Fuzzy-probabilistic evaluation for the dynamic instability of corroded buried pipes conveying fluids
Bibliographic record
Abstract
This study develops fuzzy-probabilistic models to investigate the dynamic instability (i.e., the first instability point) of corroded buried pipes conveying fluids. The models are developed via a novel hybrid of random fields and fuzzy logic methods to capture both aleatoric uncertainty , stemming from the stochastic nature of pipeline, fluid, and soil parameters, and epistemic uncertainty , arising from corrosion inspection challenges, especially in urban areas. Key features of the models include: (1) applicability to various pipe geometries, fluid types, and soil stiffness distributions ; (2) Pipe Condition Index, on 0–100 scale, updatable from field inspection to reflect corrosion levels; and (3) uncertainty quantifiers including the random field significance level and fuzzy model coefficients . Results showcase the corrosion’s significant influence on dynamic instability. Furthermore, non-uniform soil stiffness distribution, with minimum stiffness at mid-span, increases the susceptibility to dynamic instability compared to the uniform soil case. The developed models achieve a high goodness-of-fit, with R 2 within 0.91–0.96, underscoring their accuracy in predicting the dynamic instability of corroded pipelines conveying fluids.
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 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".