Evaluation of long-service-life cable-stayed bridge strengthening schemes using a two-phase finite element model updating technology

Thus far, the finite element model updating (FEMU) theory has been employed to address parameter errors between finite element models (FEMs) and actual structures. However, previous studies involving multiobjective optimization based on the FEMU of bridges focused on engineering experience or Euclidean distance alone, which affords a less efficient solution with less recognizability. To address this issue, in this work, an innovative two-phase model updating technique was developed to accurately evaluate a long-service-life cable-stayed bridge strengthening scheme. During the first phase, a sensitivity analysis was performed to determine the main updating parameters. Subsequently, the updating process was developed into a multiobjective optimization problem with the establishment of an objective function, which was solved using an improved genetic algorithm (GA). During the second phase, the ELECTRE-III method was introduced to rank the Pareto front from the first stage and determine the final updating results. Additionally, the impact of the mesh sizes of the finite element model (FEM) on the updating process was analyzed. The relative differences between the original numerical results and the elevation measurements reached 20.5 % and 25.0 %, which were then reduced to 11.7 % and 11.9 %, respectively, after the updating process. Results revealed that the updating process considerably improved the accuracy of the FEM. Based on the updated FEM, the structural responses of the Shengli Yellow River Bridge were evaluated in different cable and bolt replacement schemes. Considering construction progress and safety, optimal strengthening schemes were selected and successfully applied to the actual Shengli Yellow River Bridge reinforcement project. This work and its results are expected to serve as a reference for the effective evaluation of long-service-life cable-stayed bridge strengthening schemes.