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Numerical Fatigue Analysis of Induction-Hardened and Mechanically Post-Treated Steel Components

Chair of Mechanical Engineering, Montanuniversität Leoben, 8700 Leoben, Austria
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This paper is an extended version of our conference paper published in Leitner, M., Aigner, R., Dobberke, D. “Local fatigue strength assessment of induction hardened components based on numerical manufacturing process simulation.” In Proceedings of the 7th International Conference on Fatigue Design, Fatigue Design 2017, Senlis, France, 29–30 November 2017.
Machines 2019, 7(1), 1; https://doi.org/10.3390/machines7010001
Received: 2 November 2018 / Revised: 12 December 2018 / Accepted: 21 December 2018 / Published: 2 January 2019
(This article belongs to the Special Issue Advances in CAD/CAM/CAE Technologies)
This paper presents a numerical simulation chain covering induction hardening (IH), superimposed stroke peening (StrP) as mechanical post-treatment, and a final fatigue assessment considering local material properties. Focusing on a notched round specimen as representative for engineering components, firstly, the electro-magnetic-thermal simulation of the inductive heating is performed with the software Comsol®. Secondly, the thermo-metallurgical-mechanical analysis of the hardening process is conducted by means of a user-defined interface, utilizing the software Sysweld®. Thirdly, mechanical post-treatment is numerically simulated by Abaqus®. Finally, a strain-based approach considering the evaluated local material properties is applied, which reveals sound accordance to the fatigue tests results, exhibiting a minor conservative deviation of only up to two per cent, which validates the applicability of the presented numerical fatigue approach. View Full-Text
Keywords: fatigue; induction hardening; mechanical post-treatment; numerical simulation fatigue; induction hardening; mechanical post-treatment; numerical simulation
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Leitner, M.; Aigner, R.; Grün, F. Numerical Fatigue Analysis of Induction-Hardened and Mechanically Post-Treated Steel Components. Machines 2019, 7, 1.

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