Flow Characteristics in a Two-Stage Vegetated Compound Trapezoidal Channel

Pasha, Ghufran Ahmed; Ghumman, Abdul Razzaq; Naseer, Muhammad Junaid; Iqbal, Saman; Ahmed, Ashfaq

doi:10.1007/s40996-022-00904-y

Cited by 5 publications

(2 citation statements)

References 44 publications

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“…Anjum and Ali (2022) [41] examined the flow fields around circular and square-shaped plants in a vertically layered channel with both linear and staggered plant arrangements. Aydogdu (2023) [42] [43] examined how vegetation affects flow parameters and identified a complex flow pattern between the main channel and floodplains in two stages. Shan et al (2023) [44] measured velocity and TKE profiles within both the area where flow adjusts within the canopy and the fully developed flow region, using model plants with identical morphology to real P. australis.…”

Section: Introductionmentioning

confidence: 99%

Prediction performances of turbulence models in examining the flow characteristics of vegetated channels: CFD computations and experimentally validation

ŞİBİL

2024

Preprint

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The performance of turbulence models was investigated to predict the flow and turbulence features of the vegetated channel using Computational Fluid Dynamics (CFD). The Ansys Fluent, CFD software was implemented for the numerical studies. The flow was three-dimensional, incompressible, steady, and turbulent. Ten turbulence models, provided by Ansys Fluent were implemented for the comparative study. The numerical model was validated against an experimental study conducted in the literature. The numerical studies show that the renormalization group k-ε model (RNG) is the most successful model for predicting the flow characteristics of the vegetated channel with RMSE value of 0.2752. At the same time, the Reynolds Stress Model (RSM) gives the least successful predictive performance, indicated by an RMSE value of 0.4302. Moreover, the Spalart-Allmaras (S-A) model offers the shortest computation time with a value of 6652.393 sec, whereas the SST k-ω model proves to be the most time-consuming with a value of 11952.219 sec. The velocity of water flow in a channel is not uniform as it is slower at the surface of leaves and faster in the free zones. The maximum velocity is observed in the middle section of the channel, below the leaf, and between the roots with the value of u=0.1158 m/s. Furthermore, the characteristics of turbulence in a channel are influenced by various factors such as channel geometry, flow velocity, and vegetation distribution. As a result, the presence of vegetation in a channel affects the flow and turbulence characteristics of the water significantly.

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Section: Introductionmentioning

confidence: 99%

Prediction performances of turbulence models in examining the flow characteristics of vegetated channels: CFD computations and experimentally validation

ŞİBİL

2024

Preprint

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“…The flow characteristics around permeable dike with different staggered pore angles [12] and making a combination of circular cylinders with impermeable dike [13] were investigated using FLUENT (ANSYS). Moreover, FLUENT (ANSYS) was previously also used to investigate flow structure for vegetation [14][15]. El-Rashedy et al [16] experimentally investigated the scour mechanism around different head shapes (straight, Hockey, Mole, L shape, and T shape) of the spur.…”

Section: Introductionmentioning

confidence: 99%

Investigation of Flow Dynamics Around a Combination of Different Head Shapes of Spur Dikes

2022

Teh. vjesn.

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Spur dikes are widely used as river training structures throughout the globe to improve navigation, strengthen flood protection, and save erodible banks. This study investigates the flow behaviour of multiple spurs using similar and different head shapes instead of adding an extra structure. The novelty of the study lies in finding out the best combination of head shapes among circular (C), rectangular (R), and triangular (T) that can reduce the responsible factors of scouring and erosion. The responsible factors for scour and erosion include high magnitude velocity, pressure, turbulence kinetic energy (TKE), Reynold stresses, and wall shear stresses. Nine combinations (3 same, i.e., CCC, RRR, and TTT and six different, i.e., CRC, CTC, RCR, RTR, TCT, TRT) of spurs were investigated using Computational Fluid Dynamics (CFD) code FLUENT. Firstly, in the analysis of similar head shapes, more reduction in the values of scour and erosion responsible factors were observed in CCC combination (20% in velocity, 45% in pressure, 41% in TKE, and 43% in normal Reynold stresses). Finally, the reduction was further improved in analysing different head shapes. The CTC combination showed the most effective results in reducing the prescribed factors (43% in velocity, 57% in pressure, 51% in TKE, and 54% in normal Reynold stresses) compared to both combinations of head shapes. Therefore, to protect riverbank and spur head failure due to severe turbulent flow, the combination of spurs (CTC) could be preferred.

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3D numerical modelling and laboratory study of flow field induced by a group of submerged vegetations

John,

Pu,

Guo

et al. 2024

Ocean Engineering

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Flow Characteristics in a Two-Stage Vegetated Compound Trapezoidal Channel

Cited by 5 publications

References 44 publications

Prediction performances of turbulence models in examining the flow characteristics of vegetated channels: CFD computations and experimentally validation

Prediction performances of turbulence models in examining the flow characteristics of vegetated channels: CFD computations and experimentally validation

Investigation of Flow Dynamics Around a Combination of Different Head Shapes of Spur Dikes

3D numerical modelling and laboratory study of flow field induced by a group of submerged vegetations

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