Numerical model verification and calibration of George Massey Tunnel using centrifuge models
Bibliographic record
Abstract
Dynamic soilstructure interaction analyses were carried out for the seismic retrofit design of the immersed George Massey Tunnel, both to predict and study soil liquefaction and related tunnel movements and to design ground improvement. The proposed ground improvement included ground densification using vibroreplacement stone columns along both sides of the tunnel and seismic gravel drains adjacent to the outer edge of the densified zones. The den sification and drainage were proposed to locally mitigate soil liquefaction and reduce displacements of the tunnel to tolerable levels. Centrifuge model tests with base shaking to simulate earthquake effects were conducted to verify and calibrate the numerical models. This included simulating the effects of ground densification and drainage on reme diating tunnel movements. This paper presents the principal results from the dynamic analyses, the centrifuge model design and testing procedure, the class A predictions of the centrifuge tests, and discussions of the centrifuge test results and numerical model calibrations.Key words: immersed tunnel, seismic retrofit, soil liquefaction, design verification, centrifuge testing, numerical calibration.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| 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".