Shear Capacity of FRP Stirrups in FRP-Reinforced Concrete Beams Based on Genetic Algorithms Approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Current shear design guidelines propose that the nominal shear capacity of concrete beams reinforced with fibre-reinforced polymer (FRP) can be calculated using existing shear design equations for steel-reinforced concrete beams provided that the axial rigidity of FRP longitudinal bars and the capacity of FRP stirrups at the bent portions are accounted for. However, they noticeably vary in the manner they account for concrete contribution to shear as well as the shear capacity of FRP stirrups. This paper presents a simple yet more accurate equation to determine the shear capacity of FRP stirrups in FRP-reinforced concrete beams based on genetic algorithms approach. The shear capacity of FRP stirrups calculated using the proposed equation is compared to those obtained using equations provided by four commonly used shear design guidelines for FRP reinforced concrete beams, namely the ACI 440, CSA S806, JSCE, and ISIS Canada. Results show that current guidelines overestimate the capacity of FRP stirrups and that such capacity is best represented by a square root function of the stirrups ultimate capacity rather than a linear function as proposed by the guidelines. The shear capacity of FRP stirrups calculated using the proposed equation are in better agreement with available experimental data than those calculated using shear equations recommended by current guidelines.
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.
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) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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