Data-Driven Prediction Method for the Seismic Response of Cable-Stayed Bridges and Cross-Structure Calibration Motion Design

Calibrating seismic-response surrogates for a new bridge usually requires numerous nonlinear time-history analyses (NLTHAs). This study designs a synthetic calibration motion (SCM) that supplies the calibration response through a single NLTHA. A benchmark database is established using 100 floating-system cable-stayed bridges with main spans of 210–980 m, viscous dampers and friction pendulum bearings, and 100 pairs of real bidirectional ground motions, resulting in 10,000 response histories whose input windows have horizontal peak ground accelerations (PGAs) not exceeding 0.29 g. Eleven surrogate methods are compared against the NLTHA, followed by zero- and few-motion cross-structure calibration. The proposed SCM combines a randomized-phase broadband spectrum, a non-stationary envelope and amplitude leveling. On 21 independent blind-test bridges, one universal SCM reaches approximately 81% of the matched full-supervision score obtained with 80 motions. Across all 100 bridges, one SCM comes close to ten randomly selected calibration motions and lies between the one- and three-motion results of a greedy selection that adds, one at a time, the most effective motion from the 80-motion candidate pool. Subsequent response predictions take sub-second time. By designing the calibration excitation, the method enables a new bridge’s surrogate to be calibrated with one target-bridge analysis.