I'm a PhD student in the SISSA mathLab group, based in Trieste (Italy).
Currently working on data-driven stabilization and filtering approaches to enhance Reduced Order Models (ROMs), with applications in CFD.
Working on stabilization/closure/filtering approaches for CFD simulations under the supervision of Prof. Gianluigi Rozza (SISSA) and Dr. Giovanni Stabile (University of Urbino and Scuola Superiore Sant'Anna, Pisa).
Research activity in cooperation with FINCANTIERI S.P.A. on the development of a shape optimization pipeline for marine propellers using reduced order models. The project was under the supervision of Nicola Demo and Prof. Gianluigi Rozza.
Master thesis: "Data Enhanced Reduced Order Models for turbulent flows" under the supervision of Dr. Giovanni Stabile, Dr. Andrea Mola, Prof. Traian Iliescu, and Prof. Gianluigi Rozza, and Prof. Claudio Canuto.
Final mark: 110/110 with honors
Bachelor thesis: "Self-healing materials: study of a cohesive zone model using a thermodynamic approach", under the supervision of Dr. Marco Trullo and Prof. Rossana Dimitri.
Final mark: 110/110 with honors
Final mark: 100/100 with honors
The project is focused on creating a novel EFR approach where the filter is found by least-squares optimization using high-fidelity data.
This project is in collaboration with the group of Prof. B. Sanderse from CWI, in Amsterdam.
"A new data-driven energy-stable evolve-filter-relax model for turbulent flow simulation"by A. Ivagnes, T. V. Gastelen, S. D. Agdestein, B. Sanderse, G. Stabile, G. Rozza.
The project is focused on adaptive optimization of the EFR parameters, based on pre-computed data.
This project is in collaboration with Dr. Maria Strazzullo (PoliTo), Prof. Michele Girfoglio (University of Palermo), and Traian Iliescu (VT).
"Data‐Driven Optimization for the Evolve‐Filter‐Relax Regularization of Convection‐Dominated Flows"by A. Ivagnes, M. Strazzullo, M. Girfoglio, T. Iliescu, G. Rozza.
This project focuses on data-driven "correction" terms for POD-Galerkin ROMs which re-introduce the contribution of the neglected modes.
"Pressure data-driven variational multiscale reduced order models",by A.Ivagnes, G. Stabile, A. Mola, T. Iliescu, G. Rozza
Follow-up for parametrized test cases with machine learning:
"Data-driven Closure Strategies for Parametrized ROMs via DeepONets",
This project focused on the development of a shape optimization pipeline for marine propellers using reduced order models.
This project was in cooperation with FINCANTIERI S.P.A.
"A shape optimization pipeline for marine propellers by means of reduced order modeling techniques"by A.Ivagnes, N. Demo, G. Rozza
The project is focused on creating a model mixture based on the combination of non-intrusive ROMs, which differs for the reduction and approximation technique considered.
This project is in collaboration with Prof. Paola Cinnella, from Sorbonne university.
"Enhancing non-intrusive Reduced Order Models with space-dependent aggregation methods"by A. Ivagnes, N. Tonicello, P. Cinnella, G. Rozza