Nonlinear finite element modeling of the impact of reinforcement corrosion on bridge piers under concentric loads
Bibliographic record
Abstract
Abstract Corrosion of reinforcing steel in reinforced concrete (RC) infrastructure is one of the most detrimental deterioration mechanisms, affecting both safety and serviceability. In the present study, a comprehensive analysis methodology of corrosion damage is adopted. The detrimental effects of corrosion‐induced degradation of material properties on the ultimate capacity of an existing aging RC bridge pier under concentric loading are investigated. A three‐dimensional nonlinear finite element analysis using the commercially available finite element program DIANA is used. The main corrosion‐induced deteriorating factors considered in the present study are: concrete strength degradation within the cover and part of the confined concrete core due to corrosion‐induced cracking, degradation of confinement effects, steel area reduction due to uniform corrosion (in both longitudinal and tie reinforcement), steel ductility degradation due to pitting corrosion, buckling of compressive steel bars due to cross‐section reduction and confinement degradation, and bond strength degradation between steel and concrete induced by concrete cracking/spalling. The methodology is evaluated by comparing the numerical results to those of corroded column tests 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".