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Sinuosity effects on Longitudinal Dispersion Coefficient

Bashitialshaaer, Raed LU ; Bengtsson, Lars LU ; Larson, Magnus LU ; Persson, Kenneth M LU ; Aljaradin, Mohammad LU and Al-Itawi, Hossam (2010) The International Conference on Energy, Water and Environment (ICEWE 2010), Dec. 12-15
Abstract
A method for reaching longitudinal dispersion coefficient accounting sinuosity effects is suggested. The proposed method was verified using 43 sets of measured field data from previous study were collected from 30 streams and these data were chosen depends on characteristics availability (flow parameters, fluid properties and Sinuosity). Statistical programs namely MINITAB and SPSS were used to derive the relationship between measured longitudinal dispersion coefficient and geometric parameters were used. The new predicted formulas of the longitudinal dispersion coefficient, were correlated with a high coefficient compared to the measured data (i.e. R2 = 0.92 and 0.94) excluding and including sinuosity in the calculations respectively.... (More)
A method for reaching longitudinal dispersion coefficient accounting sinuosity effects is suggested. The proposed method was verified using 43 sets of measured field data from previous study were collected from 30 streams and these data were chosen depends on characteristics availability (flow parameters, fluid properties and Sinuosity). Statistical programs namely MINITAB and SPSS were used to derive the relationship between measured longitudinal dispersion coefficient and geometric parameters were used. The new predicted formulas of the longitudinal dispersion coefficient, were correlated with a high coefficient compared to the measured data (i.e. R2 = 0.92 and 0.94) excluding and including sinuosity in the calculations respectively. Comparisons made among 16 other studies of over long period of measured, experimental, and predicted longitudinal dispersion coefficient from different cross-sectional areas (e.g. triangle, rectangular, full and half full circular pipe, parabolic, narrow and deep and, wide and shallow).

The correlation coefficients increased when including irregularities (Sinuosity) term of the natural streams of different cross section in the calculations. Also, the second equation which including sinuosity is more precisely describing the longitudinal dispersion in the rivers and streams. Thus, we strongly prefer and recommend using the second equation for better result than the one not including sinuosity especially for mixing in the case of brine and wastewater discharge. The two results were compared for RMSE (30.1, 24.0, 51.0, 48.9, 90.6, and 70.0) to previous studies e.g. Kashefipour and Falconer (2002), Deng et al. (2001), Seo and Cheong (1998), and Iwasa and Aya (1991) respectively. (Less)
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author
organization
publishing date
type
Contribution to conference
publication status
published
subject
keywords
Longitudinal dispersion coefficient, Flow parameters, Fluid properties, Sinuosity, MINITAB, SPSS, Statistical Analysis
pages
10 pages
conference name
The International Conference on Energy, Water and Environment (ICEWE 2010), Dec. 12-15
language
English
LU publication?
yes
id
3ad901bf-d0ed-4282-b1f1-f59be8aab384 (old id 1895587)
date added to LUP
2011-04-18 13:54:26
date last changed
2016-10-07 16:29:54
@misc{3ad901bf-d0ed-4282-b1f1-f59be8aab384,
  abstract     = {A method for reaching longitudinal dispersion coefficient accounting sinuosity effects is suggested. The proposed method was verified using 43 sets of measured field data from previous study were collected from 30 streams and these data were chosen depends on characteristics availability (flow parameters, fluid properties and Sinuosity). Statistical programs namely MINITAB and SPSS were used to derive the relationship between measured longitudinal dispersion coefficient and geometric parameters were used. The new predicted formulas of the longitudinal dispersion coefficient, were correlated with a high coefficient compared to the measured data (i.e. R2 = 0.92 and 0.94) excluding and including sinuosity in the calculations respectively. Comparisons made among 16 other studies of over long period of measured, experimental, and predicted longitudinal dispersion coefficient from different cross-sectional areas (e.g. triangle, rectangular, full and half full circular pipe, parabolic, narrow and deep and, wide and shallow). <br/><br>
The correlation coefficients increased when including irregularities (Sinuosity) term of the natural streams of different cross section in the calculations. Also, the second equation which including sinuosity is more precisely describing the longitudinal dispersion in the rivers and streams. Thus, we strongly prefer and recommend using the second equation for better result than the one not including sinuosity especially for mixing in the case of brine and wastewater discharge. The two results were compared for RMSE (30.1, 24.0, 51.0, 48.9, 90.6, and 70.0) to previous studies e.g. Kashefipour and Falconer (2002), Deng et al. (2001), Seo and Cheong (1998), and Iwasa and Aya (1991) respectively.},
  author       = {Bashitialshaaer, Raed and Bengtsson, Lars and Larson, Magnus and Persson, Kenneth M and Aljaradin, Mohammad and Al-Itawi, Hossam},
  keyword      = {Longitudinal dispersion coefficient,Flow parameters,Fluid properties,Sinuosity,MINITAB,SPSS,Statistical Analysis},
  language     = {eng},
  pages        = {10},
  title        = {Sinuosity effects on Longitudinal Dispersion Coefficient},
  year         = {2010},
}