Chapter summaryΒΆ
In this chapter we reviewed the application of the uncertainty models introduced in Models of Uncertainty to the field of reliability engineering. Specifically, this chapter demonstrated how probabilistic, set-based and imprecise probability models can be used to calculate the reliability of systems under uncertainty. The optimal design of a system under uncertainty can also be computed, and the local or global sensitivity of the response of a system to changes in the system variables can be determined. For systems where the probability of failure is small, computing the failure probability using a Monte Carlo estimator can be computationally expensive. For this reason, it is necessary to apply advanced techniques in order to calculate the probability of failure in a feasible computational time. For imprecise probability models, computation of the failure probability of the system is even more expensive, and hence efficient computational techniques are also required. This motivates the novel contributions introduced in the following chapters.