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The methodologies employed in the probabilistic safety assessment (PSA) of hazardous engineering systems have reached a high level of maturity. However, a few issues are still worth of further investigation in order to increase the confidence in the results obtained. In this view, in the past 5±10 years, researchers in the field of reliability have proposed a more`dynamic' approach to PSA with the aim of addressing issues concerning the possible mutual interactions between the hardware system states and the plant physical evolution. Nonetheless, some objections have been raised against such a dynamic approach, especially against its practical complexity and the lack of a clear definition of the domain of its applicability. In this paper, an attempt to define more precisely the field of application for a dynamic approach is propounded on the basis of the concept of accident duration. The qualitative discussion is supported with examples of postulated severe accidents in nuclear power plants like those investigated in level-2 PSA. The application of Monte Carlo simulation as a tool capable, in principle, of handling all the features of dynamic PSA is illustrated. Monte Carlo algorithms are illustrated aiming at improving the stochastic part of the analysis and the deterministic integration as well, so as to allow for a considerable reduction in the computation times. # 1998 Published by IMACS/Elsevier Science B.V.

a b s t r a c tThe technological obsolescence of a unit is characterized by the existence of challenger units displaying identical functionalities, but with higher performances. This paper aims to define and model in a realistic way, possible maintenance policies of a system including replacement strategies when one type of challenger unit is available. The comparison of these possible strategies is performed based on a Monte Carlo estimation of the costs they incur.

Modelling the effect of the dynamic behaviour of a system on its PSA study leads, in a Markovian framework, to a development at first order of the Chapman-Kolmogorov equation, whose solutions are the probability densities of the problem. Because of its size, there is no hope of solving directly these equations in realistic circumstances. We present in this paper a biased simulation giving the marginals and compare different ways of speeding up the integration of the equations of the dynamics.

SUMMARYMost maintenance policies assume that failed or used components are replaced with identical units. Actually, such a hypothesis neglects the possible obsolescence of the components. When a new, more reliable and less consuming technology becomes available, a decision has to be made as for the replacement strategy to be used: old-type components can all be immediately replaced, or new-type units can be introduced progressively, each time a corrective action is undertaken. Partly corrective, partly preventive policies can also be envisioned.This work tackles this issue in the case of a series system made of n identical and independent components with a constant failure rate. It provides, under given modelling assumptions, the fully analytical expression of the mean total cost induced by each possible strategy, as well as the optimal replacement policy, as a function of the problem parameters. This is performed by accounting for different costs for preventive or corrective replacements, with some economical dependence between replacements, different energy consumption rates for old-type and new-type components as well as a discount rate.

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