Analysis of open channel flow with various layered vegetation using CFD, considering different near-wall treatment methods

Şibil, Rahim

doi:10.1108/hff-11-2023-0704

Cited by 3 publications

(1 citation statement)

References 67 publications

(112 reference statements)

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“…Asif et al (2024b) [46] explored the flow attributes and turbulence features within open channel conditions by employing computational methods, focusing on vegetation patches characterized by both irregular and a vertical double-layer structure. Şibil (2024) [47] investigated near-wall treatment methods in a numerical study to predict the flow structures in a vegetated channel. Also, some studies in the other fields of hydraulics such as pipe flow, investigate the performance of turbulence models for flows through rough pipes [48] and comparison of turbulence models in simulating swirling pipe flows [49].…”

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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Evaluation of turbulence models for the prediction of flow properties in vegetated channels

Sibil (Şibil)

2024

Physics of Fluids

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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 is the most successful model for predicting the flow characteristics of the vegetated channel with a Root Mean Square Error (RMSE) value of 0.2752. At the same time, the Reynolds Stress Model 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 s, whereas the Shear Stress Transport k–ω model proves to be the most time-consuming with a value of 11 952.219 s. 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 several 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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Integrating forecasting methods to support finite element analysis and explore heat transfer complexities

Fatima,

Kim,

Lei

et al. 2024

HFF

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Purpose This paper aims to reduce the cost of experiments required to test the efficiency of materials suitable for artificial tissue ablation by increasing efficiency and accurately forecasting heating properties. Design/methodology/approach A two-step numerical analysis is used to develop and simulate a bioheat model using improved finite element method and deep learning algorithms, systematically regulating temperature distributions within the hydrogel artificial tissue during radiofrequency ablation (RFA). The model connects supervised learning and finite element analysis data to optimize electrode configurations, ensuring precise heat application while protecting surrounding hydrogel integrity. Findings The model accurately predicts a range of thermal changes critical for optimizing RFA, thereby enhancing treatment precision and minimizing impact on surrounding hydrogel materials. This computational approach not only advances the understanding of thermal dynamics but also provides a robust framework for improving therapeutic outcomes. Originality/value A computational predictive bioheat model, incorporating deep learning to optimize electrode configurations and minimize collateral tissue damage, represents a pioneering approach in interventional research. This method offers efficient evaluation of thermal strategies with reduced computational overhead compared to traditional numerical methods.

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Analysis of open channel flow with various layered vegetation using CFD, considering different near-wall treatment methods

Cited by 3 publications

References 67 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

Evaluation of turbulence models for the prediction of flow properties in vegetated channels

Integrating forecasting methods to support finite element analysis and explore heat transfer complexities

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