3D Finite Element Prediction of Ground Movement Induced by Tunnelling Operation in London Clay
Bibliographic record
Abstract
Realistic finite element (FE) modelling of the tunnel construction process has been restricted by the computational effort needed to incorporate the three-dimensional (3D) aspects of the tunnelling operation. Two-dimensional (2D) plane strain models have therefore been widely adopted by practitioners and researchers in their studies of effects of tunnelling. However 2D modelling suffers the drawback whereby a volume loss must be assumed at the outset as the input for the FE model. This paper presents a feasible method of undertaking complex non-linear 3D numerical modelling of the tunnelling operation using Oasys LS-DYNA software, which utilises an explicit time-stepping method to undertake computationally efficient 3D modeling, without any assumptions regarding volume loss, but rather by modelling the excavation sequence and time-dependent gain in lining strength accurately. It is considered that 3D modelling techniques can be applied to different tunnelling methods in different ground conditions, and will provide an efficient means to estimate tunnelling induced settlement and the effects on nearby structures, without recourse to empirical estimates of volume loss.
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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 | 0.000 | 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 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".