Efficient Moment-Independent Sensitivity Analysis of Uncertainties in Seismic Demand of Bridges Based on a Novel Four-Point-Estimate Method

Abstract

Moment-independent importance (MII) analysis is known as a global sensitivity measurement in qualifying the influence of uncertainties, which is taken as a crucial step towards seismic performance analysis. Most MII analysis is based on Monte Carlo simulation, which leads to a high computational cost since a large number of nonlinear time history analyses are required to obtain the probability density function. To address this limitation, this study presents a computational efficient MII analysis to investigate the uncertain parameters in the seismic demands of bridges. A modified four-point-estimate method is derived from Rosenblueth’s two-point-estimate method. Thus, the statistical moments of a bridge’s seismic demands can be obtained by several sampling points and their weights. Then, the shifted generalized lognormal distribution method is adopted to estimate the unconditional and conditional probability density functions of seismic demands, which are used for the MII analysis. The analysis of seismic demands based on piers and bearings in a finite element model of a continuous girder bridge is taken as a validation example. The MII measures of the uncertain parameters are estimated by just several nonlinear time history analyses at the point-estimate sampling points, and the results by the proposed method are compared with those found by Monte Carlo simulation.