Five More Years of Data: Predicting the Performance of Prestressed Concrete Cylinder Pipes; An Updated Case Study
Bibliographic record
Abstract
In 2017, the Lake Huron Primary Water Supply System (LHPWSS) undertook a study to examine and predict the remaining useful life of its 30 mi (48-in.) PCCP pipeline. This pipeline was previously assessed using electromagnetic technology to determine broken wire wraps as well as continuously monitored for breakage with an acoustic fiber optic (AFO) cable along the length of the pipeline. The original study in 2017 focused on utilizing this inspection and monitoring data to develop a predictive model to forecast when each of the nearly 10,000 pipes will reach their respective “limit state” based on structural analysis of the pipeline. The inspection and monitoring data acquired from the pipeline was used as a case study to calculate deterioration rates across the length of the pipeline and provide the Water Supply System with information regarding when individual pipes may reach their failure limits so that long-term management strategies could be evaluated. Since the initial modelling in 2017, five more years of data have been collected along this pipeline from the AFO system. Additionally, the LHPWSS has collected high-resolution transient pressure data from points along the pipeline to determine the potential effects that the pressure changes may have on (1) pipeline damage; and (2) changes in pumping configurations. This paper is a comparative study of the initial analysis and the updated study based on the new data collected. In particular, the new analysis highlights how sections of the pipeline which resulted in high probability of failure in the 2017 study reacted to operational changes that modified the pressures in these areas in the intervening five years. The LHPWSS’ data shows that its transmission mains (like others in North America) have very low rates of damage. Regardless of any stated design life, these assets, like the Golden Gate Bridge, are not assets to be replaced after a set number of years but can be maintained virtually in perpetuity. To this end, in the near-term, the updated predictive modelling informs the urgency associated with an individual pipe segment that is showing signs of deterioration such that the LHPWSS can plan how quickly it needs to intervene and replace a pipe. In the long term, LHPWSS uses the predictive modelling information to forecast the number of pipe segments that are expected to be replaced over the capital planning period and incorporate this information into the asset management planning programme and budget development process.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".