Entropy for Determination of Suspended Sediment Concentration: Parameter Related to Granulometry

Martins, Patrícia Diniz; Poleto, Cristiano

doi:10.1061/(asce)ee.1943-7870.0001325

Cited by 2 publications

(1 citation statement)

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“…These studies have provided some physical insights to the hindered settling process of the particle in a particle-fluid mixture. During recent decades, some researchers have adopted the probability method based on entropy theory to investigate some classic hydraulic engineering problems, including predicting the one-dimensional and two-dimensional velocity distributions in open channels [19][20][21], estimating the sediment concentration distribution [22][23][24][25][26] and calculating the shear stress [27,28]. Recently, Singh et al [29] reviewed the progress in the application of the entropy theory into water engineering problems.…”

Section: The Richardson and Zakimentioning

confidence: 99%

Modelling the Hindered Settling Velocity of a Falling Particle in a Particle-Fluid Mixture by the Tsallis Entropy Theory

Zhu

Wang

Peng

et al. 2019

Entropy

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The settling velocity of a sediment particle is an important parameter needed for modelling the vertical flux in rivers, estuaries, deltas and the marine environment. It has been observed that a particle settles more slowly in the presence of other particles in the fluid than in a clear fluid, and this phenomenon has been termed ‘hindered settling’. The Richardson and Zaki equation has been a widely used expression for relating the hindered settling velocity of a particle with that in a clear fluid in terms of a concentration function and the power of the concentration function, and the power index is known as the exponent of reduction of the settling velocity. This study attempts to formulate the model for the exponent of reduction of the settling velocity by using the probability method based on the Tsallis entropy theory. The derived expression is a function of the volumetric concentration of the suspended particle, the relative mass density of the particle and the particle’s Reynolds number. This model is tested against experimental data collected from the literature and against five existing deterministic models, and this model shows good agreement with the experimental data and gives better prediction accuracy than the other deterministic models. The derived Tsallis entropy-based model is also compared with the existing Shannon entropy-based model for experimental data, and the Tsallis entropy-based model is comparable to the Shannon entropy-based model for predicting the hindered settling velocity of a falling particle in a particle-fluid mixture. This study shows the potential of using the Tsallis entropy together with the principle of maximum entropy to predict the hindered settling velocity of a falling particle in a particle-fluid mixture.

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