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.

Effectively preventing hanger bending damage during the configuration transformation of the spatial main cables in suspension bridges is a critical challenge, particularly under the influence of construction errors. This study proposes an active fault-tolerant control method that integrates real-time data feedback, tolerance interval inversion technology, and a suspended lateral bracing (SLB) system to mitigate the risk of hanger bending damage in real time. The method establishes a dynamic inversion mechanism, utilizing data feedback, constraint function reconstruction, and secondary optimization to compensate for construction errors. This ensures that hangers remain undamaged throughout the transformation process. Construction errors are quantified as intervals, with the lower bound of the reliability interval used to account for extreme disturbances. This transforms the inversion process into a multi-objective optimization problem constrained by the worst reliability conditions. By integrating finite element analysis (FEA), reliability analysis, surrogate modeling, and interval analysis, the proposed approach establishes a direct relationship between design variables and the lower bound of the reliability interval. Case study results demonstrate that the proposed method not only ensures structural performance and hanger safety, but also significantly enhances the constructability of the configuration transformation. Additionally, it provides a larger fault tolerance margin, thereby improving the overall efficiency and safety of the construction process.