Prediction of Ductile Fracture Arrest in Natural Gas Pipelines Using the Crack Tip Opening Angle
Bibliographic record
Abstract
Abstract In this paper, an analytical equation is developed to predict fracture arrest CTOA requirements for gas pipelines pressurized with natural gas that undergo single phase decompression using finite element (FE) analysis. The FE model is briefly reviewed. Dynamic pipe fracture simulations were performed to determine fracture resistance curves (crack velocity as a function of pressure at constant CTOA) for modern materials and geometries. American petroleum Institute (API) standard X80 and X100 steels were examined. Pipe diameters of 914 mm, 1219 mm, and 1422 mm, and diameter to thickness ratios ranging from 50 to 100 were considered. The commercial finite element code ABAQUS 2017x-explicit was used to generate the models and solve the analyses. The constant CTOA model was implemented through a user subroutine in conjunction with shell elements. Backfill effects were modelled using smooth particle hydrodynamics and the flap pressure profile was modelled using experimental data from previous burst tests. A CTOA-modified Two-Curve approach was used to determine the arrest CTOA for a given material and geometry. An equation for specification of the arrest CTOA as a function of steel grade and design parameters (thickness, diameter, and material properties) is presented for a gas that undergoes single-phase decompression. The proposed equation was validated through comparison with experimental data.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".