Assessing the reliability of a complex system with uncertainty propagation consists in estimating its probability of failure. Common sampling strategies for such tasks are notably based on Monte Carlo sampling. This kind of methods is well suited to characterize events of which associated probabilities are not too low with respect to the simulation budget. However, for critical systems such as aerospace vehicles, the reliability specifications often induce very low probability of failures (said below 10−4). In this case, Monte Carlo based methods are not efficient inducing unaffordable costs with regard to the available simulation budget. In this chapter, we review the main simulation techniques to estimate low failure probabilities with accuracy.
Reliability Analysis
Springer Optimization
2020-08-27
28 pages
Article/Chapter (Book)
Electronic Resource
English
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