Journal
COMPUTERS & MATHEMATICS WITH APPLICATIONS
Volume 116, Issue -, Pages 140-160Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.camwa.2021.07.016
Keywords
Reduced Order Models; Unfitted mesh; Cut Finite Element Method; Navier-Stokes equations; Parameter-dependent shape geometry
Categories
Funding
- European Union [681447]
- Hellenic Foundation for Research and Innovation (HFRI)
- General Secretariat for Research and Technology (GSRT) [1115, 3270]
- National Infrastructures for Research and Technology S.A. (GRNET S.A.) in the National HPC facility - ARIS [pa190902]
- Austrian Science Fund (FWF) [F65, P 33477]
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This study focuses on steady and unsteady Navier-Stokes flow systems in a reduced-order modeling framework using Proper Orthogonal Decomposition and a levelset geometry description. The discretization is done using an unfitted mesh Finite Element Method and extends the approaches of [1-3] to nonlinear CutFEM discretization. The study constructs and investigates a unified and geometry independent reduced basis that overcomes many barriers and complications that may occur during geometrical morphings.
We focus on steady and unsteady Navier-Stokes flow systems in a reduced-order modeling framework based on Proper Orthogonal Decomposition within a levelset geometry description and discretized by an unfitted mesh Finite Element Method. This work extends the approaches of [1 -3] to nonlinear CutFEM discretization. We construct and investigate a unified and geometry independent reduced basis which overcomes many barriers and complications of the past, that may occur whenever geometrical morphings are taking place. By employing a geometry independent reduced basis, we are able to avoid remeshing and transformation to reference configurations, and we are able to handle complex geometries. This combination of a fixed background mesh in a fixed extended background geometry with reduced order techniques appears beneficial and advantageous in many industrial and engineering applications, which could not be resolved efficiently in the past.
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