Bibliographic record
Abstract
Prestressed concrete cylinder pipe (PCCP) is widely used to construct large diameter water mains. These water mains usually have a high importance of failure, and any unexpected service interruptions from a PCCP failure may place a significant burden on the pipe owner. Utilizing the classic risk-based approach that multiplies the consequence of the failure by the probability of failure to generate an overall risk, as part of the PCCP asset management strategy, is governed by the PCCP probability of failure (POF) rather than the PCCP consequence of failure when critical transmission water mains are in question. Therefore, it is paramount to inspect and assess PCCP based on advanced state-of-the-art technologies to estimate the physical condition of the PCCP and use these inspection findings to develop a survivor curve that considers the pipe deterioration level and the pipe POF at each deterioration stage. This paper presents a method of interpreting PCCP composite stiffness measurements, which is an indicator of PCCP deterioration, and estimates the POF at each degradation stage by using the PCCP yield limit criteria. Limit states design as per AWWA C304 (serviceability, damage, and strength) will be assessed based on laminated composite plate theory and plotted on the survivor curve.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".