Technologies to Assess and Manage of Providence Water's 102" PCCP Aqueduct
Bibliographic record
Abstract
In 1996, Providence Water experienced a catastrophic failure of its 102" PCCP aqueduct pipeline. Subsequently, the main underwent an extensive assessment and repair and was returned to service with plans that the main would be re-inspected in approximately 5 years. In 2005, Providence Water re-inspected the aqueduct. Since the previous inspection, the state-of-the-art for assessing PCCP mains has progressed significantly. Non-destructive technologies, available for assessing and monitoring PCCP pipe have made significant strides. Providence Water implemented state-of-the-art inspection procedures to obtain the best possible assessment of the aqueduct. Following the assessment of 4.5 miles of the aqueduct, Providence Water opted to install a fiber optic acoustic monitoring sensor to continuously monitor the condition of the aqueduct and identify pipe sections experiencing ongoing wire break activity. Providence Water utilized the following technologies during the most recent 2005/2006 inspection/monitoring program: 1) Electromagnetic Inspection- to detect wire breaks in the prestressing wire, 2) Visual and Sounding Inspection- to inspect for cracks or delaminations, 3) Resistivity Testing- to detemine the actual number of wire breaks on excavated pipe sections (vs. the estimated number based on the electromagnetic inspection), and 4) Acoustic Monitoring- to detect future wire breaks as they occur in the operational aqueduct. Following the initial inspection, one pipe section was found to be in a state of incipient failure. As a result, several nearby pipe sections were strengthened and a decision was made to install the acoustic monitoring system. This paper focuses on the assessment and monitoring technologies used during this project and describes the capabilities and limitations of these technologies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".