Review and validation of code expressions and developed models in last three decades estimating concrete shear strength of FRP-reinforced members without stirrups
Bibliographic record
Abstract
In recent years, FRP-reinforced bars have been widely used in various structural elements due to their favorable physical and mechanical properties. Because of its brittle failure nature, particularly under shear stresses, many researchers studied the structural behavior of such elements reinforced with FRP bars to develop their performance and forecast their shear capacity. This paper, as a review article, compares seven different code models and fifteen generated models during the last three decades. These models were used to estimate shear strength of 386 tested specimens acquired from 63 studies conducted during a 51-year period. The predicted shear strength was compared to the experimental data of these specimens. A parametric analysis was carried out at various ranges of shear design parameters, employing all 22 models to explore the best model in general and the best model at particular zones of design parameters. The study concluded that, while the Canadian code CSA S806-12 is the best among the different design codes for predicting the shear strength of FRP-reinforced members in general as well as at different ranges of design parameters, only two to three developed shear-models over the last thirteen years were more accurate in estimating the shear strength of such members.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".