Uncertainty analysis of bridge flutter considering dependence and sampling error in flutter derivative measurements

Abstract

Abstract Analyzing the uncertainty of flutter propagated from different sources especially flutter derivatives is important for the risk assessment of long-span bridges. The uncertainty of flutter derivatives is often characterized based on the experimental data. Dependence and sampling error would therefore exist which may influence the onset prediction of bridges. This paper devotes to developing a framework towards the uncertainty analysis of bridge flutter considering the dependence and sampling error in flutter derivative measurements. In this framework, the dependence among different flutter derivatives is identified with Spearman’s rho instead of conventional Pearson’s product-moment correlation coefficient. A modified procedure based on bootstrap is proposed to characterize the sampling error by representing distribution parameters of flutter derivatives as interval variables. Regarding the probability-interval hybrid uncertainty, a double-layer analysis is employed. In the inner layer, probability of onset velocity is estimated using the point estimate-based probability analysis. In the outer one, the distribution envelope is obtained by the genetic algorithm-assisted interval analysis. Application of the framework to reliability assessment of bridge against flutter is also presented. In the numerical study, the influence of dependence and sampling error is verified in detail. By this framework, the distribution\xa0envelope of onset velocity or the interval of reliability index against flutter are expected to contain the true estimates. Consequently, the potential risk with respect to bridge flutter can be assessed in a conservative way.