A framework for predicting accuracy limitations in large-eddy simulation

By Bernard J. Geurts, Jochen Fröhlich. 2002

281 citations recorded by the source corpus.

Subfields: Atmospheric Science, Computational Mechanics

View Paper: https://www.semanticscholar.org/paper/198266f6c4b8dd3fb13a51736b5d2d2dabd4d138

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In Atmospheric Science

In Computational Mechanics

Citations in the corpus

A posteriori study using a DNS database describing fluid disintegration and binary-species mixing under supercritical pressure: heptane and nitrogen (2010, methodology): “This choice of IC at a time later than the DNS t∗ = 0 time station was also the approach of Geurts & Frohlich (2002) even though that flow did not display the strong non-uniformities manifested here in the HDGM regions.”
Database-analysis of errors in Large-Eddy Simulation (2003, background): “31.”
Regularization modeling for large-eddy simulation (2002, methodology): “At fixed ∆, variation of the subgrid resolution r allows an independent control over flow-smoothing and numerical representation [12].”
A new hybrid recursive regularised Bhatnagar–Gross–Krook collision model for Lattice Boltzmann method-based large eddy simulation (2018, methodology): “In the case, the regularised collision kernel is used in the ILES mode, the influence of the implicit subgrid dissipation can be evaluated thanks to the subgrid viscosity parameter s defined as [43] s = εσ εσ + εν , (53)”
Turbulence and energy budget in a self-preserving round jet: direct evaluation using large eddy simulation (2009, methodology): “…the present study, this dissipation is estimated explicitly from the LES fields, and to assess the importance of the filtering, we define, following Geurts & Fröhlich (2002), the subgrid activity parameter s = 〈 sf 〉〈 sf 〉 + 〈 μ〉 , (3.4) which represents also the filtering activity parameter in…”
The Effect of Mesh Resolution on Convective Boundary Layer Statistics and Structures Generated by Large-Eddy Simulation (2011, unknown): “The subgrid-scale model and numerical discretization errors are intertwined since both depend explicitly on the mesh spacing (Chow and Moin 2003; Meyers et al. 2007; Geurts and Fröhlich 2002).”
Large Eddy Simulations of gaseous flames in gas turbine combustion chambers (2012, background): “For example, if one accepts to change the value of the Smagorinsky constant noted CS, an optimal grid resolution CS pair exists which provides good quality predictions [193,194,196] at minimum cost and away from the DNS limit.”