Intelligent Modeling and Experimental Investigation of the Collar's Impact on Reducing Scour around the Spur Dike
Using a collar is a suitable way to protect structures in the water and reduce the scour depth around the structures. In this research, experiments were first carried out to determine the performance of the collar in reducing the scour depth of the spur dikes with different angles, and then, the per...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Pouyan Press
2025-07-01
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| Series: | Journal of Soft Computing in Civil Engineering |
| Subjects: | |
| Online Access: | https://www.jsoftcivil.com/article_201729_a8447c5c958feae4e4038ffc0b6ebdf7.pdf |
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| Summary: | Using a collar is a suitable way to protect structures in the water and reduce the scour depth around the structures. In this research, experiments were first carried out to determine the performance of the collar in reducing the scour depth of the spur dikes with different angles, and then, the percentage of scour depth reduction was predicted using intelligent models. The parameters of collar shape coefficient (Sc), the ratio of collar area to the flow depth multiplied by spur dike length (Ac/LY), the ratio of collar height to the flow depth (Zc/Y), and the spur dike angle (ɵ=60, 90, 120) were considered as input data while the reduction of scour depth around the spur dike nose (R) was addressed as the output parameter. The present study seeks to evaluate the application of the Cuckoo search (CS) algorithm and Bat algorithm (BA) to improve the performance of the Support Vector Regression (SVR) model in predicting the amount of R. The results indicated that the proposed hybrid models provided better accuracy than the simple SVR model. In all groups and studied models, the best performance was related to the Support Vector Regression–Bat Algorithm (SVR-BA) and the weakest performance was related to the SVR model. For example, in the combination of all four input data, the amount of root mean square error (RMSE) for SVR-BA was approximately 24% lower and the amount of squared correlation coefficient (R2) was approximately 2% higher, compared to SVR model. |
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| ISSN: | 2588-2872 |