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Sinuosity Effects on Longitudinal Dispersion Coefficient

Bashitialshaaer, Raed LU ; Persson, Kenneth M LU ; Bengtsson, Lars LU ; Larson, Magnus LU ; Aljaradin, Mohammad LU and Al-Itawi, Hossam I (2011) In International Journal of Sustainable Water and Environmental Systems - IASKS 2(2). p.77-84
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... (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 journal
publication status
published
subject
keywords
Statistical Analysis., SPSS, MINITAB, Sinuosity, Fluid properties, Flow parameters, Longitudinal dispersion coefficient
in
International Journal of Sustainable Water and Environmental Systems - IASKS
volume
2
issue
2
pages
8 pages
publisher
International Association for Sharing Knowledge and Sustainability
ISSN
1923-7545
DOI
10.5383/swes.02.02.002
language
English
LU publication?
yes
id
621bd22a-e012-4f21-abf9-100f7e221b25 (old id 1884803)
alternative location
http://iasks.org/sites/default/files/swes20110202077084.pdf
date added to LUP
2011-04-01 11:54:09
date last changed
2016-11-09 14:06:06
@article{621bd22a-e012-4f21-abf9-100f7e221b25,
  abstract     = {A method for reaching longitudinal dispersion coefficient accounting sinuosity effects is suggested. The proposed<br/><br>
method was verified using 43 sets of measured field data from previous study were collected from 30 streams and these<br/><br>
data were chosen depends on characteristics availability (flow parameters, fluid properties and Sinuosity). Statistical<br/><br>
programs namely MINITAB and SPSS were used to derive the relationship between measured longitudinal dispersion<br/><br>
coefficient and geometric parameters were used. The new predicted formulas of the longitudinal dispersion coefficient,<br/><br>
were correlated with a high coefficient compared to the measured data (i.e. R2 = 0.92 and 0.94) excluding and including<br/><br>
sinuosity in the calculations respectively. Comparisons made among 16 other studies of over long period of measured,<br/><br>
experimental, and predicted longitudinal dispersion coefficient from different cross-sectional areas (e.g. triangle,<br/><br>
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<br/><br>
cross section in the calculations. Also, the second equation which including sinuosity is more precisely describing the<br/><br>
longitudinal dispersion in the rivers and streams. Thus, we strongly prefer and recommend using the second equation for<br/><br>
better result than the one not including sinuosity especially for mixing in the case of brine and wastewater discharge.<br/><br>
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<br/><br>
and Falconer (2002), Deng et al. (2001), Seo and Cheong (1998), and Iwasa and Aya (1991) respectively.},
  author       = {Bashitialshaaer, Raed and Persson, Kenneth M and Bengtsson, Lars and Larson, Magnus and Aljaradin, Mohammad and Al-Itawi, Hossam I},
  issn         = {1923-7545},
  keyword      = {Statistical Analysis.,SPSS,MINITAB,Sinuosity,Fluid properties,Flow parameters,Longitudinal dispersion coefficient},
  language     = {eng},
  number       = {2},
  pages        = {77--84},
  publisher    = {International Association for Sharing Knowledge and Sustainability},
  series       = {International Journal of Sustainable Water and Environmental Systems - IASKS},
  title        = {Sinuosity Effects on Longitudinal Dispersion Coefficient},
  url          = {http://dx.doi.org/10.5383/swes.02.02.002},
  volume       = {2},
  year         = {2011},
}