Improvements to the ASME B31.8 Dent Strain Equations
Bibliographic record
Abstract
Pipelines used to transport oil and gas products are often subjected to external forces during its construction or operation, which can result in the formation of dents in the pipe. Various pipeline codes have stipulations on how a dent's severity can be ascertained in order to prioritize repairs. The most prominent being the depth-based criterion, which determines the severity of a dent by its depth. The depth-based criterion fails to consider the fact that the geometry of the dent can result in high strain concentration and eventually lead to integrity issues at the dented region. Alternatively, the strains associated with the dent can be an indicator of the dent's severity. Nonmandatory codified equations are available for evaluating the strains at the dented region of the pipe. The current implementation of these equations might fail to capture the strains that are not aligned with the most severe deformation profile of the dent and as such a global view of the strain distribution of the dented profile would be more informative as per the localized strain distribution. The study presented herein is the implementation of ASME B31.8 formulations together with the suggested modifications to evaluate the three-dimensional (3D) strain state of the dented pipe. The strain distributions obtained are compared against the strains predicted by finite element analysis (FEA) model. The correlation in the predicted strains indicates the possibility of the rapid and concise strain based characterization of dented pipes with the proposed technique.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".