Nihon Kikai Gakkai ronbunshu (Jul 2023)
Simultaneous non-destructive estimation method of welding deformations and three-dimensional residual stresses by using surface displacements and surface elastic strains
Abstract
Recently, large-scale welded structures especially in power stations have been designed and operated based on the concept of assurance of structural integrity. Here, fracture mechanics and non-destructive inspections are applied to flaw evaluations, however it is necessary to estimate three-dimensional residual stresses to predict crack growth rate for each observed crack. On the other hand, welding deformations have an influence on manufacturing accuracy and on external appearance of products. Still today, it is relatively difficult to estimate three-dimensional welding residual stresses and welding deformations accurately using the thermo-elasto-plastic FEM (Finite Element Method) analysis due to higher complexity of actual welding process. Authors have proposed a non-destructive method evaluating welding deformations and residual stresses based on the eigen-strain methodology. In this method, welding deformations and residual stresses for whole structure are calculated from eigen-strains which are estimated by the inverse analysis from surface displacements which can be measured by the digital image correlation (DIC) method. However, estimation accuracy near the weld line becomes relatively poor because it is impossible to define deformations and total strains on the weld metal by the DIC method. This study aims to improve the estimation accuracy of both welding deformations and residual stresses by adding surface elastic strains along the weld line which can be measured by X-ray diffraction. Numerical simulations for a butt-welded plate with a V-groove before welding were carried out to evaluate the estimation accuracy of this method. X-ray measurements along the weld line were effective to improve the estimation accuracy when the penalty method is combined with the Truncated Singular Value Decomposition (TSVD) method in the inverse analysis.
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