Probabilistic model data of time-dependent accident scenarios for a mixing tank mechanical system.

This article presents the risk assessment of a mixing tank mechanical system based on the failure probabilities of the components. Possible component failures can cause accidents which evolve over multiple time stages and can lead to system failure. The consequences of these accident scenarios are analyzed by quantifying the failure probabilities and severity of their outcomes. Illustrative costs and updated failure probabilities are provided to evaluate preventive safety measures. Data refers to the results of the Bayesian model presented in our research article (Mancuso et al., 2019).

Scenario Analysis for the Safety Assessment of Nuclear Waste Repositories: A Critical Review.

A major challenge in scenario analysis for the safety assessment of nuclear waste repositories pertains to the comprehensiveness of the set of scenarios selected for assessing the safety of the repository. Motivated by this challenge, we discuss the aspects of scenario analysis relevant to comprehensiveness. Specifically, we note that (1) it is necessary to make it clear why scenarios usually focus on a restricted set of features, events, and processes; (2) there is not yet consensus on the interpretation of comprehensiveness for guiding the generation of scenarios; and (3) there is a need for sound approaches to the treatment of epistemic uncertainties.

Developing robust composite measures of healthcare quality - Ranking intervals and dominance relations for Scottish Health Boards.

Although composite indicators are widely used to inform health system performance comparisons, such measures typically embed contentious assumptions, for instance about the weights assigned to constituent indicators. Moreover, although many comparative measures are constructed as ratios, the choice of denominator is not always straightforward. The conventional approach is to determine a single set of weights and to choose a single denominator, even though this involves considerable methodological difficulties. This study proposes an alternative approach to handle incomplete information about an appropriate set of weights and about a defensible denominator in composite indicators which considers all feasible weights and can incorporate multiple denominators. We illustrate this approach for comparative quality assessments of Scottish Health Boards. The results (displayed as ranking intervals and dominance relations) help identify Boards which cannot be ranked, say, worse than 4th or better than 7th. Such rankings give policy-makers a sense of the uncertainty around ranks, indicating the extent to which action is warranted. By identifying the full range of rankings that the organizations under comparison may attain, the approach proposed here acknowledges imperfect information about the "correct" set of weights and the appropriate denominator and may thus help to increase transparency of and confidence in health system performance comparisons.