Estimation of the probability and uncertainty of undesirable events in large-scale systems.

Summary The objective of this thesis is to build a framework that represents random and epistemic uncertainties based on probabilistic approaches and uncertainty theories, to compare methods and to find own applications on large systems with rare events. In the thesis, an asymptotic normality method has been proposed with Monte Carlo simulation in the binary cases as well as a semi-Markovian model in the cases of dynamic multi-state systems. Random ensemble theory has also been applied as a basic model to evaluate reliability and other performance indicators in binary and multi-state systems with bootstrap technique.