Numerical Assessment of Dented Pipe Using Inline Inspection Data
Bibliographic record
Abstract
Abstract The current finite element (FE) assessment methods of dented pipes are based on specific dent profiles, which are generally created based on the shape of indenters. However, the actual dent profile in real case scenarios is mostly irregular in shape, depending on the cause of damage. In this paper, FE analyses of dented pipes using inline inspection (ILI) data are presented. Based on the ILI data, the dent profile is generated by applying the nodal displacements to all the pipe nodes. The validation of this nodal displacement approach is discussed in this paper. Besides, a parametric study is carried out to study the behavior of dent for different dent depth, pipe geometry, and pipe grades. The significance of residual stresses generated during the dent formation on the behavior of dented pipe during the service life is also discussed. Finally, the remaining life estimation of dented pipes according to the API 579-1 is presented using FE analysis results.
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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 | 0.001 |
| 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 | 0.001 | 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".