A new method for predicting susceptibility of austenitic stainless steels to intergranular stress corrosion cracking. (February 2020)

• Record Type: Journal Article
• Authors: Rahimi, S.; Marrow, T.J.
• Is Part Of: Materials & design. Volume 187(2020)
• Publication Date: 2020-02
• Subjects: Intergranular stress corrosion cracking (IGSCC) -- Grain boundary character distribution -- Thermo-mechanical processing -- Grain boundary engineering (GBE) -- Sensitisation -- Corrosion; Materials -- Periodicals; Engineering design -- Periodicals; Matériaux -- Périodiques; Conception technique -- Périodiques; Electronic journals; 620.11
• DOI: 10.1016/j.matdes.2019.108368
• Languages: English
• ISSNs: 0264-1275

Abstract

Abstract: Microstructures of type 304 austenitic stainless steel, produced through thermo-mechanical processing, were analysed with large area EBSD and optical image analysis assessments of the attacked grain boundary cluster after DL-EPR testing. The thermo-mechanically processed microstructures were exposed to acidified potassium tetrathionate (K2 S4 O6 ) solution under tensile stress and the lengths and distributions of the initiated intergranular crack nuclei were assessed. The crack populations were quantified by fitting a Gumbel extreme value statistics distribution to evaluate their characteristic crack length. A factor (susceptibility parameter) is introduced to rank the degree of susceptibility to intergranular stress corrosion cracking of thermo-mechanically processed microstructures. This accounts for the network connectivity of the sensitised grain boundaries, the grain size and the degree of sensitisation. Similar rankings are obtained for this susceptibility parameter and characteristic crack lengths of the assessed microstructures, in which the thermo-mechanical treatments increased the population of grain boundaries with resistance to stress corrosion cracking. Graphical abstract: Unlabelled Image Highlights: A new method is proposed to rank the susceptibility of austenitic steels to IGSCC. This method measures the sensitivity of grain boundaries to IGSCC more accurately. Cluster compactness, a network connectivity measure, is used for predicting IGSCC. The populations of intergranular crack nuclei are assessed by statistic of extreme.