Uncertainty Quantification and Structural Reliability Estimation Considering Inspection Data Scarcity

Abstract

Reliability estimation of aging RC structures under environmental attack involves various sources of uncertainties. In realistic operational conditions, uncertainties due to limited number of experimental data and incomplete inspection information affect the reliability assessment of the existing RC structures. A fuzzy probabilistic methodology is proposed in this paper to consider the inspection data scarcity for the RC structures uncertainty quantification and reliability estimation. The membership function is used to describe the fuzzy characteristic of small numbers of detection results. Following this, the fuzzy variables are transformed to the equivalent random variables and the classic reliability index can be obtained. The proposed methodology is compared with the conventional probabilistic approach using the goodness-of-fit method. The effect of data scarcity is discussed in detail. Next, the developed methodology is demonstrated with a RC bridge. Parametric studies of the concrete strength, the reinforcement strength loss, and the corrosion loss on the reliability analysis are performed. Several conclusions are drawn based on the analysis results.