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Lecture

WEB Effect of nano-scaled Cu precipitates on cyclic hardening potential, fatigue strength and defect tolerance of a low carbon steel



The reliable dimensioning of components requires a sound knowledge of the materials fatigue behavior. As shown by [Mura02], microstructural defects, i.e. pores and nonmetallic inclusions, have a huge impact on the fatigue lifetime and therefore, the materials’ defect tolerance needs to be considered. Previous investigations have shown that using Cu as an alloying element in steels, combined with a suitable heat treatment, can lead to an increased defect tolerance because of the formation of nano-scaled Cu precipitates [Bamb16]. These Cu precipitates increase the materials’ cyclic hardening potential and hence, the ability to counteract stress concentrations at microstructural notches, improving the fatigue lifetime.

For a deeper understanding of the relation between Cu precipitates and resulting mechanical properties, especially the cyclic hardening potential, different heat treatment states of a Cu alloyed steel were investigated. For this, instrumented cyclic indentation tests (CITs) were conducted to efficiently determine the influence of heat treatment on the cyclic hardening potential. Additionally, atom probe tomography was performed for relevant heat treatment conditions, revealing a correlation of the materials hardness as well as cyclic hardening potential, determined by CITs, with the morphology of Cu precipitates [Schw20]. Furthermore, S-Nf curves were determined by constant amplitude tests for selected conditions, showing a good correlation between fatigue strength and cyclic hardening potential. Moreover, specimens with artificially introduced defects were investigated in fatigue tests and evaluated by using the √area concept of Murakami [Mura02] to explicitly analyze the defect tolerance. These investigations confirmed that Cu precipitates in steels increase the resulting defect tolerance and are in excellent accordance with the cyclic hardening potential determined in CITs.

 

Speaker:
David Görzen
TU Kaiserslautern
Additional Authors:
  • Dr. Hannah Schwich
    RWTH Aachen University
  • Bastian Blinn
    TU Kaiserslautern
  • Prof. Dr. Wolfgang Bleck
    RWTH Aachen University
  • Prof. Dr. Tilmann Beck
    TU Kaiserslautern