Capturing the Reynolds number dependence of subconvective wall pressure fluctuations

Wall‑pressure fluctuations beneath turbulent boundary layers drive noise and structural fatigue through interactions between fluid and structural modes. Conventional models–such as the widely accepted Goody model–fail to capture the energetic growth in the subconvective regime.

This talk begins by proposing a semi-empirical model for ϕ_pp in canonical turbulent boundary layers, pipes and channels for high frictional Reynolds number (δ⁺). The model expresses the premultiplied spectrum as the sum of two overlapping log-normal-eddy populations: an inner-scaled term that is δ⁺-invariant and an outer-scaled term whose amplitude broadens smoothly with δ⁺. Our model reproduces the convective ridge and the emergence of a sub-convective ridge at large δ⁺. The model outperforms the widely adopted Goody model at high $\Rt$ and captures the full spectrum and the logarithmic growth of its variance, laying the groundwork for more accurate engineering predictions of wall-pressure fluctuations.

A theoretical basis for the growth of the subconvective wall-pressure fluctuations is developed by considering the three-component split of the pressure-Poisson equation into it’s Linear (Fast), Nonlinear (Slow), and Viscous (Stokes) terms. We investigate the makeup of these source terms using time-resolved data from a channel flow DNS at δ⁺ = 550 to understand the potential source of energetic growth of the wall-pressure spectra in the subconvective regime. Experimental data up to δ⁺> 10,000 are used to examine the Reynolds dependencies suggested by the DNS analysis.