By addressing both the technical and operational aspects of SHM, the book serves as an invaluable foundational reference resource to equip readers with the advanced knowledge and practical expertise needed to adopt these cutting-edge systems in their own infrastructure management workflows.
Table of Contents
1. Introduction2. Bridge management
3. Case studies: structural description and data sets
4. An overview of structural health monitoring
5. Statistical pattern recognition
6. Probabilistic numerical models for hybrid databases
7. Unsupervised learning strategy
8. Supervised learning strategy
9. Transfer learning
10. The role of SHM for climate change adaptation
11. Limitation, challenges, and future trends
Authors
El�i Figueiredo Full Professor, Faculty of Engineering, Universidade Lus�fona, Lisbon, Portugal.PhD in Civil Engineering (2010) and Full Professor at Universidade Lus�fona (Portugal). Throughout his academic career, El�i has taught courses in the field of static and dynamic structural analysis, seismic engineering, and design of reinforced and prestressed concrete structures. His research has mainly focused on structural health monitoring (SHM) and management of bridges, particularly on damage identification based on machine learning techniques and finite element modeling. He is an Associate Editor of Structural Health Monitoring (SAGE) and a prolific author of books, book chapters, peer-reviewed journal articles, and conference proceedings, all of which also reflect his collaborative stance with experts from across the globe. He has recently been awarded an EEA grant to study the impact of climate change on the structural health of bridges (ClimaBridge Project) and is the leader of the Civil Research Group at Universidade Lus�fona to promote sustainable and resilient infrastructure.
Ionut Dragos Moldovan Associate Professor, Faculty of Engineering, Universidade Lus�fona, Lisbon, Portugal. PhD in Civil Engineering (2008) from the University of Lisbon, Associate Professor at Universidade Lus�fona, and Research Associate at the CERIS Research Centre (University of Lisbon). His research interests include the development of non-conventional (hybrid-Trefftz) finite elements with applications to geomechanics, structural mechanics, heat transfer and acoustics, and structural health monitoring of civil engineering structures. Ionut is the Principal Investigator of the research project CEN-DynaGeo ("Coupled Experimental and Numerical Approaches Toward Reliable Dynamic Characterization of Multi-phase Geomaterials�), funded by the Science and Technology Foundation of Portugal, and is participating simultaneously in four other research projects with national and European exposure. He is a prolific author, holds a patent for an innovative procedure for the dynamic characterization of soils using hybrid-Trefftz finite elements, and is the initiator and lead developer of FreeHyTE (e.g., the first public, open-source, and user-friendly computational platform using hybrid-Trefftz finite elements).
