Fibre-optic sensors condition monitoring and modelling of water mains in expansive clays
Bibliographic record
Abstract
The problem of failures of asbestos cement water mains in expansive clay backfills is widely recognized.A high breakage rate has been observed among ageing asbestos cement pipes in the water distribution system of Regina, Canada and has been mainly attributed to the swelling and shrinkage characteristics of the expansive clay found in the city.A field monitoring prograÍìme was undertaken to observe the development of longitudinal and hoop strains in an asbestos cement water main section using ex- pansive clay as the backfill.The development of longitudinal and hoop strains, in re- sponse to changing environmental and operating conditions, was monitored using fi- bre Bragg grating sensors for a period of about two years.The outcome from this field study, complemented by further research, will substantiate our understanding of fail- wes of AC water mains in expansive clay backfills.The study will contribute to the efforts of many cities around the world endeavouring to minimize the failures of their water mains under similar soil conditions.A two dimensional non-linear plane strain f,nite element analysis is conducted to substantiate the development of hoop strains in the AC pipe by subjecting it to observed changes in internal water pressure and tem- perature.It is observed from the study that the AC pipe is subjected to high pressure from the clay backfill during the winter season which results in development of high compressive strains in the pipe.A close correlation between the mean daily tempera- ture and development of compressive longitudinal and hoop strains in the AC pipe is observed.2.2.9 Soll and surface 1oads........... ..
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".