Field performance of water mains buried in expansive soil
Bibliographic record
Abstract
Water mains buried in expansive soils are often subjected to severe distress subsequent to installation. As the soils go through wet and dry periods, the soils swell and shrink. Water mains buried in the soils move with the soils. Excessive stresses may be induced due to uneven movement of the soils along the water mains, impairing the performance of or even breaking the water mains. Field monitoring is an important means to understand the soil behaviour and its interaction with water mains. For this purpose, field instrumentation was successfully installed to monitor the performance of a section of water main placed in an older area of Regina where frequent pipe breakage has been observed in recent years. The instrumentation included sensors to measure pipe wall strains, pipe displacement, in situ soil moisture content, soil pressure and temperature in the soil backfill and native soil around the backfill. The measurements from the sensors during the first 3 months were analyzed and the results are presented in this paper. Preliminary results indicate that the water contents in the trench backfill tended to decrease due to water drainage. The pipe initially bent downward with the mid span portion of the section having very high displacement and bending strain. The results also show that the average in situ longitudinal stress at the mid-point of the pipe section was higher than the stresses at two locations close to the joints of the pipe, probably due to soil friction effect. Some theoretical predictions agree fairly well with or fall within the measurement ranges.
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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) | 0.001 | 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 | 0.000 | 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".