Design and construction of a deep excavation in soft soils adjacent to the Shanghai Metro tunnels
Bibliographic record
Abstract
This paper presents the design and construction of a deep excavation for building foundations in saturated soil. This deep excavation was of particular interest because it was located above and beside the Shanghai Metro tunnels. The twin Shanghai Metro tunnels had to be in full operation during the deep excavation. Potential large deformation of the twin tunnels was one of the main concerns during the design and construction for the deep excavation. The paper discusses in detail the criteria and measures for controlling the soil and tunnel deformation. The measures included cast-in-place concrete diaphragm walls with bracing structural members, pumping consolidation, cementsoil mix pile systems, and rational excavation procedures. A simplified theoretical method was proposed to estimate the increment in undrained shear strength in a soft clay layer due to pumping consolidation. Furthermore, conventional finite element methods were used to predict the soil vertical and horizontal displacements induced by the excavation. Using the design and construction methods discussed in the paper, the settlement and horizontal displacement of the tunnels were successfully controlled within 5.0 mm and 9.0 mm, respectively. The curvature of longitudinal deformation curve of the tunnels was less than 1/15 000. The horizontal displacement of the braced diaphragm walls was less than 0.12% of the total excavation depth. Key words: Metro tunnels, saturated soft soil, deep excavation, design, construction, ground improvement, case studies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".