Scour Detection with Monitoring Methods and Machine Learning Algorithms—A Critical Review

Author:

Tola Sinem1,Tinoco Joaquim1ORCID,Matos José C.1ORCID,Obrien Eugene2ORCID

Affiliation:

1. Department of Civil Engineering, University of Minho, ISISE, 4800-058 Guimarães, Portugal

2. School of Civil Engineering, University College Dublin, D04 V1W8 Dublin, Ireland

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.

Funder

Portuguese national funding agency for science, research, and technology

national funds

European Horizon 2020 Joint Technology Initiative Shift2Rail

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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