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Showing 2 results for Linear Weir
Investigation of Rectangular and U-Shaped Labyrinth Weirs
M. Heidarour, S. F. Mousavi, A. R. Roushani Zarmehri,
Volume 10, Issue 3 (10-2006)
Abstract
Because of slight variation of the static head due to discharge fluctuations, the labyrinth weirs are considered to be economical structures for flood control and water level regulation in irrigation networks, as compared to other devices. Labyrinth weirs are composed of folded sections observed as trapezoidal and triangular in plan view. In this study, rectangular and U-shaped labyrinth weirs were investigated. Experiments were conducted on 15 labyrinth weir models. The models included eight rectangular labyrinth models and six U-shaped labyrinth models with different heights and lengths, and one linear model. All the experiments were performed in a horizontal rectangular flume, 7 m long, 0.32 m wide and 0.35 m high. The results indicated that for all the models, discharge coefficient increased sharply with an increase in Ht/P and attained a maximum value. This coefficient then decreased smoothly with a further increase in Ht/P. Increasing height of weirs increased the discharge coefficient for both rectangular and U-shaped weirs. The results also showed that increasing the length parallel to the flow direction decreased and increasing the length perpendicular to the flow direction increased the discharge coefficient. Generally, the discharge coefficient for rectangular weir was less than that of the U-shaped weir. The obtained results compared with those of Tullis et al. (1995) showed that discharge coefficient for U-shaped weir is more and for rectangular weir is less than that of the trapezoidal weir for angle of the side legs of 8 and 12 degrees.
Comparison of Hydraulic Efficiency of Arched Non-linear Weirs in Plan Using GEP and SVM Neural Networks
M. Majedi Asl, T. Omidpour Alavian, M. Kouhdaragh, V. Shamsi,
Volume 27, Issue 3 (12-2023)
Abstract
Non-linear weirs meanwhile economic advantages, have more passing flow capacity than linear weirs. These weirs have higher discharge efficiency with less free height upstream compared to linear weirs by increasing the length of the crown at a certain width. Intelligent algorithms have found a valuable place among researchers due to their great ability to discover complex and hidden relationships between effective independent parameters and dependent parameters, as well as saving money and time. In this research, the performance of support vector machine (SVM) and gene expression programming algorithm (GEP) in predicting the discharge coefficient of arched non-linear weirs was investigated using 243 laboratory data series for the first scenario and 247 laboratory data series for the second scenario. The geometric and hydraulic parameters were used in this research including the water load (HT), weir height (P), total water load ratio (HT/p), arc cycle angle (Ɵ), cycle wall angle (α), and discharge coefficient (Cd). The results of artificial intelligence showed that the combination of parameters (Cd, H_T/p, α, Ɵ) respectively in GEP and SVM algorithms in the training phase related to the first scenario (Labyrinth weir with cycle wall angle 6 degrees) were respectively equal to (R2=0.9811), (RMSE=0.02120), (DC=0.9807), and (R2=0.9896), (RMSE=0.0189), (DC=0.9871) in the second scenario (Labyrinth weir with a cycle wall angle of 12 degrees) it was equal to (R2=0.9770), (RMSE=0.0193), (RMSE=0.9768), and (R2 = 0.9908), (RMSE = 0.0128), (DC = 0.9905), which compared to other combinations has led to the most optimal output that shows the very favorable accuracy of both algorithms in predicting the coefficient the Weir discharge is arched non-linear. The results of the sensitivity analysis indicated that the effective parameter in determining the discharge coefficient of the arched non-linear Weir in GEP and in SVM is the total water load ratio parameter (HT/p). Comparing the results of this research with other researchers revealed that the evaluation indices for GEP and SVM algorithms of this research had better estimates than other researchers.

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