Quantifying progressive failure of micro-anchored fiber optic cable–sand interface via high-resolution distributed strain sensing
Bibliographic record
Abstract
Distributed fiber optic sensing (DFOS) is gaining increasing interest in geotechnical monitoring. By using soil-embedded fiber optic cables, strain profiles as well as deformation patterns of geotechnical infrastructures can be captured. Probing the fiber optic cable–soil interfacial behavior is vital to the advancement of DFOS-based geotechnical monitoring and our understanding of the soil–inclusion interaction mechanism. To this aim, laboratory pullout tests were performed to investigate the progressive failure of the interface between micro-anchored cables and the surrounding sand. High-resolution strain profiles recorded using Brillouin optical time-domain analysis (BOTDA) not only elucidated the influence of anchorage on strain measurements, but also allowed the classical soil–inclusion interaction problem to be studied in detail. Interfacial shear stresses calculated from step-like strain profiles provided clear evidence of the contribution of each micro-anchor to the pullout resistance. The cable–soil contact is a combination of overall bonding and point fixation depending on the level of mobilized interfacial shear stress, and therefore the validity of measured strains is correlated to a three-stage process of interface failure. This study also shows that installing heat-shrink tubes on the fiber optic cable is a rapid, low-cost, effective approach to make an anchored DFOS system for deformation monitoring of earth structures.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".