Martina Formichetti | Searcharxiv

arXiv2026

Assimilating rough features: A data-driven framework to infer rough wall properties from sparse experimental data

Surface roughness influences turbulent boundary layers (TBLs) primarily through the roughness function $\Delta U^+$ and the equivalent sand-grain roughness height $k_s$. Direct determination of $k_s$ typically requires detailed velocity and wall-shear stress measurements, which are often impractical. As an alternative, this study presents a data assimilation framework that modifies a smooth-wall Reynolds-Averaged Navier-Stokes (RANS) baseline to match sparse rough-wall particle image velocimetry (PIV) data in the fully rough regime. Through this approach, secondary variables such as the friction velocity, $u_\tau$, and $k_s$ can be inferred from the assimilated flow fields. The assimilated TBL reproduces experimental velocity profiles within 1\% and predicts friction velocity within 1-6\% of the experimental measurements. Furthermore, the $k_s$ values inferred from the assimilation also match the experimental data up to 1\%. These results demonstrate the potential of data assimilation as a cost-effective alternative to high-fidelity methods and support the generalisation of the framework to model streamwise-varying roughness by treating $k_s$ as a function of fetch length.

physics.flu-dyn↗

arXiv2024

Effects of fetch length on turbulent boundary layer recovery past a step-change in surface roughness

Recent studies focusing on the response of turbulent boundary layers (TBL) to a step-change in roughness have provided insight into the scaling and characterisation of TBLs and the development of the internal layer. Although various step-change combinations have been investigated, ranging from smooth-to-rough to rough-to-smooth, the "minimum" required roughness fetch length over which the TBL returns to its homogeneously rough behaviour remains unclear. Moreover, the relationship between a finite- and infinite-fetch roughness function (and the equivalent sandgrain roughness) is also unknown. In this study, we determine the minimum "equilibrium fetch length" for TBL developing over a smooth-to-rough step-change as well as the expected error in local skin friction if the fetch length is under this minimum threshold. An experimental study is carried out where the flow is initially developed over a smooth wall, and then a step-change is introduced using patches of P24 sandpaper. 12 roughness fetch lengths are tested in this study, systematically increasing from $L = 1\delta_2$ up to $L = 39\delta_2$ (where \textit{L} is the roughness fetch length and $\delta_2$ is the TBL thickness of the longest fetch case), measured over a range of Reynolds numbers ($4\cdot10^2 \leq Re_\tau \leq 2\cdot10^5$). Results show that the minimum fetch length needed to achieve full equilibrium recovery is around $20\delta_2$. Furthermore, we observe that $C_f$ recovers to within 10\% of its recovered value for fetch lengths $\geq 5\delta_2$. This information allows us to incorporate the effects of roughness fetch length on the skin friction and roughness function.

physics.flu-dyn↗