A New Methodology for the Diagnosis and Monitoring of Bridges Under Slow Deformation Phenomena

Roadway bridges can be subjected to several pathologies affecting their structural performance during operational conditions. Among others, slow deformation phenomena due to landslides often represent the primary cause of the onset of damage and collapse mechanisms. The timely identification of slow deformation phenomena on bridges and viaducts, as well as the evaluation of their extent and evolution over time, are therefore of crucial importance for preserving the safety conditions of road networks. In common practice, the preliminary analysis of slow deformation phenomena could be carried out over large geographical areas, hence used by managing institutions to set intervention priorities among the assets under their responsibility. In this regard, this paper proposes a new methodology for the diagnosis and monitoring of bridges under the effects of slow deformation phenomena based on the combined use of Synthetic Aperture Radar Interferometry (InSAR) techniques, visual inspections, geometric surveys, destructive and non-destructive testing methods, and numerical analyses. Specifically, InSAR is adopted to remotely identify bridges affected by slow deformation phenomena within large geographical areas/road networks. Then, visual inspections are carried out on the identified structures to investigate their defectiveness and the detected deformation phenomenon. Depending on the evaluated damage state, a bridge may be subjected to continuous InSAR monitoring, thus enabling the systematic analysis of the evolution of the deformation phenomenon and relevant anomalies over time, or an accurate structural assessment via numerical analyses. In this last circumstance, information gathered from geometric surveys and field tests can be used for the fine-tuning of the numerical models of the structures. A practical application of the proposed methodology for the diagnosis and monitoring of a curved roadway bridge subjected to landslide phenomena is also presented in the paper for illustrative purposes. Overall, the results obtained in the case study provide a sound demonstration of the effectiveness of the proposed approach.

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Publication Details

Journal
BER :
Published
2024-09-05
DOI
https://doi.org/10.70465/ber.v1i1.1
Citations
3
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
0.78

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article

A New Methodology for the Diagnosis and Monitoring of Bridges Under Slow Deformation Phenomena

Fabrizio Scozzese, Matteo Castellani, Simone Celati, Elisabetta Farneti et al.
3 citations
BER :
Structural Health Monitoring Techniques
0.78
article

A New Methodology for the Diagnosis and Monitoring of Bridges Under Slow Deformation Phenomena

Fabrizio Scozzese, Matteo Castellani, Simone Celati, Elisabetta Farneti, Filippo Ubertini, Andrea Meoni, Walter Salvatore, Michele Morici, Ilaria Venanzi, Nicola Cavalagli, Laura Ierimonti, Agnese Natali, Andrea Dall’Asta, Anil K. Agrawal, Filippo Filippucci
article en
3 citations

Abstract

Roadway bridges can be subjected to several pathologies affecting their structural performance during operational conditions. Among others, slow deformation phenomena due to landslides often represent the primary cause of the onset of damage and collapse mechanisms. The timely identification of slow deformation phenomena on bridges and viaducts, as well as the evaluation of their extent and evolution over time, are therefore of crucial importance for preserving the safety conditions of road networks. In common practice, the preliminary analysis of slow deformation phenomena could be carried out over large geographical areas, hence used by managing institutions to set intervention priorities among the assets under their responsibility. In this regard, this paper proposes a new methodology for the diagnosis and monitoring of bridges under the effects of slow deformation phenomena based on the combined use of Synthetic Aperture Radar Interferometry (InSAR) techniques, visual inspections, geometric surveys, destructive and non-destructive testing methods, and numerical analyses. Specifically, InSAR is adopted to remotely identify bridges affected by slow deformation phenomena within large geographical areas/road networks. Then, visual inspections are carried out on the identified structures to investigate their defectiveness and the detected deformation phenomenon. Depending on the evaluated damage state, a bridge may be subjected to continuous InSAR monitoring, thus enabling the systematic analysis of the evolution of the deformation phenomenon and relevant anomalies over time, or an accurate structural assessment via numerical analyses. In this last circumstance, information gathered from geometric surveys and field tests can be used for the fine-tuning of the numerical models of the structures. A practical application of the proposed methodology for the diagnosis and monitoring of a curved roadway bridge subjected to landslide phenomena is also presented in the paper for illustrative purposes. Overall, the results obtained in the case study provide a sound demonstration of the effectiveness of the proposed approach.

BER :Vol. 1(1)
University of Pisa (IT), Università di Camerino (IT), City College of New York (US), University of Perugia (IT)
European Commission, Università degli Studi di Perugia, Università degli Studi di Camerino
Sustainable cities and communities
Openalex Percentile: Top 30%
Structural Health Monitoring Techniques
0.78
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