A digital twin approach based method in civil engineering for classification of salt damage in building evaluation

J.A. Guzmán-Torres, F.J. Domínguez-Mota, E.M. Alonso Guzmán, G. Tinoco-Guerrero and J.G. Tinoco-Ruíz

Mathematics and Computers in Simulation (MATCOM), 2025, vol. 233, issue C, 433-447

Abstract: The integration of digital twins and machine learning models in civil engineering has revolutionized the inspection and maintenance of buildings and structures. Digital twins, as precise virtual replicas of physical assets, enable continuous monitoring and predictive maintenance, enhancing the reliability and efficiency of structural assessments.

Keywords: Digital twin; Salt damage; Deep learning; Damage classification; Transfer learning (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:233:y:2025:i:c:p:433-447

DOI: 10.1016/j.matcom.2025.02.003

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