Development of Testing Procedures to Study the Impact of Erosion Voids on Buried Pipes
Bibliographic record
Abstract
ABSTRACT The recently commissioned Deep Burial Simulator facility at Queen’s University allows for a water table to be raised and lowered within a test pit. The 3 m wide, 5 m long, and 4.6 m deep pit uses standpipes to supply water to the system and to control the elevation of the water table. In the current work, procedures are developed to create erosion voids adjacent to two different buried pipe specimens that initially have intact soil support conditions—tests to investigate how the volumes and shapes of those erosion voids develop. The first specimen was a two-segment reinforced concrete pipe sample with a nominal inner diameter of 825 mm and the second was a 900 mm diameter circular corrugated steel pipe. The erosion voids were created from water and soil infiltration into each of the structures through simulated defects: a leaking joint between the two pipe segments in the reinforced concrete pipe test and areas of complete wall loss along the haunch positions in the corrugated steel pipe test. The erosion voids were created from multiple infiltration events and the final geometry of all voids was captured by injecting polyurethane expanding foam into the void space before the structure was exhumed. An erosion void with an approximate total volume of 0.02 m3 was created beside the reinforced concrete pipe specimen and multiple larger erosion voids with volumes around 0.2 m3 were created beside the corrugated steel pipe specimen.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".