A Multi-Objective Particle Swarm Optimization Algorithm for the Model Updating of Bridge Infrastructures

Structural health monitoring aims to provide reliable data on the conditions of infrastructures, observe their evolution, and detect the appearance of degradations. Within this context, Model Updating is a valuable tool to achieve calibrated numerical models that improve the knowledge of the structure and can lay the foundations for non-destructive damage assessments. This work proposes a multi-objective Particle Swarm Optimization algorithm for optimizing the finite element model of infrastructures using both static and dynamic data. Tested in the model updating of a semi-viaduct, the proposed algorithm achieved the set of nondominated solutions showing excellent optimization capabilities within limited computational times.