Scour Detection with Monitoring Methods and Machine Learning Algorithms—A Critical Review
Source abstract
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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Hydrology and Sediment Transport Processes · Hydraulic flow and structures · Dam Engineering and Safety
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Civil Engineering, University of Minho, ISISE, 4800-058 Guimarães, Portugal
School of Civil Engineering, University College Dublin, D04 V1W8 Dublin, Ireland
Funding
Portuguese national funding agency for science, research, and technology · national funds (PIDDAC) · European Horizon 2020 Joint Technology Initiative Shift2Rail
References (100+)
Show source-provided references
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