A New Metric for Structural Reliability Considering Aleatory and Epistemic Uncertainty

The traditional reliability analysis method based on probabilistic method requires probability distributions of all the uncertain parameters and the probability reliability metric has been utilized to describe the structural reliability. However, in practical applications, the distributions of some parameters may not be precisely known due to the lack of sufficient sample date, hence the structures are also influenced by the epistemic uncertainty. The probabilistic theory based reliability methods only consider aleatory uncertainty and cannot directly measure the reliability of structures with epistemic uncertainty. Therefore, a hybrid reliability analysis (HRA) problem will be caused when the aleatory and epistemic uncertainties coexist in a structure. In this paper, by utilizing the chance theory, a new reliability metric is defined to uniformly assessment the reliability of structures under aleatory and epistemic uncertainties. Then, a unified hybrid uncertainty quantification model is established and the quantitative method for the structural reliability is presented. The numerical experiments illustrate the validity of the proposed reliability metric, the results show that the probabilistic reliability metric which ignores the epistemic uncertainty will overestimate the reliability of the structure, and the reliability metric proposed in this paper can provide a more accurate assessment for the structures under the mixed uncertainties.