Functional failure analysis of a thermal–hydraulic passive system by means of Line Sampling

Assessing the failure probability of a thermal–hydraulic (T–H) passive system amounts to evaluating the uncertainties in its performance. Two different sources of uncertainties are usually considered: randomness due to inherent variability in the system behavior (aleatory uncertainty) and imprecision due to lack of knowledge and information on the system (epistemic uncertainty). In this paper, we are concerned with the epistemic uncertainties affecting the model of a T–H passive system and the numerical values of its parameters. Due to these uncertainties, the system may find itself in working conditions that do not allow it to accomplish its functions as required. The estimation of the probability of these functional failures can be done by Monte Carlo (MC) sampling of the epistemic uncertainties affecting the model and its parameters, followed by the computation of the system function response by a mechanistic T–H code. Efficient sampling methods are needed for achieving accurate estimates, with reasonable computational efforts. In this respect, the recently developed Line Sampling (LS) method is here considered for improving the MC sampling efficiency. The method, originally developed to solve high-dimensional structural reliability problems, employs lines instead of random points in order to probe the failure domain of interest. An “important direction” is determined, which points towards the failure domain of interest; the high-dimensional reliability problem is then reduced to a number of conditional one-dimensional problems which are solved along the “important direction”. This allows to significantly reduce the variance of the failure probability estimator, with respect to standard random sampling. The efficiency of the method is demonstrated by comparison to the commonly adopted Latin Hypercube Sampling (LHS) and first-order reliability method (FORM) in an application of functional failure analysis of a passive decay heat removal system in a gas-cooled fast reactor (GFR) of literature.