2020
DOI: 10.1017/jfm.2019.1034
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Scaling of velocity fluctuations in statistically unstable boundary-layer flows

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Cited by 27 publications
(9 citation statements)
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“…The code was extensively utilized for thermally stratified boundary-layer flow calculations (see, e.g., Refs. [51][52][53][54][55][56][57][58], where we also validated the code for flows at both stratified and neutral conditions. It solves the filtered incompressible Navier-Stokes equations, under the Boussinesq approximation, and the filtered transport equation for the potential temperature in a half channel with height h,…”
Section: Computational Setupmentioning
confidence: 99%
See 1 more Smart Citation
“…The code was extensively utilized for thermally stratified boundary-layer flow calculations (see, e.g., Refs. [51][52][53][54][55][56][57][58], where we also validated the code for flows at both stratified and neutral conditions. It solves the filtered incompressible Navier-Stokes equations, under the Boussinesq approximation, and the filtered transport equation for the potential temperature in a half channel with height h,…”
Section: Computational Setupmentioning
confidence: 99%
“…where t is the time, P is the filtered pressure, Ũ is the filtered velocity, Θ is the filtered potential temperature, ρ is the fluid density, ν is the kinematic viscosity, D is the molecular diffusivity, Θ 0 is the reference temperature, τij = ŨiUj − Ũi Ũj is the subgrid-scale (SGS) stress, qi = ŨiΘ − Ũi Θ is the SGS heat flux, Fp is an imposed pressure gradient in the streamwise direction and is kept constant in time, uτ = √ Fph is the total/bulk friction velocity, S Θ = uτθτ/h is a source term for the potential temperature, 57,59,60 where θτ is the total/bulk surface temperature scale, i = 1, 2, and 3 are the streamwise (x), spanwise (y), and wall-normal (z) directions, respectively, δij is the Kronecker delta tensor, and the angle brackets represent a horizontal average. The SGS turbulent fluxes are modeled using the anisotropic minimum dissipation model (AMD).…”
Section: Computational Setupmentioning
confidence: 99%
“…Given the discussion on the generation and evolution of the coherent vortices, and our quantitative/qualitative study on the emergence of strong non-Gaussian statistical behavior for velocity and vorticity fluctuations, one can argue that such statistics are closely tied to and in other words, the direct result of generation and growth of coherent vortical structures due to the effect of the rotational symmetry-breaking factors. In prior studies, such connection was investigated and partially addressed in the contexts of planar mixing and free shear layers [90][91][92] , subgrid-scale (SGS) motions and their nonlocal modeling for homogeneous and wall-bounded turbulent flows 93,94 , boundary layer flows 95,96 , and turbulent flows interacting with wavy-like moving/actuated surfaces (with application to reduction and control of flow separation) 97,98 .…”
Section: Memory Effects In Vorticity Dynamics and Anomalous Time-scal...mentioning
confidence: 99%
“…A scaling that expresses one flow quantity as a function of another flow quantity – e.g. as a function of (Yang, Pirozzoli & Abkar 2020; Yang et al. 2022), or as a function of (where and are real numbers, and ) (Yang et al.…”
Section: Introductionmentioning
confidence: 99%
“…A scaling that expresses one flow quantity as a function of another flow quantity -e.g. u 2 as a function of Ū (Yang, Pirozzoli & Abkar 2020;Yang et al 2022), or exp(qu) as a function of exp( pu) (where p and q are real numbers, and p / = q) (Yang et al 2016) -are often considered weak scalings. We do not favour weak scalings because of possible error cancellation and error propagation.…”
Section: Introductionmentioning
confidence: 99%