Comparative Multi-Axial High-Cycle Fatigue Analysis of Spot Weld Models Using Findley’s Damage Criteria

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Authors Abstract
Content
High-cycle fatigue (HCF) is one of the main concerns for spot-welded structures, and finite element (FE)-based simulations have critical importance for the life assessment and design optimization. The accuracy of spot weld modeling methodologies has a key role in achieving the development objectives. This article presents a comparative study for HCF simulations of different spot weld modeling methodologies and their comparison with the test data. In this regard, HCF analyses based on Findley’s multi-axial damage model are conducted with a commercial software. Direct equivalenced spot weld modeling with and without offset adjustment, rigid spot weld, and rigid beam (single) spot weld methods are analyzed for overlapped sheet metals under axial cyclic loading. Two specimens with different thicknesses, spot weld diameters, and number of nuggets are simulated under six cyclic load cases: 2000-4000 N, 1400-2800 N, 1800-3600 N, 200-8000 N, 100-8300 N, and 200-6800 N. Direct equivalenced spot weld modeling with offset adjustment and rigid spot weld methods demonstrate high levels of accuracy with an average deviation of 8.9% from experimental data. It has been shown that it is imperative that offset adjustments be made for the direct equivalenced spot welding method since improper offset results in an artificially increased life estimate that is ten to twenty times greater than the data collected from the test. A rigid beam spot weld model with only one rigid connection concentrated at the center of the weld nugget produces artificial stress increases and, therefore, has a much shorter fatigue life cycle than the test results.
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DOI
https://doi.org/10.4271/05-16-01-0006
Pages
12
Citation
Duran, E., "Comparative Multi-Axial High-Cycle Fatigue Analysis of Spot Weld Models Using Findley’s Damage Criteria," SAE Int. J. Mater. Manf. 16(1):59-70, 2023, https://doi.org/10.4271/05-16-01-0006.
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Publisher
Published
Oct 14, 2022
Product Code
05-16-01-0006
Content Type
Journal Article
Language
English