Abstract
Laboratory experiments were conducted to study the effect of locally enhanced bottom roughness in a density-stratified two-layer flow down a slope. Three bottom roughness configurations were investigated, a smooth bed and two artificially roughened beds, employing sparse and dense roughness elements, respectively. The bottom roughness elements have shown to affect differently the generation and collapse mechanisms of large-scale two-dimensional structures observed at the interface between the two layers: dense bottom roughness inhibits the generation of large-scale structures while sparse bottom roughness inhibits their collapsing mechanism. Both bottom roughness configurations cause a reduction of the size of the large structures at the interface as compared to the smooth case. Two main sources of entrainment have been identified, namely the observed large-scale structures at the interface and enhanced bottom roughness. Sparse bottom roughness gives the lowest entrainment coefficients among the three cases due to the low interaction between the bottom boundary layer and the interface.
Highlights
Two-layer density stratified flows are commonly observed in the oceans, in lakes and in the atmosphere
Three different types of bottom roughness configurations have been used in the experiments, namely a smooth bottom and a sparse and a dense distribution of bottom roughness
By dimensional analysis of the vorticity equation, three parameters have been defined, in order to analyze the weight of each contribution of vorticity
Summary
Two-layer density stratified flows are commonly observed in the oceans, in lakes and in the atmosphere Examples of such flows in the oceanographic context include the two-layer flow in the Strait of Gibraltar exchanging the water mass between the Mediterranean sea and the North. At the interface of two-layer flows small-scale instabilities, like Kelvin–Helmholtz instabilities as well as large-scale instabilities have been observed (Sherwin and Turrell, 2005; Negretti et al, 2007). Understanding of these flow processes is crucial in predicting vertical transport of heat, oxygen, nutrients and pollutants in inland water bodies, oceans, and the atmosphere. In metereology for example, it has been estimated that instability and mixing causes a 50% increase in the drag of atmospheric flows and the study of shear instabilities in these flows is important for atmospheric flow modeling and weather forecasting (Afanasyev and Peltier, 2001)
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