A Transparent ASME B31.8-Based Strain Assessment Method Using 3D Measurement of Dent Morphology
Bibliographic record
Abstract
Abstract This paper presents a comprehensive methodology to evaluate the geometric strain of pipeline in a dented area caused by mechanical damage. This methodology was formulated based on the approach recommended by ASME B31.8 and built the transparency of the entire process of dent strain assessment using three-dimensional (3D) measurement of dent morphology reported by the Caliper tools from in-line inspection (i.e., Caliper data). The 2D Fourier Transform in conjunction with band rejection filtering method was used to filter the signal noise and smooth the 3D morphology of dent. The cubic spline was utilized to characterize the discrete 2D longitudinal and circumferential profiles for curvature and arch length calculations, which were used to evaluate the bending strain and membrane strain, respectively. The effective strain was then calculated using the method recommended by ASME B31.8. To demonstrate the application of the methodology, a tool with user-friendly interface and powerful visualization and reporting functions was developed using the methodologies reported in this paper. The reported methodology enables development of dent strain assessment tool and benefit pipeline operators to facilitate dent integrity management program.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".