Efficient uncertainty quantification of wharf structures under seismic scenarios using Gaussian Process surrogate model

Abstract

The scenario-based seismic assessment approach is illustrated within a large-scale pile-supported wharf structure (PSWS). As nonlinear seismic response analysis is computationally expensive, a novel and efficient method is developed to improve and update the traditional simulation methods. Herein, the Gaussian Process (GP) surrogate model is proposed to replace the time-consuming FE model of PSWS, which makes the quantification of uncertainty in seismic response of a large-scale PSWS resulting from structural parameter uncertainty more computationally-efficient. The feasibility of the proposed approach in seismic assessment of a large-scale PSWS under a given seismic scenario is verified by using Monte Carlo simulation.