Effect of depth on seismic response of circular tunnels
Bibliographic record
Abstract
Tunnels in seismically active areas are vulnerable to adverse effects of earthquake loading. Recent seismic events have shown that there is a need to validate current design methods to better understand the deformation mechanisms associated with the dynamic behaviour of tunnels. The research described in this paper consists of physical and numerical modelling of circular tunnels with dynamic centrifuge experiments and complementary finite element simulations. The aim is to develop an understanding of the effects of tunnel depth on the seismic behaviour of tunnels. Tunnels with different depth-to-diameter ratios were tested in dry, loose silica sand. Accelerations around the tunnel and earth pressures on the lining were measured. A high-speed digital camera was used to record soil and lining deformations. Particle image velocimetry analyses were carried out on the recorded images to measure the deformations. Complementary dynamic finite element simulations were also conducted with a code capable of managing contact simulations at the soil–lining interface. Measurement of centrifuge experiments and finite element analyses show that the tunnel shifts from a static equilibrium to a dynamic equilibrium state as soon as the earthquake starts. The nature of the dynamic equilibrium, however, is difficult to predict using conventional analysis methods.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".