Smart Structures and Systems

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Damage identification in a wrought iron railway bridge using the inverse analysis of the static stress response under rail traffic loading

  • Sidali Iglouli (Civil Engineering Department, Faculty of Technology, Tlemcen University) ;
  • Nadir Boumechra (Civil Engineering Department, Faculty of Technology, Tlemcen University) ;
  • Karim Hamdaoui (Civil Engineering Department, Faculty of Technology, Tlemcen University)
  • Received : 2022.12.20
  • Accepted : 2023.03.03
  • Published : 2023.09.25
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Abstract

Health monitoring of civil infrastructures, in particular, old bridges that are still in service, has become more than necessary, given the risk that a possible degradation or failure of these infrastructures can induce on the safety of users in addition to the resulting commercial and economic impact. Bridge integrity assessment has attracted significant research efforts over the past forty years with the aim of developing new damage identification methods applicable to real structures. The bridge of Ouled Mimoun (Tlemcen, Algeria) is one of the oldest railway structure in the country. It was built in 1889. This bridge, which is too low with respect to the level of the road, has suffered multiple shocks from various machines that caused considerable damage to its central part. The present work aims to analyze the stability of this bridge by identifying damages and evaluating the damage rate in different parts of the structure on the basis of a finite element model. The applied method is based on an inverse analysis of the normal stress responses that were calculated from the corresponding recorded strains, during the passage of a real train, by means of a set of strain gauges placed on certain elements of the bridge. The results obtained from the inverse analysis made it possible to successfully locate areas that were really damaged and to estimate the damage rate. These results were also used to detect an excessive rigidity in certain elements due to the presence of plates, which were neglected in the numerical reference model. In the case of the continuous bridge monitoring, this developed method will be a very powerful tool as a smart health monitoring system, allowing engineers to take in time decisions in the event of bridge damage.

Keywords

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