Predicting the influence of shear and lap splices on the seismic response of reinforced concrete bridges
Bibliographic record
Abstract
Many older reinforced concrete bridge columns contain poorly detailed transverse reinforcement and have lap splices in critical plastic hinge regions. These columns can fail in a brittle manner due to shear or bond distress when subjected to seismic loading. A large proportion of the bridges in Canada were built prior to the implementation of modern seismic design codes and are potentially in need of repair or retrofit. To evaluate the performance of these existing bridges and perform seismic risk assessments, a thorough understanding of the reversed-cyclic loading response of poorly detailed lap-spliced columns is required.An experimental program was conducted in which the responses of eight shear-critical rectangular columns tested under monotonic and reversed-cyclic loading were determined and compared. The main variable in these tests was the amount of transverse reinforcement. Response predictions were made for columns from this experimental program, as well as other circular, octagonal, and rectangular shear-critical and bond-critical columns tested under reversed-cyclic loading. Prediction methods included those based on current seismic guidelines. The beneficial contribution of an inclined compressive strut to shear strength was investigated. Suggestions were made for the improvement of design procedures. Nonlinear finite-element analysis was demonstrated to be capable of capturing the complex interaction between axial load, flexure, and shear, as well as the effects of confinement, bar buckling, cover spalling, opening and closing of cracks, and bond between concrete and steel reinforcement.To perform dynamic time history analyses, it is necessary to model the hysteretic behaviour of individual reinforced concrete bridge columns. An approach was presented for matching computationally efficient frame-based finite element hysteretic responses to accurate but computationally intensive two-dimensional nonlinear finite element analysis predictions to perform nonlinear dynamic time history analyses. Incremental dynamic analyses (IDA) were performed on a series of irregular archetype bridges located in Vancouver, Canada with poorly detailed lap-spliced columns, poorly detailed columns without lap splices, and ductile columns. The IDA results were then used to determine the probabilities of collapse for the different archetype bridges, enabling comparisons of the seismic risk
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".