arXiv subjects

Zhaorui Li

Publications and source records attributed to Zhaorui Li.

4 recordsLinked to original sources

arXiv2026

Scaling patch analysis of turbulent kinetic energy budget equation in wall-bounded flows

The scaling patch approach is applied to analyze the turbulent kinetic energy (TKE) budget equation in wall-bounded turbulent flows. The balance of the TKE equation is divided into several distinct regions, or scaling patches, each characterized by a dominant balance among the governing terms and its own appropriate scaling parameters. In the near-wall viscous sublayer, the TKE balance is primarily between viscous diffusion and dissipation, and the characteristic scales are set by the kinematic viscosity and the wall dissipation rate. The thickness of this sublayer is on the order of the Kolmogorov length scale. Moving away from the wall, the peak TKE production provides a natural reference scale for the inner layer, yielding the traditional inner scaling. Grouping the viscous diffusion and dissipation terms in the inner layer enhances the collapse across different Reynolds numbers. In the outer region, Prandtl's mixing-length model is used to derive a characteristic scale for TKE production. A new meso-scaling is further introduced to describe the intermediate region, ensuring a smooth transition between the inner and outer layers. The scaling patch framework offers a unified interpretation of the structure and scaling behavior of the TKE budget across all regions of wall-bounded turbulence.

physics.flu-dyn↗

arXiv2026

Natural Language based Specification and Verification

Recent frontier large language models (LLMs) have shown strong performance in identifying security vulnerabilities in large, mature open-source systems. As LLM-generated code becomes increasingly common, a natural goal is to prevent such models from producing vulnerable implementations in the first place. Formal verification offers a principled route to this objective, but existing verification pipelines typically require specifications written in rigid formal languages. Prior work has explored using LLMs to synthesize such specifications, with limited success. In this paper, we investigate a different approach: using LLMs both to generate specifications and to verify implementations compositionally when the specifications are expressed in natural language. Our preliminary results suggest that this approach is promising.

cs.SE↗

arXiv2022

Supersonic turbulent flows over sinusoidal rough walls

Direct numerical simulations were performed to characterize fully developed supersonic turbulent channel flows over isothermal rough walls. The effect of roughness was incorporated using a level-set/volume-of-fluid immersed boundary method. Turbulence statistics of five channel flows are compared, including one reference case with both walls smooth and four cases with smooth top walls and bottom walls with two-dimensional (2D) and three-dimensional (3D) sinusoidal roughnesses. Results reveal a strong dependence of the turbulence on the roughness topography and the associated shock patterns. Specifically, the 2D geometries generate strong oblique shock waves that propagate across the channel and are reflected back to the rough-wall side. These strong shocks are absent in the smooth-wall channel and are significantly weaker in cases with 3D roughness geometries, replaced by weak shocklets. At the impingement locations of the shocks on the top wall in the 2D roughness cases, localized augmentations of turbulence shear production are observed. Such regions of augmented production also exist for the 3D cases, at a much weaker level. The oblique shock waves are thought to be responsible for a more significant entropy generation for cases with 2D surfaces than those with 3D ones, leading to a higher irreversible heat generation and consequently higher temperature values in 2D roughness cases. In the present supersonic channels, the effects of roughness extend beyond the near-wall layer due to the shocks. This suggests that outer layer similarity may not fully apply to a rough-wall supersonic turbulent flow.

physics.flu-dyn↗

arXiv2020

Quantification of the Leakage in Federated Learning

With the growing emphasis on users' privacy, federated learning has become more and more popular. Many architectures have been raised for a better security. Most architecture work on the assumption that data's gradient could not leak information. However, some work, recently, has shown such gradients may lead to leakage of the training data. In this paper, we discuss the leakage based on a federated approximated logistic regression model and show that such gradient's leakage could leak the complete training data if all elements of the inputs are either 0 or 1.

cs.CR↗