Shallow turbulent mixing layers in open-channel flows

被引:0
|
作者
Proust, Sebastien [1 ]
Cerino, Bastien [1 ]
Berni, Celine [1 ]
Nikora, Vladimir I. [2 ]
机构
[1] INRAE, RiverLy, 5 Rue Doua CS 20244, F-69625 Villeurbanne, France
[2] Univ Aberdeen, Sch Engn, Aberdeen AB24 3UE, Scotland
基金
英国工程与自然科学研究理事会;
关键词
Shear layer; Shear layer turbulence; Bed-induced turbulence; Coherent structures; Secondary flows; Gravity currents; Vegetated flows; Confluences; Sediment mixing; Thermal mixing; LINEAR-STABILITY ANALYSIS; LARGE-SCALE MOTIONS; COHERENT STRUCTURES; SHEAR FLOWS; STREAM CONFLUENCES; SECONDARY CURRENTS; SUSPENDED SEDIMENT; PLANFORM GEOMETRY; DENSITY CURRENTS; VELOCITY RATIO;
D O I
10.1007/s10652-025-10013-9
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A mixing layer (ML) forms when two streams of different speeds or densities merge. MLs are ubiquitous in nature and can be often observed in the atmosphere, ocean, rivers, canals, lakes and reservoirs. This review paper focuses on the turbulent MLs developing in open-channel flows when the vertical size of the ML is smaller than its streamwise and spanwise dimensions. Such MLs are referred to as shallow MLs (SMLs). The SMLs often involve large-scale features such as quasi-two-dimensional coherent structures with a bed-normal axis, streamwise-oriented vortices, secondary currents, gravity currents, and bed-induced turbulent structures such as large- and very-large-scale motions. Considering various types of SMLs, we distinguish SMLs driven by (i) spanwise inhomogeneity of hydrodynamic parameters, (ii) lateral changes in flow resistance, and (iii) spanwise heterogeneity in fluid density. As SMLs and associated flow structures largely control transverse exchanges of various substances (e.g., sediments, pollutants, nutrients) and heat, the mixing of substances and thermal mixing are also addressed. Then, commonalities and differences among the various types of SMLs are identified. The paper is concluded with suggestions on future research efforts for advancing the knowledge on SMLs and capabilities for their predictions and control.
引用
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页数:51
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