2003
DOI: 10.1016/s0898-1221(03)90014-9
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Analysis of subgrid scale models

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Cited by 35 publications
(48 citation statements)
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“…The variability in space and time of the coefficient C in Equation can induce numerical instabilities. Therefore, it is customary to average over homogeneous direction and/or in time and to clip negative peaks of the subgrid scale viscosity. As for the averaging procedure, we notice that we cannot perform it, as it is commonly done in situations with statistically spatial homogeneity directions or temporal stationarity, due to the very different physical regimes that are present in our system both in space and time.…”
Section: Numerical Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…The variability in space and time of the coefficient C in Equation can induce numerical instabilities. Therefore, it is customary to average over homogeneous direction and/or in time and to clip negative peaks of the subgrid scale viscosity. As for the averaging procedure, we notice that we cannot perform it, as it is commonly done in situations with statistically spatial homogeneity directions or temporal stationarity, due to the very different physical regimes that are present in our system both in space and time.…”
Section: Numerical Resultsmentioning
confidence: 99%
“…The next steps will be the applications to different arterial districts (such as the aorta), the inclusion of fluid‐structure interaction to account for the vessel displacements and the test of turbulence models that take into account anisotropy effects …”
Section: Discussionmentioning
confidence: 99%
“…The resolved scales are obtained by introducing a spatial filter function, which removes the unresolvable small scales of turbulence. Of course, for the same physical conditions, the numerical cost of LES is expected to be much lower than that of direct numerical simulation [16].…”
Section: Governing Equations and Numerical Methodologymentioning
confidence: 99%
“…2,3 Due to the stochastic nature of SGS stresses, the consistent diagnostics of deterministic SGS models from a priori and a posteriori tests has been quite difficult. In addition, it has been reported [8][9][10] that high correlation coefficients observed in a priori tests of the scale similarity model, 6,11 mixed-type models, 6,12,13 and recently developed deconvolution based models 14,15 mostly come from deterministic correlations between the resolved subfilter scale stresses 16 and their approximations when formally invertible filters are adopted. On the other hand, in a posteriori tests, an actual LES with a SGS model is performed and statistics are compared with those from (filtered) DNS or experiment.…”
Section: Introductionmentioning
confidence: 99%