By National Research Council, Division on Engineering and Physical Sciences, Committee on the Evaluation of Quantification of Margins and Uncertainties Methodology for Assessing and Certifying the Reliability of the Nuclear Stockpile
Retaining the features of the nuclear guns stockpile and appearing the yearly review for the stockpile's certification contains a variety of methods, applied sciences, and services. an immense and important point supporting to hyperlink these elements is the quantification of margins and uncertainties (QMU) framework. during this publication, the nationwide examine Council evaluates: how the nationwide protection labs have been utilizing QMU, together with any major modifications one of the 3 labs; its use within the annual evaluate; and, no matter if the functions of QMU to evaluate the proposed trustworthy alternative warhead (RRW) might lessen the possibility of resuming underground nuclear trying out. This ebook provides an evaluate of every of those concerns and contains findings and proposals to aid consultant laboratory and NNSA implementation and improvement of the QMU framework. It additionally serves as a advisor for congressional oversight of these actions.
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Extra info for Evaluation of Quantification of Margins and Uncertainties Methodology for Assessing and Certifying the Reliability of the Nuclear Stockpile
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C. J. Breeding, Calculation of Reactor Accident Safety Goals, Reliability Engineering and System Safety 39(2)(1992): 129-158. 30 evaluation of qmu methodology ondary performance for a given primary input), which are carried out independently. Ideally, a full-system calculation could have a range of input parameters (uncertainties) in the codes, in material equations-of-state, and in the specification of parts. A hands-off calculation for a particular choice from the enormous parameter set, for instance, gives as output a yield of the weapon.
The firing set and the neutron generator). In principle, SNL can test its systems under many of the relevant conditions; for these conditions SNL is not forced to rely on simulation codes to generate estimates of thresholds, margins, and uncertainties. For practical reasons, SNL cannot test statistically significant numbers of some of its components and therefore still uses computational modeling; however, the models can be challenged in many cases by full system tests. LANL and LLNL, on the other hand, cannot perform full system tests and must instead rely heavily on simulation codes in their assessments of margins and uncertainties.
Use of the qmu methodology 27 INTRODUCING MORE COMPLEX PROBABILITY DISTRIBUTIONS The interpretations described above can be criticized on several grounds. First, taking TBE + U2 as the maximum credible threshold implies that the uncertainty in the threshold is bounded. This implication is equivalent to assuming that the distribution of threshold values arising from all sources of uncertainty does not have a significant tail. A similar comment applies to the metric value. Some observers argue that these distributions may have tails.