Application of Constraint-Sensitive Fracture Mechanics to the Assessment of Girth Weld Integrity
Bibliographic record
Abstract
It has been known since the 1960’s that the crack-tip fields of specimens containing sharp cracks depend on the mode of loading. Experimental evidence has shown that cracked specimens loaded in bending have lower toughness than the same material loaded in tension. This phenomenon has been attributed to the “constraint effect” on fracture. Modern constraint-sensitive fracture mechanics has brought about fundamental theoretical understandings on the constraint effects. The constraint-sensitive fracture mechanics has moved from academic circles to practical application, as evident by a number of recently published fitness-for-service (FFS) assessment procedures that incorporates the constraint effects. This paper reviews the developments in constraint-sensitive fracture mechanics with the focus on its potential applications to the assessment of pipeline girth weld integrity. The review covers (1) constraint theories and experimental evidences, (2) constraint models for brittle and ductile fracture, and (3) limitations of current constraint models. The paper closes with thoughts on the applications of the constraint models and theories to ductile fracture processes, which are the most relevant to modern linepipes and their welds.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".