2013
DOI: 10.1002/fld.3837
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Stability of a Crank–Nicolson pressure correction scheme based on staggered discretizations

Abstract: SUMMARYIn the context of LES of turbulent flows, the control of kinetic energy seems to be an essential requirement for a numerical scheme. Designing such an algorithm, that is, as less dissipative as possible while being simple, for the resolution of variable density Navier–Stokes equations is the aim of the present work. The developed numerical scheme, based on a pressure correction technique, uses a Crank–Nicolson time discretization and a staggered space discretization relying on the Rannacher–Turek finite… Show more

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Cited by 5 publications
(13 citation statements)
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“…The computed maximum drag and lift coefficients and the Strouhal number are c D = 3.24, c L = 1.01 and St = 0.300; these values belong to the reference intervals determined from the benchmark exercise [26], namely (3.22, 3.24), (0.99, 1.01) and (0.295, 0.305) respectively. They are also close to the values obtained with an algorithm based on the same space discretization but solving the equations of the asymptotic model for low Mach number flows [4].…”
Section: A Low Mach Number Casesupporting
confidence: 81%
“…The computed maximum drag and lift coefficients and the Strouhal number are c D = 3.24, c L = 1.01 and St = 0.300; these values belong to the reference intervals determined from the benchmark exercise [26], namely (3.22, 3.24), (0.99, 1.01) and (0.295, 0.305) respectively. They are also close to the values obtained with an algorithm based on the same space discretization but solving the equations of the asymptotic model for low Mach number flows [4].…”
Section: A Low Mach Number Casesupporting
confidence: 81%
“…Second, the non-dissipation of the kinetic energy is a prerequisite for numerical schemes for Large Eddy Simulation (e.g. [32,8,31,3]), and a theoretical proof of this feature thus strongly supports this kind of application. Finally, for Euler's equations, having at hand a discrete kinetic energy balance has been a key point in [24,18] to derive a consistent staggered scheme preserving the convex set of admissible states.…”
Section: Introductionmentioning
confidence: 94%
“…preserving the kinetic energy balance [25,1,3]. These techniques, implemented in the open-source software ISIS [27], have brought many outcomes, both from the theoretical and the practical points of view.…”
Section: Introductionmentioning
confidence: 99%
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“…The computational domain is Ω = (−0.5, 0.5) 2 and the initial data consists in four constant states, in each of the four sub-squares of Ω obtained by splitting it along the lines joining the mid-points of each segment of the boundary (i.e. in Ω 1,1 = (−0.5, 0) × (0, 0.5), Ω 1,2 = (0, 0.5) 2 , Ω 2,1 = (−0.5, 0) 2 and Ω 2,2 = (0, 0.5) × (−0.5, 0)). These constant states are chosen in such a way that each associated onedimensional Riemann problem (i.e.…”
Section: A Two-dimensional Riemann Problemmentioning
confidence: 99%