Comparative Study of Crack Shape on the Ductile Fracture Response of Cracked Pipelines
Bibliographic record
Abstract
Abstract Buried pipelines are subjected to various types of loads, including external pressure from soil overburden and internal pressure from pressurized fluids. These loads can induce axial and hoop stresses, which are the primary factors leading to the formation of integrity threats, such as cracks. The presence of cracks can render a pipeline susceptible to failure, posing a significant threat to its operation, safety, and the environment. This underscores the importance of promptly detecting and evaluating even seemingly minor surface defects, as they can significantly damage the structural integrity of the pipeline. It is also crucial to accurately predict the failure pressures of pipelines with cracks to ensure that the operating pressure remains below this critical limit with an adequate margin of safety. A variety of approaches exist for assessing cracks in pipes, including empirical approaches such as MAT-8, Ln-Sec and CorLAS™ models, as well as numerical approaches like the extended finite element method (XFEM). XFEM is a powerful tool to estimate the failure pressures of pipelines containing cracks. It extends the capabilities of the traditional Finite Element Method (FEM) and offers a more effective means of simulating crack propagation. In ABAQUS, initial cracks can be modelled in either sharp or blunted shapes. However, it is uncertain whether the shape of the crack affects the failure pressures of cracked pipelines. For this purpose, detailed parametric studies are necessary to investigate the implications of pre-existing cracking shapes on the ductile fracture response of pipes subjected to pure mode I loading.
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) | 0.002 | 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".