Modelling the impact of deterioration on the long-term performance of Dublin Tunnel
Bibliographic record
Abstract
The influence of tunnel deteriorations like hydraulic and mechanical deterioration on its long-term performance has received extensive attention recently. Most studies considered deteriorations by manually varying the magnitude of parameters like permeability and stiffness, often neglecting their time-dependent variation process (individual/coupled). This paper addresses this gap by investigating the impact of time-dependent hydraulic and mechanical deteriorations on the long-term behaviour of the aging Dublin Port Tunnel (DPT). Relevant geotechnical and mechanical properties of ground layers and concrete lining were firstly characterised and determined. A modified analytical relative ground-lining permeability model and calculated deteriorated lining permeability for DPT were presented, with steps and procedures generalised. The deteriorated permeability of DPT was incorporated into the hydraulic deterioration model thereafter, together with tunnel mechanical deterioration, offering a more holistic and realistic prediction of DPT’s deterioration-induced long-term performance than previously available. Numerical results, compared against field measurements, showed that (1) assuming constant tunnel permeability during its lifetime fails to accurately capture time-dependent liner deformation, and hydraulic deterioration has been identified as the dominant factor inducing an approaching squatting deformation mode, which can be attributed to twin tunnel interaction effect; (2) continuous mechanical deterioration leads to a linear growth in both vertical and horizontal convergence over time, with vertical convergence being more pronounced, indicating a squatting contraction deformation mode that could be associated with reduced ability to support ground pressure and external loads; and (3) the comparison quantitatively evaluates the impact of individual and coupled hydro-mechanical deterioration on DPT’s long-term behaviour and the agreement between field data and numerical results confirms that coupled lining deterioration is the root cause behind the monitored lining deformation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".