Use of Optical Fibers to Investigate Strength Limit States for Pressure Pipe Liners
Bibliographic record
Abstract
Cured in place pipe liners have been used for almost twenty years to repair cast iron water pipes, and research over that time has established that liner performance may be controlled by the local strain concentrations that develop where liners span across perforations in the wall of the cast iron pipe. Finite element analyses performed in a previous research study quantified the impact of those strain concentrations, but the difficulties associated with experimental strain measurements have resulted in little experimental support for the findings of that theoretical study. This paper reports on strain measurements obtained using optical fiber strain sensors installed along the inside surface of the repaired pipe and the outside of the liner where it is exposed at a perforation in the pipe wall. In addition to outlining the techniques used to obtain those measurements, the strain values are compared to theoretical calculations to assess the performance of the simple design model currently in use for selecting liner thickness. The measurements support the use of the current ASTM design rules for pressure pipe liners spanning across small sized perforations (up to 50 mm diameter in a pipe of 155 mm diameter).
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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 | 0.001 |
| 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 | 0.001 |
| 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".