Pipe-soil interaction during continuous settlement
Bibliographic record
Abstract
[Objective] Settlement is a common geological hazard encountered around buried pipelines. Such hazards have the potential to cause pipeline failure and damage, particularly in severe cases. Hence, studying pipe-soil interactions during continuous settlement is crucial to ensure the safety of buried pipelines facing settlement hazards. [Methods] This study explored the law governing pipe-soil interactions within different stratum settlement ranges and amounts, by conducting a continuous settlement experiment on a buried steel pipeline, using a specifically designed experimental system. The evolution process of pipe-soil interactions in the continuous settlement process was meticulously analyzed through numerical simulation. Furthermore, the numerical simulation results were subjected to a multivariate nonlinear fitting process, taking into account various parameters such as settlement, pipeline characteristics, and soil properties. [Results] As the stratum settlement increased,the steel pipeline and surrounding soil progressed from simultaneous settlement to separate settlement. The pipeline exhibited mechanical response in four stages: increase, unloading, fluctuation, and stabilization. As the stratum settlement range expanded, a greater amount of settlement took place before the pipeline was fully separated from the soil beneath it. With low settlement rates, the pipeline experienced significant increases in both maximum stress and settlement as the settlement rate grew. However, once the settlement rate surpassed 2×10-5 m/s,the maximum stress and settlement of the pipeline remained nearly unchanged, while the corresponding stratum settlement exhibited notable increases. Moreover, the fitting process yielded a maximum Von Mises stress prediction model for buried steel pipelines exposed to continuous settlement, achieving a calculation error dominantly within 10%. [Conclusion] The mechanical response of pipelines exhibits distinct variations across different settlement stages. Furthermore, any alterations in stratum settlement, settlement range, and settlement rate during the settlement process significantly influence the mechanical response of pipelines. In addition, the prediction model for the maximum Von Mises stress in buried steel pipelines exposed to continuous settlement is demonstrated effective. This model serves as a crucial basis for assessing the safety of buried pipelines under continuous settlement-induced disasters.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".