ZHEN C B, TIAN Z A, LIU Y C, et al. Uncertainty analysis of notch stress concentration factors for welded butt joints[J]. Chinese Journal of Ship Research, 2024, 19(2): 159–164 (in Chinese). doi: 10.19693/j.issn.1673-3185.03303
Citation: ZHEN C B, TIAN Z A, LIU Y C, et al. Uncertainty analysis of notch stress concentration factors for welded butt joints[J]. Chinese Journal of Ship Research, 2024, 19(2): 159–164 (in Chinese). doi: 10.19693/j.issn.1673-3185.03303

Uncertainty analysis of notch stress concentration factors for welded butt joints

  • Objectives This paper focuses on parametric modeling of a typical butt joint and establishes a finite element model with uncertain geometry of the weld seam, aiming to investigate the stress concentration factor Kt at the weld toe of the butt joint with uncertain weld seam geometry and analyze its distribution characteristics.
    Methods Firstly, the mesh size and element type used in the past were improved, and the influence of different types of elements and mesh sizes on Kt is studied through finite element mesh sensitivity analysis. Nodal stresses are extracted along the welding direction of the butt joint, and the location of maximum stress concentration at the weld toe is determined by plotting the stress distribution. Then, the uncertainty of the weld seam geometry is accurately reflected by introducing control points to describe the variation of the weld seam geometry. Combined with the distribution pattern of the actual measured weld seam geometry data, a large amount of weld seam geometry parameter data are randomly sampled. Finally, Kt is calculated based on the notch stress method and its distribution was statistically analyzed to explore the distribution pattern of Kt when there is uncertainty in the weld seam geometry parameters of the butt joint.
    Results The results show that the distribution of Kt follows a normal distribution.
    Conclusions Exploring the stress distribution of welding toes has great significance for analyzing fatigue strength and improving the prediction accuracy of fatigue life.
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