Predict the pipeline buckling using the broadening factor of Brillouin spectrum width
Bibliographic record
Abstract
We monitored the distributed strain during the pipeline buckling process using distributed Brillouin sensor, which allows us to predict the buckling or crack location according to the sequence and location of the deformation for the first time using the broadening factor of Brillouin spectrum width. Two pipelines were designed and instrumented with polymer and carbon/polyimide coated fibers, and then the pipelines were subjected to internal pressure, axial tensile force and bending moment. We show that 1) the localized buckling occurred at the top, median and bottom of the pipeline, where the maximum broaden factors were obtained; 2) the deformation sequence can be measured using the nonlinearity of the broadening factor, 3) a high strength carbon/polyimide-coated fiber can detect higher stress accurately than standard telecom fibers. Our results strengthen the distributed Brillouin fiber sensor position as a nervous system to identify the potential problem in early stage for structural health monitoring.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".