Investigation of New Tsallis-Based Equation to Predict Shear Stress Distribution in Circular and Trapezoidal Channels

Khozani, Sheikh; Mohtar, Wan Hanna Melini Wan

doi:10.3390/e21111046

Cited by 11 publications

(16 citation statements)

References 33 publications

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“…Successively, for the same channels Kazemian-Kale-Kale et al [39] obtained a very good estimation of experimental shear stresses for q = 3/4. This value was also applied to predict the shear stress distribution in rectangular [38] and trapezoidal [41] channels. The Lagrange multipliers can be evaluated by substituting Equation 9into the constraints, Equations (3) and (4):…”

Section: Definition Of the Tsallis Entropy And Its Maximizationmentioning

confidence: 99%

“…The concept of entropy has been analytically used by various existing methods as a robust theory for estimating the shear stress. However, the entropic approach has been given considerable attention mainly for its ability to evaluate the velocities in open channels [21][22][23][24][25][26][27][28][29][30][31][32], whereas very few studies have been carried out on its application in predicting the shear stress distribution [33][34][35][36][37][38][39][40][41].…”

Section: Introductionmentioning

confidence: 99%

“…Recently, Sheikh Khozani and Wan Mohtar [41] employed the Tsallis entropy to estimate the shear stress distribution in a circular channel with a flatbed and in a trapezoidal channel by introducing a new dimensionless parameter as function of the ratio between the mean and maximum shear stress. The model showed a higher performance for predicting shear stress distribution along the wetted perimeter of trapezoidal channels than that of those with a circular shape.…”

Section: Introductionmentioning

confidence: 99%

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Modeling Bed Shear Stress Distribution in Rectangular Channels Using the Entropic Parameter

Mirauda

Russo

2020

Entropy

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The evaluation of bed shear stress distribution is fundamental to predicting the transport of sediments and pollutants in rivers and to designing successful stable open channels. Such distribution cannot be determined easily as it depends on the velocity field, the shape of the cross section, and the bed roughness conditions. In recent years, information theory has been proven to be reliable for estimating shear stress along the wetted perimeter of open channels. The entropy models require the knowledge of the shear stress maximum and mean values to calculate the Lagrange multipliers, which are necessary to the resolution of the shear stress probability distribution function. This paper proposes a new formulation which stems from the maximization of the Tsallis entropy and simplifies the calculation of the Lagrange coefficients in order to estimate the bed shear stress distribution in open-channel flows. This formulation introduces a relationship between the dimensionless mean shear stress and the entropic parameter which is based on the ratio between the observed mean and maximum velocity of an open-channel cross section. The validity of the derived expression was tested on a large set of literature laboratory measurements in rectangular cross sections having different bed and sidewall roughness conditions as well as various water discharges and flow depths. A detailed error analysis showed good agreement with the experimental data, which allowed linking the small-scale dynamic processes to the large-scale kinematic ones.

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Section: Definition Of the Tsallis Entropy And Its Maximizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modeling Bed Shear Stress Distribution in Rectangular Channels Using the Entropic Parameter

Mirauda

Russo

2020

Entropy

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“…This theory, built on the mathematical concept of entropy, represents the quantitative measure of the information content associated with a signal. It has been widely used in different sectors of hydraulics and hydrology to derive models of rainfall-runoff, infiltration, and soil moisture [22][23][24][25][26][27] as well as distribution of velocity, sediment concentration, and shear stress in open-channel flows [28][29][30][31][32][33][34][35][36][37][38][39]. Among the different applications, information theory has also been employed for the optimization, design, and management of several gauge stations including networks of water quality and groundwater [40,41], rainfall [42,43], streamflow, and water level [44][45][46][47][48][49][50][51].…”

Section: Introductionmentioning

confidence: 99%

MIMR Criterion Application: Entropy Approach to Select the Optimal Quality Parameter Set Responsible for River Pollution

Mirauda

Ostoich

2020

Sustainability

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Surface water quality has a vital role when defining the sustainability of the ecological environment, public health, and the social and economic development of whole countries. Unfortunately, the rapid growth of the worldwide population together with the current climate change have mostly determined fluvial pollution. Therefore, the employment of effective methodologies, able to rapidly and easily obtain reliable information on the quality of rivers, is becoming fundamental for an efficient use of the resource and for the implementation of mitigation measures and actions. The Water Quality Index (WQI) is among the most widely used methods to provide a clear and complete picture of the contamination status of a river stressed by point and diffuse sources of natural and anthropic origin, leading the policy makers and end-users towards a more and more correct and sustainable management of the water resource. The parameter choice is one of the most important and complex phases and recent statistical techniques do not seem to show great objectivity and accuracy in the identification of the real water quality status. The present paper offers a new approach, based on entropy theory and known as the Maximum Information Minimum Redundancy (MIMR) criterion, to define the optimal subset of chemical, physical, and biological parameters, describing the variation of the river quality level in space and time and thus identifying its pollution sources. An algorithm was implemented for the MIMR criterion and applied to a sample basin of Northeast Italy in order to verify its reliability and accuracy. A comparison with the Principal Component Analysis (PCA) showed how the MIMR is more suitable and objective to obtain the optimal quality parameters set, especially when the amount of investigated variables is small, and can thus be a useful tool for fast and low-cost water quality assessment in rivers.

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“…Experimental, analytical and numerical procedures to determine the shear stress distribution in various shapes of channels have been exhaustively investigated [3][4][5][6][7][8][9][10]. Bed shear stress comprises of three terms, i.e.…”

Section: Introductionmentioning

confidence: 99%

Forecasting shear stress parameters in rectangular channels using new soft computing methods

Khozani¹,

Sheikhi²,

Mohtar³

et al. 2020

PLoS ONE

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Shear stress comprises basic information for predicting the average depth velocity and discharge in channels. With knowledge of the percentage of shear force carried by walls (% SF w ) it is possible to more accurately estimate shear stress values. The %SF w , non-dimension wall shear stress ( � t w t 0 ) and non-dimension bed shear stress ( � t b t 0 ) in smooth rectangular channels were predicted by a three methods, the Bayesian Regularized Neural Network (BRNN), the Radial Basis Function (RBF), and the Modified Structure-Radial Basis Function (MS-RBF). For this aim, eight data series of research experimental results in smooth rectangular channels were used. The results of the new method of MS-RBF were compared with those of a simple RBF and BRNN methods and the best model was selected for modeling each predicted parameters. The MS-RBF model with RMSE of 3.073, 0.0366 and 0.0354t 0 respectively, demonstrated better performance than those of the RBF and BRNN models. The results of MS-RBF model were compared with three other proposed equations by researchers for trapezoidal channels and rectangular ducts. The results showed that the MS-RBF model performance in estimating %SF w, � t w t 0 and � t b t 0 is superior than those of presented equations by researchers.

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Investigation of New Tsallis-Based Equation to Predict Shear Stress Distribution in Circular and Trapezoidal Channels

Cited by 11 publications

References 33 publications

Modeling Bed Shear Stress Distribution in Rectangular Channels Using the Entropic Parameter

Modeling Bed Shear Stress Distribution in Rectangular Channels Using the Entropic Parameter

MIMR Criterion Application: Entropy Approach to Select the Optimal Quality Parameter Set Responsible for River Pollution

Forecasting shear stress parameters in rectangular channels using new soft computing methods

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