Enabling methods for predictive digital twin in pavement performance modelling

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Enabling methods for predictive digital twin in pavement performance modelling

Roads are vital assets and the backbone for any transportation system and support societal development by providing the foundation for constant mobility of goods and people. However, pavements are experiencing accelerated deterioration in most developed countries due to increased traffic volume and...

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Bibliographic Details
Main Author:	Chen, Kun
Format:	Thesis (University of Nottingham only)
Language:	English
Published:	2025
Subjects:	Digital Twins Sensor Data Data Collection Frequency Machine Learning Physics Enhanced Machine Learning Physics-based Simulation Road Asset Management Pavement Performance Prediction Uncertainty Quantification
Online Access:	https://eprints.nottingham.ac.uk/80800/

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