Confinement and Bed‐Friction Effects in Shallow Turbulent Mixing Layers

Chu, Vincent H.; Babarutsi, S.

doi:10.1061/(asce)0733-9429(1988)114:10(1257)

Cited by 159 publications

(162 citation statements)

References 11 publications

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“…It is also known from shallow mixing layer studies that flow confinement and bed roughness tend to constraint the lateral extent of the mixing layer (a decrease in H or an increase in bed roughness lead to a decrease in δ). Chu and Babarutsi (1988) suggested to normalise the shallow mixing layer width δ in the way δ * = δc f /(Hλ) where c f is the averaged bed friction coefficient across the mixing layer (c f = 0.5(c f 1 + c f 2 ) with c f i = τ b /(0.5ρU 2 i ), i ∈ {1, 2} and τ b the bed shear stress) and showed that for flows that are shallow enough the quantity δ * converges towards a constant value when going downstream (δ * max ≈ 0.13). In the following a similar normalisation of the mixing layer width as done by Chu and Babarutsi (1988) is carried out.…”

Section: Mixing Layer Widthmentioning

confidence: 99%

Compound channel flow with a longitudinal transition in hydraulic roughness over the floodplains

et al. 2017

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Transitions from submerged dense vegetation (meadow) to emergent rigid vegetation (wood) and vice versa are modelled using plastic grass and vertical wooden cylinders. For a given roughness transition, the upstream discharge distribution between main channel and floodplain (called subsections) is also varied, keeping the total flow rate constant. The flows with a roughness transition are compared to flows with a uniformly distributed roughness over the whole length of the flume. Besides the influence of the downstream boundary condition, the longitudinal profiles of water depth are controlled by the upstream discharge distribution. The latter also strongly influences the magnitude of the lateral net mass exchanges between subsections, especially upstream from the roughness transition. Irrespective of flow conditions, the inflection point in the mean velocity profile across the mixing layer is always observed at the interface between subsections. The longitudinal velocity at the main channel/floodplain interface, denoted U int , appeared to be a key parameter for characterising the flows. First, the mean velocity profiles across the mixing layer, normalised using U int , are superimposed irrespective of downstream position, flow depth, floodplain roughness type and lateral mass transfers. However, the profiles of turbulence quantities do not coincide, indicating that the flows are not fully self-similar and that the eddy viscosity assumption is not valid in this case. Second, the depth-averaged turbulent intensities and Reynolds stresses, when scaled by the depth-averaged velocity U d,int exhibit two plateau values, each related to a roughness type, meadow or wood. Lastly, the same results hold when scaling by U d,int the depth-averaged lateral flux of momentum due to secondary currents. Turbulence production and magnitude of secondary currents are increased by the presence of emergent rigid elements over the floodplains. The autocorrelation functions show that the length of the coherent structures scales with the mixing layer width for all flow cases. It is suggested that coherent structures tend to a state where the magnitude of velocity fluctuations (of both horizontal vortices and secondary currents) and the spatial extension of the structures are in equilibrium.

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Section: Mixing Layer Widthmentioning

confidence: 99%

Compound channel flow with a longitudinal transition in hydraulic roughness over the floodplains

et al. 2017

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“…Polystyrene was too light; the airflow above the surface had too big an influence on the floating particles. Polyethylene (PE) and Polypropylene (PP) have a density of 0.9 g/cm 3 , which worked very well.…”

Section: Elements Of the Measuring Systemmentioning

confidence: 99%

“…Shallow flow phenomena can be found in rivers, coastal zones or the atmosphere, where the dominating processes are two-dimensional [1]. Large coherent motions, that are inititated, for instance, in shallow wake flows behind obstacles [2] or in shallow mixing layers [3][4][5] strongly influence the dynamics of such a system and are, therefore, a determining factor for the mixing and transport processes. Measurement of the velocity field describing the generation and the evolution of these coherent motions is the major aim of this investigation.…”

Section: Introductionmentioning

confidence: 99%

Large scale PIV-measurements at the surface of shallow water flows

Weitbrecht

Kühn

Jirka

2002

Flow Measurement and Instrumentation

124

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“…Although the scales of the 3D bottom turbulence and the quasi 2D turbulence are rather disparate, the energy balance of the turbulence is governed by both. Previous studies on shallow shear flows [5,7,31] have indicated that the dynamics of the quasi 2D turbulence in combination with 3D turbulence is not well understood and difficult to represent in an efficient model. [34].…”

Section: The Shallow Mixing Layermentioning

confidence: 99%

“…The arrows indicate the mean streamwise velocity 1.2 Linear behaviour of unstable flows in a shallow mixing layer A study by [33] has revealed that the spectral distribution of the large scale motions of a shallow mixing layer can be predicted from a linear stability analysis. First, the mean flow was predicted, based on the self-similarity method proposed by [5]. This resulted in the transverse profiles of the mean streamwise velocity.…”

Section: The Shallow Mixing Layermentioning

confidence: 99%

The Relevance of a Back-Scatter Model for Depth-Averaged Flow Simulation

Prooijen

Uijttewaal

2008

Flow Turbulence Combust

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This study demonstrates the importance of a sophisticated sub-grid model when performing a depth-averaged unsteady RANS simulation of a shallow flow. The reduction of resolution and the spatial dimensions exclude important physical processes as present in three-dimensional turbulence. Especially the effect of the bottom turbulence on the formation of horizontal eddies appears of key importance. A method is proposed to incorporate these effects by means of a kinematic simulation that mimics the residual turbulent fluctuations in a straight channel flow after depthaveraging. This method is developed in the context of the evolution of large eddies in a shallow mixing layer. A comparison with experiments shows that the proposed method works satisfactory. Naturally, it does not fully account for the omission of all 3D-effects.

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Confinement and Bed‐Friction Effects in Shallow Turbulent Mixing Layers

Cited by 159 publications

References 11 publications

Compound channel flow with a longitudinal transition in hydraulic roughness over the floodplains

Compound channel flow with a longitudinal transition in hydraulic roughness over the floodplains

Large scale PIV-measurements at the surface of shallow water flows

The Relevance of a Back-Scatter Model for Depth-Averaged Flow Simulation

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