Near-wall model for compressible turbulent boundary layers based on an inverse velocity transformation
- Stanford Univ., CA (United States); National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Hong Kong University of Science and Technology (HKUST) (Hong Kong)
- Stanford Univ., CA (United States)
In this work, a near-wall model, which couples the inverse of a recently developed compressible velocity transformation (Griffin et al., Proc. Natl Acad. Sci., vol. 118, 2021, p. 34) and an algebraic temperature–velocity relation, is developed for high-speed turbulent boundary layers. As input, the model requires the mean flow state at one wall-normal height in the inner layer of the boundary layer and at the boundary-layer edge. As output, the model can predict mean temperature and velocity profiles across the entire inner layer, as well as the wall shear stress and heat flux. The model is tested in an a priori sense using a wide database of direct numerical simulation high-Mach-number turbulent channel flows, pipe flows and boundary layers (48 cases, with edge Mach numbers in the range 0.77–11, and semi-local friction Reynolds numbers in the range 170–5700). The present model is significantly more accurate than the classical ordinary differential equation (ODE) model for all cases tested. The model is deployed as a wall model for large-eddy simulations in channel flows with bulk Mach numbers in the range 0.7–4 and friction Reynolds numbers in the range 320–1800. When compared to the classical framework, in the a posteriori sense, the present method greatly improves the predicted heat flux, wall stress, and temperature and velocity profiles, especially in cases with strong heat transfer. In addition, the present model solves one ODE instead of two, and has a computational cost and implementation complexity similar to that of the commonly used ODE model.
- Research Organization:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC); USDOE National Nuclear Security Administration (NNSA); Exascale Computing Project (ECP)
- Grant/Contract Number:
- AC36-08GO28308
- OSTI ID:
- 2280665
- Report Number(s):
- NREL/JA--2C00-86886; MainId:87661; UUID:859c290d-412c-47a0-a933-d0bd0c2b73d2; MainAdminID:71427
- Journal Information:
- Journal of Fluid Mechanics, Journal Name: Journal of Fluid Mechanics Vol. 970; ISSN 0022-1120
- Publisher:
- Cambridge University PressCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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