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Suggested Citation:"Appendix C: Glossary." National Research Council. 2009. Evaluation of Quantification of Margins and Uncertainties Methodology for Assessing and Certifying the Reliability of the Nuclear Stockpile. Washington, DC: The National Academies Press. doi: 10.17226/12531.
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Suggested Citation:"Appendix C: Glossary." National Research Council. 2009. Evaluation of Quantification of Margins and Uncertainties Methodology for Assessing and Certifying the Reliability of the Nuclear Stockpile. Washington, DC: The National Academies Press. doi: 10.17226/12531.
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Suggested Citation:"Appendix C: Glossary." National Research Council. 2009. Evaluation of Quantification of Margins and Uncertainties Methodology for Assessing and Certifying the Reliability of the Nuclear Stockpile. Washington, DC: The National Academies Press. doi: 10.17226/12531.
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Suggested Citation:"Appendix C: Glossary." National Research Council. 2009. Evaluation of Quantification of Margins and Uncertainties Methodology for Assessing and Certifying the Reliability of the Nuclear Stockpile. Washington, DC: The National Academies Press. doi: 10.17226/12531.
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Appendix C Glossary Assessment Assessment is a yearly procedure conducted to determine confidence in the original certification. It is much abbreviated compared to the certification. Certification Certification is the procedure required to assure the DOD that a warhead will operate within the military characteristics if the limits of the specified stockpile-to-target sequence are not violated. It is an elaborate procedure and does not need to be repeated often. Hydrodynamic Tests (Hydrotests) Hydrotests are non-nuclear experiments that study the behavior of a nuclear weapon primary from the ignition of the high explosive that drives the implosion to the point where the nuclear chain reaction would begin. These experiments are performed on inert primary pits that con- tain nonfissile material having properties similar to those of fissile plu- tonium. A variety of methods are used to monitor the behavior of the imploding inert pit metal. In one such method, pin domes are used (see below). Another method is to pass pulses of high-energy X rays through the imploding pit to record images of the process. The results of these 77

78 evaluation of qmu methodology hydrotests are used to validate models simulating the implosion of a weapon primary. Input Parameters Input parameters are the physical data that characterize the behavior of the materials used in a simulation. Examples are equations of state, opac- ity, and neutron cross sections. Input parameters can be selected for best fit to integral data such as that from underground nuclear tests. Input data are not knobs. Once selected for optimizing a baseline calculation, they remain fixed until the model is changed. Knobs Knobs are a resort to ad hoc normalization to integral data. There is no firm physics in a knob. If knobs are used in a baseline calculation, the knobs should remain unchanged from one calculation in a baseline suite of data to another. The degree to which knobs are used in a simulation weakens the ability of that simulation to model similar data. Nuclear Explosive Package The nuclear explosive package—also called the physics package—is the portion of a nuclear weapon that contains all of the components that gen- erate the actual nuclear explosion; specifically, the fission primary—with its plutonium pit—and the thermonuclear secondary device. Performance Gate A performance gate is a range of acceptable values, defined by subsystem margins and uncertainties, for the performance of each of many subsys- tems in the chain of events occurring in a nuclear explosion. It is a range of values for some performance metric that must be achieved for success. These values are associated with the key components and operating char- acteristics of the weapon; their failure would severely compromise the overall performance of the weapon. Performance gates vary in importance and type. All involve a performance threshold, expected performance variations, and performance margins. The nature of the margin depends on the gate. Examples include shape, timing, neutron fluence, criticality, temperature, yield, and functional mode. The understanding of performance gates is incomplete. Physical Inputs Physical inputs define the problem to be simulated. Size, shape, thickness, mass, material, and density are examples. These are measurements and subject to random uncertainties.

APPENDIX C 79 Pin Dome Shots One method for monitoring the behavior of an imploding pit is to mount a set of radial pins or wires of varying length in the shape of a dome at the center of a mock primary pit. During the implosion, the pins are short- circuited when the imploding pit metal comes in contact with the wire. The method produces a series of measurements giving the position of the implosion as a function of time. Probability of Frequency For repetitive risk scenarios for which the repetition frequency is uncer- tain but for which some evidence exists, the state of knowledge of that frequency value can be expressed by a probability distribution called a probability of frequency. See Appendix A for a more detailed discussion of this concept. QMU QMU is an important part of the process by which the results of weapons simulation computer models, experiments producing no nuclear yield, data from earlier underground nuclear tests, and expert judgment are brought to bear to assess the reliability of the existing weapons stock- pile. The QMU process is analogous to the concept of engineering safety margins—i.e., the system is designed so that its operating margins are far enough from the failure thresholds to provide high confidence that the system will work reliably even though the magnitude and uncertainty of the margin for a particular performance metric may not be known with great precision. Subcritical Subcritical nuclear tests are tests of nuclear materials and com­ponents that do not produce a nuclear chain reaction—that is, they do not reach critical mass and therefore produce no nuclear yield. These tests are meant to produce data to help validate the simulation models and to be used in other aspects of the stockpile stewardship program.

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Maintaining the capabilities of the nuclear weapons stockpile and performing the annual assessment for the stockpile's certification involves a wide range of processes, technologies, and expertise. An important and valuable framework helping to link those components is the quantification of margins and uncertainties (QMU) methodology.

In this book, the National Research Council evaluates:

  • how the national security labs were using QMU, including any significant differences among the three labs
  • its use in the annual assessment
  • whether the applications of QMU to assess the proposed reliable replacement warhead (RRW) could reduce the likelihood of resuming underground nuclear testing

This book presents an assessment of each of these issues and includes findings and recommendations to help guide laboratory and NNSA implementation and development of the QMU framework. It also serves as a guide for congressional oversight of those activities.

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