Visualization and Location Determination of Pit Initiation Sites in Martensitic Stainless Steel during Corrosion-Fatigue Cyclic Plastic Deformation
Bibliographic record
Abstract
Low-carbon martensitic stainless steels, such as 13%Cr4%Ni, are widely used in manufacturing hydraulic turbine runners. High tensile strength steel, such as cast CA6NM or wrought S41500 martensitic stainless steel, has an acceptable resistance to corrosion and cavitation, and reduces the weight and cost while offering a more efficient design. During operation, the combined effect of cyclic loading (fatigue) and corrosion reduces the fatigue strength and can initiate cracks at localized corrosion surface defects. In this study, we determined the bulk and localized corrosion behavior of wrought (S41500) and cast (CA6NM) 13%Cr4%Ni stainless steel before and after plastic deformation. Susceptibility to pitting corrosion was studied using open circuit potential and potentiodynamic polarization measurements in 0.020 M NaCl. Localized corrosion behavior was studied using a scanning droplet cell (SDC) and oil immersed scanning electrochemical cell microscopy (OI-SECCM). The bulk and localized electrochemical measurements after different surface preparation methods (mechanical polishing, followed by etching or electro-etching in different media) were compared. The surface defects including micro-voids and inclusions of different types were characterized. The location of pit initiation was then determined using scanning electron microscopy and profilometry imaging. A three-electrode microcell with a working electrode of 1 mm² was designed and hyphenated with optical microscope to allow in situ tracking of pit initiation and growth. Chronopotentiometry and chronoamperometry controlled pit initiation, while optical microscopy demonstrated dynamic release of corrosion products and measured oxide repassivation kinetics. Finally, the in situ technique was developed further to include a microtensiometer fatigue apparatus to study the synergy effect between corrosion and fatigue. Location of pit initiation was compared with and without plastic deformation. Videos of pit initiation and growth will be presented.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".