Computational Analysis of Hydrogen Contribution to the Near-Neutral pH Stress Corrosion Cracking
Bibliographic record
Abstract
Hydrogen plays a critical role in near-neutral pH SCC in pipelines, but the precise mechanism of its effect on crack initiation and propagation is still not well understood. Fundamentally, the process starts on the atomic level and at the root is dislocation formation and propagation due to various factors. In the present study a molecular statics simulation has been applied for the analysis of the contribution of hydrogen to the near-neutral pH stress corrosion cracking. A 3D crystal structure in which the interatomic forces between the hydrogen-iron and iron-iron atoms were defined, respectively, by the Morse and modified Morse potential functions was tested numerically. The model and the code developed were applied to both a hydrogen-free bcc iron crystal with the premade edge slit and to a bcc iron crystal with the hydrogen atoms aggregated near the crack tip. The width of the reference structure was chosen to be large enough to avoid any significant effects of free boundaries while preserving the basic properties of the structure. The edge slit was obtained by removing of a monolayer of iron; it was assumed that this slit was formed previously as a result of dissolution and the hydrogen-assisted cracking. Simulation results demonstrated that the presence of dissolved hydrogen causes severe distortion of the lattice and results in a weakened zone of interatomic bonds in the vicinity of the hydrogen atom even before the external load is applied to the structure. This phenomenon leads to the nucleation of nano-voids and later to the formation of edge dislocations array, and to the newly nucleated voids coalescing. Consequently the sliding processes start earlier (under the smaller load) leading to a 15–20% loss of residual strength in comparison with the hydrogen free sample.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".