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Strategies for Treating Weld Residual Stresses in Probabilistic Fracture Mechanics Codes

[+] Author Affiliations
Frederick W. Brust, R. E. Kurth, D. J. Shim

Engineering Mechanics Corporation of Columbus, Columbus, OH

David Rudland

US Nuclear Regulatory Commission, Washington, DC

Paper No. PVP2011-57937, pp. 585-593; 9 pages
  • 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


Risk based treatment of degradation and fracture in nuclear power plants has emerged as an important topic in recent years. One degradation mechanism of concern is stress corrosion cracking. Stress corrosion cracking is strongly driven by the weld residual stresses (WRS) which develop in nozzles and piping from the welding process. The weld residual stresses can have a large uncertainty associated with them. This uncertainty is caused by many sources including material property variations of base and welds metal, weld sequencing, weld repairs, weld process method, and heat inputs. Moreover, often mitigation procedures are used to correct a problem in an existing plant, which also leads to uncertainty in the WRS fields. The WRS fields are often input to probabilistic codes from weld modeling analyses. Thus another source of uncertainty is represented by the accuracy of the predictions compared with a limited set of measurements. Within the framework of a probabilistic degradation and fracture mechanics code these uncertainties must all be accounted for properly. Here we summarize several possibilities for properly accounting for the uncertainty inherent in the WRS fields. Several examples are shown which illustrate ranges where these treatments work well and ranges where improvement is needed. In addition, we propose a new method for consideration. This method consists of including the uncertainty sources within the WRS fields and tabulating them within tables which are then sampled during the probabilistic realization. Several variations of this process are also discussed. Several examples illustrating the procedures are presented.

Copyright © 2011 by ASME



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