Kinematic responses of lead-caulked joints for cast iron pipelines subjected to strike-slip faulting
Bibliographic record
Abstract
Buried cast iron pipelines are susceptible to damage at joints under fault movements. In this paper, a new three-dimensional soil-pipe continuum model for segmented pipelines undergoing fault rupture is introduced, in which both the nonlinear behavior of lead-caulked joints and post-peak softening behavior of dense sand are properly characterized. The rationality of the developed numerical model is validated against experimental results reported in the literature. Parametric analyses indicate that ignoring the strain softening behavior of soil would underestimate the maximum joint rotations, and the parameters of fault-pipe intersection angle, cast iron-lead adhesion, and burial depth play a notable role on the magnitude of joint kinematics. Numerical fault rupture analyses are then conducted for cast iron pipelines with nominal diameters ranging from 900 to 1500 mm. Based on the numerical results, predictive solutions are developed for estimating the maximum axial translations and joint rotations under fault movements. The residuals of the proposed solutions are generally unbiased. The proposed solutions can be used to evaluate the maximum joint kinematics in terms of axial translations and joint rotations for large-diameter cast iron pipelines with lead-caulked joints undergoing strike-slip fault ruptures.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".