Engineering Approach for Ductile Fracture Arrest Based on CTOA
Bibliographic record
Abstract
Abstract Ductile fracture propagation control and arrest are important elements in fracture control of pipelines transporting natural gas and other high-vapour-pressure media (e.g., dense-phase carbon dioxide). The most familiar crack arrest methodology, the Battelle Two-Curve Method (BTCM), is based on Charpy absorbed energy, and is well known to under-predict requirements for current high-strength high-toughness steels. Adjustments have been made, either by using correction factors or using absorbed energy from the drop-weight tear test (DWTT), but these remain empirical. The crack-tip opening angle (CTOA) has been proposed for a number of years as a fundamental parameter to characterize propagation toughness in aerospace and pipeline applications. It is convenient for finite element (FE) modelling of fracture in full-scale structures such as pipe. However, early procedures to measure pipe CTOA by a “two-specimen” method have been shown to be unreliable. Moreover, previous CTOA models (PFRAC and PICPRO) produced very different results. Recent work has addressed both shortcomings, including validation of a practical test for determining CTOA of pipe steels (ASTM E3039) and development of reliable FE models for axial crack propagation in pipes. Fracture resistance curves (crack velocity as a function of pressure at constant CTOA) including the effect of backfill have been computed over a wide range of variables. For a given design (pipe geometry, gas pressure and backfill) only tensile properties and CTOA are required to determine conditions for arrest; there are no adjustable constants in the methodology. Results to date are in good agreement with full-scale burst tests (FSBTs) by researchers at TC Energy and at the University of Tokyo, and with Maxey’s original treatment of the effect of backfill on fracture velocity at high pressures.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".