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On the Correlation between Fatigue Behaviour and the Multiphase Microstructure of a Super Duplex Stainless Steel
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  • Aida B. Moreira,
  • Ana P. O. Costa,
  • Laura M.M. Ribeiro,
  • Abel D. Santos,
  • Abilio De Jesus
Aida B. Moreira
University of Porto

Corresponding Author:[email protected]

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Ana P. O. Costa
Faculty of Engineering of University of Porto
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Laura M.M. Ribeiro
University of Porto
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Abel D. Santos
Faculty of Engineering of University of Porto
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Abilio De Jesus
Faculty of Engineering of University of Porto
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Abstract

Super duplex stainless steels (SDSS) have an ideally dual-phase microstructure composed of austenite and ferrite. However, due to variations in cooling rate, secondary phases (SP), such as sigma, may arise, jeopardising the fatigue performance. This work investigates the correlation between macroscale fatigue behaviour and the multiphase microstructure in SDSS. Fatigue tests were conducted using miniature specimens representative of three regions of a cast C-Ring with different cooling rates, meaning distinct SP amounts. A numerical model was proposed to assess the fatigue test parameters. SEM and EBSD techniques were used to quantify the SP and analyse the fatigue-crack propagation, complemented by hardness and tensile test results. Regression models were developed to correlate the percentage of SP, the fatigue resistance and the number of cycles to failure, and to predict the microstructural stress concentrations from the amount of SP. In addition, a methodology is proposed for predicting S-N curves as a function of the amount of SP. The results show a high correspondence in the increase of the percentage of SP with the decrease in fatigue life. The fatigue strength, for a given number of cycles to failure, tends to decrease linearly with increasing the SP. The microstructural stress concentration factor tends to increase with increasing SP. The research described in this manuscript contributes to further knowledge on predicting the behaviour of SDSS under different cyclic conditions, which can be valuable for optimizing design and performance in various applications.