Finite element study on seismic performance of reinforced concrete bridge pier with kinked rebars
Bibliographic record
Abstract
This paper presents a new design for cost-effective and easily constructed kinked rebar reinforced concrete bridge piers to improve their deformation capacity and energy dissipation during earthquakes, addressing issues of uneven concrete damage and challenging post-disaster repairs. Based on uniaxial tensile tests, mechanical properties of kinked rebars are determined, focusing on steel bar diameter ( d) and kinked ratio αkb. In ABAQUS simulations, three pier models are created: a regular reinforced concrete bridge pier and two reinforced concrete bridge piers with kinked rebars, varying the kink ratio. Under 0.1 axial compression ratio, these piers undergo low-cycle reciprocating loading; their seismic performance is assessed through hysteresis curves, skeleton curves, residual displacements, and energy dissipation capacities. Results demonstrate that kinked rebars effectively concentrate concrete damage and enhance ductility and energy absorption. Piers exhibit increased post-yield stiffness and gradual capacity growth in later loading stages, providing robustness throughout the loading process. This validates the use of kinked steel bars in bridge piers.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".