Work

Field data-based prediction of local scour depth around bridge piers using interpretable machine learning

Year: 2025

Type: article

Source: Transportation Geotechnics

DOI: 10.1016/j.trgeo.2025.101567

Authors: Taeyoon Kim, Azmayeen R. Shahriar, Woo-Dong Lee, Yongjin Choi, Siyoon Kwon, Mohammed A. Gabr.

Institutions: North Carolina State University, Pukyong National University, Gyeongsang National University, University of Wollongong, The University of Texas at Austin

Language: English

Topic: Hydrology and Sediment Transport Processes

Subfield: Ecology

Field: Environmental Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: closed

Funders: National Research Foundation of Korea, Institute for Information and Communications Technology Promotion

Awards: G1762035644, G2319719052

OpenAlex ID: W4409563191

FWCI: 4.149

Cites: 72

Cited by: 8

Related to: 10