Experimental study of the progressive collapse mechanism of excavations retained by cantilever piles
Bibliographic record
Abstract
An increasing number of catastrophic progressive collapses of deep excavations have occurred throughout the world. However, the research on progressive collapse mechanisms is limited. In this paper, two categories of model tests were conducted to investigate the mechanism of partial collapse (sudden failures of certain retaining piles) and progressive collapse. The model test results show that partial collapse can cause a sudden increase in the bending moments of adjacent piles via an arching effect. The load-transfer coefficients are defined to be equal to the peak increase ratios of the maximum bending moments in adjacent piles (peak moments caused by collapse over the values before the collapse). When the maximum load-transfer coefficient is larger than the bearing capacity safety factor of the piles, the partial failure will lead to progressive collapse. The influential factors of the progressive collapse mechanism, such as the partial collapse extent, excavation depth, and capping beam, were also investigated. During progressive collapse, the previous failed pile could cause new stress arching; simultaneously, the soil behind certain nearest intact piles could become loosened and destroy the arch springing of the stress arching, causing the progressive collapse to cease gradually.
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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".