Multiaxial fatigue strength assessment of welded joints using the Peak Stress Method – Part I: Approach and application to aluminium joints
Source abstract
Abstract
Abstract The notch stress intensity factor (NSIF) approach for the fatigue strength assessments of welded joints assumes the weld toe as a sharp V-notch with tip radius equal to zero and the weld root as a pre-crack. The Peak Stress Method (PSM) is an approximate, FE-oriented application of the NSIF-based approaches to fatigue design of welded joints and it is based on the singular linear elastic peak stresses calculated from FE analyses carried out by using a proper mesh pattern; more precisely, the element type is fixed, the average element size is kept uniform in the mesh pattern and before running the mesh generation algorithm the size can be chosen arbitrarily within a given range. The PSM allows to adopt rather coarse FE meshes if compared to those required for the NSIFs evaluation from the local stress fields. While originally the PSM was validated for pure axial or bending loadings as well as pure torsion loadings, here the PSM is extended for the first time to analyse the fatigue strength of welded joints subjected to in-phase as well as out-of-phase multiaxial fatigue loadings. By adopting the averaged Strain Energy Density (SED) as a fatigue strength criterion, a so-called equivalent peak stress is defined and it is adopted to assess either weld toe and weld root fatigue failures in conjunction with a properly defined design curve. Some multiaxial fatigue test data taken from the literature and relevant to welded joints made of aluminium alloys are analysed using the Peak Stress Method. The equivalent peak stress has shown to correlate with good approximation all the experimental data.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Fatigue and fracture mechanics · Advanced Welding Techniques Analysis · Structural Load-Bearing Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (53)
Show source-provided references
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