Impact of downstream obstructions on ogee weir efficiency: a regression analysis

Author:

S. M. Shravan Kumar1ORCID,Patil Chidanand2,Yadav Anamika3,Bukke Lavanya1,Reddy R. Laxmana1,Sakare Praveen Kumar4

Affiliation:

1. a SNIST: Sreenidhi Institute of Science and Technology, Hyderabad, Telangana, India

2. b KLE DR MSSCET: DR MS Sheshgiri College of Engineering and Technology, Belgaum, Karnataka, India

3. c IIT Guwahati: Indian Institute of Technology, Guwahati, Assam, India

4. d SDMCET: Sri Dharmasthala Manjunatheshwara College of Engineering and Technology, Dharwad, Karnataka, India

Abstract

ABSTRACT This study delves into the impact of downstream obstruction angles on the discharge coefficient (Cd) over ogee weirs within open channel flows, a critical factor for accurate flow rate predictions in hydraulic engineering. Employing a series of detailed laboratory experiments, the influence of various obstruction angles on Cd was scrutinized applying a suite of regression analysis to develop predictive models. The analysis was enriched by considering hydraulic parameters such as flow rate, water level, and weir geometry. Despite the established importance of Cd in hydraulic designs the nuanced effects of downstream obstructions have received limited attention, highlighting a critical research gap. The findings highlight a strong correlation between obstruction angles and Cd, with developed regression models demonstrating notable predictive strength. Remarkably the models exhibited varying levels of accuracy, with the Random Forest regressor achieving an exceptionally low root mean square error (RMSE) of 0.005, indicating superior predictive performance. Conversely, traditional models like Decision tree and XG BOOST reflected higher RMSE values of 0.60, suggesting less predictive accuracy in this context. LASSO, Bayesian Ridge, and OMP regressors stood out with an RMSE of zero, denoting perfect predictions under the study's specific conditions.

Publisher

IWA Publishing

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