Model order reduction in computational fluid dynamics: focus on stabilisation and applications
The aim of the course is to provide an introduction to reduced order methods with particular emphasis on fluid dynamics problems. It also includes some practical exercises using the computational framework developed at SISSA.
Outline of the course: intrusive approaches: POD (Proper Orthogonal Decomposition); non-intrusive approaches: POD-I (Proper Orthogonal Decomposition with Interpolation); reduction in parameter space; model order reduction for turbulence flows; geometry parametrisation; flow control; worked problems in ITHACA-FV (open source library developed at SISSA upon OpenFoam).
Schedule:
Monday 5 December, 14:30–16:15 and 16:30–18:15;
Tuesday 6 December, 08:30–10:15 and 10:30–12:15.
The course is offered by the PhD course in Mathematical and Physical Sciences of the University of Udine. Course page: https://www.dmif.uniud.it/dottorato/smf/offerta-didattica/model-order-reduction-in-computational-fluid-dynamics-focus-on-stabilisation-and-applications/.
Gianluigi Rozza & Giovanni Stabile
Gianluigi Rozza is Full Professor in Numerical Analysis and Scientific Computing at SISSA MathLab – International School for Advanced Studies, Trieste, Italy. Master of Science in Aerospace Engineering (2002) at Politecnico di Milano, PhD in Applied Mathematics (2005) at Ecole Polytechnique Fédérale de Lausanne, Switzerland. Research Assistant (2002–06), Researcher and Lecturer (2008–12) at École Polytechnique Fédérale de Lausanne; Post Doctoral Associate Researcher (2006–08) at Massachusetts Institute of Technology, Boston MA, USA; Researcher (2012–14) and Associate Tenured Professor (2014–17) at International School for Advanced Studies, Trieste, Italy. His research interests include: Numerical Analysis, Numerical Simulation, Scientific Computing; Reduced Order Modelling and Methods with special focus on viscous flows and complex geometrical parametrizations; Efficient Reduced-Basis Methods for parametrized PDEs and a posteriori error estimation; Computational Fluid Dynamics with applications in Aero-Naval-Mechanical Engineering and Environmental Fluid Dynamics; Fluid–Structure Interaction Problems; Parametrized Navier–Stokes Equations for Bifurcations and stability of flow; Optimal Control, Flow Control based on PDEs, Shape Optimization, Uncertainty quantification, data assimilation; Machine Learning. Author of about 180 scientific papers receiving more than 4500 citations (H-index 32) Recipient of Bill Morton CFD Prize (2004) by Institute of Computational Fluid Dynamics, University of Oxford (UK), ECCOMAS Ph.D Award (2005) by European Community on Computational Methods in Applied Sciences, Springer Computational Science and Engineering Prize (2009), ECCOMAS Jacques Louis Lions Award in Computational Mathematics (2014), ERC consolidator grant ‘Advanced Reduced Order Methods with Applications in Computational Fluid Dynamics’ (AROMA-CFD, 2016–2021), ERC–Proof of Concept Grant ‘Advanced Reduced Groupware Online Simulation’ (ARGOS, 2022). (https://people.sissa.it/~grozza/)
Giovanni Stabile is assistant professor (RTD-B) in numerical analysis at the Department of Pure and Applied Sciences (DiSPeA), University of Urbino, Italy. From 2016 to 2022 he was assistant professor (RTD-A) and previously PostDoc at SISSA MathLab – International School for Advanced Studies, Trieste, Italy. He received his Ph.D. in 2016 from a joint Ph.D. school between the TU Braunschweig in Germany and the University of Florence in Italy. His current research interests include several aspects concerning the numerical approximation of partial differential equations, with a special emphasis on model order reduction techniques for computational fluid dynamic problems. He has worked with industrial partners on a variety of projects aimed at exporting advanced numerical methods to the industrial world. He is also the maintainer and lead developer of ITHACA-FV, a C++ implementation of several reduced order modeling techniques. (https://www.giovannistabile.com/)
