Data-Driven Modeling Algorithms for Cable-Stayed Bridges Considering Mechanical Behavior - Chang-Su Shim; Gi-Tae Roh (Applied Sciences, 2021)
Digital transformation of bridge engineering utilizes distinct modeling techniques to combine domain knowledge with digital information modeling. In particular, a long-span bridge is a key link in a transportation network, with more than 100 years of service life. BIM (building information modeling) is an effort towards improving the current data delivery in the construction industry. However, it is limited by the rigidity that geometry affords; this is particularly problematic when the structure to be modelled is a deformable body. The quality and value of information for the bridges can be enhanced by establishing a data-driven digital information delivery through the entire life-cycle of the bridges. In this study, a data-driven modeling algorithm for cable-stayed bridges is proposed, considering the geometry change determining the mechanical behavior. Data delivery is accomplished by a combination of datasets and algorithms based on the different purposes. The master information model considers alignment of the bridge and essential constraints for the main members, such as stiffening girders, pylons, and cables, between the digital models. Geometry control of the stiffening girders and tension forces of cables are supported by the modeling algorithm of the interoperable target configuration under dead load analysis. The suggested modeling algorithm is verified by comparison with previous analytical studies on cable-stayed bridges.