Predicting the Influence of Shear on the Seismic Response of Bridge Columns
Bibliographic record
Abstract
In the seismic design and evaluation of bridges, a method is required for determining the shear strength of reinforced concrete columns to avoid brittle shear failures. In addition, detailed design and evaluation often require predictions of the complete hysteretic response of bridge columns to accurately model the nonlinear dynamic response of the bridge. Predictions of the shear strength of columns using the provisions of the AASHTO Specifications are compared with the reversed-cyclic loading test results of shear-critical columns. It is found that the Simplified Procedure results in very conservative predictions of the seismic shear strength. The General Procedure provides conservative and more accurate predictions of the seismic shear strength. It is suggested that the AASHTO reduction factor on the concrete contribution resisting shear for low compressive axial load levels be removed. Nonlinear finite element analysis predictions are made for a selection of rectangular and circular columns tested in reversed-cyclic loading and are compared with the experimental results. The ability of nonlinear finite element analysis to predict the reversed-cyclic loading responses of columns with a wide range of variables and having different failure modes is demonstrated.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".