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000171823 020__ $$a978-3-319-05788-0 (print)
000171823 020__ $$a978-3-319-05789-7 (electronic)
000171823 0247_ $$2doi$$a10.1007/978-3-319-05789-7_61
000171823 0247_ $$2WOS$$aWOS:000347877900061
000171823 037__ $$aFZJ-2014-05382
000171823 1001_ $$0P:(DE-Juel1)132268$$aSpeck, Robert$$b0$$eCorresponding Author$$ufzj
000171823 1112_ $$aDomain Decomposition Methods in Science and Engineering XXI$$cRennes$$d2012-06-25 - 2012-06-29$$gDD21$$wFrance
000171823 245__ $$aIntegrating an N-Body Problem with SDC and PFASST
000171823 260__ $$bSpringer International Publishing$$c2014
000171823 300__ $$a637 - 645
000171823 3367_ $$0PUB:(DE-HGF)8$$2PUB:(DE-HGF)$$aContribution to a conference proceedings$$bcontrib$$mcontrib$$s1414497442_8209
000171823 3367_ $$033$$2EndNote$$aConference Paper
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000171823 3367_ $$2BibTeX$$aINPROCEEDINGS
000171823 4900_ $$aLecture Notes in Computational Science and Engineering$$v98
000171823 520__ $$aVortex methods for the Navier–Stokes equations are based on a Lagrangian particle discretization, which reduces the governing equations to a first-order initial value system of ordinary differential equations for the position and vorticity of N particles. In this paper, the accuracy of solving this system by time-serial spectral deferred corrections (SDC) as well as by the time-parallel Parallel Full Approximation Scheme in Space and Time (PFASST) is investigated. PFASST is based on intertwining SDC iterations with differing resolution in a manner similar to the Parareal algorithm and uses a Full Approximation Scheme (FAS) correction to improve the accuracy of coarser SDC iterations. It is demonstrated that SDC and PFASST can generate highly accurate solutions, and the performance in terms of function evaluations required for a certain accuracy is analyzed and compared to a standard Runge–Kutta method.
000171823 536__ $$0G:(DE-HGF)POF2-411$$a411 - Computational Science and Mathematical Methods (POF2-411)$$cPOF2-411$$fPOF II$$x0
000171823 536__ $$0G:(GEPRIS)450829162$$aDFG project 450829162 - Raum-Zeit-parallele Simulation multimodale Energiesystemen (450829162)$$c450829162$$x1
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000171823 7001_ $$0P:(DE-HGF)0$$aRuprecht, Daniel$$b1
000171823 7001_ $$0P:(DE-HGF)0$$aKrause, Rolf$$b2
000171823 7001_ $$0P:(DE-HGF)0$$aEmmett, Matthew$$b3
000171823 7001_ $$0P:(DE-HGF)0$$aMinion, Michael$$b4
000171823 7001_ $$0P:(DE-Juel1)140128$$aWinkel, Mathias$$b5
000171823 7001_ $$0P:(DE-Juel1)132115$$aGibbon, Paul$$b6$$ufzj
000171823 773__ $$a10.1007/978-3-319-05789-7_61
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000171823 9132_ $$0G:(DE-HGF)POF3-511$$1G:(DE-HGF)POF3-510$$2G:(DE-HGF)POF3-500$$aDE-HGF$$bPOF III$$lKey Technologies$$vSupercomputing & Big Data $$x0
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000171823 9141_ $$y2014
000171823 920__ $$lyes
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