Experimental study on progressive collapse mechanism in braced and tied-back retaining systems of deep excavations
Bibliographic record
Abstract
Collapses of braced or tied-back excavations have occurred frequently. However, the influence of the failure of some retaining structure members on the overall safety performance of a retaining system has not been studied. Model tests of failures of retaining piles, struts or anchors were conducted in this study and the load-transfer mechanisms underlying these conditions were analysed. When failures or large deformations occurred in certain piles, the increasing ratios of the bending moments in adjacent piles were much larger in the braced retaining system than in the cantilever system and more easily triggered progressive failure. When the strut elevation was lower or the excavation depth was greater, the degree of influence and range of pile failures became larger. When certain struts or anchors failed, their loads transferred to a few adjacent struts or anchors, possibly leading to further strut or anchor failure. The influence mechanisms of strut or anchor failure on piles were different from those of pile failure. As the number of failed struts or anchors increases, the bending moments of the piles in the failure zone first decrease and then increase to very high values. Therefore, the progressive failure path extends from struts or anchors to piles and will lead to large-scale collapse.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".