Probabilistic approach to modeling of velocity distributions in fluid flows

Chiu, Chao‐Lin; Hsu, Shih-Meng

doi:10.1016/j.jhydrol.2005.04.011

Cited by 62 publications

(47 citation statements)

References 10 publications

(14 reference statements)

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“…Thus, the model of Dingman is likely to present the same weak points as the logarithmic law, namely the difficulty of describing velocity profiles at the bottom of the flow and at the water surface, especially when maximum velocity appears under the water surface (Chiu 2007). But for the rivers where there is a preponderance of high velocities, the law of Dingman and Chiu seems to be superimposed (Dingman 2007).…”

Section: Introductionmentioning

confidence: 99%

Estimation of Algerian rivers discharges based one Chiu's equation

Ammari¹,

Rémini

2009

Arab J Geosci

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The introduction of the entropy concept in hydraulics by Chiu gives the possibility to develop a simple method to measure discharges in natural streams. The application of this method on four streams in north Algeria made a possibility to develop a linear mean-max velocity models, deduce the entropy parameters and the cross sectional areas expressions for all streams in order to obtain the water discharges easily with minimum errors. The Chiu's velocity distribution equation was also checked for a large range of discharges, water levels, and flow pattern, where it proves its efficacy.

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Section: Introductionmentioning

confidence: 99%

Estimation of Algerian rivers discharges based one Chiu's equation

Ammari¹,

Rémini

2009

Arab J Geosci

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“…This mean and maximum relation has been implemented in several areas, such as the United States [19], Italy [20], Algeria [21] and Taiwan [22], to estimate discharge in non-tidal effect streams. If the variation of natural channels is small, then the ratio of mean velocity to its maximum should be a constant [23]. Once the parameter Φ is calibrated, the cross-sectional mean velocity can be easily determined based on Equation (6) with the cross-sectional maximum velocity.…”

Section: Estimation Of Cross-sectional Mean Velocitymentioning

confidence: 99%

Pollutant Flux Estimation in an Estuary Comparison between Model and Field Measurements

et al. 2014

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This study proposes a framework for estimating pollutant flux in an estuary. An efficient method is applied to estimate the flux of pollutants in an estuary. A gauging station network in the Danshui River estuary is established to measure the data of water quality and discharge based on the efficient method. A boat mounted with an acoustic Doppler profiler (ADP) traverses the river along a preselected path that is normal to the streamflow to measure the velocities, water depths and water quality for calculating pollutant flux. To know the characteristics of the estuary and to provide the basis for the pollutant flux estimation model, data of complete tidal cycles is collected. The discharge estimation model applies the maximum velocity and water level to estimate mean velocity and cross-sectional area, respectively. Thus, the pollutant flux of the estuary can be easily computed as the product of the mean velocity, cross-sectional area and pollutant concentration. The good agreement between the observed and estimated pollutant flux of the Danshui River estuary shows that the pollutant measured by the conventional and the efficient methods are not fundamentally different. The proposed method is cost-effective OPEN ACCESSEnvironments 2014, 1 108 and reliable. It can be used to estimate pollutant flux in an estuary accurately and efficiently.

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“…Accordingly, we have to mention the studies of complexity [4], as well as other probabilistic approaches [5], [6].…”

Section: Incas Bulletin Volume 6 Issue 4/ 2014mentioning

confidence: 99%