SPH modelling of depth‐limited turbulent open channel flows over rough boundaries

Kazemi, Ehsan; Nichols, Andrew; Tait, Simon; Shao, Songdong

doi:10.1002/fld.4248

Cited by 48 publications

(19 citation statements)

References 51 publications

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“…κ = 0.41 is the Von Kármán constant, y is the distance from the wall, l max is a cutoff maximum value and the damping function in the first factor of the RHS avoids a non-physical growth of l near the free-surface when the particle distribution is irregular and the SPH evaluation of the gradient of a constant function departs sharply from zero: this function plays therefore a different role than the one of a wake function, such as the one included in the mixing-length model by [69] to simulate turbulent, open-channel uniform flows; the use of a wake function was not considered here because relevant turbulence effects occur mostly close to the hydraulic jump, where the flow conditions are in any case far from uniform; (2) A SPH version of the standard k-ε turbulence model by [70], in which µ T = c µ k 2 ε and the two equations for the turbulent kinetic energy k and for the turbulent dissipation rate ε are:…”

Section: Sph Numerical Methodsmentioning

confidence: 99%

SPH Modelling of Hydraulic Jump Oscillations at an Abrupt Drop

Padova

Mossa

Sibilla

2017

Water

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This paper shows the results of the numerical modelling of the transition from supercritical to subcritical flow at an abrupt drop, which can be characterised by the occurrence of oscillatory flow conditions between two different jump types. Weakly-Compressible Smoothed Particle (WCSPH) model was employed and both an algebraic mixing-length model and a two-equation model were used to represent turbulent stresses. The purpose of this paper is to obtain through the SPH model a deeper understanding of the physical features of a flow, which is, in general, difficult to be reproduced numerically, owing to its unstable character. In particular, the experience already gained in SPH simulations of vorticity-dominated flows allows one to assess the fluctuations of hydrodynamic characteristics of the flow field, (e.g., free surface profile downstream of the jump, velocity, pressure and vorticity). Numerical results showed satisfactory agreement with measurements and most of the peculiar features of the flow were qualitatively and quantitatively reproduced.

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Section: Sph Numerical Methodsmentioning

confidence: 99%

SPH Modelling of Hydraulic Jump Oscillations at an Abrupt Drop

Padova

Mossa

Sibilla

2017

Water

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“…Conversely, in the Marañon lowland, the Ecuadorian tributaries supply al- most 55 % of the water discharge and could significantly contribute to the river sediment load. The Napo River example (Laraque et al, 2009;Armijos et al, 2013) shows that the lowland part of the basin can be the main sediment source for these Ecuadorian tributaries. The river incision of this secondary source, and/or the Ecuadorian Andes, could provide coarser elements than the central Andean source does and explain why the ratios α are higher at BEL and REG than at the other sites.…”

Section: Index Concentration Relations Calibrated For Surface Index Smentioning

confidence: 99%

An index concentration method for suspended load monitoring in large rivers of the Amazonian foreland

et al. 2019

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Abstract. Because increasing climatic variability and anthropic pressures have affected the sediment dynamics of large tropical rivers, long-term sediment concentration series have become crucial for understanding the related socioeconomic and environmental impacts. For operational and cost rationalization purposes, index concentrations are often sampled in the flow and used as a surrogate of the cross-sectional average concentration. However, in large rivers where suspended sands are responsible for vertical concentration gradients, this index method can induce large uncertainties in the matter fluxes. Assuming that physical laws describing the suspension of grains in turbulent flow are valid for large rivers, a simple formulation is derived to model the ratio (α) between the depth-averaged and index concentrations. The model is validated using an exceptional dataset (1330 water samples, 249 concentration profiles, 88 particle size distributions and 494 discharge measurements) that was collected between 2010 and 2017 in the Amazonian foreland. The α prediction requires the estimation of the Rouse number (P), which summarizes the balance between the suspended particle settling and the turbulent lift, weighted by the ratio of sediment to eddy diffusivity (β). Two particle size groups, fine sediments and sand, were considered to evaluate P. Discrepancies were observed between the evaluated and measured P, which were attributed to biases related to the settling and shear velocities estimations, but also to diffusivity ratios β≠1. An empirical expression taking these biases into account was then formulated to predict accurate estimates of β, then P (ΔP=±0.03) and finally α. The proposed model is a powerful tool for optimizing the concentration sampling. It allows for detailed uncertainty analysis on the average concentration derived from an index method. Finally, this model could likely be coupled with remote sensing and hydrological modeling to serve as a step toward the development of an integrated approach for assessing sediment fluxes in poorly monitored basins.

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“…Thus, bedforms locally modify the ratio between the laminar and turbulent stresses, inducing different lifting profile shapes in the inner region (e.g. Kazemi et al, 2017) and causing the mixing length theory to fail in the overlap region.…”

Section: Estimation Of the Diffusivity Ratiomentioning

confidence: 99%

An index concentration method for suspended load monitoring in large rivers of the Amazonian foreland

Santini¹,

Camenen²,

Coz³

et al. 2019

Preprint

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Because increasing climatic variability and anthropic pressures have affected the sediment dynamics of large tropical rivers, long-term sediment concentration series have become crucial for understanding the related socio-economic and environmental impacts. For operational and cost rationalization purposes, index concentrations are often sampled in the flow and used as a surrogate of the cross-sectional average concentration. However, in large rivers where suspended sands are responsible for vertical concentration gradients, this index method can induce large uncertainties in the matter fluxes. 20Assuming that physical laws describing the suspension of grains in turbulent flow are valid for large rivers, a simple formulation is derived to model the ratio ( ) between index and average concentrations. The model is validated using an exceptional dataset (1330 water samples, 249 concentration profiles, 88 particle size distributions (PSDs) and 494 discharge measurements) that was collected between 2010 and 2017 in the Amazonian foreland. The prediction requires the estimation of the Rouse number ( ), which summarizes the balance between the suspended particle settling and the turbulent lift, weighted 25 by the ratio of sediment to eddy diffusivity ( ). Two particle size groups, washload and sand, were considered to evaluate .Discrepancies were observed between the evaluated and measured , that were attributed to biases related to the settling and shear velocities estimations, but also to diffusivity ratios ≠ 1. An empirical expression taking into account these biases was then formulated to predict accurate estimates of , then (∆ = ±0.03) and finally .The proposed model is a powerful tool for optimizing the concentration sampling. It allows for detailed uncertainty analysis 30 on the average concentration derived from an index method. Finally, this model can be coupled with remote sensing and hydrological modeling to serve as a step toward the development of an integrated approach for assessing sediment fluxes in poorly monitored basins.Earth Surf. Dynam. Discuss., https://doi.

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SPH modelling of depth‐limited turbulent open channel flows over rough boundaries

Cited by 48 publications

References 51 publications

SPH Modelling of Hydraulic Jump Oscillations at an Abrupt Drop

SPH Modelling of Hydraulic Jump Oscillations at an Abrupt Drop

An index concentration method for suspended load monitoring in large rivers of the Amazonian foreland

An index concentration method for suspended load monitoring in large rivers of the Amazonian foreland

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