Proposed prediction models for shear strength of fiber reinforced polymer reinforced concrete deep members without stirrups
Why this work is in the frame
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Bibliographic record
Abstract
Arch action in deep reinforced concrete (RC) members has a beneficial effect on shear capacity. The Strut-and-Tie Method (STM) is one of the proposed methods for the design of steel reinforced deep beams (DBs). However, some iterations may require to obtain the optimum solution. This paper investigates the shear capacity of fiber reinforced polymer (FRP)-reinforced DBs using STM and sectional methods of Canadian Standard Association (CSA) and American Concrete Institute (ACI) design provisions. To this end, 106 FRP-reinforced DBs were compiled from the literature. It has been found that current sectional methods do not adequately account for the effects of arch. action on DBs. From this investigation, modifications were proposed in the current sectional methods to calculate the shear capacity of FRP-reinforced DBs. The proposed modifications were found to significantly improve the prediction accuracy. The sectional methods proposed by CSA and ACI were found to be better than the CSA-STM method in predicting the shear capacity of FRP-reinforced DBs.. The mean, standard deviation and coefficient of variation for the proposed CSA sectional method are 1.00, 0.28 and 28.2% and for the proposed ACI sectional method are 1.01, 0.26 and 25.6, respectively. The same for the CSA-STM method are 2.20, 0.76 and 34.4%, respectively. The proposed methods can be used to predict the shear capacity of FRP reinforced deep members.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it