Sustainable FRP-Confined Symmetric Concrete Structures: An Application Experimental and Numerical Validation Process for Reference Data
Bibliographic record
Abstract
The use of fiber-reinforced polymer (FRP) jackets as external confinement is becoming popular, especially in seismic areas, because of its ability to enhance the strength and ductility of reinforced concrete to perform as a sustainable symmetric structural member. Therefore, various researchers have worked out for the prediction of strength and strain models of FRP-confined concrete. This study presents the improved strain models for the FRP confined cylindrical concrete members. Different previously proposed models of axial strain of FRP-confined concrete were evaluated based on a large database of 678 specimens from previous experiments and an improved model was proposed using the general regression analysis technique. Furthermore, the proposed model was validated using the previous experimental work of FRP-wrapped concrete cylinders and their finite elements analysis (FEA) using the ABAQUS software. The accuracy of the proposed strain model was quite satisfactory in comparison with the previous experimental and FEA results of the present study. Moreover, the proposed empirical strain model was used for the parametric study to investigate the effect of different geometric and material parameters such as the compressive strength of unconfined concrete, diameter of the cylinder, elastic modulus and thickness of the FRP layers, on the axial strain of FRP-wrapped cylinders. A close agreement among the proposed strain models and experimental outputs was observed. This study will help in understanding the behavior of sustainable FRP-confined symmetric concrete members.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".