Rethinking tunnel-soil relative stiffness: insights from interactions between tunnels and strata subjected to ground surcharge
Bibliographic record
Abstract
The stiffness difference between tunnels and surrounding strata can lead to relative deformations when subjected to factors such as ground surcharge, significantly influencing the earth pressure on tunnel linings. To address this, the concept of tunnel-soil relative stiffness has been introduced to evaluate these pressures. Existing methods, however, often treat tunnels and surrounding strata as independent entities, thus overlooking their complex interactions. Drawing insights from a recorded experiment, this paper redefines tunnel-soil relative stiffness, now conceptualized as the ratio of natural ground deformation to tunnel deformation subsequent to their interactions. Based on this definition, an analytical formula is derived to calculate the defined relative stiffness. A numerical case study is subsequently conducted to verify and evaluate the effectiveness of the proposed methods. It is found that traditional methods lead to a notable underestimation of tunnel-soil relative stiffness and consequently, the earth pressures on the tunnel linings; in contrast, the proposed method exhibits relatively better accuracy. The intrinsic physical reasons for the enhanced accuracy of the proposed method are discussed. Finally, leveraging the proposed method, insights on enhancing the load-bearing performance of tunnel linings in soft soils are presented, which may provide a valuable reference for the design and maintenance of tunnel linings in soft soil regions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".