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Physics-Informed Intelligence in Structural Health Monitoring: A State-of-the-Art Review and Roadmap Towards Digital Twins
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DOI：10.1016/j.dibe.2026.100977.png)
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Abstract
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• Reviews recent studies on physics-informed intelligence for bridge monitoring. • Introduces a seven-criterion quality appraisal for reviewed studies. • Compares graph, operator, parallel, and real-time updated models. • Finds uncertainty quantification is the field's weakest validation practice. • Proposes a three-phase roadmap for bridge digital twin deployment.
Keywords:
Bridge engineering
Digital twin
Physics-informed neural networks
Structural health monitoring
Deep learning
Damage detection
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