Random large-deformation modelling on face stability considering dynamic excavation process during tunnelling through spatially variable soils
Bibliographic record
Abstract
Face stability is one of the key considerations for safe construction during earth pressure shield tunnelling. Both dynamic excavation of cutterhead and spatial variability of soil are widely reported to notably affect face stability. This study therefore proposed a three-dimensional random large-deformation computational framework to explore the combined effect of these two factors on face stability, via the coupled Eulerian–Lagrangian technique and Monte Carlo simulations. The findings demonstrate that incorporating excavation process improves face stability for small opening ratios but diminishes it for large opening ratios. Moreover, the cutterhead excavation process weakens face stability while soil spatial variability will further reduce face stability. This emphasizes the necessity to concurrently account for the effects of cutterhead excavation and soil spatial randomness in the design of chamber pressure. Finally, a factor of safety-based method is proposed for predicting the chamber pressure, which accounts for both effects of cutterhead excavation and soil spatial randomness. The capability and advantages of the implemented method in estimating the chamber pressure are further demonstrated by the simplified sample developed from a real tunnel project.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".