220 citations · 660 across the 24 of their papers we have counts for
24 papers
Constraint-driven Optimization and Parametrization of Industrial NURBS Geometries via Neural Deformation Field
Federico Tamburlin, Giovanni Canali, Giuseppe Alessio D'Inverno +3
This work presents a differentiable framework for the parametrization and shape optimization of industrial CAD geometries represented by multi-patch NURBS surfaces. The method enab…
An efficient hyper reduced-order model for segregated solvers for geometrical parametrization problems
Valentin Nkana Ngan, Giovanni Stabile, Andrea Mola +1
We propose an efficient hyper-reduced order model (HROM) designed for segregated finite-volume solvers in geometrically parametrized problems. The method follows a discretize-then-…
A hybrid reduced-order model for segregated fluid-structure interaction solvers in an ALE approach at high Reynolds number
Valentin Nkana Ngan, Giovanni Stabile, Andrea Mola +1
This study introduces a first step for constructing a hybrid reduced-order models (ROMs) for segregated fluid-structure interaction in an Arbitrary Lagrangian-Eulerian (ALE) approa…
Mathematical modelling and computational reduction of molten glass fluid flow in a furnace melting basin
Francesco Ballarin, Enrique Delgado Ávila, Andrea Mola +1
In this work, we present the modelling and numerical simulation of a molten glass fluid flow in a furnace melting basin. We first derive a model for a molten glass fluid flow and p…
A reduced-order model for segregated fluid-structure interaction solvers based on an ALE approach
Valentin Nkana Ngan, Giovanni Stabile, Andrea Mola +1
This article presents a Galerkin projection-based reduced-order modelling (ROM) approach for segregated fluid-structure interaction (FSI) problems, formulated within an Arbitrary L…
A unified steady and unsteady formulation for hydrodynamic potential flow simulations with fully nonlinear free surface boundary conditions
Andrea Mola, Nicola Giuliani, Óscar Crego +1
This work discusses the correct modeling of the fully nonlinear free surface boundary conditions to be prescribed in water waves flow simulations based on potential flow theory. Th…
Hybrid Data-Driven Closure Strategies for Reduced Order Modeling
Anna Ivagnes, Giovanni Stabile, Andrea Mola +2
In this paper, we propose hybrid data-driven ROM closures for fluid flows. These new ROM closures combine two fundamentally different strategies: (i) purely data-driven ROM closure…
Pressure Data-Driven Variational Multiscale Reduced Order Models
Anna Ivagnes, Giovanni Stabile, Andrea Mola +2
In this paper, we develop data-driven closure/correction terms to increase the pressure and velocity accuracy of reduced order models (ROMs) for fluid flows. Specifically, we propo…
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…
Hull shape design optimization with parameter space and model reductions, and self-learning mesh morphing
Nicola Demo, Marco Tezzele, Andrea Mola +1
In the field of parametric partial differential equations, shape optimization represents a challenging problem due to the required computational resources. In this contribution, a…
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…
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…
Propagating geometry information to finite element computations
Luca Heltai, Wolfgang Bangerth, Martin Kronbichler +1
The traditional workflow in continuum mechanics simulations is that a geometry description -- for example obtained using Constructive Solid Geometry or Computer Aided Design tools…
Data-Driven POD-Galerkin Reduced Order Model for Turbulent Flows
Saddam Hijazi, Giovanni Stabile, Andrea Mola +1
In this work we present a Reduced Order Model which is specifically designed to deal with turbulent flows in a finite volume setting. The method used to build the reduced order mod…
Efficient Reduction in Shape Parameter Space Dimension for Ship Propeller Blade Design
Andrea Mola, Marco Tezzele, Mahmoud Gadalla +4
In this work, we present the results of a ship propeller design optimization campaign carried out in the framework of the research project PRELICA, funded by the Friuli Venezia Giu…
A complete data-driven framework for the efficient solution of parametric shape design and optimisation in naval engineering problems
Nicola Demo, Marco Tezzele, Andrea Mola +1
In the reduced order modeling (ROM) framework, the solution of a parametric partial differential equation is approximated by combining the high-fidelity solutions of the problem at…
Non-Intrusive Polynomial Chaos Method Applied to Full-Order and Reduced Problems in Computational Fluid Dynamics: a Comparison and Perspectives
Saddam Hijazi, Giovanni Stabile, Andrea Mola +1
In this work, Uncertainty Quantification (UQ) based on non-intrusive Polynomial Chaos Expansion (PCE) is applied to the CFD problem of the flow past an airfoil with parameterized a…
Advances in Reduced Order Methods for Parametric Industrial Problems in Computational Fluid Dynamics
Gianluigi Rozza, Haris Malik, Nicola Demo +4
Reduced order modeling has gained considerable attention in recent decades owing to the advantages offered in reduced computational times and multiple solutions for parametric prob…
An integrated data-driven computational pipeline with model order reduction for industrial and applied mathematics
Marco Tezzele, Nicola Demo, Andrea Mola +1
In this work we present an integrated computational pipeline involving several model order reduction techniques for industrial and applied mathematics, as emerging technology for p…
Model Order Reduction by means of Active Subspaces and Dynamic Mode Decomposition for Parametric Hull Shape Design Hydrodynamics
Marco Tezzele, Nicola Demo, Mahmoud Gadalla +2
We present the results of the application of a parameter space reduction methodology based on active subspaces (AS) to the hull hydrodynamic design problem. Several parametric defo…
An efficient shape parametrisation by free-form deformation enhanced by active subspace for hull hydrodynamic ship design problems in open source environment
Nicola Demo, Marco Tezzele, Andrea Mola +1
In this contribution, we present the results of the application of a parameter space reduction methodology based on active subspaces to the hull hydrodynamic design problem. Severa…
Dimension reduction in heterogeneous parametric spaces with application to naval engineering shape design problems
Marco Tezzele, Filippo Salmoiraghi, Andrea Mola +1
We present the results of the first application in the naval architecture field of a methodology based on active subspaces properties for parameters space reduction. The physical p…
Pod-Galerkin Reduced Order Methods for CFD Using Finite Volume Discretisation: Vortex Shedding Around a Circular Cylinder
Giovanni Stabile, Saddam Hijazi, Andrea Mola +2
Vortex shedding around circular cylinders is a well known and studied phenomenon that appears in many engineering fields. A Reduced Order Model (ROM) of the incompressible flow aro…
A stable and adaptive semi-Lagrangian potential model for unsteady and nonlinear ship-wave interactions
Andrea Mola, Luca Heltai, Antonio DeSimone
We present an innovative numerical discretization of the equations of inviscid potential flow for the simulation of three dimensional unsteady and nonlinear water waves generated b…