Hierarchical propagation of probabilistic and non-probabilistic uncertainty in the parameters of a risk model

• Published in: Computers & structures 2013-09, Vol.126, p.199-213
• Main Authors: Pedroni, N., Zio, E., Ferrario, E., Pasanisi, A., Couplet, M.
• Format: Article
• Language: English
• Subjects: Computer simulation; Dependences; Dikes; Engineering Sciences; Flood protection dike; Floods; Fuzzy interval analysis; Hierarchical uncertainty; Mathematical models; Possibility distributions; Probabilistic methods; Probability theory; Risk; Two-level Monte Carlo method; Uncertainty
• ISSN: 0045-7949; 1879-2243
• DOI: 10.1016/j.compstruc.2013.02.003

► We perform the hierarchical propagation of hybrid uncertainties in risk assessment. ► We study the effects of dependence between epistemically uncertain parameters. ► We study the effects of different representations of epistemic uncertainty. ► Different methods generate different results and decisions in risk problems. ► Non-probabilistic representations of uncertainty produce conservative results. We consider a model for the risk-based design of a flood protection dike, and use probability distributions to represent aleatory uncertainty and possibility distributions to describe the epistemic uncertainty associated to the poorly known parameters of such probability distributions. A hybrid method is introduced to hierarchically propagate the two types of uncertainty, and the results are compared with those of a Monte Carlo-based Dempster–Shafer approach employing independent random sets and a purely probabilistic, two-level Monte Carlo approach: the risk estimates produced are similar to those of the Dempster–Shafer method and more conservative than those of the two-level Monte Carlo approach.