic mode decomposition (DMD) has recently become a popular tool for ...
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Model order reduction for bifurcating phenomena in FluidStructure Interaction problems
This work explores the development and the analysis of an efficient redu...
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Consistency of the Full and Reduced Order Models for EvolveFilterRelax Regularization of ConvectionDominated, MarginallyResolved Flows
Numerical stabilization is often used to eliminate (alleviate) the spuri...
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An artificial neural network approach to bifurcating phenomena in computational fluid dynamics
This work deals with the investigation of bifurcating fluid phenomena us...
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Thermomechanical modelling for industrial applications
In this work we briefly present a thermomechanical model that could serv...
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The Neural Network shiftedProper Orthogonal Decomposition: a Machine Learning Approach for Nonlinear Reduction of Hyperbolic Equations
Models with dominant advection always posed a difficult challenge for pr...
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Verifiability of the DataDriven Variational Multiscale Reduced Order Model
In this paper, we focus on the mathematical foundations of reduced order...
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A Hybrid Reduced Order Model for nonlinear LES filtering
We develop a Reduced Order Model (ROM) for a Large Eddy Simulation (LES)...
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A local approach to parameter space reduction for regression and classification tasks
Frequently, the parameter space, chosen for shape design or other applic...
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Hybrid neural network reduced order modelling for turbulent flows with geometric parameters
Geometrically parametrized Partial Differential Equations are nowadays w...
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Pressure stabilization strategies for a LES filtering Reduced Order Model
We present a stabilized PODGalerkin reduced order method (ROM) for a Le...
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ATHENA: Advanced Techniques for High Dimensional Parameter Spaces to Enhance Numerical Analysis
ATHENA is an open source Python package for reduction in parameter space...
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An optimal control approach to determine resistancetype boundary conditions from invivo data for cardiovascular simulations
The choice of appropriate boundary conditions is a fundamental step in c...
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A monolithic and a partitioned Reduced Basis Method for FluidStructure Interaction problems
The aim of this work is to present a brief report concerning the various...
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A Reduced basis stabilization for the unsteady Stokes and NavierStokes equations
In the Reduced Basis approximation of Stokes and NavierStokes problems,...
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A weighted PODreduction approach for parametrized PDEconstrained Optimal Control Problems with random inputs and applications to environmental sciences
Reduced basis approximations of Optimal Control Problems (OCPs) governed...
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A Certified Reduced Basis Method for Linear Parametrized Parabolic Optimal Control Problems in SpaceTime Formulation
In this work, we propose to efficiently solve time dependent parametrize...
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Fluidstructure interaction simulations with a LES filtering approach in solids4Foam
We consider the interaction of an incompressible fluid described by a Le...
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A numerical approach for heat flux estimation in thin slabs continuous casting molds using data assimilation
In the present work, we consider the industrial problem of estimating in...
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Hull shape design optimization with parameter space and model reductions, and selflearning mesh morphing
In the field of parametric partial differential equations, shape optimiz...
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Gaussian process approach within a datadriven POD framework for fluid dynamics engineering problems
This work describes the implementation of a datadriven approach for the...
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Reduced order methods for parametric flow control problems and applications
In this contribution we propose reduced order methods to fast and reliab...
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Driving bifurcating parametrized nonlinear PDEs by optimal control strategies: application to NavierStokes equations with model order reduction
This work deals with optimal control problems as a strategy to drive bif...
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Multifidelity data fusion for the approximation of scalar functions with low intrinsic dimensionality through active subspaces
Gaussian processes are employed for nonparametric regression in a Bayes...
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A comparison of reducedorder modeling approaches for PDEs with bifurcating solutions
This paper focuses on reducedorder models (ROMs) built for the efficien...
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A Reduced Order Cut Finite Element method for geometrically parameterized steady and unsteady NavierStokes problems
This work focuses on steady and unsteady NavierStokes equations in a re...
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A PODGalerkin reduced order model for a LES filtering approach
We propose a Proper Orthogonal Decomposition (POD)Galerkin based Reduce...
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A Reduced Order Model for a stable embedded boundary parametrized CahnHilliard phasefield system based on cut finite elements
In the present work, we investigate for the first time with a cut finite...
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Kernelbased Active Subspaces with application to CFD parametric problems using Discontinuous Galerkin method
A new method to perform a nonlinear reduction in parameter spaces is pro...
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Nonintrusive PODIROM for patientspecific aortic blood flow in presence of a LVAD device
Left ventricular assist devices (LVADs) are used to provide haemodynamic...
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On the comparison of LES datadriven reduced order approaches for hydroacoustic analysis
In this work, Dynamic Mode Decomposition (DMD) and Proper Orthogonal Dec...
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MicroROM: An Efficient and Accurate Reduced Order Method to Solve ManyQuery Problems in MicroMotility
In the study of microswimmers, both artificial and biological ones, man...
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A supervised learning approach involving active subspaces for an efficient genetic algorithm in highdimensional optimization problems
In this work, we present an extension of the genetic algorithm (GA) whic...
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An efficient computational framework for naval shape design and optimization problems by means of datadriven reduced order modeling techniques
This contribution describes the implementation of a data–driven shape op...
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PODGalerkin Model Order Reduction for Parametrized Nonlinear Time Dependent Optimal Flow Control: an Application to Shallow Water Equations
In this work we propose reduced order methods as a reliable strategy to ...
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Enhancing CFD predictions in shape design problems by model and parameter space reduction
In this work we present an advanced computational pipeline for the appro...
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Stabilized reduced basis methods for parametrized steady Stokes and NavierStokes equations
It is well known in the Reduced Basis approximation of saddle point prob...
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Discontinuous Galerkin Model Order Reduction of Geometrically Parametrized Stokes Equation
The present work focuses on the geometric parametrization and the reduce...
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Reduced order methods for parametrized nonlinear and time dependent optimal flow control problems, towards applications in biomedical and environmental sciences
We introduce reduced order methods as an efficient strategy to solve par...
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Efficient computation of bifurcation diagrams with a deflated approach to reduced basis spectral element method
The majority of the most common physical phenomena can be described usin...
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Extension and comparison of techniques to enforce boundary conditions in Finite Volume PODGalerkin reduced order models for fluid dynamic problems
A FiniteVolume based PODGalerkin reduced order model is developed for ...
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Basic Ideas and Tools for ProjectionBased Model Reduction of Parametric Partial Differential Equations
We provide first the functional analysis background required for reduced...
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Overcoming slowly decaying Kolmogorov nwidth by transport maps: application to model order reduction of fluid dynamics and fluid–structure interaction problems
In this work we focus on reduced order modelling for problems for which ...
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Gianluigi Rozza
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