Joint kinematics and sealing capacity assessment of ductile iron pipes under abrupt transverse ground movements
Bibliographic record
Abstract
Joint kinematic behaviour, i.e., joint rotation and axial translation, can partially help pipelines to accommodate abrupt ground movements, and cause leaking if joint service limit is exceeded, even without any structural failure. Kinematic behaviour of bell-spigot jointed ductile iron (DI) pipes and its influence on joint sealing capacity under abrupt transverse ground movements are investigated in this study. Firstly, a beam-on-spring finite element analysis on joint kinematics of DI pipes is conducted, in which different fault–pipe crossing positions are implemented. Based on simulated results, a modified joint kinematic solution incorporating pipe deflection and joint shear force under different fault–pipe crossing positions is proposed. Then, a Monte Carlo simulation (MCS)-based reliability assessment procedure for joint sealing capacity is developed. Sensitivity analysis is subsequently conducted to investigate the effects of uncertainties associated with initial axial translation, soil properties, and crossing positions on the joint sealing capacity, and the effects of different deterministic solutions are compared. The proposed method allows engineers to effectively evaluate how the joint sealing capacity of DI pipes changes with consideration of uncertainties when abrupt transverse ground movements are encountered.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".