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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

ISBN-10: 0309128536

ISBN-13: 9780309128537

Conserving the functions of the nuclear guns stockpile and acting the yearly overview for the stockpile's certification consists of a variety of procedures, applied sciences, and services. a major and useful point assisting to hyperlink these elements is the quantification of margins and uncertainties (QMU) framework. during this ebook, the nationwide examine Council evaluates: how the nationwide defense labs have been utilizing QMU, together with any major modifications one of the 3 labs; its use within the annual review; and, even if the purposes of QMU to evaluate the proposed trustworthy substitute warhead (RRW) may well decrease the chance of resuming underground nuclear trying out. This publication offers an evaluation 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 consultant for congressional oversight of these actions.

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Additional resources for Evaluation of Quantification of Margins and Uncertainties Methodology for Assessing and Certifying the Reliability of the Nuclear Stockpile

Sample text

Comparison against experiment is the only way to quantify model error and is the only connection between a simulation and reality. If a particular experiment were perfectly characterized, measured data were free from error, and the mathematical model equations were solved perfectly, the difference between the mathematical solution and the experimental measurement would be the model error for the measured quantity. In practice the picture is muddied by imperfect characterization of experiments, imperfect measurements, numerical approximations of the mathematical model equations, and coding errors.

S. S. Nuclear Power Plants, NUREG-1150, Vols. S. 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.

In the presentations to the committee, the input distributions were simply uniform, meaning that each selected input value was considered just as likely as any other. The meaning of the shapes of the output distributions is not clear in this case. Fifth, there are similar questions about the meaning of the span of the distributions, which is a direct result of the span chosen for the input parameters as well as the particular (small set of) input parameters chosen for variation. If additional uncertain parameters are chosen, the width of the output distributions will almost certainly increase, the chosen metrics used to describe the distributions will change, and the conclusions drawn from the analysis also will likely change.

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Evaluation of Quantification of Margins and Uncertainties Methodology for Assessing and Certifying the Reliability of the Nuclear Stockpile 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


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