Empirical prediction of horizontal movements induced by tunnelling in fine-grained soils
Bibliographic record
Abstract
For tunnelling in fine-grained soils, available evidence indicates that the focal depth of displacement vectors along the ground surface decreases with the transverse distance from the tunnel centre-line. Based on field and centrifuge observations, this paper presents a new empirical method in which the focal depth is a function of the transverse offset and, possibly, the tunnel volume loss. The comparison with experimental data from centrifuge experiments and case histories confirms the reliability of the proposed method, in terms of both surface horizontal displacements and strains. In particular, the predicted horizontal displacement profiles, both in terms of maximum value and extent, are in better agreement with the available experimental evidence than those obtained using the empirical and analytical methods currently adopted in design. Finally, an operational way to obtain the complete horizontal displacement field at the surface, near-surface, and at depths down to the tunnel crown is suggested and the importance of carrying out field monitoring for surface and subsurface horizontal displacements is highlighted.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".