Maximum Velocity and Regularities in Open-Channel Flow

Chiu, Chao‐Lin; Tung, Ning-Chien

doi:10.1061/(asce)0733-9429(2002)128:4(390)

Cited by 128 publications

(93 citation statements)

References 11 publications

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“…By contrast, although the velocity dip phenomenon has been reported for a long time (Leighly 1932), our understanding of it is poor and only a few studies on it can be found in the literature (Sarma et al 1983(Sarma et al , 2000Chiu and Said 1995;Chiu and Tung 2002;Moramarco et al 2004;Guo and Julien 2001). The velocity dip phenomenon can hardly be modeled with log-wake velocity profiles because it imposes a velocity increase with distance from the boundary.…”

Section: Introductionmentioning

confidence: 99%

Application of Modified Log-Wake Law in Open-Channels

Guo¹,

Juliën

2006

World Environmental and Water Resource Congress 2006

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The modified log-wake law, which was developed for turbulent boundary layers and pipe flows, is extended to turbulent flows in open-channels. Turbulent velocity profiles in open-channels can be approximated with three components: (1) the law of the wall that results from the constant bed shear stress; (2) the law of the wake that reflects the effects of gravity, secondary currents and bed roughness; and (3) the cubic correction near the maximum velocity. A procedure to determine the four model parameters from velocity measurements while keeping κ = 0.41 is presented. The modified log-wake law compares very well with experimental data from Coleman, Lyn, Kironoto and Graf and Sarma et al. It also replicates the measured velocity profiles of the Mississippi River. In particular, it can well fit the velocity dip phenomenon in openchannels where the conventional log-wake law fails.

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Section: Introductionmentioning

confidence: 99%

Application of Modified Log-Wake Law in Open-Channels

Guo¹,

Juliën

2006

World Environmental and Water Resource Congress 2006

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“…1 and 2. A sediment concentration distribution was calculated using the calculated equilibrium state N by (14). The accuracy of the measured sediment concentration distribution and calculated sediment distribution is shown in Fig.…”

Section: Results Analysis and Discussionmentioning

confidence: 99%

“…Therefore, the present study proposed a formula that can calculate a mean sediment concentration by simplifying parameters as much as possible. The detailed elicitation process in the calculation formula of velocity distribution and mean velocity, which are required to understand the calculation formula of mean sediment concentration using the probabilistic entropy concept, are found in the previous studies done by Chiu and Choo so they were omitted in this paper [4], [6], [11]- [14].…”

Section: Theoretical Backgroundmentioning

confidence: 99%

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Derivation of Equation for Mean Suspended Sediment Based on Probabilistic Concept

Yoon¹,

Lee²,

Park³

2017

IJESD

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Abstract-An accurate estimation of sediment discharge in rivers and streams should be solved for the appropriate river management and monitoring. In this study, a new formula which has minimum parameters considering existing ones with a concept of entropy by a probabilistic approach, was developed and mean suspended sediment concentration were estimated. Results of this new formula were verified with the experimental results which were conducted with a steady state and gradually injecting sediment (D= 105 ㎛) in a rectangular cross-sectional flume previously. The relationship between the measured sediment distribution and the estimated sediment distribution has a good agreement.Index Terms-Entropy, entropy suspended sediment parameter, mean suspended sediment concentration, Probabilistic approach.

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“…From a practical viewpoint, the maximum point velocity is a parameter that can be easily determined during an event, as it generally manifests itself in the upper portion of the flow area, where velocity points can be sampled even when water levels rise considerably [1,17]. The parameter M, on the other hand, is estimated by linear regression performed on a substantial set of pairs of values u max -Ū, which are obtained by means of the velocity-area method.…”

Section: Introductionmentioning

confidence: 99%

Three Methods for Estimating the Entropy Parameter M Based on a Decreasing Number of Velocity Measurements in a River Cross-Section

Farina

Alvisi

Franchini

et al. 2014

Entropy

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Abstract:The theoretical development and practical application of three new methods for estimating the entropy parameter M used within the framework of the entropy method proposed by Chiu in the 1980s as a valid alternative to the velocity-area method for measuring the discharge in a river is here illustrated. The first method is based on reproducing the cumulative velocity distribution function associated with a flood event and requires measurements regarding the entire cross-section, whereas, in the second and third method, the estimate of M is based on reproducing the cross-sectional mean velocity U by following two different procedures. Both of them rely on the entropy parameter M alone and look for that value of M that brings two different estimates of U , obtained by using two different M-dependent-approaches, as close as possible. From an operational viewpoint, the acquisition of velocity data becomes increasingly simplified going from the first to the third approach, which uses only one surface velocity measurement. The procedures proposed are applied in a case study based on the Ponte Nuovo hydrometric station on the Tiber River in central Italy.

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Maximum Velocity and Regularities in Open-Channel Flow

Cited by 128 publications

References 11 publications

Application of Modified Log-Wake Law in Open-Channels

Application of Modified Log-Wake Law in Open-Channels

Derivation of Equation for Mean Suspended Sediment Based on Probabilistic Concept

Three Methods for Estimating the Entropy Parameter M Based on a Decreasing Number of Velocity Measurements in a River Cross-Section

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