Framework for Durability-Based Design for Concrete-Steel Bond against Corrosion
Bibliographic record
Abstract
The current understanding of the mechanics of bond resistance at the interface between concrete and plain and deformed steel bars is reviewed briefly along with the influence of corrosion on the phenomenon. Some of the available research on analytical models in both corroded and uncorroded steel bars is also reviewed. The influence of some of the significant parameters influencing the behavior of corroded bars, such as the concrete strength, crack width, extent of rebar corrosion (measured by mass loss), concrete cover thickness, bar diameter, and the loss of rebar lugs is reviewed. In addition, a preliminary framework is presented for design of reinforced concrete for durability against deterioration of bond due to steel rebar corrosion. A framework for design of structural concrete for durability against deterioration of bond at the steel-concrete interface due to corrosion of rebars is proposed. The technical note also stresses the need for more research on the above and other parameters influencing the deterioration of bond due to corrosion, before establishing a reliable design method using a semiprobabilistic approach in the design of structural concrete for other phenomena.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".