Technical Note: Visualization of Stress Corrosion Cracks Emerging from Pits

• Published in: Corrosion (Houston, Tex.) Tex.), 2006-07, Vol.62 (7), p.555-558
• Main Authors: Turnbull, A., Zhou, S., Orkney, L., McCormick, N.
• Format: Article
• Language: English
• Subjects: Applied sciences; Corrosion; Corrosion environments; Corrosion mechanisms; Cracks; Exact sciences and technology; Metals. Metallurgy; Pits; Pitting (corrosion); Steam turbines; Stress corrosion; Stress corrosion cracking; Turbine engines; Turbines
• ISSN: 0010-9312; 1938-159X
• DOI: 10.5006/1.3280668

ABSTRACTIn many applications, pitting is the precursor to stress corrosion cracking (SCC) because it provides the combination of a local aggressive solution chemistry and a stress concentrating feature. The fundamental steps in the overall process of crack development involve pit initiation, pit growth, the transition from a pit to a crack, short crack growth, and long crack growth. In predictive schemes,1-5 the pit-to-crack transition is based on the phenomenological requirements1 that the pit depth must be greater than a threshold depth, corresponding to a threshold stress intensity factor, and that the crack growth rate should exceed the pit growth rate. Such models are continuum-based, but the detail of how a stress corrosion crack actually emerges from a pitting corrosion precursor has neverTo obtain the flaw profile, pit plus crack, a systematic layer removal process was undertaken on discrete specimens. The gauge length of the tensile cylindrical specimens was mounted longitudinally in a thermoplastic resin. The top 1.5 mm of the specimen was removed initially by grinding and the specimen was then polished to remove controlled thicknesses of approximately 40 µm. For each exposed layer, 30 photographs were taken along the length using a computer-controlled optical microscope with a magnification of X85. These images were then "stitched" together using an image processing computer software to provide a large high-resolution image of the whole section. Smaller lower-resolution images of individual pits were then extracted for processing into 3-D images. These images were assembled as an image stack and aligned before being transformed into a data set for processing with a data visualization computer software. An explorer map was used to process the data set by finding iso-surfaces of constant image intensity that corresponded to the boundary between