Microstructural Feature Analysis of X65 Steel Exposed to Ripple Load Testing Under Near Neutral pH Conditions
Bibliographic record
Abstract
Newly designed miniature Compact Tension (CT) specimens, designed according to standard ASTM dimension ratios, and machined out of previously in-service X65 pipeline steel were exposed to super-imposed cyclic loading at high mean stresses in NS4 solution to determine the behaviour of X65 steel to ripple loading under near neutral pH conditions. Electron Back-Scatter Diffraction (EBSD) was used to study the microstructural grain geometry to determine if it influences stress-corrosion cracking (SCC) initiation and propagation. Prior to ripple load testing, finely polished X65 surfaces were subjected to EBSD measurements to characterize the microstructure’s geometry; i.e., grain and grain boundary orientations and texture. On the same locations where EBSD maps were recorded, a grid of cross-shaped resist markings — approximately 1–5 μm in size — were deposited every 15 μm across the analyzed surfaces. Following microscopic analyses the specimens were pre-cracked and re-examined to determine whether the crack initiation procedure preconditions the residual strain (quantified by grain misorientations) around an induced crack. Then, ripple load testing at stress levels characterized by load ratios (R) greater than 0.9 was performed, while simultaneously monitoring the open-circuit potential (OCP) at room temperature. The originally characterized surface was again re-examined to determine if the crack tip propagated preferably along a specific crystallographic grain orientation by comparing the shifts in each cross-shaped grid. Results from this investigation will help determine if there is a link between microstructural grain geometries and transgranular stress corrosion cracking.
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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) | 0.002 | 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".