Application of machine learning methods on investigation the effect of interrupted deflector's height and downstream depth changes on energy dissipation at flip bucket spillways
Flip bucket is a type of energy dissipator structure. Flip buckets can sometimes be improved by adding wedge-shaped deflectors. This research introduced the best height proportion of used deflector on the flip buckets to increase energy dissipation. It used 4 types of deflector series including 32,...
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| Format: | Article |
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Shahid Chamran University of Ahvaz
2024-04-01
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| Series: | Journal of Hydraulic Structures |
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| Online Access: | https://jhs.scu.ac.ir/article_19162_623454327552f89cf146454e08a2a636.pdf |
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| author | Arash Adib Danial Ebrahimzadeh Mahmood S. Bejestan Morteza Lotfirad Masoud Oulapour |
| author_facet | Arash Adib Danial Ebrahimzadeh Mahmood S. Bejestan Morteza Lotfirad Masoud Oulapour |
| author_sort | Arash Adib |
| collection | DOAJ |
| description | Flip bucket is a type of energy dissipator structure. Flip buckets can sometimes be improved by adding wedge-shaped deflectors. This research introduced the best height proportion of used deflector on the flip buckets to increase energy dissipation. It used 4 types of deflector series including 32, 45, 47 and 55 degrees toward horizon with two different regular and irregular layouts and 19 different heights from 2.31 to 5.6 cm and in different hydraulic condition and the results were compared with a flip bucket without a deflector. The characteristics of laboratory flume were: length= 7.5 m, width= 0.58 m and height= 1.6 m. The results illustrates that the energy dissipation in the model with deflectors increased from 11.83 to 19.38 percent as compared with model without a deflector. The greatest percentage of energy dissipation was 80.74% which observed at a deflector angle of 55° and a discharge of 10 L/s, at deflector’s ratio of n=0.8 and in non-uniform layout and in free hydraulic jump. Larger deflector angles and side lengths initially boosted energy dissipation, but this effect plateaued or even reversed at very large angles. For calculating energy dissipation and hydraulic jump length parameters, the regression relations were extracted in this research and results of this relations were compared with results of the gene expression programming (GEP), random forest (RF) and multivariate adaptive regression splines (MARS) methods. The results showed that the RF method is the most accurate method for calculating energy dissipation and hydraulic jump length parameters. |
| format | Article |
| id | doaj-art-b893d6696e064c35bc487b8c4148b7bc |
| institution | OA Journals |
| issn | 2345-413X 2345-4156 |
| language | English |
| publishDate | 2024-04-01 |
| publisher | Shahid Chamran University of Ahvaz |
| record_format | Article |
| series | Journal of Hydraulic Structures |
| spelling | doaj-art-b893d6696e064c35bc487b8c4148b7bc2025-08-20T02:33:05ZengShahid Chamran University of AhvazJournal of Hydraulic Structures2345-413X2345-41562024-04-01103517110.22055/jhs.2024.46835.129819162Application of machine learning methods on investigation the effect of interrupted deflector's height and downstream depth changes on energy dissipation at flip bucket spillwaysArash Adib0Danial Ebrahimzadeh1Mahmood S. Bejestan2Morteza Lotfirad3Masoud Oulapour4Civil Engineering and Architecture Faculty, Shahid Chamran University of Ahvaz, Ahvaz, Iran.Civil Engineering and Architecture Faculty, Shahid Chamran University of Ahvaz, Ahvaz, Iran.Hydraulic Structure Department, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.Civil Engineering and Architecture Faculty, Shahid Chamran University of Ahvaz, Ahvaz, Iran.Civil Engineering and Architecture Faculty, Shahid Chamran University of Ahvaz, Ahvaz, Iran.Flip bucket is a type of energy dissipator structure. Flip buckets can sometimes be improved by adding wedge-shaped deflectors. This research introduced the best height proportion of used deflector on the flip buckets to increase energy dissipation. It used 4 types of deflector series including 32, 45, 47 and 55 degrees toward horizon with two different regular and irregular layouts and 19 different heights from 2.31 to 5.6 cm and in different hydraulic condition and the results were compared with a flip bucket without a deflector. The characteristics of laboratory flume were: length= 7.5 m, width= 0.58 m and height= 1.6 m. The results illustrates that the energy dissipation in the model with deflectors increased from 11.83 to 19.38 percent as compared with model without a deflector. The greatest percentage of energy dissipation was 80.74% which observed at a deflector angle of 55° and a discharge of 10 L/s, at deflector’s ratio of n=0.8 and in non-uniform layout and in free hydraulic jump. Larger deflector angles and side lengths initially boosted energy dissipation, but this effect plateaued or even reversed at very large angles. For calculating energy dissipation and hydraulic jump length parameters, the regression relations were extracted in this research and results of this relations were compared with results of the gene expression programming (GEP), random forest (RF) and multivariate adaptive regression splines (MARS) methods. The results showed that the RF method is the most accurate method for calculating energy dissipation and hydraulic jump length parameters.https://jhs.scu.ac.ir/article_19162_623454327552f89cf146454e08a2a636.pdfdeflectorflip buckethydraulic jumpfroude numberrf |
| spellingShingle | Arash Adib Danial Ebrahimzadeh Mahmood S. Bejestan Morteza Lotfirad Masoud Oulapour Application of machine learning methods on investigation the effect of interrupted deflector's height and downstream depth changes on energy dissipation at flip bucket spillways Journal of Hydraulic Structures deflector flip bucket hydraulic jump froude number rf |
| title | Application of machine learning methods on investigation the effect of interrupted deflector's height and downstream depth changes on energy dissipation at flip bucket spillways |
| title_full | Application of machine learning methods on investigation the effect of interrupted deflector's height and downstream depth changes on energy dissipation at flip bucket spillways |
| title_fullStr | Application of machine learning methods on investigation the effect of interrupted deflector's height and downstream depth changes on energy dissipation at flip bucket spillways |
| title_full_unstemmed | Application of machine learning methods on investigation the effect of interrupted deflector's height and downstream depth changes on energy dissipation at flip bucket spillways |
| title_short | Application of machine learning methods on investigation the effect of interrupted deflector's height and downstream depth changes on energy dissipation at flip bucket spillways |
| title_sort | application of machine learning methods on investigation the effect of interrupted deflector s height and downstream depth changes on energy dissipation at flip bucket spillways |
| topic | deflector flip bucket hydraulic jump froude number rf |
| url | https://jhs.scu.ac.ir/article_19162_623454327552f89cf146454e08a2a636.pdf |
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