A probabilistic strategy to evaluate scour around bridge deepwater foundations considering a reliability assessment

Wang, C; Yuan, Y; Zhu, W; Wang, C; Yu, X

A probabilistic strategy to evaluate scour around bridge deepwater foundations considering a reliability assessment

Wang, C

Yuan, Y Zhu, W Wang, C

Yu, X

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Publisher:: TAYLOR & FRANCIS INC
Publication Type:: Journal Article
Citation:: Marine Georesources and Geotechnology, 2023, 41, (1), pp. 54-66
Issue Date:: 2023-01-01

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Field	Value	Language
dc.contributor.author	Wang, C https://orcid.org/0000-0002-2802-1394
dc.contributor.author	Yuan, Y
dc.contributor.author	Zhu, W
dc.contributor.author	Wang, C https://orcid.org/0000-0002-2802-1394
dc.contributor.author	Yu, X
dc.date.accessioned	2024-06-05T00:03:51Z
dc.date.available	2024-06-05T00:03:51Z
dc.date.issued	2023-01-01
dc.identifier.citation	Marine Georesources and Geotechnology, 2023, 41, (1), pp. 54-66
dc.identifier.issn	1064-119X
dc.identifier.issn	1521-0618
dc.identifier.uri	http://hdl.handle.net/10453/179392
dc.description.abstract	Currently, an increasing number of deepwater foundations have been built in marine regions, and most of them have to deal with scour problems. Recent design codes of superstructures usually adopt the probability-based method, in which loads are treated as probabilistic parameters. However, for the design of substructures, the impact of scour is generally regarded as a deterministic value represented by the estimated scour depth. This inconsistency in the design strategies brings difficulties in considering the uncertainties associated with scour effects. Fundamentally, this is due to the challenges in the scour estimation using a probabilistic method. Based on an augmented scour database analyzed using the artificial neural-network (ANN), this study quantifies the uncertainties of four types of scour predictive methods. Based on this, it proposes a probabilistic approach for scour estimation according to different cases. Six typical conditions and two practical cases were analyzed using the probabilistic approach. The overall reliability index showed that all these existing scour estimation methods have certain limitations, including inconsistent reliability and unreliable scour depth predictions. To prevent these problems, a concept based on the probability of nonexceedance of a given scour depth has been proposed, which was determined by different target reliability requirements.
dc.language	English
dc.publisher	TAYLOR & FRANCIS INC
dc.relation.ispartof	Marine Georesources and Geotechnology
dc.relation.isbasedon	10.1080/1064119X.2021.2011505
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0405 Oceanography, 0914 Resources Engineering and Extractive Metallurgy
dc.subject.classification	Oceanography
dc.subject.classification	4005 Civil engineering
dc.title	A probabilistic strategy to evaluate scour around bridge deepwater foundations considering a reliability assessment
dc.type	Journal Article
utslib.citation.volume	41
utslib.for	0405 Oceanography
utslib.for	0914 Resources Engineering and Extractive Metallurgy
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
utslib.copyright.status	closed_access	*
dc.date.updated	2024-06-05T00:03:49Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	41
utslib.citation.issue	1

Abstract:

Currently, an increasing number of deepwater foundations have been built in marine regions, and most of them have to deal with scour problems. Recent design codes of superstructures usually adopt the probability-based method, in which loads are treated as probabilistic parameters. However, for the design of substructures, the impact of scour is generally regarded as a deterministic value represented by the estimated scour depth. This inconsistency in the design strategies brings difficulties in considering the uncertainties associated with scour effects. Fundamentally, this is due to the challenges in the scour estimation using a probabilistic method. Based on an augmented scour database analyzed using the artificial neural-network (ANN), this study quantifies the uncertainties of four types of scour predictive methods. Based on this, it proposes a probabilistic approach for scour estimation according to different cases. Six typical conditions and two practical cases were analyzed using the probabilistic approach. The overall reliability index showed that all these existing scour estimation methods have certain limitations, including inconsistent reliability and unreliable scour depth predictions. To prevent these problems, a concept based on the probability of nonexceedance of a given scour depth has been proposed, which was determined by different target reliability requirements.

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http://hdl.handle.net/10453/179392