Open channel sluice gate scouring parameters prediction: different scenarios of dimensional and non-dimensional input parameters

The determination of scour characteristics in the downstreamof sluice gate is highly important for designing and protection of hydraulic structure. The applicability of modern data-intelligence technique known as extreme learning machine (ELM) to simulate scour characteristics has been examined in t...

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Main Authors: Yousif, Ali A., Sulaiman, Sadeq Oleiwi, Diop, Lamine, Ehteram, Mohammad, Shahid, Shamsuddin, Al-Ansari, Nadhir, Yaseen, Zaher Mundher
Format: Article
Language:English
Published: MDPI AG 2019
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Online Access:http://eprints.utm.my/id/eprint/88983/1/ShamsuddinShahid2019_OpenChannelSluiceGateScouring.pdf
http://eprints.utm.my/id/eprint/88983/
http://dx.doi.org/10.3390/w11020353
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Institution: Universiti Teknologi Malaysia
Language: English
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spelling my.utm.889832021-01-26T08:36:25Z http://eprints.utm.my/id/eprint/88983/ Open channel sluice gate scouring parameters prediction: different scenarios of dimensional and non-dimensional input parameters Yousif, Ali A. Sulaiman, Sadeq Oleiwi Diop, Lamine Ehteram, Mohammad Shahid, Shamsuddin Al-Ansari, Nadhir Yaseen, Zaher Mundher TA Engineering (General). Civil engineering (General) The determination of scour characteristics in the downstreamof sluice gate is highly important for designing and protection of hydraulic structure. The applicability of modern data-intelligence technique known as extreme learning machine (ELM) to simulate scour characteristics has been examined in this study. Three major characteristics of scour hole in the downstream of a sluice gate, namely the length of scour hole (Ls), the maximum scour depth (Ds), and the position of maximum scour depth (Lsm), are modeled using different properties of the flow and bed material. The obtained results using ELM were compared with multivariate adaptive regression spline (MARS). The dimensional analysis technique was used to reduce the number of input variable to a smaller number of dimensionless groups and both the dimensional and non-dimensional variables were used to model the scour characteristics. The prediction performances of the developed models were examined using several statistical metrics. The results revealed that ELM can predict scour properties with much higher accuracy compared to MARS. The errors in prediction can be reduced in the range of 79%-81% using ELM models compared to MARS models. Better performance of the models was observed when dimensional variables were used as input. The result indicates that the use of ELM with non-dimensional data can provide high accuracy in modeling complex hydrological problems. MDPI AG 2019-02-19 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/88983/1/ShamsuddinShahid2019_OpenChannelSluiceGateScouring.pdf Yousif, Ali A. and Sulaiman, Sadeq Oleiwi and Diop, Lamine and Ehteram, Mohammad and Shahid, Shamsuddin and Al-Ansari, Nadhir and Yaseen, Zaher Mundher (2019) Open channel sluice gate scouring parameters prediction: different scenarios of dimensional and non-dimensional input parameters. Water (Switzerland), 11 (2). pp. 1-14. ISSN 2073-4441 http://dx.doi.org/10.3390/w11020353 DOI:10.3390/w11020353
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Yousif, Ali A.
Sulaiman, Sadeq Oleiwi
Diop, Lamine
Ehteram, Mohammad
Shahid, Shamsuddin
Al-Ansari, Nadhir
Yaseen, Zaher Mundher
Open channel sluice gate scouring parameters prediction: different scenarios of dimensional and non-dimensional input parameters
description The determination of scour characteristics in the downstreamof sluice gate is highly important for designing and protection of hydraulic structure. The applicability of modern data-intelligence technique known as extreme learning machine (ELM) to simulate scour characteristics has been examined in this study. Three major characteristics of scour hole in the downstream of a sluice gate, namely the length of scour hole (Ls), the maximum scour depth (Ds), and the position of maximum scour depth (Lsm), are modeled using different properties of the flow and bed material. The obtained results using ELM were compared with multivariate adaptive regression spline (MARS). The dimensional analysis technique was used to reduce the number of input variable to a smaller number of dimensionless groups and both the dimensional and non-dimensional variables were used to model the scour characteristics. The prediction performances of the developed models were examined using several statistical metrics. The results revealed that ELM can predict scour properties with much higher accuracy compared to MARS. The errors in prediction can be reduced in the range of 79%-81% using ELM models compared to MARS models. Better performance of the models was observed when dimensional variables were used as input. The result indicates that the use of ELM with non-dimensional data can provide high accuracy in modeling complex hydrological problems.
format Article
author Yousif, Ali A.
Sulaiman, Sadeq Oleiwi
Diop, Lamine
Ehteram, Mohammad
Shahid, Shamsuddin
Al-Ansari, Nadhir
Yaseen, Zaher Mundher
author_facet Yousif, Ali A.
Sulaiman, Sadeq Oleiwi
Diop, Lamine
Ehteram, Mohammad
Shahid, Shamsuddin
Al-Ansari, Nadhir
Yaseen, Zaher Mundher
author_sort Yousif, Ali A.
title Open channel sluice gate scouring parameters prediction: different scenarios of dimensional and non-dimensional input parameters
title_short Open channel sluice gate scouring parameters prediction: different scenarios of dimensional and non-dimensional input parameters
title_full Open channel sluice gate scouring parameters prediction: different scenarios of dimensional and non-dimensional input parameters
title_fullStr Open channel sluice gate scouring parameters prediction: different scenarios of dimensional and non-dimensional input parameters
title_full_unstemmed Open channel sluice gate scouring parameters prediction: different scenarios of dimensional and non-dimensional input parameters
title_sort open channel sluice gate scouring parameters prediction: different scenarios of dimensional and non-dimensional input parameters
publisher MDPI AG
publishDate 2019
url http://eprints.utm.my/id/eprint/88983/1/ShamsuddinShahid2019_OpenChannelSluiceGateScouring.pdf
http://eprints.utm.my/id/eprint/88983/
http://dx.doi.org/10.3390/w11020353
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