Modern bridge construction towards a higher degree of low carbonization and assembly has been the general trend, while developing and broadening the low-carbon and assembled-oriented Accelerated Bridge Construction (ABC) technology can better realize the trade-offs between construction quality, efficiency, cost and sustainability. In the current mainstream ABC technologies such as precast-assembled concrete bridge and assembled steel bridge schemes, it is difficult to achieve an excellent balance between the above multicriterion trade-offs. To this end, this paper proposes a novel low-carbon and assembled composite bridge scheme as an innovative case of ABC technology based on a 26.7 km-length urban viaduct project in China with urgent environmental protection and assembly demands. Construction sustainability, the comprehensive economy and low-carbon performance are well balanced by the collaborative application of new steel–concrete composite structures, the rapid assembly interface design and low-carbon material technologies. The proposed scheme has been applied to a completed real-scale bridge, and the whole construction process only experienced 105 days of effective time, accompanied with slight environmental interference and construction noise and a small amount of labor and equipment input. In addition, the safety of the bridge, the rationality of the design concept and the calculation method have been verified by the static and dynamic loading tests of the real-scale bridge.

Because the adjustment of the stay cable tension and girder counterweight is limited at the operation stage it is a difficult problem to control the negative reaction risk of the auxiliary pier (NRRAP) caused by multisource construction uncertainties and traffic growth. This paper proposes a pavement strategy optimization to control the NRRAP by adjusting the pavement thickness. The pavement strategy optimization is formulated as a reliability-constrained, multiobjective optimization problem, which is resolved by the nondominated sorting genetic algorithm (NSGA-II). A sensitivity analysis and a reliability analysis based on the generalized regression neural network (GRNN) surrogate model were performed to illustrate the significance of the uncertainty level in auxiliary pier negative reactions. The Pareto front examines the balance of construction cost, driving comfort and specified reliability threshold. The efficiency and accuracy of the proposed method are validated in a real cable-stayed bridge, and the results exhibit its advantages in controlling the NRRAP.