Automated geometric digital twinning of bridges from segmented point clouds by parametric prototype models.

Digital Twins (DTs) provide a promising solution for the maintenance and operation of bridges, thanks to their ability to mirror physical/structural conditions. A bridge DT generally consists of a geometric-semantic model whose creation, however, requires extensive manual effort. This paper presents an automated framework to generate the parametric model of bridges from their segmented point clouds. Following the concept of reverse engineering with parametric modeling, Parametric Prototype Models (PPMs) are proposed as tools to extract parameter values from point clouds. A local and global optimization problem is defined to adjust and assemble PPMs into an integrated model. The proposed approach has been validated by applying it to the point cloud of bridge components as well as point clouds captured from six concrete bridges in Bavaria, Germany. The results show that the proposed approach can generate the parametric model of bridges with a mean absolute error (MAE) of 8.71 cm. • A reverse engineering approach is proposed for the parametric modeling of bridges. • Parametric Prototype Models (PPMs) are introduced to describe bridge point clouds. • Local and global optimization problems are defined to adjust and assemble PPMs. • Metaheuristic optimization algorithms are utilized to derive parameter values. • The method is validated with the point cloud of six bridges in Bavaria, Germany. [ABSTRACT FROM AUTHOR]