journal article·2016-12

Cyclic deformation behavior of austenitic Cr–Ni-steels in the VHCF regime: Part I – Experimental study

A.C. Grigorescu, P.-M. Hilgendorff, M. Zimmermann, C.-P. Fritzen, H.-J. Christ

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Abstract

Abstract A stable (AISI 316L) and a metastable (AISI 304L) austenitic stainless steel were investigated with respect to their VHCF behavior. The focus of the paper lies on the investigation of the cyclic deformation behavior of the two materials at very low stress amplitudes. The 304L steel is characterized by a pronounced cyclic softening during its initial stage of cyclic deformation. In the course of the following loading cycles, a phase transformation (γ-austenite → α′-martensite), accompanied by volume expansion is associated with the reduction of the global plastic strain amplitude and induces compressive stresses in the near surface layer. As a consequence, the material shows no failure up to 109 cycles at 240 MPa. In contrast, the type 316L steel has a higher stacking fault energy and the microstructure remains fully austenitic during cyclic deformation when analyzed by means of magneto-inductive methods. In this case, very localized plastic shear occurs and the slip band topography reveals the formation of pronounced intrusions. Microcracks initiate from these intrusions in the VHCF regime and samples failed also beyond 107 cycles. This study presents a comparative investigation of the damage evolution – including dislocation morphology and phase transformations – during cyclic loading for both materials. The combined effect of the individual deformation mechanisms is investigated for both materials in the context of a microstructure-sensitive simulation discussed in Part II of this study.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Microstructure and Mechanical Properties of Steels · Hydrogen embrittlement and corrosion behaviors in metals · High Temperature Alloys and Creep

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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