Hydrogen uptake and embrittlement behavior in pipeline steels: Insights from slow strain rate testing and synchrotron micro-CT imaging
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
• Synchrotron micro-CT enhanced visualization of internal cracks undetectable in 2D analysis. • Steel microstructure influenced hydrogen diffusion and trapping, affecting crack initiation and severity. • Simultaneous hydrogen ingress and stress resulted in more severe embrittlement. • Hydrogen retention, not just crack initiation, critically drives embrittlement and failure mode. Hydrogen embrittlement (HE) presents a major challenge to the integrity of steel pipelines, often leading to premature failure. Traditional methods using two-dimensional (2D) analysis of damaged structures, often overlook critical features related to failure. Hence, this study investigates the hydrogen embrittlement susceptibility of two pipeline steels, X60 and X65, using a combination of mechanical testing, hydrogen diffusion and trapping studies, microstructural characterization, and synchrotron micro-computed tomography (micro-CT) imaging. The results highlight the critical role of hydrogen trapping and retention in HE, with steel microstructure significantly affecting hydrogen uptake and diffusion as well as crack nucleation and propagation. Synchrotron micro-CT imaging provided more accurate crack pattern assessments than traditional 2D methods, revealing potential misinterpretations from 2D cross-sectional analysis. This study concludes that simultaneous hydrogen ingress and mechanical loading is more damaging than pre-charging with high hydrogen concentrations, and that hydrogen retention capacity plays a greater role in embrittlement behavior than crack initiation. The failure mechanism of the hydrogen-charged steels shifted from being plasticity-based to decohesion-driven, based on the hydrogen content and retention in the steel, which is in line with the unified HELP+HEDE model.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 it