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An Intelligent Optimised Estimation of the Hydraulic Jump Roller Length

Antonio Agresta Orcid Logo, Chiara Biscarini Orcid Logo, Fabio Caraffini Orcid Logo, Valentino Santucci Orcid Logo

Applications of Evolutionary Computation, Pages: 475 - 490

Swansea University Author: Fabio Caraffini Orcid Logo

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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...

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Published in: Applications of Evolutionary Computation
ISBN: 9783031302282 9783031302299
ISSN: 0302-9743 1611-3349
Published: Cham Springer Nature Switzerland 2023
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URI: https://cronfa.swan.ac.uk/Record/cronfa63102
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last_indexed 2023-04-10T03:21:47Z
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spelling 2023-04-09T15:55:54.2558381 v2 63102 2023-04-09 An Intelligent Optimised Estimation of the Hydraulic Jump Roller Length d0b8d4e63d512d4d67a02a23dd20dfdb 0000-0001-9199-7368 Fabio Caraffini Fabio Caraffini true false 2023-04-09 MACS 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. Book chapter Applications of Evolutionary Computation 475 490 Springer Nature Switzerland Cham 9783031302282 9783031302299 0302-9743 1611-3349 1 1 2023 2023-01-01 10.1007/978-3-031-30229-9_31 http://dx.doi.org/10.1007/978-3-031-30229-9_31 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University Not Required 2023-04-09T15:55:54.2558381 2023-04-09T10:40:40.8966643 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Antonio Agresta 0000-0003-4037-7403 1 Chiara Biscarini 0000-0003-2279-7244 2 Fabio Caraffini 0000-0001-9199-7368 3 Valentino Santucci 0000-0003-1483-7998 4
title An Intelligent Optimised Estimation of the Hydraulic Jump Roller Length
spellingShingle An Intelligent Optimised Estimation of the Hydraulic Jump Roller Length
Fabio Caraffini
title_short An Intelligent Optimised Estimation of the Hydraulic Jump Roller Length
title_full An Intelligent Optimised Estimation of the Hydraulic Jump Roller Length
title_fullStr An Intelligent Optimised Estimation of the Hydraulic Jump Roller Length
title_full_unstemmed An Intelligent Optimised Estimation of the Hydraulic Jump Roller Length
title_sort An Intelligent Optimised Estimation of the Hydraulic Jump Roller Length
author_id_str_mv d0b8d4e63d512d4d67a02a23dd20dfdb
author_id_fullname_str_mv d0b8d4e63d512d4d67a02a23dd20dfdb_***_Fabio Caraffini
author Fabio Caraffini
author2 Antonio Agresta
Chiara Biscarini
Fabio Caraffini
Valentino Santucci
format Book chapter
container_title Applications of Evolutionary Computation
container_start_page 475
publishDate 2023
institution Swansea University
isbn 9783031302282
9783031302299
issn 0302-9743
1611-3349
doi_str_mv 10.1007/978-3-031-30229-9_31
publisher Springer Nature Switzerland
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
url http://dx.doi.org/10.1007/978-3-031-30229-9_31
document_store_str 0
active_str 0
description 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.
published_date 2023-01-01T02:40:36Z
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score 11.048042

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