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An Intelligent Optimised Estimation of the Hydraulic Jump Roller Length
Applications of Evolutionary Computation, Pages: 475 - 490
Swansea University Author: Fabio Caraffini
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DOI (Published version): 10.1007/978-3-031-30229-9_31
Abstract
In this paper, we address a problem in the field of hydraulics which is also relevant in terms of sustainability. Hydraulic jump is a physical phenomenon that occurs both for natural and man-made reasons. Its importance relies on the exploitation of the intrinsic energy dissipation characteristics a...
Published in: | Applications of Evolutionary Computation |
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ISBN: | 9783031302282 9783031302299 |
ISSN: | 0302-9743 1611-3349 |
Published: |
Cham
Springer Nature Switzerland
2023
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Online Access: |
Check full text
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URI: | https://cronfa.swan.ac.uk/Record/cronfa63102 |
Abstract: |
In this paper, we address a problem in the field of hydraulics which is also relevant in terms of sustainability. Hydraulic jump is a physical phenomenon that occurs both for natural and man-made reasons. Its importance relies on the exploitation of the intrinsic energy dissipation characteristics and on the other hand the danger that might produce on bridges and river structures as a consequence of the interac- tion with the large vortex structures that are generated. In the present work, we try to address the problem of estimating the hydraulic jump roller length, whose evaluation is inherently affected by empirical errors related to its dissipative nature. The problem is approached using a regression model and exploiting a dataset of observations. Regression is performed by minimising the loss function using ten different black-box optimisers. In particular, we selected some of the most used metaheuristis, such as Evolution Strategies, Particle Swarm Optimisation, Differential Evolution and others. Furthermore, an experimental analysis has been conducted to validate the proposed approach and compare the effectiveness of the metaheuristics. |
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College: |
Faculty of Science and Engineering |
Start Page: |
475 |
End Page: |
490 |