The following paper presents a global methodology to analyze the set of results generated by a probabilistic analysis. The approach regroups traditional analyses such as Sensitivity Analysis (SA), Uncertainty Analysis (UA), and stability analysis as well as sensitivity studies (both deterministic and probabilistic) with enhanced sampling techniques (double loop to separate aleatory from epistemic uncertainty, importance sampling, adaptive sampling) in an incremental set of steps, with the goal to give the analyst and decision maker the most comprehensive and defensible collection of results.

An example using the xLPR code and a selected scenario is used to illustrate each step of the approach.

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