Refined deformation limit states for circular reinforced concrete bridge columns
Bibliographic record
Abstract
Abstract One hurdle against the widespread implementation of the performance‐based design (PBD) for bridges is the lack of consensus among practitioners, researchers, and code committees on engineering demand parameter (EDP) limits defining the onset of various types of damage and their variability. This study seeks to bring consistency to the PBD methodology by establishing refined EDP limits at concrete cover spalling and bar buckling for circular reinforced concrete bridge columns. To this end, a database consisting of 118 previously tested flexure‐dominant bridge columns was formulated and analyzed. The EDP limit considered at the member level was drift ratio, whereas, at the sectional level, the EDP limits considered were material strain and curvature ductility. State‐of‐the‐art symbolic regression was adopted to fit the resulting data to mathematical expressions. At the member level, predicted drift ratio limits at the two damage states obtained with the proposed expressions were associated with lower root‐mean‐square error (RMSE) than those obtained from other similar expressions in the literature. At the sectional level, drift ratios at concrete cover spalling were adequately predicted with compressive strain limits in concrete ranging from 0.004 to 0.007 and a curvature ductility limit of 6.3. More accurate predictions of drift ratios at bar buckling were attained with variable sectional EDP limits, particularly for columns subjected to relatively high axial load. Two expressions predicting the tensile strain limit in the rebar and curvature ductility limit at bar buckling were proposed. The ratios of the measured drift ratio at bar buckling to the drift ratio predicted based on the proposed variable tensile strain limit had a mean of 0.99 and a coefficient of variation (COV) of 33%. Corresponding ratios based on the proposed variable curvature ductility limit had a mean of 1.02 and a COV of 31%. Fragility functions relating the likelihood of concrete cover spalling and bar buckling to the considered EDP limits were also developed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".