Application and Evaluation of Non-Destructive Testing Methods for Buried Pipes
Bibliographic record
Abstract
This thesis investigated and evaluated non-destructive condition assessment methods for both cast iron water pipes and large diameter sewer and culvert systems. A state-of-the-art review of Non-destructive Testing (NDT) technologies available for cast iron water pipes and corrugated steel culverts identified the strengths and weaknesses of each technology. Guidelines were developed for selecting NDT technologies for use in industry. An investigation of NDT techniques to help establish the relationship between ground movement and cast iron water pipe breaks was then undertaken. A total of fifteen segments of 150 mm cast iron water pipes were monitored using an acoustic-based pipe condition assessment technique to estimate the remaining wall thickness and presence of leaks. Three of the fifteen segments were then selected for seasonal ground deformation monitoring using both a Total Station and LiDAR system. Results showed that both technologies could be used to monitor differential ground movement. Ground movements of 20-25 mm were observed for the pavement above a location with a confirmed leak while minimal movement was seen on the street without leaks. Finally, an investigation of NDT techniques for erosion void detection was conducted. A testbed consisting of two buried pipes (a reinforced concrete pipe with 1.2 m internal diameter and a corrugated steel horizontal ellipse culvert with a span of 1.6 m and a height of 1.35 m) was prepared in the West Pit of the Geoengineering Laboratory at Queen’s University, featuring prefabricated erosion voids of known dimensions adjacent to the pipes. Tests were conducted using handheld and conventional Backscatter Computed Tomography (BCT), Pipe Penetrating Radar (PPR), Ground Penetrating Radar (GPR), and Infrared Thermography (IRT) to evaluate the detection and characterization accuracy of these technologies. Results showed that both the BCT technologies detected all three voids behind the corrugated steel pipe wall, while PPR and GPR found one of the three voids next to the reinforced concrete pipe. Results also showed that cooling down thermography was success in detecting three voids behind the corrugated steel pipe wall and their approximate locations as well as the longitudinal and circumferential dimensions of void contact with the pipe.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".