Assessment of Shear Stress Distribution in Meandering Compound Channels with Differential Roughness Through Various Artificial Intelligence Approach

Mohanta, Abinash; Pradhan, Arpan; Mallick, Monalisa; Patra, Kanhu Charan

doi:10.1007/s11269-021-02966-5

Cited by 11 publications

(2 citation statements)

References 51 publications

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“…In this study, Khuntia et al (2018) used an ANN methodology to forecast the distribution of wall shear stress in straight compound channels. Mohanta et al (2021) used several AI techniques, such as MARS, GMDH-NN, and GEP, to formulate model equations for compound channels characterized by meandering patterns and relative roughness. In comparison to the GEP and MARS models, the findings indicate that the proposed GMDH-NN model exhibited a high degree of accuracy in predicting the values.…”

Section: Introductionmentioning

confidence: 99%

Prediction of shear stress distribution in compound channel with smooth converging floodplains

Kaushik,

Kumar

2024

Journal of Hydrology and Hydromechanics

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Climate change can have a profound impact on river flooding, leading to increased frequency and severity of floods. To mitigate these effects, it is crucial to focus on enhancing early warning systems and bolstering infrastructure resilience through improved forecasting. This proactive approach enables communities to better plan for and respond to flood events, thereby minimizing the adverse consequences of climate change on river floods. During river flooding, the channels often take on a compound nature, with varying geometries along the flow length. This complexity arises from construction and agricultural activities along the floodplains, resulting in converging, diverging, or skewed compound channels. Modelling the flow in these channels requires consideration of additional momentum transfer factors. In this study, machine learning techniques, including Gene Expression Programming (GEP), Artificial Neural Networks (ANN), and Support Vector Machines (SVM), were employed. The focus was on a compound channel with converging floodplains, predicting the shear force carried by the floodplains in terms of non-dimensional flow and hydraulic parameters. The findings indicate that the proposed ANN model outperformed GEP, SVM, and other established approaches in accurately predicting floodplain shear force. This research underscores the efficacy of utilizing machine learning techniques in the examination of river hydraulics.

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Section: Introductionmentioning

confidence: 99%

Prediction of shear stress distribution in compound channel with smooth converging floodplains

Kaushik,

Kumar

2024

Journal of Hydrology and Hydromechanics

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“…Various studies have investigated the lateral velocity profile, sharing of depth averaged velocity as well as shear force, transference of momentum, and discharge calculation in meandering compound channels ([1]; [2]; [3]; [4]; [5]; [6]; [7]; [8]; [9]; [10][11][12][13][14][15]). Also numerous investigations were carried out to examine the flow pattern at channel confluence considering various geometrical parameters by using numerical methods ( [16]; [17]; [18]; [19]; [20]; [21]; [22]; [23]; [24]; [25][26][27]).…”

Section: Introductionmentioning

confidence: 99%

Validation of Computational Fluid Dynamics Approach of Lateral Velocity Profile Due to Curvature Effect on Floodplain Levee of Two-stage Meandering Channel

Rathor

Mohanta

Patra

2022

Water Resour Manage

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Runoff Simulation Under Future Climate Change Conditions: Performance Comparison of Data-Mining Algorithms and Conceptual Models

Yoosefdoost

Khashei-Siuki

Tabari

et al. 2022

Water Resour Manage

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Assessment of Shear Stress Distribution in Meandering Compound Channels with Differential Roughness Through Various Artificial Intelligence Approach

Cited by 11 publications

References 51 publications

Prediction of shear stress distribution in compound channel with smooth converging floodplains

Prediction of shear stress distribution in compound channel with smooth converging floodplains

Validation of Computational Fluid Dynamics Approach of Lateral Velocity Profile Due to Curvature Effect on Floodplain Levee of Two-stage Meandering Channel

Runoff Simulation Under Future Climate Change Conditions: Performance Comparison of Data-Mining Algorithms and Conceptual Models

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