Effect of Residual Stress or Plastic Deformation History on Fatigue Life Simulation of Pipeline Dents
Bibliographic record
Abstract
Mechanical dents often occur in transmission pipelines, and are recognized as one of major threats to pipeline integrity because of the potential fatigue failure due to cyclic pressures. With matured in-line-inspection (ILI) technology, mechanical dents can be identified from the ILI runs. Based on ILI measured dent profiles, finite element analysis (FEA) is commonly used to simulate stresses and strains in a dent, and to predict fatigue life of the dented pipeline. However, the dent profile defined by ILI data is a purely geometric shape without residual stresses nor plastic deformation history, and is different from its actual dent that contains residual stresses/strains due to dent creation and re-rounding. As a result, the FEA results of an ILI dent may not represent those of the actual dent, and may lead to inaccurate or incorrect results. To investigate the effect of residual stress or plastic deformation history on mechanics responses and fatigue life of an actual dent, three dent models are considered in this paper: (a) a true dent with residual stresses and dent formation history, (b) a purely geometric dent having the true dent profile with all stress/strain history removed from it, and (c) a purely geometric dent having an ILI defined dent profile with all stress/strain history removed from it. Using a three-dimensional FEA model, those three dents are simulated in the elastic-plastic conditions. The FEA results showed that the two geometric dents determine significantly different stresses and strains in comparison to those in the true dent, and overpredict the fatigue life or burst pressure of the true dent. On this basis, suggestions are made on how to use the ILI data to predict the dent fatigue life.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".