Modeling of Shear-Critical Reinforced Concrete Structures Repaired with Fiber-Reinforced Polymer Composites
Bibliographic record
Abstract
This paper describes a study in which finite-element (FE) analysis procedures were used to predict the behavior of a reinforced concrete (RC) frame shear strengthened with fiber-reinforced polymer (FRP) composites. Details are presented of the numerical techniques used to represent the RC frame, the FRP, and the bond properties between the FRP and the concrete. The FE analysis is performed using a two-dimensional nonlinear FE analysis program based on the disturbed stress field model. To augment verification studies undertaken with beam specimens previously tested, a large-scale RC frame with one-span and two-story height was constructed and tested under lateral load conditions. The frame was first heavily damaged in shear, repaired with FRP wrap, and then subjected to a regime of reversed cyclic loads. A detailed comparison is carried out between analytical and experimental results for the hysteretic response, damage mode, crack pattern, and deformation of the frame. It is concluded that reasonably accurate simulations of the behavior of FRP-repaired shear-critical structures can be achieved through finite-element modeling.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".