Effects of the construction sequence of twin tunnels at different depths on an existing pile
Bibliographic record
Abstract
Any tunnelling process inevitably induces changes in stress in the ground and may adversely affect nearby pile foundations. The interaction between tunnelling and an existing pile has been investigated by researchers and a certain amount of fundamental understanding has been gained. However, the effects of different tunnel excavation sequences on an adjacent pile remain to be understood. In this paper, a series of three-dimensional centrifuge model tests and numerical back-analyses were carried out to investigate the effects of construction sequence of twin tunnels on an existing pile in dry sand. Two tunnelling sequences were investigated: (i) a sequence involving tunnelling near the pile toe followed by tunnelling near the mid-depth of the pile shaft (i.e., test TS); (ii) sequence involving tunnelling near the mid-depth of the pile shaft followed by tunnelling near the pile toe (i.e., test ST). The measured cumulative pile settlement was about 33% larger for tunnelling sequence ST than for tunnelling sequence TS. Due to different tunnelling sequences, the apparent losses of pile capacity were 40% and 29% for sequences ST and TS, respectively. Although the computed reductions in normal stress acting on the pile induced by twin tunnelling were almost the same in tests TS and ST, tunnelling near the pile toe induced a larger decrease in the end-bearing and shaft resistances at the lower part of the pile in test ST than in test TS. In contrast to the measured pile head settlements, different tunnelling sequences had a limited effect on measured ground surface settlements and additional bending moments in the pile.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".