Geometric Analysis of Pipeline Elbows Through Reverse Engineering and Their Associated Imperfections
Bibliographic record
Abstract
Pipe elbow is a common feature in pipelines and piping systems as a means to changing directions of otherwise straight pipelines. Irrespective of the processes involved in manufacturing pipe elbows, it is of interest to investigate whether they have any geometric imperfections. Researchers at the University of Alberta have devised a technique to measure initial imperfection of straight pipes prior to testing, using high resolution 3D surface profiler in conjunction with 3D reverse engineering software. The objective of the current study is to extend the imperfections measurement technique from measuring straight pipe segments to pipe elbows. Six (6) ninety (90) degree elbows are measured in this research with outside diameters ranging from NPS 12 inch to NPS 42 inch. A 3D laser scanner is used to acquire surface data and create 3D models corresponding to each elbow. A method for the geometric analysis of the elbows is developed using 3D inspection and reverse engineering software Geomagic®. The geometric idealization of a pipe elbow is a torus, which can be defined by a circle revolving around an axis, coplanar with the circle. The idealized geometry for each elbow is obtained through the developed method of geometric analysis, which includes the diameter of the circle defining the torus, and its distance from the axis of revolution. The difference between the ideal torus and the scanned geometry is considered as imperfection of each pipe elbow. The wall thickness values at the ends or edges of select pipe elbows are also measured from the scanned data and are reported as percentage deviation from the specified wall thickness around the perimeter at different cross sections. The 3D reverse engineering of the elbows indicated that they resemble the ideal geometry very closely. The ovalization imperfections are seen to be well within the value specified by CSA Z662-11. The wall thickness deviations are seen to vary between −10% to +25% of the specified value, with increased thickness being more prominent in the elbows. Finite element analysis of an elbow with thickness imperfection shows that higher hoop stress appears on the intrados than initially intended.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".