Estimation of one-dimensional velocity distribution by measuring velocity at two points

Yeganeh, Maryam Teymouri; Heidari, Mohammad Mehdi

doi:10.1016/j.flowmeasinst.2020.101737

Cited by 3 publications

(3 citation statements)

References 22 publications

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“…Normalized RMSE gives a measure (%) of the relative difference of simulated versus observed data. The simulation was considered excellent with a normalized RMSE of less than 10%, which is desired if the normalized RMSE was greater than 10% and less than 20%, fair if the normalized RMSE was greater than 20% and less than 30%, and poor if the normalized RMSE was greater than 30% (Bannayan & Hoogenboom, 2009; Jamieson, Porter, & Wilson, 1991; Yeganeh & Heidari, 2020). An NRMSE equal to 11.57% has been calculated by estimating the discharge based on the entropy theory in laboratory observations (Yeganeh & Heidari, 2020).…”

Section: Resultsmentioning

confidence: 99%

“…The simulation was considered excellent with a normalized RMSE of less than 10%, which is desired if the normalized RMSE was greater than 10% and less than 20%, fair if the normalized RMSE was greater than 20% and less than 30%, and poor if the normalized RMSE was greater than 30% (Bannayan & Hoogenboom, 2009; Jamieson, Porter, & Wilson, 1991; Yeganeh & Heidari, 2020). An NRMSE equal to 11.57% has been calculated by estimating the discharge based on the entropy theory in laboratory observations (Yeganeh & Heidari, 2020). As far as the correlation coefficient is concerned, in all cases, it shows high agreement between the discharge based on the reference method and the discharge based on the other methods.…”

Section: Resultsmentioning

confidence: 99%

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Evaluation of discharge measurements methods in a natural river of low or middle flow using an electromagnetic flow meter

Pantelakis¹,

Doulgeris²,

Hatzigiannakis³

et al. 2022

River Research & Apps

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Measurement of river discharge should be accurate, as it is key environmental data and essential for hydrologic simulations, regardless of whether the flow is high, medium, or low. Herein, conventional methods based on velocity measurements at different depths (i.e., one-point method, two-point method, and threepoint method) are evaluated with a method using a surface velocity index and a method based on the entropy theory to estimate river discharge. All the methods were implemented to calculate the discharge of Agios Germanos River, located in Northern Greece, based on 2 years of measurement. Considering that the uncertainty in flow measurement is decreasing by increasing the number of velocity measurements points (EN ISO, 2007), in this work, the reference method is the conventional three-point method. Results show that the other two conventional methods (the one-point and the two-point) estimate the discharge with an error of about 3%, while the error of the other two methods ranges between 11 and 14%. Nevertheless, the nonconventional methods could be considered acceptable and could be used safely to minimize time and subsequently, the cost of field measurements.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Evaluation of discharge measurements methods in a natural river of low or middle flow using an electromagnetic flow meter

Pantelakis¹,

Doulgeris²,

Hatzigiannakis³

et al. 2022

River Research & Apps

View full text Add to dashboard Cite

show abstract

“…For the same discharge, the transverse water surface gradients are large at the downstream positions adjacent to the apex sections and small near the middle positions of the crossover areas. Yeganeh & Heidari (2022) used the entropy concept and the principle of maximum entropy to drive one-dimensional velocity distribution in an open channel. Results showed that the Tsallis entropy method is more accurate than other forms of entropy, showing much better simulation.…”

Section: Introductionmentioning

confidence: 99%

Characteristics of the flow in channels with extended boundaries

Kamal

Fattouh

Mokhtar

et al. 2023

Water Practice and Technology

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In the flow in channels with extended boundaries, the channel sides are extended covering parts of the channel flow surface symmetrically or asymmetrically. The pressure on the top surface remains approximately atmospheric, while the distributions of both velocities and discharges in the flow cross-section are severely affected. In this study, cases with different asymmetric extension ratios and aspect ratios were experimentally examined. The effect of the roughness of both extensions and the flume bed was investigated. The velocity data were sampled using Acoustic Doppler Velocimeters. The resulting velocity iso-lines showed deformations due to asymmetricity and the maximum velocity distribution was shifted towards the sides of smaller extension ratios. Low-velocity zones were formed bounded by the extensions, the side boundaries, and the flume bed where the flow resembles that of a closed conduit with maximum velocity value near the middle, but with a major difference that the iso-lines are not closed due to the absence of the fourth boundary. In cases with a bigger aspect ratio and roughness, high turbulence was noticed with severe cross-currents resulting in a low-flow velocity component. Results were demonstrated through figures and tables and the data were tested against well-known equations available in the literature.

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Image-based river discharge estimation by merging heterogeneous data with information entropy theory

Chahrour

Castaings²,

Barthelemy

2021

Flow Measurement and Instrumentation

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Estimation of one-dimensional velocity distribution by measuring velocity at two points

Cited by 3 publications

References 22 publications

Evaluation of discharge measurements methods in a natural river of low or middle flow using an electromagnetic flow meter

Evaluation of discharge measurements methods in a natural river of low or middle flow using an electromagnetic flow meter

Characteristics of the flow in channels with extended boundaries

Image-based river discharge estimation by merging heterogeneous data with information entropy theory

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