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Details

Autor(en) / Beteiligte
Titel
Determining the Scour Dimensions Around Submerged Vanes in a 180° Bend with the Gene Expression Programming Technique
Ist Teil von
  • Journal of marine science and application, 2018-06, Vol.17 (2), p.233-240
Ort / Verlag
Harbin: Harbin Engineering University
Erscheinungsjahr
2018
Link zum Volltext
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
  • Submerged vanes are installed on rivers and channel beds to protect the outer bank bends from scouring. Also, local scouring occurs around the submerged vanes over time, and identifying the effective factors on the scouring phenomena around these submerged vanes is one of the important issues in river engineering. The most important aim of this study is investigation of scour pattern around submerged vanes located in 180° bend experimentally and numerically. Firstly, the effects of various parameters such as the Froude number ( Fr ), angle of submerged vanes to the flow ( α ), angle of submerged vane location in the bend ( θ ), distance between submerged vanes ( d ), height ( H ), and length ( L ) of the vanes on the dimensionless volume of the scour hole were experimentally studied. The submerged vanes were installed on a 180° bend whose central radius and channel width were 2.8 and 0.6 m, respectively. By reducing the Froude number, the scour hole volume decreased. For all Froude numbers, the biggest scour hole formed at θ  = 15°. In all models, by increasing the Froude number, the scour hole volume significantly increases. In addition, by increasing the submerged vanes’ length and height, the scour hole dimensions also grow. Secondly, using gene expression programming (GEP), a relationship for determining the scour hole volume around the submerged vanes was provided. For this model, the determination coefficients ( R 2 ) for the training and test modes were computed as 0.91 and 0.9, respectively. In addition, this study performed partial derivative sensitivity analysis (PDSA). According to the results, the PDSA was calculated as positive for all input variables.

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