Analysis of HDPE Failure Data in Support of Development of Flaw Acceptance Criteria for Butt Fusion Joints
Bibliographic record
Abstract
Abstract There is a need for ASME B&PV Code procedures and acceptance criteria for evaluation of flaws detected by inspection of high density polyethylene (HDPE) piping items in safety Class 3 systems. To support the development of flaw acceptance criteria for butt fusion joints in HDPE pipes, a series of coupon tests have been completed for specimens cut from butt fused HDPE pipes with surface or subsurface flaws placed in the joints prior to fusion process. Specimens containing known flaw sizes were tested under axial load at accelerated stresses and temperatures until failure; or until a prescribed number of test hours was reached. The failure time from the tests has been correlated to the net section stress and the stress intensity factor, and the results showed that the failure time can be better represented by the stress intensity factor. The test results were then used to fit the Brown and Lu formula that predicts the time to failure due to the slow crack growth of flaws as a function of stress intensity factor and temperature. With the developed Brown and Lu equation, the allowable stress intensity factors for a piping lifetime of 50 years at the maximum code allowable temperature of 60°C have been proposed for both surface and subsurface flaws in HDPE butt fusion joints. Examples of what might be corresponding allowable flaw sizes in the butt fusion joints of piping are also provided.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".