0

Full Content is available to subscribers

Subscribe/Learn More  >

Degradation Susceptibility Metrics as the Bases for Bayesian Reliability Models of Aging Passive Components and Long-Term Reactor Risk

[+] Author Affiliations
Stephen D. Unwin, Peter P. Lowry, Michael Y. Toyooka, Benjamin E. Ford

Pacific Northwest National Laboratory, Richland, WA

Paper No. PVP2011-58073, pp. 1069-1075; 7 pages
doi:10.1115/PVP2011-58073
From:
  • ASME 2011 Pressure Vessels and Piping Conference
  • Volume 6: Materials and Fabrication, Parts A and B
  • Baltimore, Maryland, USA, July 17–21, 2011
  • Conference Sponsors: Pressure Vessels and Piping Division
  • ISBN: 978-0-7918-4456-4
  • Copyright © 2011 by ASME

abstract

Conventional probabilistic risk assessments (PRAs) are not well-suited to addressing long-term reactor operations. Since passive structures, systems and components are among those for which refurbishment or replacement can be least practical, they might be expected to contribute increasingly to risk in an aging plant. Yet, passives receive limited treatment in PRAs. Furthermore, PRAs produce only snapshots of risk based on the assumption of time-independent component failure rates. This assumption is unlikely to be valid in aging systems. The treatment of aging passive components in PRA does present challenges. First, service data required to quantify component reliability models are sparse, and this problem is exacerbated by the greater data demands of age-dependent reliability models. A compounding factor is that there can be numerous potential degradation mechanisms associated with the materials, design, and operating environment of a given component. This deepens the data problem since the risk-informed management of materials degradation and component aging will demand an understanding of the long-term risk significance of individual degradation mechanisms. In this paper we describe a Bayesian methodology that integrates the metrics of materials degradation susceptibility being developed under the Nuclear Regulatory Commission’s Proactive Materials Degradation Assessment Program with available plant service data to estimate age-dependent passive component reliabilities. Integration of these models into conventional PRA will provide a basis for materials degradation management informed by the predicted long-term operational risk.

Copyright © 2011 by ASME
Topics: Reliability

Figures

Tables

Interactive Graphics

Video

Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In