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Grant support

This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 958171. This work has been partially supported by the Spanish Ministry of Science and Innovation through the PONT3 project Ref. PID2021-124236OB-C33. This work has also been supported by the Spanish Ministry of Science, Innovation, and Universities through the grant PRE2019-087331 for the training of predoctoral researchers. This document reflects only the views of the authors. Neither the Innovation and Networks Executive Agency (INEA) nor the European Commission is in any way responsible for any use that may be made of the information it contains.

Analysis of institutional authors

Barros, BCorresponding Author

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December 23, 2024
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Gaussian Copula-based Bayesian network approach for characterizing spatial variability in aging steel bridges

Publicated to:Structural Safety. 106 102403- - 2023-11-06 106(), DOI: 10.1016/j.strusafe.2023.102403

Authors: Barros, B; Conde, B; Riveiro, B; Morales-Napoles, O

Affiliations

Delft Univ Technol, Fac Civil Engn & Geosci, POB 5, NL-2600 AA Delft, Netherlands - Author
Univ Vigo, CINTECX, GeoTECH Grp, Campus Univ Vigo, Vigo 36310, Spain - Author

Abstract

Finite Element (FE) modeling often requires unavoidable simplifications or assumptions due to a lack of experimental data, modeling complexity, or non-affordable computational cost. One such simplification is modeling corrosion phenomena or material properties, which are usually assumed to be uniform throughout the structure. However, e.g., corrosion has a local nature and severe consequences on the behavior of steel structures that should not be overlooked. To improve the current numerical modeling techniques in aging steel bridges, this paper proposes a Gaussian Copula-based Bayesian Network (GCBN) approach to model the spatial variability of structural element properties. Accordingly, a study of the automatic Bayesian network generation process is first conducted. Subsequently, the methodology is applied to a severely damaged riveted steel bridge built in 1897. The results show that the methodology has excellent flexibility for generating properties variability in FE models at a low computational cost, thus ensuring its practical feasibility and robustness for accurate numerical modeling.

Keywords

Aging steel bridgeCorrosionFe modelingFieldGaussian copula-based bayesian networkInferenceMasonry arch bridgesModelRandom fieldReinforced-concrete structuresReliability-analysisResidual strengthSystemsTensile-strength

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Structural Safety due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2023, it was in position 16/182, thus managing to position itself as a Q1 (Primer Cuartil), in the category Engineering, Civil. Notably, the journal is positioned above the 90th percentile.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2025-07-17:

  • WoS: 2

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-07-17:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 9.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 16 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 1.
  • The number of mentions on the social network X (formerly Twitter): 1 (Altmetric).

Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Netherlands.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (Barros González, Brais) .

the author responsible for correspondence tasks has been Barros González, Brais.