Stability of a single tunnel in cohesive–frictional soil subjected to surcharge loading
Bibliographic record
Abstract
This paper focuses mainly on the stability of a square tunnel in cohesive–frictional soils subjected to surcharge loading. Large-size noncircular tunnels are quickly becoming a widespread building technology by virtue of the development of advanced tunneling machines. The stability of square tunnels in cohesive–frictional soils subjected to surcharge loading has been investigated theoretically and numerically, assuming plane strain conditions. Despite the importance of this problem, previous research on the subject is very limited. At present, no generally accepted design or analysis method is available to evaluate the stability of tunnels or openings in cohesive–frictional soils. In this study, a continuous loading is applied to the ground surface, and both smooth and rough interface conditions between the loading and soil are modelled. For a series of tunnel geometries and material properties, rigorous lower and upper bound solutions for the ultimate surcharge loading of the considered soil mass are obtained by applying recently developed numerical limit analysis techniques. The results obtained are presented in the form of dimensionless stability charts for practical convenience, with the actual surcharge loads being closely bracketed from above and below. As a handy practical means, upper bound rigid-block mechanisms for square tunnels have also been developed, and the obtained values of collapse loads were compared with the results from numerical limit analysis to verify the accuracy of both approaches. Finally, an expression that approximates the ultimate surcharge load of cohesive–frictional soils with the inclusion of shallow square tunnels has been devised for use by practicing engineers.
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 | 0.001 | 0.000 |
| 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".