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FEniCS-HPC: Coupled Multiphysics in Computational Fluid Dynamics
KTH, School of Computer Science and Communication (CSC). Basque Center for Applied Mathematics (BCAM), Bilbao, Spain.ORCID iD: 0000-0003-4256-0463
KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST). Basque Center for Applied Mathematics (BCAM), Bilbao, Spain.ORCID iD: 0000-0002-1695-8809
KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
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2017 (English)In: High-Performance Scientific Computing: Jülich Aachen Research Alliance (JARA) High-Performance Computing Symposium / [ed] Edoardo Di Napoli, Marc-André Hermanns, Hristo Iliev, Andreas Lintermann, Alexander Peyser, Springer, 2017, 58-69 p.Conference paper, (Refereed)
Abstract [en]

We present a framework for coupled multiphysics in computational fluid dynamics, targeting massively parallel systems. Our strategy is based on general problem formulations in the form of partial differential equations and the finite element method, which open for automation, and optimization of a set of fundamental algorithms. We describe these algorithms, including finite element matrix assembly, adaptive mesh refinement and mesh smoothing; and multiphysics coupling methodologies such as unified continuum fluid-structure interaction (FSI), and aeroacoustics by coupled acoustic analogies. The framework is implemented as FEniCS open source software components, optimized for massively parallel computing. Examples of applications are presented, including simulation of aeroacoustic noise generated by an airplane landing gear, simulation of the blood flow in the human heart, and simulation of the human voice organ.

Place, publisher, year, edition, pages
Springer, 2017. 58-69 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 10164
Keyword [en]
FEniCS, Unicorn, Eunison, High-performance computing, Multiphysics, Computational fluid dynamics, Adaptive finite element method
National Category
Computational Mathematics Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-202694DOI: 10.1007/978-3-319-53862-4_6Scopus ID: 2-s2.0-85014945510ISBN: 978-3-319-53861-7 (print)ISBN: 978-3-319-53862-4 (electronic)OAI: oai:DiVA.org:kth-202694DiVA: diva2:1078151
Conference
Jülich Aachen Research Alliance (JARA) High-Performance Computing Symposium
Note

QC 20170314

Available from: 2017-03-02 Created: 2017-03-02 Last updated: 2017-03-14Bibliographically approved

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Hoffman, JohanJansson, JohanDegirmenci, Niyazi CemSpühler, Jeannette HiromiVilela de Abreu, RodrigoJansson, Niclas
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