Bibliographic record
Abstract
Piles are largely back-rotated in sliding slope or subjected to lateral spreading. This paper reveals for the first time that response of these piles (e.g., displacement, rotation, bending moment, and shear force) is amplified against forward rotating piles. In particular, magnification is detrimental, once normalized rotational stiffness (NRS) of the piles is around a singularity value (i.e., normalized singularity stiffness, NSS). New expressions are developed to gain the NSS value, the magnification degree, and the sliding depth to incur the singularity. The NRS is assessed using 1g model tests. The solutions are adopted to capture the response of the model piles, to detect new failure mechanism of Showa Bridge, and to check the safety of Christchurch bridges. The main conclusions are as follows: (i) piles are prone to response amplification, when subjected to lateral spreading or in sliding slopes. (ii) The NRS is only slightly affected by soil movement profiles and sliding depths. (iii) Showa Bridge collapsed from displacement amplification of back-rotated piles. Finally, (iv) the roller connections between girder and piers, and an integral abutment and piers are proved to be effective to curb the amplification. The amplified response needs to be assessed in practice to lessen failure of back-rotated piles.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".