Finite-element modelling of RC beams with carbon FRP strengthened web openings
Bibliographic record
Abstract
Web openings are commonly used in reinforced concrete (RC) beams to accommodate pipes, ducts, and utilities. The expected reduction in strength can be compensated by locally strengthening the beam opening with carbon fibre-reinforced polymer (CFRP). In this paper, a robust non-linear finite-element model (FEM) is developed to simulate the behavior of RC beams with/without openings. The model can simulate the strengthening of the beam opening with CFRP sheets. The developed FEM is validated using seven simply supported RC beams that were previously tested under monotonic two concentrated loads. The crack pattern and load-deflection relationship, from the FEM, were compared to those obtained from the experiments. The developed FEM was utilised to conduct a parametric study on 32 beams to investigate the behavior of RC beams with CFRP strengthened openings. The parametric study showed that the opening width did not significantly affect the load at failure. However, both the opening depth and distance from support had a clear effect on the failure load. Increasing the stirrups diameter from 8 to 10 mm increased the shear capacity of RC beams by 3–16%. The failure loads obtained from the proposed FEM were compared to those obtained from international design codes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".