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Quantification of margins and uncertainties: A probabilistic framework
Authors:Timothy C Wallstrom
Affiliation:Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, United States
Abstract:Quantification of margins and uncertainties (QMU) was originally introduced as a framework for assessing confidence in nuclear weapons, and has since been extended to more general complex systems. We show that when uncertainties are strictly bounded, QMU is equivalent to a graphical model, provided confidence is identified with reliability one. In the more realistic case that uncertainties have long tails, we find that QMU confidence is not always a good proxy for reliability, as computed from the graphical model. We explore the possibility of defining QMU in terms of the graphical model, rather than through the original procedures. The new formalism, which we call probabilistic QMU, or pQMU, is fully probabilistic and mathematically consistent, and shows how QMU may be interpreted within the framework of system reliability theory.
Keywords:QMU  Graphical model  Bayesian network  System reliability
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