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Corrosion Fatigue of Low Carbon Steel under Compressive Residual Stress Field

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2018 English Publisher:Elsevier BVJournal:Procedia Engineering, volume 213, pages 674-681 (issn: 1877-7058, Copyright policy )Funded by:EC | APESA
Authors: Okorokov, Volodymyr; Morgantini, Marta; Gorash, Yevgen; Comlekci, Tugrul; MacKenzie, Donald; van Rijswick, Ralph;

doi: 10.1016/j.proeng.2018.02.063

Corrosion Fatigue of Low Carbon Steel under Compressive Residual Stress Field

Abstract

This paper presents experimental investigation and numerical modeling of the effect of compressive residual stress on the corrosion fatigue life of a low carbon steel. A fatigue life test methodology based on double notched tensile test specimens is proposed. A new plasticity model is proposed for accurate simulation of compressive residual stress and calibrated to experimental stress-strain curves obtained for low carbon steel. The proposed model is implemented as a user-material in the ANSYS Workbench Finite Element Analysis program and utilized in plastic analysis and fatigue assessment. Corrosion fatigue test results are discussed and compared to numerical predictions.

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Keywords

autofrettage, cyclic plasticity, Mechanical engineering and machinery, crack arrest, compressive residual stress, TJ, 624, corrosion fatigue, 620

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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