@inproceedings{eb279a7dad63440b9874eb7a28375154,
title = "The Effort of Increasing Reynolds Number in Projection-Based Reduced Order Methods: From Laminar to Turbulent Flows",
abstract = "We present in this double contribution two different reduced order strategies for incompressible parameterized Navier-Stokes equations characterized by varying Reynolds numbers. The first strategy deals with low Reynolds number (laminar flow) and is based on a stabilized finite element method during the offline stage followed by a Galerkin projection on reduced basis spaces generated by a greedy algorithm. The second methodology is based on a full order finite volume discretization. The latter methodology will be used for flows with moderate to high Reynolds number characterized by turbulent patterns. For the treatment of the mentioned turbulent flows at the reduced order level, a new POD-Galerkin approach is proposed. The new approach takes into consideration the contribution of the eddy viscosity also during the online stage and is based on the use of interpolation. The two methodologies are tested on classic benchmark test cases.",
keywords = "Data driven model reduction, Projection based model reduction, SUPG, Stabilised RB methods, Turbulence modelling, Viscous flows, Data driven model reduction, Projection based model reduction, SUPG, Stabilised RB methods, Turbulence modelling, Viscous flows",
author = "Saddam Hijazi and Shafqat Ali and Giovanni Stabile and Francesco Ballarin and Gianluigi Rozza",
year = "2020",
doi = "10.1007/978-3-030-30705-9_22",
language = "English",
isbn = "978-3-030-30704-2",
volume = "132",
series = "LECTURE NOTES IN COMPUTATIONAL SCIENCE AND ENGINEERING",
pages = "245--264",
booktitle = "Numerical Methods for Flows: FEF 2017 Selected Contributions",
note = "19th International Conference on Finite Elements in Flow Problems, FEF 2017 ; Conference date: 05-04-2017 Through 07-04-2017",
}