Bibliographic record
Abstract
The failure of buried reticulation pipes has been reported to peak during winter months in a number of countries, including Canada and the United Kingdom, prompting much research. In Australia, the number of pipe failures has been reported to peak during summer. However, this peak does not occur in a consistent manner, varying in magnitude to such a degree as to be strongly evident in some years and scarcely observable in others. No quantitative explanation of the cause of such variation has, as yet been published. Consequently, little is known about the specific causes of seasonal failures in the Australian context. This thesis investigates the causes of the seasonal variations in the failure of Australian water reticulation pipes. An exploratory statistical analysis of historical data was undertaken and used as the basis to develop the hypothesis that the seasonal variation in pipe failure numbers in Melbourne, Australia occurs as the result of soil shrinkage. A detailed field study was then undertaken on an in-service pipe and its surrounding environment to test this hypothesis. Analysis of the data collected during the field study supported this hypothesis. A model to represent the mechanism by which soil shrinkage results in the development of pipe flexural stress is also presented. This model enables the knowledge gained from the field study to be generalised and applied elsewhere. The model uses a novel constitutive surface to determine soil stiffness and hydric expansion coefficient, and a numerical sub-model to determine the equilibrium state of the pipe-soil system. Validation of the model against data collected during the field study showed good agreement. This thesis has improved the understanding of the causes of the failure of buried water reticulation pipe, specifically focusing on the interrelated factors causing the seasonal variation of buried water reticulation pipe failures. This improved understanding will assist asset managers by enabling them to identify assets at high risk of failure due to environmental and climatic conditions.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".