Behaviour of H-piles supporting an integral abutment bridge
Bibliographic record
Abstract
Integral abutment bridges accommodate thermal superstructure movements through flexible foundations rather than expansion joints. While these structures are a common alternative to conventional design, the literature on measured field stresses in piles supporting integral abutments appears to be quite limited. Therefore, field data from strain gauges installed on the abutment foundation piles of a 76 m long; two-span integral abutment bridge are the focus of this paper. Axial load, weak- and strong-axis bending moments of the foundation piles, as well as abutment movement and backfill response, are presented and discussed. Results indicate that the abutment foundation piles are bending in double curvature about the weak axis, as a result of thermal bridge movements, and bending also about the strong axis due to tilting of the abutments. A simple subgrade modulus approach is used to show its applicability in predicting behaviour under lateral loading. In the past, much emphasis has been placed on the lateral displacements of piles and less on variations of axial load. In this paper, a new hypothesis, which offers insight into the mechanisms behind the observed thermal variations in axial load, is proposed and assessed. The data from the field monitoring are also compared with the limited data reported in the literature.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".