A New Stress Monitoring Method for Mechanical State of Buried Steel Pipelines under Geological Hazards
Bibliographic record
Abstract
Long-distance pipelines are threatened by a variety of natural geological hazards. A stress monitoring system driven by the strain-stress solution algorithm was proposed; it can achieve real-time maximum axial stress measurement by installing vibrating wire gauges (VWGs) on the surface of the pipe. To verify the effectiveness of the algorithm, a large-scale pipe mechanical loading experiment combined with a finite element model (FEM) was conducted. The results show that VWGs were reliable with a relative error of 1.19%∼7.98% compared with resistance strain gauges (SGs). The FEM was also reliable with a maximum relative error of 4.04% compared with theoretical analysis. When the reasonable combination modes of VWGs were chosen utilizing the least square method, the error of the pipe stress detection algorithm could be controlled within the range of −13.33∼16.66%. This pipeline stress monitoring technology can meet the requirement of 24-hour dynamic monitoring of the underground pipeline’s mechanical state, realizing the early warning of geohazards.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".