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Adaptive Computation of Aeroacoustic Sources for a Rudimentary Landing Gear
KTH, School of Computer Science and Communication (CSC), High Performance Computing and Visualization (HPCViz). KTH, School of Engineering Sciences (SCI), Centres, Linné Flow Center, FLOW.
KTH, School of Computer Science and Communication (CSC), High Performance Computing and Visualization (HPCViz).ORCID iD: 0000-0002-5020-1631
KTH, School of Computer Science and Communication (CSC), High Performance Computing and Visualization (HPCViz).ORCID iD: 0000-0003-4256-0463
2014 (English)In: International Journal for Numerical Methods in Fluids, ISSN 0271-2091, E-ISSN 1097-0363, Vol. 74, no 6, 406-421 p.Article in journal (Refereed) Published
Abstract [en]

We present our simulation results for the benchmark problem of the flow past a rudimentary landing gear using a General Galerkin FEM, also referred to as adaptive DNS/LES. In General Galerkin, no explicit subgrid model is used; instead, the computational mesh is adaptively refined with respect to an a posteriori error estimate of a quantity of interest in the computation, in this case, the drag force on the rudimentary landing gear. Turbulent boundary layers are modeled using a simple wall-layer model with the shear stress at walls proportional to the skin friction, which here is assumed to be small and, therefore, can be approximated by zero skin friction. We compare our results with experimental data and other state of the art computations, where we find good agreement in sound pressure levels, surface velocities, and flow separation. We also compare with detailed surface pressure experimental data where we find largely good agreement, apart from some local differences for which we discuss possible explanations.

Place, publisher, year, edition, pages
2014. Vol. 74, no 6, 406-421 p.
Keyword [en]
aeroacoustics, aerodynamics, finite element, incompressible flow, LES, large Eddy simulations;turbulent flow
National Category
Computational Mathematics
URN: urn:nbn:se:kth:diva-125722DOI: 10.1002/fld.3856ISI: 000329509500002ScopusID: 2-s2.0-84891832461OAI: diva2:640301
Swedish Foundation for Strategic Research EU, European Research CouncilSwedish Research CouncilSwedish Energy Agency

QC 20140131

Available from: 2013-08-13 Created: 2013-08-13 Last updated: 2014-01-31Bibliographically approved
In thesis
1. High Performance Adaptive Finite Element Methods: With Applications in Aerodynamics
Open this publication in new window or tab >>High Performance Adaptive Finite Element Methods: With Applications in Aerodynamics
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The massive computational cost for resolving all scales in a turbulent flow makes a direct numerical simulation of the underlying Navier-Stokes equations impossible in most engineering applications. Recent advances in adaptive finite element methods offer a new powerful tool in Computational Fluid Dynamics (CFD). The computational cost for simulating turbulent flow can be minimized by adaptively resolution of the mesh, based on a posteriori error estimation. Such adaptive methods have previously been implemented for efficient serial computations, but the extension to an efficient parallel solver is a challenging task. This work concerns the development of an adaptive finite element method that enables efficient computation of time resolved approximations of turbulent flow for complex geometries with a posteriori error control. We present efficient data structures and data decomposition methods for distributed unstructured tetrahedral meshes. Our work also concerns an efficient parallelization of local mesh refinement methods such as recursive longest edge bisection, and the development of an a priori predictive dynamic load balancing method, based on a weighted dual graph. We also address the challenges of emerging supercomputer architectures with the development of new hybrid parallel programming models, combining traditional message passing with lightweight one-sided communication. Our implementation has proven to be both general and efficient, scaling up to more than twelve thousands cores.

Abstract [sv]

Den höga beräkningskostnaden för att lösa upp alla turbulenta skalor för ett realistiskt problem gör en direkt numerisk simulering av Navier-Stokes ekvationer omöjlig. De senaste framstegen inom adaptiva finita element metoder ger ett nytt kraftfullt verktyg inom Computational Fluid Dynamics (CFD). Beräkningskostnaden för en simulering av turbulent flöde kan minimeras genom att beräkningsnätet adaptivt förfinas baserat på en a posteriori feluppskattning. Dessa adaptiva metoder har tidigare implementerats för seriella beräkningar, medan en effektiv parallellisering av metoden inte är trivial. I denna avhandling presenterar vi vår utveckling av en adaptiv finita element lösare, anpassad för att effektivt beräkna tidsupplösta approximationer i komplicerade geometrier med a posteriori felkontroll. Effektiva datastrukturer och metoder för ostrukturerade beräkningsnät av tetrahedrar presenteras. Avhandlingen behandlar även effektiv parallellisering av lokala nätförfiningsmetoder, exempelvis recursive longest edge bisection. Även lastbalanseringsproblematiken behandlas, där problemet lösts genom utvecklandet av en prediktiv dynamisk lastbalanseringsmetod, baserad på en viktad dualgraf av beräkningsnätet. Slutligen avhandlas även problematiken med att effektivt utnyttja nytillkomna superdatorarkitekturer, genom utvecklandet av en hybrid parallelliserings modell som kombinerar traditionell meddelande baserad parallellisering med envägskommunikation. Detta har resulterat i en generell samt effektiv implementation med god skalning upp till fler än tolv tusen processorkärnor.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2013. xii, 50 p.
TRITA-CSC-A, ISSN 1653-5723 ; 2013:07
National Category
Computational Mathematics
urn:nbn:se:kth:diva-125742 (URN)978-91-7501-814-0 (ISBN)
Public defence
2013-09-11, F3, Lindstedtsvägen 26, KTH, Stockholm, 10:15 (English)

QC 20130816

Available from: 2013-08-16 Created: 2013-08-13 Last updated: 2016-02-02Bibliographically approved

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Vilela de Abreu, RodrigoJansson, NiclasHoffman, Johan
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