Combined Application of Optical Fibers and CRLD Bolts to Monitor Deformation of a Pit‐in‐Pit Foundation
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Bibliographic record
Abstract
“Pit‐in‐pit” foundations, where the overall pit is divided into inner and outer pits, present a wide range of engineering problems and yet have received little detailed study. Among the many factors that affect the stability of a deep foundation pit, loading and rainfall are the two most important. Therefore, in this study, physical model experiments are carried out in the laboratory based on a pit‐in‐pit foundation that is typical of engineering applications in China, simulating the deformation of the system under different loading and rainfall flow conditions. Optical fibers along with constant resistance and large deformation (CRLD) bolts are adopted to collectively monitor the stress and strain inside the pit‐in‐pit foundation, assisted by fiber Bragg grating (FBG) displacement meters. The results of the monitoring show that the position of the inner pit relative to the outer pit has a strong influence on the stability of the outer pit. The side on which the inner pit is closest to the outer pit wall is the most prone to instability and should thus be reinforced. Comparison and analysis of monitoring results obtained with optical fibers and CRLD bolts allow a potentially dangerous slip surface to be identified, indicating the value of using this type of collective monitoring in deep foundation pits.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it