journal article·2016-01

Intergranular damage during stress relaxation in AISI 316L-type austenitic stainless steels: Effect of carbon, nitrogen and phosphorus contents

H. Pommier, E.P. Busso, T.F. Morgeneyer, A. Pineau

Acta Materialia· Volume 103
Publisher page

Abstract

This work concerns a study of the mechanisms responsible for intergranular cracking during high temperature stress relaxation in AISI 316L-type austenitic stainless steels. This phenomenon, also known as reheat cracking, is typically present in heat affected zones of massive welded parts used in the energy industry. Here, five steel grades with different C, N and P contents were considered to assess the effects of chemical composition on the three main mechanisms potentially responsible for reheat cracking, namely intergranular M23C6 carbide precipitation, stress relaxation phenomena, and intergranular P segregation. After testing the five AISI 316L-type grades under reheat cracking conditions by a pre-compressed CT-like specimen technique, different degrees of intergranular damage were observed in the specimens by optical microscopy and synchrotron X-ray tomography. Detailed grain boundary analyses by SEM and TEM in the five different steel grades showed the main mechanism responsible for reheat cracking to be the nucleation of microcavities at intergranular M23C6 carbides in high residual stress regions. The addition of P was found to increase the number of cavitated GBs but not to be the dominant mechanism responsible for intergranular damage. A comparison between elasto-plastic finite element predictions of the residual stresses in the CT-specimens and the results of microstructural investigations revealed no intergranular damage in regions where the initial maximum principal stresses in the specimens were below 740 ± 30 MPa.
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Research context

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

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

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