Scour detection with monitoring methods and machine learning algorithms - a critical review

doi:10.3390/app13031661

Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/84726

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Campo DC	Valor	Idioma
dc.contributor.author	Tola, Sinem	por
dc.contributor.author	Tinoco, Joaquim	por
dc.contributor.author	Matos, José C.	por
dc.contributor.author	Obrien, Eugene	por
dc.date.accessioned	2023-05-25T13:34:57Z	-
dc.date.available	2023-05-25T13:34:57Z	-
dc.date.issued	2023-01-28	-
dc.identifier.citation	Tola, S.; Tinoco, J.; Matos, J.C.; Obrien, E. Scour Detection with Monitoring Methods and Machine Learning Algorithms—A Critical Review. Appl. Sci. 2023, 13, 1661. https://doi.org/10.3390/app13031661	por
dc.identifier.uri	https://hdl.handle.net/1822/84726	-
dc.description.abstract	Foundation scour is a widespread reason for the collapse of bridges worldwide. However, assessing bridges is a complex task, which requires a comprehensive understanding of the phenomenon. This literature review first presents recent scour detection techniques and approaches. Direct and indirect monitoring and machine learning algorithm-based studies are investigated in detail in the following sections. The approaches, models, characteristics of data, and other input properties are outlined. The outcomes are given with their advantages and limitations. Finally, assessments are provided at the synthesis of the research.	por
dc.description.sponsorship	This research was funded by FCT (Portuguese national funding agency for science, research, and technology)/MCTES through national funds (PIDDAC) under the R&D Unit Institute for Sustainability and Innovation in Structural Engineering (ISISE), under reference UIDB/04029/2020 and trough the doctoral Grant 2021.06162.BD. This work has also been partly financed within the European Horizon 2020 Joint Technology Initiative Shift2Rail through contract no. 101012456 (IN2TRACK3).	por
dc.language.iso	eng	por
dc.publisher	Multidisciplinary Digital Publishing Institute (MDPI)	por
dc.relation	info:eu-repo/grantAgreement/FCT/POR_NORTE/2021.06162.BD/PT	por
dc.relation	info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04029%2F2020/PT	por
dc.relation	info:eu-repo/grantAgreement/EC/H2020/101012456/EU	por
dc.rights	openAccess	por
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/	por
dc.subject	Bridge scour	por
dc.subject	Scour detection	por
dc.subject	Scour monitoring	por
dc.subject	Machine learning algorithms	por
dc.title	Scour detection with monitoring methods and machine learning algorithms - a critical review	por
dc.type	article	-
dc.peerreviewed	yes	por
dc.relation.publisherversion	https://www.mdpi.com/2076-3417/13/3/1661	por
oaire.citationStartPage	1	por
oaire.citationEndPage	25	por
oaire.citationIssue	3	por
oaire.citationVolume	13	por
dc.identifier.eissn	2076-3417	por
dc.identifier.doi	10.3390/app13031661	por
dc.subject.fos	Engenharia e Tecnologia::Engenharia Civil	por
dc.subject.wos	Science & Technology	por
sdum.journal	Applied Sciences	por
oaire.version	VoR	por
dc.identifier.articlenumber	1661	por
Aparece nas coleções:	ISISE - Artigos em Revistas Internacionais

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2023_[Sinem2023 - ApplSci] Scour Detection with Monitoring Methods and Machine Learning Algorithms - A Critical Review.pdf	Journal paper	743,53 kB	Adobe PDF	Ver/Abrir

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