Field investigation on long-term deformation characteristics of long-and-narrow basements in soft clays
Bibliographic record
Abstract
Two long-and-narrow station basements, constructed using zoned and staged ramp excavation sequences, are extensively monitored to study the long-term ground and structure deformations. During the main excavation stages (i.e., soil removal), the lateral wall movements increase rapidly with the excavation depth. However, the rate of increase in the lateral wall movements decreases dramatically during casting of concrete slabs. Meanwhile, the post-excavation induced ground surface settlements increase by up to 29.7%. The long-term wall deflections and soil settlements are significant, but these long-term deformations are suppressed after casting the top concrete slabs. Although the bottom-up construction technique is used for the basement excavation, the measured ground surface settlements are substantially smaller than those associated with the top-down construction technique. This is primarily attributed to the adoption of zoned and staged ramp excavation sequences, which effectively control ground settlements. Unlike wall deflections and ground surface settlements, a decrease is observed in the column and wall heaves during post-excavation. The measured heaves of the interior columns and retaining walls are 0.08%–0.15% H (excavation depth) and 0.04%–0.11% H, respectively. A series of deformation envelopes are proposed to estimate ground and structural deformations due to the long-and-narrow basement excavations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".