Temperature and Loading Frequency Effects in the Mechanism for NNpH SCC of Pipeline Steel
Bibliographic record
Abstract
Abstract Cracking is a leading cause of pipeline failure and rupture in large-diameter transmission lines. Thus, developing and improving crack management programs is a strategic priority for pipeline operators. The most common cracking mechanism in Canada is Near Neutral pH Stress Corrosion Cracking (NNpH SCC). A key component of such a program is a growth model that captures the underlying growth mechanism; yet, there is disagreement on the nature of this cracking mechanism. Pipeline operators have deployed various growth models to differing degrees of success, including fatigue models, classical electrochemical SCC models, and hydrogen-enhanced corrosion fatigue models. This paper presents experimental evidence and theoretical analysis suggesting a diffusible species, namely hydrogen, plays a pivotal role in NNpH SCC by enhancing the corrosion fatigue mechanism. Past work performed by the Chen group (University of Alberta – PRCI Project SCC 2-12) identified a critical frequency at which the crack growth rate reaches its maximum. We expand this body of work by examining the effect of loading frequency at multiple temperatures. First, we use a simple diffusion model to estimate the critical frequency at the targeted experimental temperatures calibrated with the known room temperature data. Next, we perform experimental testing across various loading frequencies to prove or disprove this prediction. Experimentally, we fabricated specialized surface crack tension (SCT) specimens from X65 pipeline steel designed to simulate the geometry of features found in the field. These specimens are pre-cracked in the air and then immersed in an NNpH SCC electrolyte (C2 solution) at the test temperature for 12 days. Next, the samples are loaded under constant amplitude cyclic loading at various loading frequencies; the initial maximum and minimum stress intensities are held constant. The experimental results find a critical frequency that agrees with the theoretical calculations suggesting that hydrogen is the diffusible species playing a pivotal role in NNpH SCC growth.
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How this classification was reachedexpand
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 | 0.002 | 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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".