Using sensitivity analysis to identify the critical factors that lower the factor of safety of large-diameter cast iron mains
Why this work is in the frame
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Bibliographic record
Abstract
The aim of the paper was to identify the pipe and soil parameters that reduce the factor of safety against failure of large-diameter cast iron (CI) water mains. A mechanics model was developed and used to examine the sensitivity of 29 parameters on pipe factor of safety. The expected value and range of the 29 parameters were based on representative values taken from the research literature. Unsurprisingly, results showed that increasing wall thickness for all pipe diameters increased the factor of safety. Increasing the value of the final pit depth rate, the pitting depth scaling constant, and the corrosion rate inhibition factor lowered the pipe factor of safety. For pipes smaller than 762 mm, increasing diameter produced a higher incremental increase in strength than in loading and increased the factor of safety. Future work should focus on better establishing the relationship between the pipe and soil properties and environmental factors.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 it