arXiv subjects

Zifei Yin

Publications and source records attributed to Zifei Yin.

4 recordsLinked to original sources

arXiv2026

A field-equation semi-local transformation for compressible wall turbulence

Compressibility and wall heat transfer change the inner scaling of wall turbulence through the mean density and viscosity fields. Most semi-local transformations are applied after a wall-normal profile has been selected. Here the transformed coordinate and transformed velocity are defined by wall-anchored field equations before any profile is extracted. Wall density and friction velocity enter as boundary data for auxiliary field equations; the resulting reference density and friction velocity, together with the local density and viscosity, set the viscous scaling in the wall layer. The local logarithmic density contrast is introduced as a bounded correction to the coordinate-stretching factor. For weak density variation the corrected stretch follows the local inverse kinematic-viscosity variation, while the bounded form limits the influence of finite density contrasts. The transformed coordinate $Y^+$ and transformed velocity $\bm{U}^+$ are obtained from field equations using the corrected stretching and the mean viscous shear. In the constant-property limit the density contrast vanishes, $Y^+$ reduces to the ordinary wall coordinate and each transformed velocity component reduces to the conventional mean velocity component in wall units. For channel flows, the field equations are solved with wall boundary data and the extracted profiles retain their own wall origins. A cooled shock/boundary-layer interaction examines the response when the wall density and friction velocity vary in the streamwise direction. Across the cooled high-speed boundary layers considered here, the bounded density correction narrows the inner- and buffer-layer profile spread...

physics.flu-dyn↗

arXiv2026

Modification of the $k-ω_0$ model for roughness

Surface roughness plays a substantial role in many flows for which Reynolds averaged prediction is needed. The transformation used in the k-omega0 model is extended to rough surfaces by adding an effective origin. The log-layer offset is computed as a function of this effective origin, thereby creating a correspondence between effective origin and equivalent sandgrain roughness. A formula is derived for the virtual origin of the fully rough log law. It is shown how the present model is consistent with the fully rough limit.

physics.flu-dyn↗

arXiv2025

Data-driven detached-eddy simulations based on explicit algebraic stress expressions for turbulent flows

This work proposes a data-driven explicit algebraic stress-based detached-eddy simulation (DES) method. Despite the widespread use of data-driven methods in model development for both Reynolds-averaged Navier-Stokes (RANS) and large-eddy simulations (LES), their applications to DES remain limited. The challenge mainly lies in the absence of modelled stress data, the requirement for proper length scales in RANS and LES branches, and the maintenance of a reasonable switching behaviour. The data-driven DES method is constructed based on the algebraic stress equation. The control of RANS/LES switching is achieved through the eddy viscosity in the linear part of the modelled stress, under the $\ell^2-ω$ DES framework. Three model coefficients associated with the pressure-strain terms and the LES length scale are represented by a neural network as functions of scalar invariants of velocity gradient. The neural network is trained using velocity data with the ensemble Kalman method, thereby circumventing the requirement for modelled stress data. Moreover, the baseline coefficient values are incorporated as additional reference data to ensure reasonable switching behaviour. The proposed approach is evaluated on two challenging turbulent flows, i.e., the secondary flow in a square duct and the separated flow over a bump. The trained model achieves significant improvements in predicting mean flow statistics compared to the baseline model. This is attributed to improved predictions of the modelled stress. The trained model also exhibits reasonable switching behaviour, enlarging the LES region to resolve more turbulent structures. Furthermore, the model shows satisfactory generalization capabilities for both cases in similar flow configurations.

physics.flu-dyn↗

arXiv2025

Compressibility correction to the k-$ω$ turbulence model that considers the wall-cooling effect

In supersonic and hypersonic flows, the near-wall density variation due to wall cooling poses a challenge for accurately predicting the near-wall velocity and temperature profiles using classical eddy viscosity turbulence models. Compressible turbulent boundary layers are known to follow the universal wall law via semi-local transformation. However, developing a turbulence model that predicts a velocity profile, which, via semi-local transformation, follows the universal wall law, remains challenging. The current paper builds upon Danis-Durbin's practice of modifying the $ω$ equation and proposes a simple modification to the $k-ω$ two-equation model. The formulation of the proposed modification involves dimensional analysis and the proper selection of the local length scale. The newly introduced modification is used to modify the slope of the velocity profile starting from the viscous layer to above. It recovers a semi-local scaling of turbulent kinetic energy, viscosity, and eddy frequency, then achieves a very decent correction of the velocity profile in compressible turbulent channel flows, satisfying the universal wall law after applying Trettel \& Larsson's transformation. The proposed new $k-ω$ model can also improve the velocity and temperature predictions in strongly wall-cooled zero-pressure-gradient hypersonic turbulent boundary layers, compared to the original $k-ω$ model. Validation using the favorable and adverse pressure gradient boundary layers suggests that the model does not impose a negative effect on the original $k-ω$ model.

physics.flu-dyn↗