2007
DOI: 10.1080/14685240701420478
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Extension of Boussinesq turbulence constitutive relation for bridging methods

Abstract: Bridging methods for turbulence simulation are adaptive eddy-viscosity schemes based on the accuracy-on-demand paradigm, much like hybrid approaches. The object is to resolve more scales of motion than Reynolds-averaged Navier-Stokes (RANS) by suitably reducing the eddy viscosity as a function of grid spacing. Currently, there are two proposals for extending the RANS two-equation model with Boussinesq constitutive relation to bridging methods. In the first approach, it is suggested that the coefficient in the … Show more

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Cited by 20 publications
(11 citation statements)
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“…[3][4][5] In addition, the fixed point analysis of Girimaji et al 1 demonstrated that the PANS bridging approach recovers the correct energetics in homogeneous turbulence. Furthermore, the computational study of Lakshmipathy and Girimaji 6 demonstrated that PANS a posteriori results are consistent with a priori length-scale cut-off and viscosity reduction specifications. Since its initial formulation, the PANS method has been enhanced to include near-wall effects 7 and added fidelity in regions of resolution variation to address commutation error.…”
Section: Introductionsupporting
confidence: 50%
“…[3][4][5] In addition, the fixed point analysis of Girimaji et al 1 demonstrated that the PANS bridging approach recovers the correct energetics in homogeneous turbulence. Furthermore, the computational study of Lakshmipathy and Girimaji 6 demonstrated that PANS a posteriori results are consistent with a priori length-scale cut-off and viscosity reduction specifications. Since its initial formulation, the PANS method has been enhanced to include near-wall effects 7 and added fidelity in regions of resolution variation to address commutation error.…”
Section: Introductionsupporting
confidence: 50%
“…It is important to note that (16) only provides an estimate for the smallest value of F R that a given computational grid can support. A constraint for F R that is similar to (16) has also been proposed by Lakshmipathy and Girimaji [17]. However, rather than using the integral length scale l RANS for turbulence in the constraint for F R , Lakshmipathy and Girimaji argued alternatively for the use of the Taylor microscale as the characteristic length scale.…”
Section: Prnsmentioning
confidence: 92%
“…In consequence, the k and ε quantities used in our current PRNS approach should be interpreted as (estimates of) "RANS" quantities, which are subsequently used to determine the integral length scale l i required in our F R formulation [cf. (17), (18), and (21)]. From this perspective, the use of conventional RANS values for the turbulence closure coefficients in the k-ε model is justifiable.…”
Section: Prnsmentioning
confidence: 97%
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“…But, still these values need to be justified by a post simulation check, to know whether the desired physical resolution is achieved or not. Lakshmipathy and Girimaji [25] suggested the eddy viscosity recovery as the parameter to check the credentials of the calculated f k . They contended that, as the extent of the resolution is increased the value of the eddy viscosity should decrease.…”
Section: Validation Of Flow Dynamicsmentioning
confidence: 99%