Pinpointing Exfiltration in Large Diameter Pressurized Wastewater Pipelines with the Sahara Tethered System
Bibliographic record
Abstract
Building on the success of the Sahara Leak Location system in potable water mains, a new service is now being finalized for use in rising mains and other pressurized wastewater pipelines to pinpoint exfiltration. Failure of wastewater forcemains cause an environmental hazard as well as extreme operational difficulties while the forcemain is being repaired. Previous research has shown that pipes at greatest risk of failure have often been leaking for some time, but unfortunately, to date there has been no technology available to undertake an effective force main inspection in a live operating condition without excavation. As with the water main leak detection system, the intention is for surveys to be carried out with the pipe remaining in service and provide real time information on the exact location of leaks of any size of plastic, fiberglass, iron, concrete, steel, ductile iron, cast iron or clay pipes. It has become apparent that water utilities would prefer any device put inside their live pipelines to be tethered so that the device can be controlled and removed. This preference is echoed with wastewater system operators who realize the serious potential problems associated with lost equipment in an operating pressurized system. This paper discusses some of the important operational issues to consider when using an intrusive tethered survey tool in wastewater pipelines and some of the challenges overcome during the development and adaptation of the Sahara system. Field trials conducted by WRc that have shown that the Sahara leak location system can be successfully deployed and operated in wastewater piping systems are presented.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".