A Simplified Approach to Model Deck Resistance and Back Rotation of Abutments due to Lateral Spreading
Bibliographic record
Abstract
Past earthquakes have indicated that bridge superstructure tends to restrain the movements at the top of the abutments (or piers) while lateral spreading tends to push the piles towards the direction of soil movement. This leads to the back-rotation of abutment and piles, which is different to the pile response estimated using traditional fixed or free pile head conditions. Although, the superstructure (deck) resistance is considered in simplified methods such as the Caltrans (2012) approach, the analysis cannot mimic the pile/abutment back-rotation besides several other limitations related to the approach used to account for the deck resistance. This paper introduces a modified approach to overcome these limitations. The revised approach is based on the same basic framework as in Caltrans (2012) but modifications are introduced to properly account for the deck resistance. A user-defined “deck spring” is introduced into the pushover analysis to represent the superstructure resistance instead of applying it to the slope stability model. The differences between these two approaches are highlighted using an example.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".