Structural Health Monitoring in Bridge Engineering

A special issue of Infrastructures (ISSN 2412-3811).

Deadline for manuscript submissions: 10 June 2025 | Viewed by 100

Special Issue Editors


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Guest Editor
Graduate Program in Civil Engineering, Faculty of Engineering, University of Juiz de Fora, Juiz de Fora 36036-900, MG, Brazil
Interests: structural health monitoring; data science; damage detection
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Guest Editor
Structural Dynamics and Assessment Laboratory, School of Civil Engineering, University College Dublin, D04 V1W8 Dublin, Ireland
Interests: structural dynamics and assessments; railway track monitoring; railway bridge monitoring; machine learning for SHM
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Guest Editor
Department of Mechanical and Industrial Engineering, University of Massachusetts Lowell, Lowell, MA 01852, USA
Interests: artificial intelligence; computer vision; drone-borne inspection; non-destructive evaluations (NDE); structural health monitoring (SHM); sensors; smart structures
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Graduate Program in Civil Engineering, Faculty of Engineering, University of Juiz de Fora, Juiz de Fora 36036-900, MG, Brazil
Interests: structures and materials

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Guest Editor
Department of Structural, Geotechnical and Building Engineering (DISEG), Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Turin, Italy
Interests: damage detection; structural health monitoring; mechanical testing; structural dynamics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As bridges worldwide age and become more complex, the need for effective Structural Health Monitoring (SHM) tools has never been more urgent. SHM systems can provide real-time assessments, early detection of potential problems, and proactive maintenance strategies to prevent catastrophic failures. Recent advancements in artificial intelligence and big data have significantly accelerated the development of SHM techniques for critical civil structures and infrastructure, such as bridges and viaducts.

This Special Issue brings together the latest research, findings, and practical applications in the field of SHM for bridge structures. Contributions should focus on innovative approaches that enhance the reliability, efficiency, and cost-effectiveness of bridge health assessment and management.

Potential topics include but are not limited to:

  • Novel SHM technologies: Wireless sensor networks, fiber optic sensors, unmanned aerial vehicles (UAVs), ground-penetrating radar (GPR), computer vision (CV), and other emerging techniques.
  • Data-driven SHM: Machine learning, deep learning, and artificial intelligence applications for data analysis, damage detection, and prognosis.
  • Multi-sensor fusion: Integration of different sensor modalities for comprehensive bridge monitoring and assessment.
  • SHM for specific bridge types: Applications for various bridge types, such as concrete, steel, composite, and cable-stayed bridges.
  • SHM in extreme events: Monitoring and assessment of bridge structures during and after natural disasters, earthquakes, and other extreme events.
  • SHM for long-term monitoring: Long-term monitoring strategies and data management techniques for bridge health evaluation.
  • SHM for maintenance and rehabilitation: Integration of SHM data into bridge maintenance and rehabilitation planning and decision-making.
  • Case studies and practical applications: Real-world examples of SHM implementation in bridge engineering projects.

Authors are invited to submit original research papers, review articles, or technical notes on SHM of bridges. Submissions should present novel methods, experiments, or applications that advance SHM technology. We encourage interdisciplinary approaches, theoretical developments, and practical innovations. All submitted papers will undergo rigorous peer review. This Special Issue aims to foster collaborations and knowledge exchange in bridge engineering to address critical SHM challenges.

Dr. Alexandre A. Cury
Dr. Abdollah Malekjafarian
Dr. Alessandro Sabato
Dr. Flavio Barbosa
Dr. Marco Civera
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Infrastructures is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • novel SHM technologies
  • data-driven SHM
  • multi-sensor fusion
  • SHM for specific bridge types
  • SHM in extreme events
  • SHM for long-term monitoring
  • SHM for maintenance and rehabilitation
  • case studies and practical applications

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Published Papers

This special issue is now open for submission.
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