Seismic Optimization Design Method of Long-Span Concrete-Filled Steel Tubular Arch Bridge Based on Energy-Dissipation Brace Under Near-Fault Ground Motions

To improve the seismic performance of long-span concrete-filled steel tubular arch bridges under near-fault ground motions, a novel super-long shuttle-shaped buckling-restrained energy-dissipation brace has been developed, and a corresponding seismic optimization design method based on this energy-dissipation brace is proposed. First, using a long-span concrete-filled steel tubular arch bridge as a case study, a simplified analysis model of the arch rib-brace system is established. The seismic damage mode of the arch rib-brace is then identified through static elastic-plastic analysis. Subsequently, three groups of near-fault ground motions are selected to perform nonlinear time-history analyses of the whole bridge. Finally, the optimal design parameters of the energy-dissipation brace are determined using the Response Surface Method (RSM) polynomial function and the Non-dominated Sorting Genetic Algorithm II (NSGA-II). The results indicate that the damage evolution path of the arch rib-brace structure primarily follows the sequence “brace [Formula: see text] arch rib [Formula: see text] arch foot”, establishing a distinct damage mechanism characterized by a strong arch and weak brace. The type of near-fault ground motion significantly influences the damping effect of the energy-dissipation brace, with the damping effect ranking as follows: fling-step effect [Formula: see text] forward-directivity effect [Formula: see text] non-pulse ground motion. The third-order polynomial response surface model exhibits good predictability and high fitting accuracy, making it suitable as a mathematical model for the parameter optimization of the energy-dissipation brace. The proposed optimization method comprehensively considers the randomness of ground motions, the position of member damage, and failure probability. It avoids the uncertainty associated with empirical parameter selection, thereby ensuring the reliability and applicability of the optimization results.