High-resolution spatiotemporal measurement of wall shear stress (WSS, τw) in turbulent boundary layers represents a fundamental challenge in fluid mechanics and is essential for understanding drag generation mechanisms. This study introduces the Polar Coordinate System Similarity-based Particle Image Stratification Algorithm (PCSS-PISA), a non-intrusive method for precise WSS determination within the viscous sublayer. Using particle image velocimetry, PCSS-PISA stratifies particle velocities into distinct wall-normal sublayers via equiprobable partitioning, achieving spatial resolutions of Δx+≈4.5, Δz+≈1.1, and a temporal resolution of ΔT+≈0.11. The method resolves near-wall velocity gradients with high accuracy by analyzing the stratified velocity distribution. Validated against direct numerical simulation data at Reτ=360, the method yields WSS fields with errors below 10%. Measurements reveal clustering of positive WSS streaks in the streamwise–spanwise plane, correlated with near-wall coherent vortical structures. Premultiplied spectral analysis identifies small-scale turbulent structures (λx+≈200, λz+≈50) alongside larger buffer-layer streaks, indicating multi-scale turbulence organization. Statistical analysis shows positive skewness in WSS fluctuations, driven by extreme positive events, and strong streamwise alignment of the WSS vector (Ψ≈0°). A consistent convection velocity (Uc/uτ¯≈11) across Reτ=415,526,601 supports the method's robustness. PCSS-PISA provides a powerful tool for elucidating WSS dynamics and advancing turbulence modeling and drag reduction strategies.
Chen et al. (Fri,) studied this question.
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