12 citations · 32 across the 14 of their papers we have counts for
4 papers · 1 filter
A new data-driven energy-stable Evolve-Filter-Relax model for turbulent flow simulation
Anna Ivagnes, Toby van Gastelen, Syver Døving Agdestein +3
We present a novel approach to define the filter and relax steps in the evolve-filter-relax (EFR) framework for simulating turbulent flows. The EFR main advantages are its ease of…
Machine Learning-based quadratic closures for non-intrusive Reduced Order Models
Gabriele Codega, Anna Ivagnes, Nicola Demo +1
In the present work, we introduce a data-driven approach to enhance the accuracy of non-intrusive Reduced Order Models (ROMs). In particular, we focus on ROMs built using Proper Or…
Data-driven Closure Strategies for Parametrized Reduced Order Models via Deep Operator Networks
Anna Ivagnes, Giovanni Stabile, Gianluigi Rozza
In this paper, we propose an equation-based parametric Reduced Order Model (ROM), whose accuracy is improved with data-driven terms added into the reduced equations. These addition…
Data-driven Optimization for the Evolve-Filter-Relax regularization of convection-dominated flows
Anna Ivagnes, Maria Strazzullo, Michele Girfoglio +2
Numerical stabilization techniques are often employed in under-resolved simulations of convection-dominated flows to improve accuracy and mitigate spurious oscillations. Specifical…