The Effect of Cooling Mode on Slow Crack Growth Resistance of Polyethylene Pipe
Bibliographic record
Abstract
High-density polyethylene (HDPE) pipes have been widely used as gas or water transport pipes owing to their comprehensive advantages. One of the principal failure modes determining pipe service lifetime is slow crack growth (SCG) with the crack occurring first at the inner surface due to the slow cooling rate of the pipe's inner wall during polyethylene (PE) pipe extrusion. In order to change the conventional cooling mode and increase the cooling rate in the inner wall of PE pipe during extrusion, a novel extrusion equipment was designed and manufactured by our research team. For this paper, compressed air as a cooling medium was introduced through the interior of the hot extruded pipe during its extrusion to realize the quick inner wall cooling, and the effects of the inner wall's cooling rate on the microstructure and mechanical properties of the PE pipe were investigated. The experimental results showed that simultaneously cooling of both the outer and inner walls could decrease the difference in the solidification rate across the pipe and reduce the residual internal stresses in PE pipe. The quick cooling of the inner wall of the extruded pipe could also decrease the PE crystal thickness, and increase the number of tie molecules in the inner wall, which is a key parameter determining the resistance to SCG. As a result, compared to the PE pipe produced by the conventional extrusion, the crack initiation time of the PE pipe manufactured by the novel method increased from 27 h to 45 h and the crack growth rate was slower.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".