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@ARTICLE{SchlottkeLakemper:842367,
author = {Schlottke-Lakemper, Michael and Yu, Hans and Berger, Sven
and Meinke, Matthias and Schröder, Wolfgang},
title = {{A} fully coupled hybrid computational aeroacoustics method
on hierarchical {C}artesian meshes},
journal = {Computers $\&$ fluids},
volume = {144},
issn = {0045-7930},
address = {Amsterdam [u.a.]},
publisher = {Elsevier Science},
reportid = {FZJ-2018-00608},
pages = {137 - 153},
year = {2017},
abstract = {Hybrid computational fluid dynamics (CFD) – computational
aeroacoustics (CAA) schemes are the standard method for
aeroacoustics simulations. This approach requires the
exchange of information between the CFD and the CAA step,
which is usually accomplished by storing acoustic source
data. This data exchange procedure, however, poses two
problems when such hybrid methods are used for large-scale
problems with $O(10^9)$ degrees of freedom: On the one hand,
the required disk space becomes large and reaches hundreds
of terabytes for a single simulation. On the other hand, the
parallel scalability of the overall numerical scheme is
limited by the available I/O bandwidth, which typically
peaks between 5,000 and 10,000 cores. To avoid these
problems, a highly scalable direct-hybrid scheme is
presented, in which both the flow and the acoustics
simulations run simultaneously. That is, all data between
the two solvers is transferred in-memory, avoiding the
restrictions of the I/O subsystem. Both solvers operate on a
joint hierarchical Cartesian grid, which enables efficient
parallelization and dynamic load balancing and inherently
supports local mesh refinement. To demonstrate the
capabilities of the new scheme, the aeroacoustic field of a
co-rotating vortex pair is computed. The results show that
the direct-hybrid method is able to efficiently predict the
acoustic pressure field and that it is suitable for highly
parallel simulations. Furthermore, in comparison to the
hybrid method with data exchange via disk I/O, the novel
approach shows superior performance when scaling to
thousands of cores.},
ddc = {004},
pnm = {511 - Computational Science and Mathematical Methods
(POF3-511) / PhD no Grant - Doktorand ohne besondere
Förderung (PHD-NO-GRANT-20170405) / Prediction of jet
engine noise $(jhpc23_20151101)$},
pid = {G:(DE-HGF)POF3-511 / G:(DE-Juel1)PHD-NO-GRANT-20170405 /
$G:(DE-Juel1)jhpc23_20151101$},
typ = {PUB:(DE-HGF)16},
doi = {10.1016/j.compfluid.2016.12.001},
url = {https://juser.fz-juelich.de/record/842367},
}