ArticleHeliyon2022
Predictive model to design for high cycle fatigue of stainless steels produced by metal additive manufacturing.
Article in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
This work develops a predictive model of S-N curves capable of proving the lower and upper bounds for fatigue behaviour of parts fabricated using different metal laser-based additive manufacturing (AM) and post-processing technologies. Alongside the ultimate strength of the material and its endurance limit, a surface factor and a defect factor are incorporated in the model to consider the effects of the AM process induced defects on the S-N curves. The model is correlated to comprehensive load-controlled fatigue experimental data from the literature for 316L stainless steel (SS) samples manufactured using metal laser-based AM technologies of various process and post-process conditions. It was demonstrated that the proposed model can capture and represent the effects of the induced defects as well as the mean stress effect. The value of the proposed model is that it can be integrated into existing industrial design workflows for fatigue assessment of AM 316L SS. Furthermore, it has the potential to be extended to other AM materials.
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Registered trials
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