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In 2001, the National Nuclear Security Administration of the U.S. Department of Energy in conjunction with the national security laboratories (i.e, Los Alamos National Laboratory, Lawrence Livermore National Laboratory and Sandia National Laboratories) initiated development of a process designated Quantification of Margins and Uncertainty (QMU) for the use of risk assessment methodologies in the certification of the reliability and safety of the nation's nuclear weapons stockpile. This presentation discusses and illustrates the conceptual and computational basis of QMU in analyses that use computational models to predict the behavior of complex systems. Topics considered include (1) the role of aleatory and epistemic uncertainty in QMU, (2) the representation of uncertainty with probability, (3) the probabilistic representation of uncertainty in QMU analyses involving only epistemic uncertainty, (4) the probabilistic representation of uncertainty in QMU analyses involving aleatory and epistemic uncertainty, (5) procedures for sampling-based uncertainty and sensitivity analysis, (6) the representation of uncertainty with alternatives to probability such as interval analysis, possibility theory and evidence theory, (7) the representation of uncertainty with alternatives to probability in QMU analyses involving only epistemic uncertainty, and (8) the representation of uncertainty with alternatives to probability in QMU analyses involving aleatory and epistemic uncertainty. Concepts and computational procedures are illustrated with both notional examples and examples from reactor safety and radioactive waste disposal

Conceptual and computational basis for the quantification of margins and uncertainty.