Second-Order Closure Study of Open-Channel Flows

Čokljat, Davor; Younis, Bassam A.

doi:10.1061/(asce)0733-9429(1995)121:2(94)

Cited by 77 publications

(55 citation statements)

References 17 publications

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“…This model has provided accurate results in many cases (see [58]) for mean-flow variables and turbulence statistics. However, the model has been found to be not completely adequate for solving certain aspects of highly anisotropic flows such as the flows in compound channels, meandering channels in which curvature effects are important, vegetated channels, and swirling flows; in those cases the RSM becomes a more accurate tool [15,16,35,59,63,75]. The RSM has been recently shown to improve also the predictions of shear stresses and some turbulence statistics in wall-bounded flows [33] and open-channel flows with vegetation [15].…”

Section: Some Recent Contributions On Turbulence Closuresmentioning

confidence: 99%

Two-phase modeling of turbulence in dilute sediment-laden, open-channel flows

Jha

Bombardelli

2009

Environ Fluid Mech

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In this paper, we focus on assessing the performance of diverse turbulence closures in the simulation of dilute sediment-laden, open-channel flows. To that end, we base our analysis on a framework developed in a companion paper of this special issue, which puts forward a standard sediment transport model (SSTM), a partial two-fluid model (PTFM) and a complete two-fluid model (CTFM), in three-and one-dimensional (3D and 1D) versions. First, we propose in this paper extensions of the transport equations for the Reynolds stresses, and of the equations of the K-ω model to two-phase flows, starting from the general two-fluid model. We consider the drag force to be the predominant force amongst all the interactions between the two phases (water and sediment). Second, under the framework of models formed by the SSTM, the PTFM and the CTFM, we discuss simulation results obtained by employing the Reynolds stress model (RSM), the algebraic stress model (ASM), and the K-ε and the K-ω models (in their standard and extended versions), paired with each member of the framework. To assess the accuracy of the models, we compare numerical results with the experimental datasets of Vanoni, Trans ASCE 111:67-133, 1946 available data, and we provide an explanation for the variation of the Schmidt number with the ratio of the fall velocity and the wall-friction (shear) velocity. Finally, we corroborate that the Schmidt number is the key parameter to obtain satisfactory predictions of sediment transport in suspension.

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Section: Some Recent Contributions On Turbulence Closuresmentioning

confidence: 99%

Two-phase modeling of turbulence in dilute sediment-laden, open-channel flows

Jha

Bombardelli

2009

Environ Fluid Mech

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“…The relative importance of these two issues for flow in natural gravel-bed rivers has yet to be evaluated. Simulation of turbulence-driven secondary circulation in straight ducts and channels demands the use of a full Reynolds stress model (Naot and Rodi, 1982;Cokljat and Younis, 1995). However, simpler twoequation turbulence models have been found to yield acceptable results for flow over regular bedforms (Patel and Yoon, 1995;Cokljat and Kralj, 1997), and have been widely employed in natural channels with complex configurations where turbulence anisotropy has been deemed a less significant control on flow hydraulics (cf.…”

Section: Introductionmentioning

confidence: 99%

Computational fluid dynamics modelling of boundary roughness in gravel‐bed rivers: an investigation of the effects of random variability in bed elevation

Nicholas

2001

Earth Surf Processes Landf

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Results from a series of numerical simulations of two-dimensional open-channel flow, conducted using the computational fluid dynamics (CFD) code FLUENT, are compared with data quantifying the mean and turbulent characteristics of openchannel flow over two contrasting gravel beds. Boundary roughness effects are represented using both the conventional wall function approach and a random elevation model that simulates the effects of supra-grid-scale roughness elements (e.g. particle clusters and small bedforms). Results obtained using the random elevation model are characterized by a peak in turbulent kinetic energy located well above the bed (typically at y/h = 0Á1-0Á3). This is consistent with the field data and in contrast to the results obtained using the wall function approach for which maximum turbulent kinetic energy levels occur at the bed. Use of the random elevation model to represent supra-grid-scale roughness also allows a reduction in the height of the near-bed mesh cell and therefore offers some potential to overcome problems experienced by the wall function approach in flows characterized by high relative roughness. Despite these benefits, the results of simulations conducted using the random elevation model are sensitive to the horizontal and vertical mesh resolution. Increasing the horizontal mesh resolution results in an increase in the near-bed velocity gradient and turbulent kinetic energy, effectively roughening the bed. Varying the vertical resolution of the mesh has little effect on simulated mean velocity profiles, but results in substantial changes to the shape of the turbulent kinetic energy profile. These findings have significant implications for the application of CFD within natural gravel-bed channels, particularly with regard to issues of topographic data collection, roughness parameterization and the derivation of mesh-independent solutions.

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“…The shear stress distribution on the bed of the main channel predicted by the ve introduced models is shown in Figure 10 and compared with Cokljat and Younis' experimental data [27]. Figure 10 indicates that the KPM and YLM models predicted a similar shear stress distribution pattern for the main channel bed that is contrary to laboratorial outcomes.…”

Section: Shear Stress On the Main Channel Bedmentioning

confidence: 95%

“…All these geometrical models are also compared with each other and the most appropriate model in predicting shear stress is introduced. To verify the results, the laboratorial outcomes obtained by Rajaratnam and Ahmadi [25], Myers and Elsawy [26], and Cokljat and Younis [27] are utilized. …”

Section: Introductionmentioning

confidence: 99%

Comparison of five different models in predicting the shear stress distribution in straight compound channels

Khozani¹,

Bonakdari

2016

Scientia Iranica

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. SKM performed adequately in predicting the pattern of shear stress distribution on the main channel bed, but on a oodplain bed; it predicted a constant value over the entire wetted perimeter. The SKM method outperformed YLM and KPM with 2 to 20% MAPE. The ZAM and BAM methods produced the best results for shear stress distribution in compound channels with average MAPE of 2.67 and 5.66% MAPE , respectively. Although ZAM showed more accurate results than BAM, however, BAM required solving much fewer equations than ZAM and presented more accurate results than other geometric methods. Among all models, BAM is proposed as a simple and accurate model for predicting the shear stress distribution in compound channels.

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Second-Order Closure Study of Open-Channel Flows

Cited by 77 publications

References 17 publications

Two-phase modeling of turbulence in dilute sediment-laden, open-channel flows

Two-phase modeling of turbulence in dilute sediment-laden, open-channel flows

Computational fluid dynamics modelling of boundary roughness in gravel‐bed rivers: an investigation of the effects of random variability in bed elevation

Comparison of five different models in predicting the shear stress distribution in straight compound channels

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