scholarly journals Probabilistic comparison between turbulence closure model and Bulk Richardson Number approach for ABL height estimation using copula

2019 ◽  
Vol 87 ◽  
pp. 101094
Author(s):  
Shikhar Upadhyay ◽  
Sarit K. Das ◽  
C.S.P. Ojha
2010 ◽  
Vol 40 (6) ◽  
pp. 1243-1262 ◽  
Author(s):  
Hans Burchard ◽  
Robert D. Hetland

Abstract This numerical modeling study quantifies for the first time the contribution of various processes to estuarine circulation in periodically stratified tidal flow under the impact of a constant horizontal buoyancy gradient. The one-dimensional water column equations with periodic forcing are first cast into nondimensional form, resulting in a multidimensional parameter space spanned by the modified inverse Strouhal number and the modified horizontal Richardson number, as well as relative wind speed and wind direction and the residual runoff. The along-tide momentum equation is then solved for the tidal-mean velocity profile in such a way that it is equated to the sum of the contributions of tidal straining (resulting from the temporal correlation between eddy viscosity and vertical shear), gravitational circulation (resulting from the depth-varying forcing by a constant horizontal buoyancy gradient), wind straining, and depth-mean residual flow (resulting from net freshwater runoff). This definition of tidal straining does not only account for tidal asymmetries resulting from horizontal buoyancy gradients but also from wind straining and residual runoff. For constant eddy viscosity, the well-known estuarine circulation analytical solution with polynomial residual profiles is directly obtained. For vertically parabolic and constant-in-time eddy viscosity, a new analytic solution with logarithmic residual profiles is found, showing that the intensity of the gravitational circulation scales with the horizontal Richardson number. For scenarios with realistic spatially and temporally varying eddy viscosity, a numerical water column model equipped with a state-of-the-art two-equation turbulence closure model is applied to quantify the individual contributions of the various processes to estuarine circulation. The fundamental outcome of this study is that, for irrotational flow with periodic stratification and without wind forcing and residual runoff, the tidal straining is responsible for about two-thirds and gravitational circulation is responsible for about one-third of the estuarine circulation, proportionally dependent on the horizontal Richardson number, and weakly dependent on the Strouhal number. This new and robust result confirms earlier estimates by H. Burchard and H. Baumert, who suggested that tidal straining is the major generation mechanism for estuarine turbidity maxima. However, a sensitivity analysis of the model results to details of the turbulence closure model shows some uncertainty with respect to the parameterization of sheared convection during flood. Increasing down-estuary wind straining and residual runoff reduce the quantitative contribution of tidal straining. For relatively small horizontal Richardson numbers, the tidal straining contribution to estuarine circulation may even be reversed by down-estuary wind straining.


Author(s):  
Muhammad A. R. Sharif ◽  
Yat-Kit E. Wong

Abstract The performance of a nonlinear k-ϵ turbulence closure model (NKEM), in the prediction of isothermal incompressible turbulent flows, is compared with that of the stress transport models such as the differential Reynolds stress transport model (RSTM) and the algebraic stress transport model (ASTM). Fully developed turbulent pipe flow and confined turbulent swirling flow with a central non-swirling jet are numerically predicted using the Marker and Cell (MAC) finite difference method. Comparison of the prediction with the experiment show that all three models perform reasonably well for the pipe flow problem. For the swirling flow problem, the RSTM and ASTM is superior than the NKEM. RSTM and ASTM provide good agreement with measured mean velocity profiles. However, the turbulent stresses are over- or under-predicted. NKEM performs badly in prediction of mean velocity as well as the turbulent stresses.


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