Squeeze the Crack Out of It - With Type A Compression Sleeves
Bibliographic record
Abstract
Abstract Type A Compression Sleeves have been a technically viable repair method for corrosion, lamination-like features, and longitudinal crack-like features for the past 20+ years. A Type A Compression Sleeve relies on thermal expansion/contraction of the steel sleeve, which once the sleeve long seam welds are made, results in a compressive hoop stress in the carrier pipe at levels equal to or greater than generated at max operating pressure. This repair technology has been mostly marketed in Canada, and therefore, CSA Z662 includes the Type A Compression Sleeve in their list of approved permanent repair technologies. Over the past five years, there’s been an increased awareness in the United States as the technology has become referenced in industry documents such as the PRCI Pipeline Repair Manual and API 1176. This paper provides an overview of a Type A Compression Sleeve, including the basis of how the repair system functions and how the sleeve is installed. Finally, this paper presents a series of full-scale tests and numerical modeling validating this innovative repair system. The use of induction heat, rather than open flame, provides a more consistent and traceable heat signature, allowing for confidence in the installed repair. Tests include synthetic cracks generated by precracking an EDM notch to generate a sharp-tipped crack, then heat tinted to provide a distinguishable boundary. The EDM notches, installed at a maximum of 50% of the wall thickness within the ERW seam, were subsequently repaired via the induction heating sleeve technology with and without flowing water in the carrier pipe. Test samples were cycled to 100,000 cycles, burst, and metallurgically examined. Post-test examination of the fracture surfaces revealed no discernable growth, therefore, indicating the technical viability of the repair technology as a permanent repair of crack-like features and provides an Operator another option when making repair decisions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 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".