title: A Critical Discussion and Practical Recommendations on Some Issues Relevant to the Nonprobabilistic Treatment of Uncertainty in Engineering Risk Assessment.
abstract: Models for the assessment of the risk of complex engineering systems are affected by uncertainties due to the randomness of several phenomena involved and the incomplete knowledge about some of the characteristics of the system. The objective of this article is to provide operative guidelines to handle some conceptual and technical issues related to the treatment of uncertainty in risk assessment for engineering practice. In particular, the following issues are addressed: (1) quantitative modeling and representation of uncertainty coherently with the information available on the system of interest; (2) propagation of the uncertainty from the input(s) to the output(s) of the system model; (3) (Bayesian) updating as new information on the system becomes available; and (4) modeling and representation of dependences among the input variables and parameters of the system model. Different approaches and methods are recommended for efficiently tackling each of issues (1)-(4) above; the tools considered are derived from both classical probability theory as well as alternative, nonfully probabilistic uncertainty representation frameworks (e.g., possibility theory). The recommendations drawn are supported by the results obtained in illustrative applications of literature.
authors.affiliation: Chair "System Science and the Energy Challenge"-Fondation Electricité de France (EdF) at the Laboratoire Genie Industriel (LGI), CentraleSupélec, Université Paris-Saclay, Chatenay-Malabry, France.
authors.forename: Nicola
authors.initials: N
authors.lastname: Pedroni
authors.affiliation: Chair "System Science and the Energy Challenge"-Fondation Electricité de France (EdF) at the Laboratoire Genie Industriel (LGI), CentraleSupélec, Université Paris-Saclay, Chatenay-Malabry, France.|Energy Department, Politecnico di Milano, Milano, Italy.
authors.forename: Enrico
authors.initials: E
authors.lastname: Zio
authors.affiliation: EDF R&D-EIFER, Karlsruhe, Germany.
authors.forename: Alberto
authors.initials: A
authors.lastname: Pasanisi
authors.affiliation: Electricité de France, R&D, Chatou, France.
authors.forename: Mathieu
authors.initials: M
authors.lastname: Couplet
keywords: Bayesian update; dependences; uncertainty representation and propagation