activity
20122026
most citedData-Driven POD-Galerkin Reduced Order Model for Turbulent Flows

220 citations · 660 across the 24 of their papers we have counts for

collaborators
Showing 2019Show all

5 papers · 1 filter

math.NA2019★ 18 cited

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…

math.NA2019★ 220 cited

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…

cs.CE2019★ 3 cited

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…

math.NA2019★ 14 cited

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…

math.NA2019★ 2 cited

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…