When to Intervene? Using Rates of Failure to Determine the Time to Shut Down Your PCCP Line
Bibliographic record
Abstract
Performing structural evaluations of aged civil engineering structures has traditionally been performed on a static basis. The condition of the structure is tested either destructively or non-destructively to determine its present day condition and the strength is evaluated to determine if the structure can safely withstand anticipated loads. One of the problems with managing structures in this fashion is that structures do not behave in a static fashion. This is especially true for large diameter PCCP (Prestressed concrete cylinder pipeline) mains that have wire break damage resulting from corrosion or cracking from hydrogen embrittlement. Given the variability in rate of deterioration in a PCCP main the risk associated with a pipe section changes with time. Pipe sections where risk is deemed to be acceptable may change to a point where risk is not acceptable in a relatively short duration of time. This phenomenon has been observed on multiple pipe sections. This paper examines the rate of deterioration of PCCP mains to evaluate how risk changes or does not change with time and how this information can be used to determine when a pipeline should be repaired.
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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 | 0.003 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".