Comparison of turbulence schemes for prediction of wave-induced near-bed sediment suspension above a plane bed |
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Authors: | Chi Zhang Jin-hai Zheng Yi-gang Wang Meng-tao Zhang Dong-sheng Jeng Ji-sheng Zhang |
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Institution: | ZHANG Chi a,b,ZHENG Jin-hai a,1,WANG Yi-gang b,ZHANG Meng-tao b,JENG Dong-sheng c,d and ZHANG Ji-sheng d a State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering,Hohai University,Nanjing 210098,China b College of Harbor,Coastal and Offshore Engineering,China c Center for Marine Geotechnical Engineering Research,Shanghai Jiao Tong University,Shanghai 200240,China d Division of Civil Engineering,University of Dundee,Dundee DD1 4HN,Uni... |
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Abstract: | Based on a wave bottom boundary layer model and a sediment advection-diffusion model, seven turbulence schemes are compared
regarding their performances in prediction of near-bed sediment suspension beneath waves above a plane bed. These turbulence
algorithms include six empirical eddy viscosity schemes and one standard two-equation k-? model. In particular, different combinations of typical empirical formulas for the eddy viscosity profile and for the wave
friction factor are examined. Numerical results are compared with four laboratory data sets, consisting of one wave boundary
layer hydrodynamics experiment and three sediment suspension experiments under linear waves and the Stokes second-order waves.
It is shown that predictions of near-bed sediment suspension are very sensitive to the choices of the empirical formulas in
turbulence schemes. Simple empirical turbulence schemes are possible to perform equally well as the two-equation k-? model. Among the empirical schemes, the turbulence scheme, combining the exponential formula for eddy viscosity and Swart
formula for wave friction factor, is the most accurate. It maintains the simplicity and yields identically good predictions
as the k-? model does in terms of the wave-averaged sediment concentration. |
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Keywords: | sediment transport wave boundary layer turbulence scheme |
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