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Assessment of Welding-Induced Plasticity in Austenitic Steel Weldments

[+] Author Affiliations
Ondrej Muránsky, Cory J. Hamelin

Australian Nuclear Science and Technology Organisation, Lucas Heights, Australia

Minh Tran

University of California, Davis, CA

Chedly Braham

ENSAM, Paris, France

Michael C. Smith

University of Manchester, Manchester, UK

Paper No. PVP2016-63358, pp. V06BT06A071; 10 pages
doi:10.1115/PVP2016-63358
From:
  • ASME 2016 Pressure Vessels and Piping Conference
  • Volume 6B: Materials and Fabrication
  • Vancouver, British Columbia, Canada, July 17–21, 2016
  • Conference Sponsors: Pressure Vessels and Piping Division
  • ISBN: 978-0-7918-5043-5
  • Copyright © 2016 by ASME

abstract

Historically, weld residual stresses (WRS) have been used as the primary validation parameter for welding simulations, largely due to the importance of predicting WRS for structural integrity assessments. However, the extent of welding-induced plasticity (WIP) caused by the plastic flow of near-weld material is also an important characteristic affecting weld performance. WIP has been shown to negatively affect weld integrity, since the associated accumulation of defects (dislocations) in the material will accelerate the nucleation of macro-scale defects that lead to component failure. Information on WIP is particularly important when attempting to validate the constitutive models used for weld simulation, and can assist with the proper definition of material yield strength.

The present study highlights two approaches to assess WIP in welded structures. The first approach involves the development of a micro-hardness correlation to infer the level of WIP across the near-weld region. The second approach uses electron backscatter diffraction (EBSD) data to directly calculate the average crystal misorientation in the region of interest, which is proportional to the amount of geometrically necessary dislocations present. The dissimilar approach to determine WIP between the two characterization methods allows a degree of confidence in the results obtained, therefore providing an accurate dataset for weld model validation. To exemplify this point, the two approaches are used to characterize WIP across a three-pass slot weld in AISI 316 steel (NeT TG4 specimen), and the results are compared to weld modelling predictions.

Copyright © 2016 by ASME
Topics: Plasticity , Steel , Welding

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