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Application of data-driven models to predict the dimensions of flow separation zone.

Authors :
Gharehbaghi A
Ghasemlounia R
Latif SD
Haghiabi AH
Parsaie A
Source :
Environmental science and pollution research international [Environ Sci Pollut Res Int] 2023 May; Vol. 30 (24), pp. 65572-65586. Date of Electronic Publication: 2023 Apr 22.
Publication Year :
2023

Abstract

In this research, the effect of a submerged multiple-vane system on the dimensions of flow separation zone (DFSZ) is assessed via 192 measured datasets. The vanes' shape comprised two segments, curved and flat plates which are located in the connection of main channel to the lateral intake channel with an angle of 55°. In this direction, a butterfly's array for the vanes' arrangement along with different main controlling factors such as distances of vanes along the flow (δ <subscript>l</subscript> ), degree of curvature (β), and angles of attack to the local primary flow direction (θ) is utilized. Through capturing photos and utilizing AutoCAD and SURFER software, maximum relative length and width are calculated. Based on the experimental measurements, maximum percentage reduction of DFSZ, in comparison with the controlled test (without submerged vanes), is obtained with θ = 30°, β = 34°, and δ <subscript>l</subscript>  = 10 cm with value of 78 and 76%, respectively. Moreover, several data-driven models, namely, gene expression programming (GEP), support vector regression (SVR), and a robust hybrid SVR with an ant colony optimization algorithm (ACO) (i.e., hybrid SVR-ACO model), are developed in order to predict DFSZ via the operative dimensionless variables realized by Spearman's rho and Pearson's coefficient processes. In accordance with the statistical metrics, model grading process, scatter plot, and the hybrid SVR(RBF)-ACO model are preferred as the best and most precise model to predict maximum relative length and width with a total grade (TG) of 6.75 and 5.8, respectively. The generated algebraic formula for DFSZ under the optimal scenario of GEP is equated with the corresponding measured ones and the results are within 0-10%.<br /> (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Subjects

Subjects :
Algorithms
Software

Details

Language :
English
ISSN :
1614-7499
Volume :
30
Issue :
24
Database :
MEDLINE
Journal :
Environmental science and pollution research international
Publication Type :
Academic Journal
Accession number :
37085682
Full Text :
https://doi.org/10.1007/s11356-023-27024-y