Efficient design parameter selection for nonlinear bearings to achieve multi-objective optimization of seismic performance of girder bridges by utilizing the stochastic structural response of equivalent linear systems

In the process of performance-based design of bridges with aseismic bearings, there exist intrinsic trade-off between minimization of the bearing displacement and pier displacement during strong earthquake events. However, difficulty in selecting the optimal parameters of the bearings that satisfy the two objectives arises, in conjunction with considerable computational resource requirements for nonlinear time-history analysis (NTHA). A computationally efficient approach to determine the optimal bearing design parameters by utilizing the stochastic structural response of equivalent linear systems is proposed in this paper. The key idea is to use the assumed optimal parameters obtained from a stochastic model as the approximation of the exact optimal parameters found from a deterministic model. The stochastic model allows rapid exploration of optimal parameter candidates. A computationally intensive deterministic model is used to determine the performance-based optimal design by performing NTHA only for the design parameter candidates obtained by exploiting the stochastic model. Compared with the exhaustive search approach, the required number of NTHA cases in this method can be significantly reduced. As a numerical example, the proposed method is applied to optimal parameter selection of two slide type bearings in a girder bridge, namely the uplifting slide shoe and the functionally discrete bearings. The seismic performance indices of the bridge with the design parameters determined by the proposed procedure are shown to be almost equivalent to the optimal values found by the exhaustive search approach. An extended parameter search algorithm is incorporated with the proposed procedure for refinement of the assessment at the slightly increased cost of computation.