Field Trial: Inspection of Cement Mortar-Lined Ductile Iron Pipe
Bibliographic record
Abstract
The Region of Peel (Region) has implemented a replacement program for its ductile iron (DI) pipe 300 mm and smaller due to the high number of failures experienced with this type of pipe. As part of the replacement program, a section of the distribution system was scheduled to be abandoned in Caledon, Ontario, during the spring of 2013. The abandoned main was made of 300 mm cement mortar-lined DI pipe, Class 52. Prior to abandoning the main the Region of Peel chose to conduct field trials on a 150 m section of the water main using multiple inspection platforms and technologies being developed by Pure Technologies (Pure). The first field inspection was completed while the pipeline remained in service using the Sahara II platform, which simultaneously deploys closed-circuit television (CCTV), acoustic leak detection, and acoustic pipe wall assessment. A second inspection was conducted, after the line was taken out of service, utilizing a magnetic flux leakage (MFL) tool capable of penetrating a mortar lining. Overall, the inspections determined that the line was in great shape with only minor isolated areas of wall loss. Individual pipes identified to have defects were removed from the ground and taken to the shop for validation testing. Collaboration between pipeline owners and technology suppliers to conduct field trials is an important step in developing new technologies. Lessons learned from performing the field trial will be discussed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".