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Ponte Moesa Campagnola: A Bridge Benchmark for Structural Identification under Controlled Damage Progression.

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Title: Ponte Moesa Campagnola: A Bridge Benchmark for Structural Identification under Controlled Damage Progression.
Authors: Garcia-Ramonda, Larisa1 (AUTHOR) larisa.garcia.ramonda@upc.edu, Bogoevska, Simona2 (AUTHOR) simona.bogoevska@gf.ukim.edu.mk, Reuland, Yves3 (AUTHOR) reuland@irmos-tech.com, Martakis, Panagiotis4 (AUTHOR) martakis@irmos-tech.com, Dertimanis, Vasilis5 (AUTHOR) v.derti@ibk.baug.ethz.ch, Chatzi, Eleni6 (AUTHOR) chatzi@ibk.baug.ethz.ch
Source: Journal of Structural Engineering. Dec2025, Vol. 151 Issue 12, p1-15. 15p.
Subjects: Structural health monitoring, Bridge testing, Structural analysis (Engineering), Bridge design & construction, Empirical research
Abstract: In addressing the challenge of ageing infrastructure, continuous structural monitoring has figured prominently in the development of tools for risk management and life-cycle prognostic strategies. However, a primary challenge lies in robustly quantifying structural condition using, typically indirect, monitoring observations. In recent years, a vast number of various data-driven or hybrid analysis methods have been proposed, targeting different levels of the so-called Rytter's hierarchy of damage identification. The more advanced identification tasks, relating to a more precise characterization (e.g., location and quantity) of damage are nontrivial to address. A primary difficulty in this respect relates to lack of labelled data corresponding to predefined damage states of the structure of interest. This implies that for most practical contexts, such structural identification ought to be achieved in an unsupervised manner. This work presents a new full-scale bridge experimental benchmark which can serve as a case study for verification and validation of damage identification schemes. The Ponte Moesa Campagnola (PMC) benchmark structure, which was decommissioned in 2019, represents a typical bridge structure of the Swiss Roadway Network. The bridge was subjected to a 4-day monitoring campaign, during which controlled damage progression scenarios were implemented. The monitored quantities comprised a multimodal mix of both acceleration and strain information, continually recorded during the 4-day campaign. The reported results demonstrate the potential of this data set to serve for structural identification and damage detection (DD) purposes. To this end, we present—merely as a viability study—the successful implementation of three damage-sensitive features (DSFs). The goal was to describe the data set and introduce it for further study, testing, and validation of emerging DD algorithms tailored for full-scale structural health monitoring (SHM) utilization. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Structural Engineering is the property of American Society of Civil Engineers and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 188757536
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Ponte Moesa Campagnola: A Bridge Benchmark for Structural Identification under Controlled Damage Progression.
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  Data: <searchLink fieldCode="AR" term="%22Garcia-Ramonda%2C+Larisa%22">Garcia-Ramonda, Larisa</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> larisa.garcia.ramonda@upc.edu</i><br /><searchLink fieldCode="AR" term="%22Bogoevska%2C+Simona%22">Bogoevska, Simona</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> simona.bogoevska@gf.ukim.edu.mk</i><br /><searchLink fieldCode="AR" term="%22Reuland%2C+Yves%22">Reuland, Yves</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> reuland@irmos-tech.com</i><br /><searchLink fieldCode="AR" term="%22Martakis%2C+Panagiotis%22">Martakis, Panagiotis</searchLink><relatesTo>4</relatesTo> (AUTHOR)<i> martakis@irmos-tech.com</i><br /><searchLink fieldCode="AR" term="%22Dertimanis%2C+Vasilis%22">Dertimanis, Vasilis</searchLink><relatesTo>5</relatesTo> (AUTHOR)<i> v.derti@ibk.baug.ethz.ch</i><br /><searchLink fieldCode="AR" term="%22Chatzi%2C+Eleni%22">Chatzi, Eleni</searchLink><relatesTo>6</relatesTo> (AUTHOR)<i> chatzi@ibk.baug.ethz.ch</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Structural+Engineering%22">Journal of Structural Engineering</searchLink>. Dec2025, Vol. 151 Issue 12, p1-15. 15p.
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  Data: <searchLink fieldCode="DE" term="%22Structural+health+monitoring%22">Structural health monitoring</searchLink><br /><searchLink fieldCode="DE" term="%22Bridge+testing%22">Bridge testing</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+analysis+%28Engineering%29%22">Structural analysis (Engineering)</searchLink><br /><searchLink fieldCode="DE" term="%22Bridge+design+%26+construction%22">Bridge design & construction</searchLink><br /><searchLink fieldCode="DE" term="%22Empirical+research%22">Empirical research</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: In addressing the challenge of ageing infrastructure, continuous structural monitoring has figured prominently in the development of tools for risk management and life-cycle prognostic strategies. However, a primary challenge lies in robustly quantifying structural condition using, typically indirect, monitoring observations. In recent years, a vast number of various data-driven or hybrid analysis methods have been proposed, targeting different levels of the so-called Rytter's hierarchy of damage identification. The more advanced identification tasks, relating to a more precise characterization (e.g., location and quantity) of damage are nontrivial to address. A primary difficulty in this respect relates to lack of labelled data corresponding to predefined damage states of the structure of interest. This implies that for most practical contexts, such structural identification ought to be achieved in an unsupervised manner. This work presents a new full-scale bridge experimental benchmark which can serve as a case study for verification and validation of damage identification schemes. The Ponte Moesa Campagnola (PMC) benchmark structure, which was decommissioned in 2019, represents a typical bridge structure of the Swiss Roadway Network. The bridge was subjected to a 4-day monitoring campaign, during which controlled damage progression scenarios were implemented. The monitored quantities comprised a multimodal mix of both acceleration and strain information, continually recorded during the 4-day campaign. The reported results demonstrate the potential of this data set to serve for structural identification and damage detection (DD) purposes. To this end, we present—merely as a viability study—the successful implementation of three damage-sensitive features (DSFs). The goal was to describe the data set and introduce it for further study, testing, and validation of emerging DD algorithms tailored for full-scale structural health monitoring (SHM) utilization. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Structural Engineering is the property of American Society of Civil Engineers and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1061/JSENDH.STENG-15086
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      – Code: eng
        Text: English
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        PageCount: 15
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      – SubjectFull: Structural health monitoring
        Type: general
      – SubjectFull: Bridge testing
        Type: general
      – SubjectFull: Structural analysis (Engineering)
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      – SubjectFull: Bridge design & construction
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      – SubjectFull: Empirical research
        Type: general
    Titles:
      – TitleFull: Ponte Moesa Campagnola: A Bridge Benchmark for Structural Identification under Controlled Damage Progression.
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            NameFull: Garcia-Ramonda, Larisa
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              M: 12
              Text: Dec2025
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              Y: 2025
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