Important Parameters for a Predictive Model of ks for Zero-Pressure-Gradient Flows

Abstract

To predict drag on a rough surface under turbulent flow conditions, practitioners rely on roughness correlations that map topographical features of the surface to the equivalent sand-grain roughness Ks However, details of the data that underpin these empirical correlations are not always immediately evident for comparison and discussion. Therefore, here we compile a table of roughness correlations with unified notation, in chronological order, listing the parameter ranges and the roughness types used in their development, noting idiosyncrasies. Overall, the table shows that tested roughness types have increased in generality from regular roughness elements to random surface elevations, and t..